From caeebe4d7f293316d66e961864e8f23c3d8dc1a1 Mon Sep 17 00:00:00 2001
From: mapleeit <mapleeit@users.noreply.github.com>
Date: Wed, 27 Dec 2023 09:56:29 +0000
Subject: [PATCH] =?UTF-8?q?Deploying=20to=20master=20from=20@=20jina-ai/we?=
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 .../index.html                                | 564 +++++++++---------
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 282 files changed, 2580 insertions(+), 2580 deletions(-)
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diff --git a/404.html b/404.html
index 4c30ffc05a7..cc31f22cb6a 100644
--- a/404.html
+++ b/404.html
@@ -9,6 +9,6 @@
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     gtag('js', new Date());
 
-    gtag('config', 'G-9T52NXDS9T');</script>  <script type="module" crossorigin src="/assets/index.2b6e3ac7.js"></script>
+    gtag('config', 'G-9T52NXDS9T');</script>  <script type="module" crossorigin src="/assets/index.ae19b4cb.js"></script>
   <link rel="stylesheet" href="/assets/index.9fe6336f.css">
 </head><body><div id=q-app></div></body></html>
\ No newline at end of file
diff --git a/about-us/index.html b/about-us/index.html
index 1208c8d7776..6627508197b 100644
--- a/about-us/index.html
+++ b/about-us/index.html
@@ -1,6 +1,6 @@
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>About Jina AI</title><meta charset="utf-8"><meta name="title" content="About Jina AI"><meta name="description" content="The future starts here."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/about-us"><meta property="og:title" content="About Jina AI"><meta property="og:description" content="The future starts here."><meta property="og:image" content="https://jina.ai/banner-about-us.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/about-us"><meta property="twitter:title" content="About Jina AI"><meta property="twitter:description" content="The future starts here."><meta property="twitter:image" content="https://jina.ai/banner-about-us.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">meeting_room</i><span class="block">Open day</span></span></a></div></div></div></div></div></div><div class="q-py-xl bg-dark relative-position"><div class="row justify-center"><div class="col-11 q-py-xl col-md-6 text-subtitle1 text-grey-5 text-center q-my-xl">From diverse corners of the globe, we're co-creating the future of multimodal AI. Our distinct lifestyles and perspectives enrich our work, sparking creativity and progress. Within this portal, we embrace our individuality, cherish our freedom, and passionately pursue our dreams. Welcome to the portal of the AI future.</div></div><div class=""><div class="q-carousel q-panel-parent q-carousel--without-padding q-carousel--dark q-dark transparent col-12" style="height: 500px;"><div class="q-carousel__slides-container"><div class="q-panel scroll" role="tabpanel" style="--q-transition-duration:300ms;"><div class="q-carousel__slide row no-wrap items-center justify-around"><div class="q-card q-card--dark q-dark q-card--flat no-shadow col-12 col-lg-4"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/IMG_6916.605585ab.jpg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div></div></div><div class="row q-my-xl justify-center q-gutter-y-lg"><div class="q-card q-card--dark q-dark q-card--flat no-shadow col-auto bg-transparent q-ma-xl"><div class="q-card__section q-card__section--vert text-weight-bold text-h3 q-pa-none">2020</div><div class="q-card__section q-card__section--vert text-subtitle1 text-uppercase text-grey-5 q-pa-none">Founded in</div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow col-auto bg-transparent q-ma-xl"><div class="q-card__section q-card__section--vert text-weight-bold text-h3 q-pa-none">50</div><div class="q-card__section q-card__section--vert text-subtitle1 text-uppercase text-grey-5 q-pa-none">Employees</div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow col-auto bg-transparent q-ma-xl"><div class="q-card__section q-card__section--vert text-weight-bold text-h3 q-pa-none">1,000+</div><div class="q-card__section q-card__section--vert text-subtitle1 text-uppercase text-grey-5 q-pa-none">Developers Empowered</div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow col-auto bg-transparent q-ma-xl"><div class="q-card__section q-card__section--vert text-weight-bold text-h3 q-pa-none">400,000+</div><div class="q-card__section q-card__section--vert text-subtitle1 text-uppercase text-grey-5 q-pa-none">Users Registered</div></div></div></div><div class="q-py-xl row justify-center relative-position"><div class="q-img q-img--menu absolute-top" role="img" style="width: 40%; left: -10%; z-index: -10;"><div style="padding-bottom: 83.2138%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/pattern-team-image.9687aaf5.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="col-11 col-md-10 q-py-xl row justify-between q-gutter-y-lg items-center" id="vision"><div class="col-12 col-md-5"><div class="text-h2">Pioneering the Future of Multimodal AI</div><div class="text-subtitle1 text-grey-5 q-mt-lg" style="white-space: pre-line; overflow-wrap: break-word;">Founded in 2020 and based in Berlin, Germany, Jina AI has swiftly risen as a leader in multimodal AI, focusing on prompt and embedding techniques. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jerboa</div><div class="q-item__label q-item__label--caption text-caption">An experimental finetuner for open-source LLMs</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="5f8e33af-d25d-485f-8f1e-6001a1d660fe" aria-label="Expand &quot;Company&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><span class="q-icon" aria-hidden="true" role="presentation"><img src="/J.svg"></span></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Company</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="5f8e33af-d25d-485f-8f1e-6001a1d660fe" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/about-us"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">About us</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/contact-sales"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Contact sales</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/open-day"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Open day</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/internship"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Intern program</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://jobs.lever.co/jina-ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Join us</div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">open_in_new</i></div></div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div></div></div></div><div class="q-scrollarea__bar q-scrollarea__bar--v absolute-right q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__bar q-scrollarea__bar--h absolute-bottom q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--v absolute-right q-scrollarea__thumb--invisible" aria-hidden="true" style="top: 0px; height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main class="q-page" style="min-height: 449px;"><div class="row justify-center bg-dark"><div class="q-card q-card--dark q-dark q-card--flat no-shadow col-12"><div class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 50%;"></div></div><div class="q-responsive__content absolute-full fit"><video autoplay="" loop="" playsinline="" class="non-selectable"><source src="/assets/portal-3.39abc5d6.mp4" type="video/mp4"></video></div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable q-ml-sm q-pl-sm"><div class="q-card__section q-card__section--vert text-h2 text-weight-bold">The Future <div>Starts <span class="dynamic-text">Here</span></div><div class="q-card__actions justify-start q-card__actions--horiz row q-mt-sm"><div class="q-btn-group row no-wrap q-btn-group--outline q-btn-group--square inline"><a class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="/contact-sales" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">handshake</i><span class="block">Contact sales</span></span></a><hr class="q-separator q-separator--vertical q-separator--dark" aria-orientation="vertical"><a class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="https://jobs.lever.co/jina-ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">emoji_people</i><span class="block">Join us</span></span></a><hr class="q-separator q-separator--vertical q-separator--dark" aria-orientation="vertical"><a class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="/open-day" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">meeting_room</i><span class="block">Open day</span></span></a></div></div></div></div></div></div><div class="q-py-xl bg-dark relative-position"><div class="row justify-center"><div class="col-11 q-py-xl col-md-6 text-subtitle1 text-grey-5 text-center q-my-xl">From diverse corners of the globe, we're co-creating the future of multimodal AI. Our distinct lifestyles and perspectives enrich our work, sparking creativity and progress. Within this portal, we embrace our individuality, cherish our freedom, and passionately pursue our dreams. Welcome to the portal of the AI future.</div></div><div class=""><div class="q-carousel q-panel-parent q-carousel--without-padding q-carousel--dark q-dark transparent col-12" style="height: 500px;"><div class="q-carousel__slides-container"><div class="q-panel scroll" role="tabpanel" style="--q-transition-duration:300ms;"><div class="q-carousel__slide row no-wrap items-center justify-around"><div class="q-card q-card--dark q-dark q-card--flat no-shadow col-12 col-lg-4"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 75%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/5.60cebb9f.jpg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div></div></div><div class="row q-my-xl justify-center q-gutter-y-lg"><div class="q-card q-card--dark q-dark q-card--flat no-shadow col-auto bg-transparent q-ma-xl"><div class="q-card__section q-card__section--vert text-weight-bold text-h3 q-pa-none">2020</div><div class="q-card__section q-card__section--vert text-subtitle1 text-uppercase text-grey-5 q-pa-none">Founded in</div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow col-auto bg-transparent q-ma-xl"><div class="q-card__section q-card__section--vert text-weight-bold text-h3 q-pa-none">50</div><div class="q-card__section q-card__section--vert text-subtitle1 text-uppercase text-grey-5 q-pa-none">Employees</div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow col-auto bg-transparent q-ma-xl"><div class="q-card__section q-card__section--vert text-weight-bold text-h3 q-pa-none">1,000+</div><div class="q-card__section q-card__section--vert text-subtitle1 text-uppercase text-grey-5 q-pa-none">Developers Empowered</div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow col-auto bg-transparent q-ma-xl"><div class="q-card__section q-card__section--vert text-weight-bold text-h3 q-pa-none">400,000+</div><div class="q-card__section q-card__section--vert text-subtitle1 text-uppercase text-grey-5 q-pa-none">Users Registered</div></div></div></div><div class="q-py-xl row justify-center relative-position"><div class="q-img q-img--menu absolute-top" role="img" style="width: 40%; left: -10%; z-index: -10;"><div style="padding-bottom: 83.2138%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/pattern-team-image.9687aaf5.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="col-11 col-md-10 q-py-xl row justify-between q-gutter-y-lg items-center" id="vision"><div class="col-12 col-md-5"><div class="text-h2">Pioneering the Future of Multimodal AI</div><div class="text-subtitle1 text-grey-5 q-mt-lg" style="white-space: pre-line; overflow-wrap: break-word;">Founded in 2020 and based in Berlin, Germany, Jina AI has swiftly risen as a leader in multimodal AI, focusing on prompt and embedding techniques. As a company rooted in the EU, our vision and services extend worldwide, providing businesses and developers with innovative platforms to harness the power of AI for value creation and cost savings. 
 
-Our commitment to open-source and open research has shaped our identity as a commercial open-source software company. This dedication to innovation is underscored by our financial growth, marked by a $38M raise in our Series A round in November 2021. At Jina AI, we're bridging the gap between advanced AI and practical applications on a global scale.</div></div><div class="col-12 col-md-5"><div class="q-img q-img--menu rounded-borders" role="img"><div style="padding-bottom: 164.202%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/office-outside.97d7c497.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div><div class="q-py-xl row justify-center"><div class="col-11 col-md-10 col-xl-8"><div class="text-h3 text-center q-pa-md">Awards &amp; Recognition</div><div class="q-carousel q-panel-parent q-carousel--with-padding q-carousel--dark q-dark transparent q-mt-md non-selectable" style="height: 280px;"><div class="q-carousel__slides-container"><div class="q-panel scroll" role="tabpanel" style="--q-transition-duration:300ms;"><div class="q-carousel__slide row no-wrap justify-center"><div class="q-card q-card--dark q-dark q-card--flat no-shadow bg-transparent cursor-pointer" style="width: 240px;"><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 180px; height: 120px;"><div style="padding-bottom: 66.6667%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/ai_hot_75.3ee7d295.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert text-center">The AI Hot 75</div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow bg-transparent cursor-pointer" style="width: 240px;"><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 180px; height: 120px;"><div style="padding-bottom: 66.6667%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/generative_developer_tools_Infrastructure.f8c5f480.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert text-center">Generative AI: Developer Tools &amp; Infrastructure</div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow bg-transparent cursor-pointer" style="width: 240px;"><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 180px; height: 120px;"><div 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style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="q-img q-img--menu" role="img" style="width: 170px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" width="170px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/SAPPHIRE.7f816c96.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div><div class="q-py-xl row justify-center q-gutter-y-xl"><div class="col-11 col-md-10 q-py-xl row justify-between q-gutter-y-lg items-center" id="vision"><div class="col-12 col-md-5"><div class="text-h2">Our Vision</div><div class="text-subtitle1 text-grey-5 q-mt-lg">Jina AI envisions paving the way towards the future of AI as a multimodal reality. We recognize that the existing machine learning and software ecosystems face challenges in handling multimodal AI. As a response, we're committed to developing pioneering tools and platforms that assist businesses and developers in navigating these complexities. Our vision is to play a crucial role in helping the world harness the vast potential of multimodal AI and truly revolutionize the way we interpret and interact with information.</div></div><div class="col-12 col-md-6 row justify-center q-px-xl"><div class="q-message q-message-received"><div class="q-message-container row items-end no-wrap"><img class="q-message-avatar q-message-avatar--received" src="/assets/yannlecun.96954f76.jpg" aria-hidden="true"><div class="col-10"><div class="q-message-name q-message-name--received">Yann LeCun</div><div class="q-message-text q-message-text--received text-msg-bubble"><div class="q-message-text-content q-message-text-content--received text-white"><div><div class="handwritten2 text-h5 q-pa-lg">An artificial intelligence system trained on words and sentences alone will never approximate human understanding.</div></div></div></div></div></div></div><div class="q-message q-message-sent"><div class="q-message-container row items-end no-wrap reverse"><img class="q-message-avatar q-message-avatar--sent" src="/Jina - Dark.svg" aria-hidden="true"><div class="col-10"><div class="q-message-name q-message-name--sent">Jina AI</div><div class="q-message-text q-message-text--sent text-msg-bubble2"><div class="q-message-text-content q-message-text-content--sent"><div><div class="handwritten1 text-h5 q-pa-lg">Absolutely, Yann. We're on it, building bridges to a multimodal AI future!</div></div></div></div></div></div></div></div></div><div class="col-11 col-md-10 q-py-xl row justify-between q-gutter-y-lg items-center" id="mission"><div class="col-12 col-md-5"><div class="text-h2">Our Mission</div><div class="text-subtitle1 text-grey-5 q-mt-lg" style="white-space: pre-line; overflow-wrap: break-word;">At Jina AI, our mission is to lead the advancement of multimodal AI through innovative embedding and prompt-based technologies, focusing specifically on areas like natural language processing, image and video analysis, and cross-modal data interaction. This specialization allows us to provide unique solutions that turn complex, multi-source data into actionable insights and groundbreaking applications.</div><div class="q-list q-list--dark q-my-lg"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">diamond</i></div><div class="q-item__section column q-item__section--main justify-center text-weight-bold">Understand Our View</div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f51170c4-2d55-4898-b7f1-a7d0f84df08c" aria-label="Expand &quot;Prompt &amp; agent engineering&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">arrow_right</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Prompt &amp; agent engineering</div></div></div><div class="q-expansion-item__content relative-position" id="f51170c4-2d55-4898-b7f1-a7d0f84df08c" style="display: none;"><div class="q-card q-card--dark q-dark text-caption q-pa-lg" style="white-space: pre-line; overflow-wrap: break-word;">At Jina AI, we recognize prompt engineering as vital for interacting with large language models (LLMs). As these models advance, the complexity of prompts escalates, encompassing intricate reasoning and logic. This advancement underscores the intertwined growth of LLMs and prompt sophistication.
+Our commitment to open-source and open research has shaped our identity as a commercial open-source software company. This dedication to innovation is underscored by our financial growth, marked by a $38M raise in our Series A round in November 2021. 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style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="q-img q-img--menu" role="img" style="width: 170px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" width="170px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/SAPPHIRE.7f816c96.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div><div class="q-py-xl row justify-center q-gutter-y-xl"><div class="col-11 col-md-10 q-py-xl row justify-between q-gutter-y-lg items-center" id="vision"><div class="col-12 col-md-5"><div class="text-h2">Our Vision</div><div class="text-subtitle1 text-grey-5 q-mt-lg">Jina AI envisions paving the way towards the future of AI as a multimodal reality. We recognize that the existing machine learning and software ecosystems face challenges in handling multimodal AI. As a response, we're committed to developing pioneering tools and platforms that assist businesses and developers in navigating these complexities. Our vision is to play a crucial role in helping the world harness the vast potential of multimodal AI and truly revolutionize the way we interpret and interact with information.</div></div><div class="col-12 col-md-6 row justify-center q-px-xl"><div class="q-message q-message-received"><div class="q-message-container row items-end no-wrap"><img class="q-message-avatar q-message-avatar--received" src="/assets/yannlecun.96954f76.jpg" aria-hidden="true"><div class="col-10"><div class="q-message-name q-message-name--received">Yann LeCun</div><div class="q-message-text q-message-text--received text-msg-bubble"><div class="q-message-text-content q-message-text-content--received text-white"><div><div class="handwritten2 text-h5 q-pa-lg">An artificial intelligence system trained on words and sentences alone will never approximate human understanding.</div></div></div></div></div></div></div><div class="q-message q-message-sent"><div class="q-message-container row items-end no-wrap reverse"><img class="q-message-avatar q-message-avatar--sent" src="/Jina - Dark.svg" aria-hidden="true"><div class="col-10"><div class="q-message-name q-message-name--sent">Jina AI</div><div class="q-message-text q-message-text--sent text-msg-bubble2"><div class="q-message-text-content q-message-text-content--sent"><div><div class="handwritten1 text-h5 q-pa-lg">Absolutely, Yann. We're on it, building bridges to a multimodal AI future!</div></div></div></div></div></div></div></div></div><div class="col-11 col-md-10 q-py-xl row justify-between q-gutter-y-lg items-center" id="mission"><div class="col-12 col-md-5"><div class="text-h2">Our Mission</div><div class="text-subtitle1 text-grey-5 q-mt-lg" style="white-space: pre-line; overflow-wrap: break-word;">At Jina AI, our mission is to lead the advancement of multimodal AI through innovative embedding and prompt-based technologies, focusing specifically on areas like natural language processing, image and video analysis, and cross-modal data interaction. This specialization allows us to provide unique solutions that turn complex, multi-source data into actionable insights and groundbreaking applications.</div><div class="q-list q-list--dark q-my-lg"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">diamond</i></div><div class="q-item__section column q-item__section--main justify-center text-weight-bold">Understand Our View</div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="71652d2d-f4bc-4430-bfd3-e065038db101" aria-label="Expand &quot;Prompt &amp; agent engineering&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">arrow_right</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Prompt &amp; agent engineering</div></div></div><div class="q-expansion-item__content relative-position" id="71652d2d-f4bc-4430-bfd3-e065038db101" style="display: none;"><div class="q-card q-card--dark q-dark text-caption q-pa-lg" style="white-space: pre-line; overflow-wrap: break-word;">At Jina AI, we recognize prompt engineering as vital for interacting with large language models (LLMs). As these models advance, the complexity of prompts escalates, encompassing intricate reasoning and logic. This advancement underscores the intertwined growth of LLMs and prompt sophistication.
 
-We foresee a future where LLMs act as compilers, with prompts becoming the new programming language. This shift suggests that future technological proficiency may focus more on prompt mastery than traditional coding. Our commitment at Jina AI is to lead in this transformative area, making advanced AI accessible and practical for everyday use by mastering this emerging 'language'.</div></div></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="a9a97f8f-f147-45a8-bb92-b9cf0523da25" aria-label="Expand &quot;Embeddings&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">arrow_right</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Embeddings</div></div></div><div class="q-expansion-item__content relative-position" id="a9a97f8f-f147-45a8-bb92-b9cf0523da25" style="display: none;"><div class="q-card q-card--dark q-dark text-caption q-pa-lg" style="white-space: pre-line; overflow-wrap: break-word;">At Jina AI, we harness the power of embedding technology to revolutionize diverse AI applications. This technology serves as a unified method to efficiently represent and compress various data types, ensuring no loss of critical information. Our focus is on transforming complex datasets into a universally understandable embedding format, which is essential for precise and insightful AI analysis.
+We foresee a future where LLMs act as compilers, with prompts becoming the new programming language. This shift suggests that future technological proficiency may focus more on prompt mastery than traditional coding. Our commitment at Jina AI is to lead in this transformative area, making advanced AI accessible and practical for everyday use by mastering this emerging 'language'.</div></div></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f3c20a37-680e-401b-a709-35ca59a3cdcb" aria-label="Expand &quot;Embeddings&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">arrow_right</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Embeddings</div></div></div><div class="q-expansion-item__content relative-position" id="f3c20a37-680e-401b-a709-35ca59a3cdcb" style="display: none;"><div class="q-card q-card--dark q-dark text-caption q-pa-lg" style="white-space: pre-line; overflow-wrap: break-word;">At Jina AI, we harness the power of embedding technology to revolutionize diverse AI applications. This technology serves as a unified method to efficiently represent and compress various data types, ensuring no loss of critical information. Our focus is on transforming complex datasets into a universally understandable embedding format, which is essential for precise and insightful AI analysis.
 
-Embeddings are fundamental, especially in applications like precise image and voice recognition, where they help discern fine-grained details and nuances. In natural language processing, embeddings enhance understanding of context and sentiment, leading to more accurate conversational AI and language translation tools. They are also crucial in developing sophisticated recommendation systems that require a deep understanding of user preferences across different content forms, such as text, audio, and video.</div></div></div></div></div></div><div class="col-12 col-md-6 row justify-center"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/prompt-embedding.88c09167.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div class="col-11 col-md-10 q-py-xl row justify-between q-gutter-y-lg items-center" id="approach"><div class="col-12 col-md-5"><div class="text-h2">Our Approach</div><div class="text-subtitle1 text-grey-5 q-mt-lg">In the rapidly evolving world of AI, strategies need to be both nimble and forward-thinking. While our core offering remains centered on enterprises, the AI landscape has shifted in ways that necessitate a rethinking of our approach to customer acquisition. Here's why introducing power users as the entry point of our funnel isn't just innovative, but crucial for our sustained growth in the enterprise sector.</div><div class="q-list q-list--dark q-my-lg"><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="3b3e75ec-eb05-414e-96e2-0e99ac7d0967" aria-label="Expand &quot;Prompt-based Technology: A New Paradigm&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">arrow_right</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Prompt-based Technology: A New Paradigm</div></div></div><div class="q-expansion-item__content relative-position" id="3b3e75ec-eb05-414e-96e2-0e99ac7d0967" style="display: none;"><div class="q-card q-card--dark q-dark text-caption q-pa-lg">2023 heralded a significant change: the rise of prompt-based technology. By simplifying the AI development process, it has democratized access to AI tools. Now, those without extensive programming experience—termed as 'power users'—can engage in AI development without the steep learning curves associated with tools like Pytorch, Docker, or Kubernetes.
+Embeddings are fundamental, especially in applications like precise image and voice recognition, where they help discern fine-grained details and nuances. In natural language processing, embeddings enhance understanding of context and sentiment, leading to more accurate conversational AI and language translation tools. They are also crucial in developing sophisticated recommendation systems that require a deep understanding of user preferences across different content forms, such as text, audio, and video.</div></div></div></div></div></div><div class="col-12 col-md-6 row justify-center"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/prompt-embedding.88c09167.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div class="col-11 col-md-10 q-py-xl row justify-between q-gutter-y-lg items-center" id="approach"><div class="col-12 col-md-5"><div class="text-h2">Our Approach</div><div class="text-subtitle1 text-grey-5 q-mt-lg">In the rapidly evolving world of AI, strategies need to be both nimble and forward-thinking. While our core offering remains centered on enterprises, the AI landscape has shifted in ways that necessitate a rethinking of our approach to customer acquisition. Here's why introducing power users as the entry point of our funnel isn't just innovative, but crucial for our sustained growth in the enterprise sector.</div><div class="q-list q-list--dark q-my-lg"><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="d0ff003f-580a-4638-b20e-902a0628b7ab" aria-label="Expand &quot;Prompt-based Technology: A New Paradigm&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">arrow_right</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Prompt-based Technology: A New Paradigm</div></div></div><div class="q-expansion-item__content relative-position" id="d0ff003f-580a-4638-b20e-902a0628b7ab" style="display: none;"><div class="q-card q-card--dark q-dark text-caption q-pa-lg">2023 heralded a significant change: the rise of prompt-based technology. By simplifying the AI development process, it has democratized access to AI tools. Now, those without extensive programming experience—termed as 'power users'—can engage in AI development without the steep learning curves associated with tools like Pytorch, Docker, or Kubernetes.
 
-Drawing a parallel, this is akin to the evolution of personal computing. Initially, only tech experts operated computers. But with the advent of user-friendly interfaces, a broader audience could participate. Today, with prompt-based technology, we're witnessing a similar democratization in AI.</div></div></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="cb7fb1a7-7d53-4e2b-a81c-742ae9e9d48c" aria-label="Expand &quot;Why Traditional MLOps Miss the Mark&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">arrow_right</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Why Traditional MLOps Miss the Mark</div></div></div><div class="q-expansion-item__content relative-position" id="cb7fb1a7-7d53-4e2b-a81c-742ae9e9d48c" style="display: none;"><div class="q-card q-card--dark q-dark text-caption q-pa-lg">While the influx of power users is significant, traditional MLOps tools are ill-equipped to cater to their needs. These tools are reminiscent of using a tractor to navigate city streets—they're heavy and often excessive. The new-gen developers demand agile, intuitive tools that complement their rapid development pace.</div></div></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="d4bab41b-528a-4bc3-8889-97c0acd64ae9" aria-label="Expand &quot;Connecting the Dots: Power Users to Enterprises&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">arrow_right</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Connecting the Dots: Power Users to Enterprises</div></div></div><div class="q-expansion-item__content relative-position" id="d4bab41b-528a-4bc3-8889-97c0acd64ae9" style="display: none;"><div class="q-card q-card--dark q-dark text-caption q-pa-lg">So, why is a power user focus essential for our enterprise-centric model? Because it’s about establishing early relationships. By catering to power users now, we're building bridges to the enterprises they'll influence in the future. It’s a strategic play—a long-term investment to ensure our enterprise offering remains top-of-mind when these power users ascend to decision-making roles within organizations.</div></div></div></div></div><div class="text-subtitle1 text-grey-5 q-mt-lg">At Jina AI, our strategy is to be proactive rather than reactive. The inclusion of power users as the funnel's entry point ensures we're not only capturing current market trends but are also strategically poised for future enterprise growth. Our commitment to enterprises remains unwavering; however, our approach to reaching them is innovative, robust, and, above all, forward-thinking.</div></div><div class="col-12 col-md-6 row justify-center"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jina-ai-user-funnel.3b8bc315.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div class="col-11 col-md-10 q-py-xl row justify-between q-gutter-y-lg items-center" id="value"><div class="col-12 col-md-5"><div class="text-h2">Our Value</div><div class="text-subtitle1 text-grey-5 q-mt-lg">At Jina AI, we believe in the power of open-source technology to accelerate innovation, foster collaboration, and empower communities. We're not just advocates - we are active contributors, investing significantly in the open-source community.
+Drawing a parallel, this is akin to the evolution of personal computing. Initially, only tech experts operated computers. But with the advent of user-friendly interfaces, a broader audience could participate. Today, with prompt-based technology, we're witnessing a similar democratization in AI.</div></div></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="9192009c-8aea-4055-b862-48c2f165a668" aria-label="Expand &quot;Why Traditional MLOps Miss the Mark&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">arrow_right</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Why Traditional MLOps Miss the Mark</div></div></div><div class="q-expansion-item__content relative-position" id="9192009c-8aea-4055-b862-48c2f165a668" style="display: none;"><div class="q-card q-card--dark q-dark text-caption q-pa-lg">While the influx of power users is significant, traditional MLOps tools are ill-equipped to cater to their needs. These tools are reminiscent of using a tractor to navigate city streets—they're heavy and often excessive. The new-gen developers demand agile, intuitive tools that complement their rapid development pace.</div></div></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="e954bd19-829f-432a-b7c1-21a46c7ac498" aria-label="Expand &quot;Connecting the Dots: Power Users to Enterprises&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">arrow_right</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Connecting the Dots: Power Users to Enterprises</div></div></div><div class="q-expansion-item__content relative-position" id="e954bd19-829f-432a-b7c1-21a46c7ac498" style="display: none;"><div class="q-card q-card--dark q-dark text-caption q-pa-lg">So, why is a power user focus essential for our enterprise-centric model? Because it’s about establishing early relationships. By catering to power users now, we're building bridges to the enterprises they'll influence in the future. It’s a strategic play—a long-term investment to ensure our enterprise offering remains top-of-mind when these power users ascend to decision-making roles within organizations.</div></div></div></div></div><div class="text-subtitle1 text-grey-5 q-mt-lg">At Jina AI, our strategy is to be proactive rather than reactive. The inclusion of power users as the funnel's entry point ensures we're not only capturing current market trends but are also strategically poised for future enterprise growth. Our commitment to enterprises remains unwavering; however, our approach to reaching them is innovative, robust, and, above all, forward-thinking.</div></div><div class="col-12 col-md-6 row justify-center"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jina-ai-user-funnel.3b8bc315.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div class="col-11 col-md-10 q-py-xl row justify-between q-gutter-y-lg items-center" id="value"><div class="col-12 col-md-5"><div class="text-h2">Our Value</div><div class="text-subtitle1 text-grey-5 q-mt-lg">At Jina AI, we believe in the power of open-source technology to accelerate innovation, foster collaboration, and empower communities. We're not just advocates - we are active contributors, investing significantly in the open-source community.
 
 From being the driving force behind FastAPI, to our ongoing support for the Linux and Python Foundations, we are passionate about giving back. But we don’t stop there; we’ve also open-sourced our core infrastructure, sharing our multimodal AI expertise with the world.
 
diff --git a/assets/AboutUsPage.aa080515.js b/assets/AboutUsPage.df03abe0.js
similarity index 98%
rename from assets/AboutUsPage.aa080515.js
rename to assets/AboutUsPage.df03abe0.js
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--- a/assets/AboutUsPage.aa080515.js
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",de="data:image/png;base64,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FilczahcDukLaU81T0rF40zYEY40mWXk/ed6ecZxfHcMsBY41eOF4zQxOncaVb5377i9/tOeuH8byVee4qayAqNw2f+dEmlenRgrfhwIH6NlL3L8yZGsRgfMtyEGfZg/8Zxw7UvaVld900Cz0vmyHw5JpdwluHlYUfW2Tom2XdRF6jxEEgaRwZhktV2m4Pd26nyqL4loXu2azr/miMF83ajPj0XltS8ijTSzNiJBvlGbofQw4Vzt/qNT8nrXh3APPQvDleV0EVo8GsdW55RcEYhM/nUZI/FIif6ZC+izHBhfuWeF9oIWhv43XP/CYYyFLJa5T+hJc9jqhQ9ayAjHzJ5YnT9ELm5jgc1Ay+mUqftPdyp1DDhrow6X53f97aIwYgpYX/5ACFB+v4CWsASpv/aYI7HOSkLGgTRRrlLo+z0n/SHZ5qtUE9b7ZDyA6qNkrcp/SA8ZagGHYz0JtutvrAonyyUTJv/YHymOSMM42AueXkxDEWSl/FWWTFwCPkUosazRRrDLHj+dWWrr7ngQo7plmO6i0AXlaoaPhel53rMvBca5EGNa+B9o1MiljlZqbcc60KvL8Vo1+1i3poNqeu8U4zEkxxa59VcXH6WDl+bZ3/LPI7MnGMCX2lFQNDEHPjk1SWo6xGcpzk6TSYvy52ztSlxN60OjfbUb3puHVcOjEGjg01vC80Hxz7P2hNcr7wyW2Urmf1NwbTay9h/5/bo9YJdt+zjUdCj1PEVM4I488VMWrMVxoj3W5+P494rsALHGglcHOFaoaZwp/UcKM5IxgGoenOBa4U7vlmpVk9dY45Nhbh5cprm9WA7nvcIscPrM31+PRGKxN3PHOtdjCQ8b+OdRu7m0rRLw9gkWJkPNY7f4pFW6GwwNHD8CA02I9USXsn9clZRfnECBavnolLO/YKIm7uxlywhytL74z0GVGKfDuGhjci5TxqT6lFcBabVT6+mIDzxHX6zec9VhS5V3H5/tCVFr2zNNUUsz57APM+uZEHXzXAaIdK162L443CuW1iOb6nK/P7SvTVCuoH7woNao01kUKLys6k/A2L5mJpsJeQrUJYIftaeoPEL/LbSmt2Rh40OowRWcYVRiBeEI7YWQ3yHsm5aT6OKflRMdO+rXJnnoEnIz08g3hHjJjMia+UDM2Kj0O8+9IAWgieQd/3342uY6w4rNYyeeVjpGSqcLRT8d6KxPt+F1jXiet6mzWZwt/ocet1fAeHPxcvjkMK3oqqyEtakGdipuIpfTwqmKjzVYGiuxwYfa/X/WW/TXObRY08Sd4ySCbK/y6Vn1GaBXuWMI7XMQ4G9Nqxek6Hwrpm7MLIshMN8umUJGPvonrtzEEtw/WOudJMewuh98zA8DnJZr3LLo9sWP8xaOrniTkGssu3l/yMi0v/8Kxrpb9mV4m+GLfaqV18FYwRbB8nwOIyn/GgcvJQj1dKfGJScVknQgVkBBlukb8rFZkv273HovVEKvpGixb926v4puaB5ffExPELlZJ7RX3ciIa6PdulzYescFyn8aNx0DGxp48OYVlO2ekIr07uAewid1mktu+Zco1y4Zhd1DGhbL4brTaoR5Qrz4rKJ0jvdXnVi7kWbdvDbuI3yg5XrkAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQOBtyxvOOlSN/KcTIAAAAABJRU5ErkJggg==",de="data:image/png;base64,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diff --git a/assets/ClosePopup.93058c13.js b/assets/ClosePopup.84f03a4a.js
similarity index 90%
rename from assets/ClosePopup.93058c13.js
rename to assets/ClosePopup.84f03a4a.js
index 1cae19023c3..35d157b3045 100644
--- a/assets/ClosePopup.93058c13.js
+++ b/assets/ClosePopup.84f03a4a.js
@@ -1 +1 @@
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+import{b5 as s,b6 as d,b7 as a,H as c}from"./index.ae19b4cb.js";function n(e){if(e===!1)return 0;if(e===!0||e===void 0)return 1;const t=parseInt(e,10);return isNaN(t)?0:t}var u=s({name:"close-popup",beforeMount(e,{value:t}){const o={depth:n(t),handler(r){o.depth!==0&&setTimeout(()=>{const p=d(e);p!==void 0&&a(p,r,o.depth)})},handlerKey(r){c(r,13)===!0&&o.handler(r)}};e.__qclosepopup=o,e.addEventListener("click",o.handler),e.addEventListener("keyup",o.handlerKey)},updated(e,{value:t,oldValue:o}){t!==o&&(e.__qclosepopup.depth=n(t))},beforeUnmount(e){const t=e.__qclosepopup;e.removeEventListener("click",t.handler),e.removeEventListener("keyup",t.handlerKey),delete e.__qclosepopup}});export{u as C};
diff --git a/assets/ContactUs.8bc0a33d.js b/assets/ContactUs.0a81ef6e.js
similarity index 91%
rename from assets/ContactUs.8bc0a33d.js
rename to assets/ContactUs.0a81ef6e.js
index e1be89834c4..2a88ace5d5b 100644
--- a/assets/ContactUs.8bc0a33d.js
+++ b/assets/ContactUs.0a81ef6e.js
@@ -1 +1 @@
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diff --git a/assets/InternshipPage.97bcdb4b.js b/assets/InternshipPage.3127fdca.js
similarity index 93%
rename from assets/InternshipPage.97bcdb4b.js
rename to assets/InternshipPage.3127fdca.js
index 1d868c251ae..392d3f31244 100644
--- a/assets/InternshipPage.97bcdb4b.js
+++ b/assets/InternshipPage.3127fdca.js
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diff --git a/assets/LabeledPanel.3dabe762.js b/assets/LabeledPanel.e1df998a.js
similarity index 97%
rename from assets/LabeledPanel.3dabe762.js
rename to assets/LabeledPanel.e1df998a.js
index c0fba14c455..9edcec0b6d1 100644
--- a/assets/LabeledPanel.3dabe762.js
+++ b/assets/LabeledPanel.e1df998a.js
@@ -1,4 +1,4 @@
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diff --git a/assets/LandingPage.90c8a1d3.js b/assets/LandingPage.48c02c99.js
similarity index 95%
rename from assets/LandingPage.90c8a1d3.js
rename to assets/LandingPage.48c02c99.js
index be056245030..dbfd0b0b4d2 100644
--- a/assets/LandingPage.90c8a1d3.js
+++ b/assets/LandingPage.48c02c99.js
@@ -1 +1 @@
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diff --git a/assets/LegalPage.afc92350.js b/assets/LegalPage.1fc54ab9.js
similarity index 99%
rename from assets/LegalPage.afc92350.js
rename to assets/LegalPage.1fc54ab9.js
index 5ecea7acf8b..4107868af98 100644
--- a/assets/LegalPage.afc92350.js
+++ b/assets/LegalPage.1fc54ab9.js
@@ -1 +1 @@
-import{e as A,bs as C,u as T,a6 as k,K as P,bt as m,a7 as r,a8 as i,a9 as o,az as t,aB as S,ai as a,ab as s,aa as n,ak as h,ac as y,ad as D,ae as G,bw as J,ah as c,af as b,j as R,bx as _}from"./index.2b6e3ac7.js";import{Q as q}from"./QList.77d2e514.js";import{Q as F,a as L}from"./QTable.c2f82dde.js";import{Q as j}from"./QPage.9d7ab03a.js";import{_ as E}from"./plugin-vue_export-helper.21dcd24c.js";import"./QSelect.ada2cea3.js";import"./QChip.dae6efcf.js";import"./QItemLabel.4068d6dd.js";import"./QMenu.d2069e37.js";import"./position-engine.7fb36afb.js";import"./selection.e82f8124.js";import"./format.988231da.js";import"./use-fullscreen.92026c44.js";const l={title:"Legal Information",subTitle:"Last Modified: Oct 26 2023",menus:[{label:"Terms and Conditions",link:"#terms-and-conditions"},{label:"Privacy Policy",link:"#privacy-policy"},{label:"Imprint",link:"#Imprint"}],content:[{tag:"h1",text:"Terms and Conditions",id:"terms-and-conditions"},{tag:"h2",text:"1. Scope and Subject Matter"},{tag:"p",text:'1.1 These terms and conditions (hereinafter referred to as "TCs") govern the legal relationship between you (the \u201CCustomer\u201D or \u201Cyou\u201D) and Jina AI GmbH, Leipziger Stra\xDFe 96, 10117 Berlin, Germany ("Jina AI", \u201Cwe\u201D or \u201Cus\u201D) when you access and use our services, including any content, functionality, software, application programming interface, tool, data, documentation, websites and services offered on or through Jina AI (the \u201CServices\u201D). These TCs shall apply exclusively; deviating Customer terms shall not apply except if we have expressly confirmed their application in writing.'},{tag:"p",text:"1.2 These TCs (as updated from time to time) shall also govern all future transactions between you and us."},{tag:"p",text:'1.3 The Services to be provided by Jina AI are set out in product descriptions (the \u201CProduct Descriptions\u201D as updated from time to time) in the online ordering pages (for Services ordered through our website, the \u201COnline Services\u201D) or a separate written order form which has been agreed between the Parties (together the "Order Form"). The Order Form has precedence over the terms of these TCs.'},{tag:"p",text:"1.4 The Order Form submitted by the Customer to Jina AI shall constitute a binding offer to enter into a contract with Jina AI on the provision of the Services identified in the Order Form. Jina AI can accept such offer (and thereby establish a binding contract) by providing the Customer with a corresponding order confirmation or by way of allowing the Customer the use of the Services online in case of Online Services."},{tag:"h2",text:"2. Registration and Access"},{tag:"p",text:"2.1 To use the Services Customers must register with Jina AI and create an account, providing all required data and information in an accurate and complete manner."},{tag:"p",text:"2.2 By registering, Customers agree to be fully responsible for all activities conducted through their account or using their access credentials."},{tag:"p",text:"2.3 Jina AI reserves the right, at its own discretion, to suspend or delete at any time and without notice, Customer accounts which it deems inappropriate, offensive or in violation of these TCs."},{tag:"h2",text:"3. Services of Jina AI"},{tag:"p",text:"3.1 Jina AI will provide the Services as specified in the Order Form and in accordance with the respective Product Description. Jina AI shall be entitled to determine the manner and means of performing and providing the Services at its own reasonable discretion, provided that the Services shall meet the material requirements as set out in the Product Description. Unless expressly agreed otherwise in the Order Form, the statutory terms for works contracts shall not apply to the Services and they shall not be subject to an acceptance procedure."},{tag:"p",text:"3.2 Unless expressly agreed otherwise in the Order Form, the Services are standard services which Jina AI makes available in a standard format to multiple Customers. Jina AI may from time to time improve, modify, extend and enhance the Services (while retaining their core functions as specified in the Product Description). In that case, Jina AI will update the Product Description accordingly and notify the Customer of such changes reasonably in advance of their implementation."},{tag:"p",text:"3.3 Dates and time periods set out in the Order Form or communicated otherwise by Jina AI are non-binding estimates unless it is expressly agreed between the parties in text form that they are binding."},{tag:"p",text:'3.4 Jina AI may temporarily suspend the Customer\u2019s access to the Services if and in so far as Jina AI reasonably considers such suspension to be required to stop or reduce a material risk to the Services or the Jina AI platforms or systems used to provide the Services (the "Jina AI Systems") or any Customer systems or data. Jina AI will inform the Customer of such suspension without undue delay and will reinstate the Customer\u2019s access to the Services as soon as the risk does no longer apply.'},{tag:"p",text:"3.5 The Services of Jina AI are designed only as a tool using artificial intelligence. No specific Output are owed by Jina AI to the user when using the Services. The Services do not claim to meet all Customer expectations for every situation. The Output made available to the user when using the Services therefore do not claim to be complete, accurate or true. Any of such Output must therefore be reviewed by the Customer for its use case and the Output does not replace the Customer's own considerations, evaluations and actions."},{tag:"h2",text:"4. Intellectual Property Rights"},{tag:"p",text:"4.1 All software, data bases, documents, information, algorithms, processes, prototypes, ideas, knowhow, patents, trademarks or other work results (\u201CIP\u201D) used by Jina AI to provide the Services or made available to the Customer by Jina AI are owned by Jina AI or its licensors (\u201CJina AI IP\u201D). Jina AI does not grant any licenses in the Jina AI IP or any other rights to use the Jina AI IP to the Customer."},{tag:"p",text:"4.2 Where Jina AI as part of its Services makes Jina AI IP available to the Customer, Jina AI grants the Customer (subject to the payment of the Service Charges, cf. Section 6 of these TCs) a non-exclusive, non-sublicensable, non-transferable, revocable and limited right to use such Jina AI IP strictly for the purpose of using the Services agreed in an Order Form and for the term set out in Section 11. Any other rights of the Customer in the Jina AI IP are excluded. Nothing in these TCs shall limit or exclude Jina AI's right to use the Jina AI IP or any other materials developed, used or provided by Jina AI under these TCs for its own business purposes or for other customers."},{tag:"p",text:"4.3 Where as an outcome of the Customer\u2019s use of the Services certain results (e.g. pictures, text, software, graphics, presentations, documents, data, works of art, or IP) are created through the Services (collectively, the \u201COutput\u201D), Jina AI (except as expressly stated otherwise herein) claims no rights to such Output and imposes no restrictions on the Customer regarding the use of the Output unless otherwise agreed in an agreement with the Customer. The Customer shall be responsible for such Output and its compliance with applicable law and applicable third party rights. In particular, Jina AI does not warrant that any Output is free of, or does not infringe, third party rights."},{tag:"p",text:"4.4 The Customer must ensure that any information, pictures, text, software, graphics, presentations, documents, work results, IP or other data the Customer provides in the course of using the Services (collectively \u201CInput\u201D), e.g. Input that the Customer uploads to Jina AI or processes through the Services, comply with all applicable laws and regulations, the terms of these TCs, and are not illegal, immoral or defamatory (e.g. do not include defamatory, pornographic, racist or violent content). The Customer confirms and commits that the Input and its use with the Services does not infringe any third party intellectual property or privacy rights and that the Customer is entitled to use the Input with the Services. If the Customer breaches its obligations under this Section 4.4, Jina AI may remove, delete or block the Input at its own discretion and, without prior notice, deny the Customer access to the Services."},{tag:"p",text:"4.5 Customers must not (i) reverse engineer, decompile, translate or otherwise attempt to discover the source code or underlying components of the Services or Jina AI\u2019s IP (except to the extent permitted under applicable mandatory law); (ii) use the Services in a way that infringes, misappropriates or violates any third party rights; (iii) use any Output from the Services to develop applications or services that compete with the Services offered by Jina AI; or (iv) use automated methods to extract information, data or result from the JINA-AI website or the Services, including by means of scraping, harvesting, or web data extraction."},{tag:"p",text:"4.6 Unless agreed otherwise (e.g. in these TCs) Jina AI will only store Input or Output on its servers to the extent required to provide the Services."},{tag:"p",text:"4.7 In the provision of the Services (and without prejudice to Section 4.2 above), Jina AI may use open source software components which may be subject to specific open sources license terms. Where relevant for the Customer, Jina AI will disclose such open source license terms to the Customer."},{tag:"h2",text:"5. Customer Obligations"},{tag:"p",text:"5.1 The Customer shall use the Services solely for the purposes established in the respective Order Form and Product Description."},{tag:"p",text:"5.2 The Customer shall reasonably support Jina AI in the provision of the Services as further set out in the Product Description. In addition, the Customer shall provide Jina AI with access to Customer's information, data, systems, personnel and premises as reasonably required by Jina AI for the provision of the Services. The Customer shall make decisions and provide feedback relating to the Services within a reasonable time period after receipt of a corresponding request by Jina AI."},{tag:"p",text:"5.3 Where to use the Services the Customer needs to connect to Jina AI Systems or platforms the Customer is responsible for establishing and maintaining the data connection between the interface of the relevant Jina AI Systems to the internet and the Customer\u2019s systems."},{tag:"p",text:"5.4 If the Customer fails to perform the Customer obligations, then the obligations of Jina AI which cannot be rendered without such Customer performance (or only by incurring disproportionate additional expenses) shall be suspended for the duration of such default and a reasonable start-up period. Additional expenses reasonably incurred by Jina AI shall be reimbursed by the Customer on a time and material basis applying the rates set out in the Order Form."},{tag:"h2",text:"6. Service Charges, Terms of Payment and Credits"},{tag:"p",text:'6.1 The Customer shall pay the fees for the Services as set out in the Order Form ("Service Charges"). Unless stated otherwise in the Order Form are exclusive of applicable VAT which the customer shall pay in addition to the Service Charges.'},{tag:"p",text:"6.2 Jina AI will invoice recurring lump sum Service Charges in advance prior to the beginning of the time period to which they relate (\u201DService Period\u201D). If applicable, Service Charges for time & material services will be invoiced monthly in arrears."},{tag:"p",text:"6.3 If applicable, expenses and disbursements shall be invoiced additionally in accordance with the principles set out in the Order Form. Where Service Charges are invoiced on a time & material basis, Jina AI will charge units of 15 minutes; travel time shall be chargeable as working time."},{tag:"p",text:"6.4 Unless otherwise agreed in the Order Form, invoices are due for payment within 14 days of receipt of the invoice by the Customer."},{tag:"p",text:"6.5 For certain Services the Customer receives from Jina AI a specific number of credits as set out in the Order Form (\u201CCredits\u201D). The Customer may use these Credits for obtaining Services during the respective Service Period. The Customer may roll over remaining Credits to the next Service Period, unless expressly agreed otherwise in the Order Form. If the Credits are used up, the Customer can purchase additional Credits; details are set out in the Order Form. The credits purchased by the client are not refundable nor exchangeable. The Credit System and the measurement of individual Credits may differ depending on the type of Service."},{tag:"h2",text:"7. Defects"},{tag:"p",text:"7.1 Services provided by Jina AI will essentially comply with the description in the Order Form and the Product Description. However, the Services are subject to continuous modification and improvement. The parties therefore agree that the Services may contain errors and malfunctions and that they may not comply in all aspects with general market standards, public statements, announcements or advertisements by Jina AI. Jina AI provides the Services to Customer \u201Cas is\u201D and except as expressly set out otherwise herein, the statutory liability for defects shall be excluded. The Customer acknowledges that the Services may not be fit for the purpose intended by the Customer, and that the Customer, being aware of this, uses the Services in its own responsibility and at its own risk."},{tag:"p",text:"7.2 If the Customer detects any defects in the Services, it shall notify Jina AI (in writing or text form) thereof without undue delay and shall provide a comprehensive description of the defects and the time and circumstances of their occurrence. Jina AI will use reasonable commercial efforts to (in its sole discretion) either remedy/correct the defect (if reasonable) or provide the affected Service (or part of the Service) again without defects and at no extra charge to the Customer. If an attempted remedy has failed for the third time, the Customer is entitled to reduce the Service Charge for the affected Service appropriately. Further claims for defects shall be excluded."},{tag:"p",text:"7.3 The Customer's rights due to defects are excluded, if the Customer has modified the Services or has not used the Services in accordance with the requirements set out in the Product Description or otherwise agreed between the parties, except if the Customer proves that the defect was not caused by such modification or non-compliance."},{tag:"p",text:"7.4 Jina AI may charge the Customer at the agreed rates for efforts and expenses incurred by Jina AI for the investigation or elimination of defects which were caused by the Customer or its delegates."},{tag:"p",text:"7.5 The limitation period for claims based on defects shall be 12 months from the occurrence of the defect, or (if the Service is subject to an acceptance) from Acceptance."},{tag:"h2",text:"8. Limitation of Liability"},{tag:"p",text:"8.1 Jina AI's liability for damages resulting from injury to life, limb or health as well as for intent, gross negligence and - insofar as applicable - in accordance with the German Product Liability Act (Produkthaftungsgesetz) shall be unlimited in accordance with the statutory provisions."},{tag:"p",text:`8.2 In cases of simple/normal negligence, Jina AI shall only be liable if essential contractual obligations ("cardinal obligations") have been breached and in these cases Jina AI's liability shall be limited to the damages which were reasonably foreseeable.`},{tag:"p",text:"8.3 Jina AI's liability pursuant to Section 8.2 shall be limited to a total maximum amount equal to 50% of the Service Charges the Customer has paid to Jina AI for the Services during the 12 months period immediately preceding the damaging event. Except in the cases set out in Section 8.1, Jina AI's liability for indirect and consequential damages (including loss of profit) shall be excluded entirely."},{tag:"p",text:"8.4 The limitations of liability set forth in this Section 8 shall apply to all claims for damages or compensation under or in relation to the Services irrespective of the legal grounds of such claims."},{tag:"p",text:"8.5 Any other liability of Jina AI shall be excluded."},{tag:"h2",text:"9. Confidentiality"},{tag:"p",text:"9.1 Each party agrees that all information received from the other party under these TCs which is (i) marked as confidential or (ii) from an objective perspective must be considered to be confidential, shall be maintained in confidence and shall not be disclosed to others. The receiving party agrees that without the prior written consent of the other party it will not use such information for any purpose other than the fulfillment of this contract."},{tag:"p",text:"9.2 Each party shall use no lesser standard of care to protect the confidentiality of information received from the other party than it uses to protect its own confidential information, and shall limit disclosure of such information to those of its group companies, personnel and consultants who have an actual need to know for purposes related to this contract and who have a written obligation to protect the confidentiality of such information."},{tag:"p",text:"9.3 Upon termination of the contract, each party will return to the other party such party's confidential information and data and will delete all copies of such information/data under its and its subcontractors' control (subject to applicable retention requirements)."},{tag:"p",text:"9.4 Jina AI shall, subject to applicable mandatory data protection requirements, be entitled to retain data uploaded to the Jina AI Systems or otherwise provided by the Customer or collected by Jina AI in the course of providing the Services and to use such data in anonymized/pseudonymized format for its business purposes including to improve its artificial intelligence applications."},{tag:"h2",text:"10. Data Protection"},{tag:"p",text:'10.1 Jina AI will comply with all applicable data protection requirements. Please see for further details the Jina AI Data Protection Policy under <a href="/legal/#privacy-policy" style="color: white">Privacy Policy</a>.'},{tag:"p",text:"10.2 Where Jina AI in providing the Services acts as a data processor pursuant to Art. 28 GDPR, Jina AI and Customer will enter into a data processing agreement in accordance with the requirements of Art. 28 GDPR."},{tag:"h2",text:"11. Term and Termination"},{tag:"p",text:"11.1 The contract between Jina AI and the Customer enters into force upon Jina AI's acceptance of the Order Form submitted by the Customer. Unless agreed otherwise in the Order Form, the contract continues to apply for an indefinite period of time. It can be terminated by each party in writing with a notice period of four (4) weeks to the end of a calendar quarter. Any ordinary termination is excluded during any minimum contract term the parties may have agreed in the Order Form."},{tag:"p",text:"11.2 Each party's statutory right to terminate this contract for good cause with immediate effect shall remain unaffected. A breach of contract shall only entitle a party to terminate the contract for good cause if the other party has breached a material obligation and \u2013 provided that the breach is curable \u2013 has failed to cure the breach within a reasonable grace period of at least twenty working days from receipt of a corresponding written warning notice served by the terminating party."},{tag:"h2",text:"12. Final Provisions"},{tag:"p",text:"12.1 Collateral agreements and amendments to these TCs must be made in writing. This also applies to a waiver of this written form requirement. Where these TCs establish a written form requirement, text form shall be sufficient unless expressly provided otherwise (e.g. by reference to Section 126 German Civil Code)."},{tag:"p",text:"12.2 Jina AI reserves the right to transfer, assign or dispose of by novation any or all rights or obligations under these T&Cs, taking the Customers\u2019 legitimate interests into account. The Customer may not assign to any third party any of its rights under the contract in whole or in part without the prior written consent of Jina AI."},{tag:"p",text:"12.3 Jina AI shall be entitled to involve subcontractors in the provision of the Services."},{tag:"p",text:"12.4 Unless agreed otherwise in the Order Form, the place of performance for Services shall be the business seat of Jina AI."},{tag:"p",text:"12.5 Offsetting and retention rights of the Customer shall be excluded. This shall not apply if its corresponding counterclaims have been confirmed by a final court order or acknowledged by Jina AI in writing."},{tag:"p",text:"12.6 Jina AI shall be entitled to update and change these TCs from time to time. In this case, Jina AI will inform the Customer of such changes with a notice period of at least six (6) weeks before such changes become effective. If the Customer does not object in writing to the changes within four (4) weeks from receipt of the notice, the changes shall be deemed approved. If the Customer objects to the changes, the changes will not become effective between Jina AI and the Customer but Jina AI shall, within four (4) weeks from receipt of the objection, be entitled to terminate this contract with a notice period of six (6) weeks to the end of a month."},{tag:"p",text:"12.7 German law shall apply, excluding its conflict of laws rules and the UNCISG. The courts competent for Berlin shall have exclusive jurisdiction over all matters relating to these TCs."},{tag:"p",text:"12.8 If any provision of these TCs should be invalid in whole or in part or if these TCs contain any omission, the effectiveness of the remaining provisions shall not be affected. The invalid or omitted provision shall be replaced with retroactive effect by an effective and enforceable provision which most closely legally and financially approximates to what the parties intended or would have intended if they had taken such invalidity into account when agreeing these TCs."},{tag:"h1",text:"Privacy Policy",id:"privacy-policy"},{tag:"h2",text:"Who we are"},{tag:"p",text:"The data controller responsible in accordance with the purposes of the General Data Protection Regulation (GDPR) of the European Union and other data protection regulations is:"},{tag:"p",text:"Jina AI GmbH"},{tag:"p",text:"Leipziger Str. 96"},{tag:"p",text:"10117 Berlin"},{tag:"p",text:"Germany"},{tag:"p",text:"030 224 88295"},{tag:"p",text:"support@jina.ai"},{tag:"p",text:"https://jina.ai/ "},{tag:"h2",text:"How to contact the data protection officer"},{tag:"p",text:"The designated data protection officer is:"},{tag:"p",text:"DataCo GmbH"},{tag:"p",text:"Dachauer Str. 65"},{tag:"p",text:"80335 Munich"},{tag:"p",text:"Germany"},{tag:"p",text:"+49 89 7400 45840"},{tag:"p",text:'<a href="https://www.dataguard.de" style="color: white">www.dataguard.de</a>'},{tag:"h2",text:"General information on data processing"},{tag:"p",text:"On this page, we provide you with information regarding the processing of your personal data on our website."},{tag:"p",text:"How we collect and use your personal data will depend on how you interact with us or the services you use. We only collect, use or share your personal data where we have a legitimate purpose and a legal basis for doing so."},{tag:"h2",text:"What do we mean by 'legal basis'?"},{tag:"p",text:"<b>Consent</b> (Art. 6(1)(a) GDPR) - You have given us your consent to process your personal data for the specific purpose we have explained to you. You have the right to withdraw your consent at any time. For further information on how to withdraw consent, please see the \u2018Exercising your rights\u2019 subsections in the subsequent sections of this Privacy Policy."},{tag:"p",text:"<b>Contract</b> (Art 6(1)(b) GDPR) - We need to use your data to fulfill a contract you have with us. Alternatively, it\u2019s necessary to use your data because we have asked you to, or you have taken yourself, specific steps before entering that contract."},{tag:"p",text:"<b>Legal Obligation</b> (Art 6(1)(c) GDPR) - We need to use your data to comply with the law."},{tag:"p",text:"<b>Vital Interests</b> (Art 6(1)(d) GDPR) - Processing your data is necessary to protect your vital interests or of another person. For example, to prevent you from serious physical harm."},{tag:"p",text:"<b>Public Task</b> (Art 6(1)(e) GDPR) - Using your data is necessary for the performance of a task carried out in the public interest, or because it is covered by a task set out in law, for example, for a statutory function."},{tag:"p",text:"<b>Legitimate Interests</b> (Art 6(1)(f) GDPR) - Processing your data is necessary to support a legitimate interest we or another party has, only where this is not outweighed by your own interests."},{tag:"p",text:"Please note where your data is processed under the performance of a contract or for a legal obligation, if you do not provide the data requested, we may be unable to provide you with our app."},{tag:"h2",text:"Data sharing and international transfers"},{tag:"p",text:"As explained throughout this Privacy Policy, we use various service providers to help us deliver our services and keep your data secure. When we use these service providers, it is necessary for us to share your personal data with them."},{tag:"p",text:"We have agreements in place with all our service providers that we share your data with that oblige them to protect your data."},{tag:"p",text:"Where your personal data is shared outside the EU, we ensure that your personal data is given an equivalent level of protection, either because the jurisdiction to which your data is transferred has an \u2018adequate\u2019 data protection standard according to the European Commission, or by using another safeguard such as an enhanced contractual agreement, i.e. Standard Contractual Clauses adopted by the European Commission (SCCs)."},{tag:"p",text:"For example, where we use US service providers, we either rely on SCCs or the EU-US Data Protection Framework, depending on the specific provider. You can request a copy of SCCs we have concluded with our service providers by sending an email to the email address provided in this Privacy Policy."},{tag:"h2",text:"Your rights"},{tag:"p",text:"When your personal data is processed, you are a data subject within the meaning of the GDPR and have the following rights:"},{tag:"h3",text:"1. Right of access (Art. 15 GDPR)"},{tag:"p",text:"You may request the data controller to confirm whether your personal data is processed by them."},{tag:"p",text:"If such processing occurs, you can request the following information from the data controller:"},{tag:"li",text:"Purposes of processing"},{tag:"li",text:"Categories of personal data being processed."},{tag:"li",text:"Recipients or categories of recipients to whom the personal data have been or will be disclosed."},{tag:"li",text:"Planned storage period or the criteria for determining this period"},{tag:"li",text:"The existence of the rights of rectification, erasure or restriction or opposition."},{tag:"li",text:"The existence of the right to lodge a complaint with a supervisory authority."},{tag:"li",text:"If applicable, origin of the data (if collected from a third party)."},{tag:"li",text:"If applicable, existence of automated decision-making including profiling with meaningful information about the logic involved, the scope and the effects to be expected."},{tag:"li",text:"If applicable, transfer of personal data to a third country or international organization."},{tag:"h3",text:"2. Right to rectification (Art. 16 GDPR)"},{tag:"p",text:"You have a right to rectification and/or modification of the data, if your processed personal data is incorrect or incomplete. The data controller must correct the data without delay."},{tag:"h3",text:"3. Right to the restriction of processing (Art. 18 GDPR)"},{tag:"p",text:"You may request the restriction of the processing of your personal data under the following conditions:"},{tag:"li",text:"If you challenge the accuracy of your personal data for a period that enables the data controller to verify the accuracy of your personal data."},{tag:"li",text:"The processing is unlawful, and you oppose the erasure of the personal data and instead request the restriction of their use instead."},{tag:"li",text:"The data controller or its representative no longer need the personal data for the purpose of processing, but you need it to assert, exercise or defend legal claims; or"},{tag:"li",text:"If you have objected to the processing pursuant and it is not yet certain whether the legitimate interests of the data controller override your interests."},{tag:"h3",text:'4. Right to erasure ("Right to be forgotten") (Art. 17 GDPR)'},{tag:"p",text:"If you request from the data controller to delete your personal data without undue delay, they are required to do so immediately if one of the following applies:"},{tag:"li",text:"Personal data concerning you is no longer necessary for the purposes for which they were collected or processed."},{tag:"li",text:"You withdraw your consent on which the processing is based pursuant to and where there is no other legal basis for processing the data."},{tag:"li",text:"You object to the processing of the data and there are no longer overriding legitimate grounds for processing, or you object pursuant to Art. 21 (2) GDPR."},{tag:"li",text:"Your personal data has been processed unlawfully."},{tag:"li",text:"The personal data must be deleted to comply with a legal obligation in Union law or Member State law to which the data controller is subject."},{tag:"li",text:"Your personal data was collected in relation to information society services offered pursuant to Art. 8 (1) GDPR."},{tag:"p",text:"The right to deletion does not exist if the processing is necessary"},{tag:"li",text:"to exercise the right to freedom of speech and information;"},{tag:"li",text:"to fulfill a legal obligation required by the law of the Union or Member States to which the data controller is subject, or to perform a task of public interest or in the exercise of public authority delegated to the representative."},{tag:"li",text:"for reasons of public interest in the field of public health."},{tag:"li",text:"for archival purposes of public interest, scientific or historical research purposes or for statistical purposes."},{tag:"li",text:"to enforce, exercise or defend legal claims."},{tag:"h3",text:"5. Right to data portability"},{tag:"p",text:"You have the right to receive your personal data given to the data controller in a structured and machine-readable format. In addition, you have the right to transfer this data to another person without hindrance by the data controller who was initially given the data."},{tag:"h3",text:"6. Right to object"},{tag:"p",text:"For reasons that arise from your particular situation, you have, at any time, the right to object to the processing of your personal data pursuant to Art. 6 (1) (e) or 6 (1) (f) GDPR; this also applies to profiling based on these provisions."},{tag:"p",text:"If the personal data relating to you are processed for direct marketing purposes, you have the right to object at any time to the processing of your personal data in regard to such advertising; this also applies to profiling associated with direct marketing."},{tag:"h3",text:"7. Right to complain to a supervisory authority"},{tag:"p",text:"Without prejudice to any other administrative or judicial remedy, you have the right to lodge a complaint with a supervisory authority if you consider that the processing of personal data concerning you infringes the GDPR. The supervisory authority to which the complaint has been lodged shall inform the complainant of the status and outcome of the complaint, including the possibility of a judicial remedy under Art. 78 GDPR. A list of the locally competent supervisory authorities in Germany can be found on the website of the Federal Commissioner for Data Protection at the following link:"},{tag:"p",text:'<a href="https://www.bfdi.bund.de/DE/Service/Anschriften/Laender/Laender-node.html" style="color: white">https://www.bfdi.bund.de/DE/Service/Anschriften/Laender/Laender-node.html</a>'},{tag:"h2",text:"Data processing when you load our website"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"Each time our website is accessed, our system automatically collects data and relevant information from the computer system of the calling device."},{tag:"p",text:"The following data is collected:"},{tag:"li",text:"Information about the browser type and the version used"},{tag:"li",text:"The user's operating system"},{tag:"li",text:"Date and time of access"},{tag:"p",text:"This data is stored in the log files of our system."},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The temporary storage of the IP address by the system is necessary for the delivery of the website to the computer of the user. For this purpose, the user\u2019s IP address must be kept for the duration of the session."},{tag:"p",text:"The storage in log files is done to ensure the functionality of the website. The data is also used to optimize the website and to ensure the security of our IT systems. An analysis of the data for marketing purposes does not take place."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The legal basis for the temporary storage of data and logfiles is Art. 6 (1) (f) GDPR."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"The data will be deleted as soon as it is no longer necessary for the purpose of its collection. The session is complete when the collection of data for the provision of the website is accomplished."},{tag:"p",text:"If the data is stored in log files, this is the case after seven days at the latest. Storage beyond this is possible. In this case, the IP addresses of the users are deleted or alienated so that an assignment of the calling client is not possible."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"The collection of data for the provision of the website and the storage of the data in log files is absolutely necessary for the operation of the website. The user can object to this. Whether the objection is successful is to be determined within the framework of a balancing of interests."},{tag:"h2",text:"Use of cookies"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"When you visit our website, we use technical tools for various functions, in particular cookies, which can be stored on your device. When you visit our website for the first time and at any time later, you have the choice of whether you generally permit the setting of cookies or which individual additional functions you would like to select. You can make changes in your browser settings or via our consent manager. Cookies are text files or information in a database that are stored on your hard drive and assigned to the browser you are using so that certain information can be passed to the entity that sets the cookie. We use technically necessary cookies, which are required for the technical structure of the website. Without these cookies, our website cannot be displayed (completely correctly) or the support functions are not possible."},{tag:"p",text:"The following data is stored and transmitted in the technical necessary cookies:"},{tag:"li",text:"Language settings"},{tag:"li",text:"Log-in information"},{tag:"li",text:"Entered search terms"},{tag:"li",text:"Frequency of page views"},{tag:"li",text:"Use of website functionalities"},{tag:"p",text:"We use cookies on our website that are not technically necessary. Technically unnecessary cookies are text files that are not only used for the functionality of the website, but also collect other data."},{tag:"p",text:"As a result, the following data will be processed:"},{tag:"li",text:"IP-address"},{tag:"li",text:"Internet user location"},{tag:"li",text:"Date and time of the website request"},{tag:"li",text:"Customization of advertisements to the user"},{tag:"li",text:"Tracking of the surfing behavior"},{tag:"li",text:"Linking the website visit with other social media platforms"},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The purpose of using technically necessary cookies is to ensure the functionality of our website. Some functions of our website cannot be offered without the use of cookies. For these, it is necessary that the browser is recognized even after a page change."},{tag:"p",text:"We need technical necessary cookies for the following purposes:"},{tag:"li",text:"Storage of language settings"},{tag:"li",text:"Storage of search queries"},{tag:"li",text:"Functionality of the website"},{tag:"p",text:"The use of technically not necessary cookies is carried out for the purpose of improving the quality of our website, its content, and thus our reach and profitability. By setting these cookies, we learn how the website is used and can thus constantly optimize our offer. These cookies serve us particularly for the following purposes:"},{tag:"li",text:"Improving the quality of our website and its content. Through the analysis cookies, we learn how the website is used and thus can constantly optimize our offer."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The regulations of the Telecommunications-Telemedia Data Protection Act (TTDSG) are relevant for the storage of information in the end user's terminal equipment and/or access to information already stored in the end user's terminal equipment. If the setting and reading of cookies is technically necessary, this is done to ensure the functionality of our website. In this case, the storage of and access to cookies on your terminal equipment is carried out on the basis of \xA7 25(2)(2) TTDSG. This storage of and access to the information in your terminal equipment serves to facilitate your use of our website and to be able to offer you our services as you have requested. Some functions of our website also do not work without the use of these cookies and could therefore not be offered. The cookies are generally deleted after the session ends (e.g. logging out or closing the browser) or after the expiry of a specified duration. Information on different storage periods for cookies can be found in the following sections of this data protection declaration."},{tag:"p",text:"As far as cookies are set that are not technically necessary, this is done on the basis of your expressed consent, which you can provide via the cookie banner. The basis for storing and accessing information in this case is \xA7 25(1) TTDSG in conjunction with. Art. 6(1)(1)(a), Art. 7 GDPR. You can withdraw your consent at any time with effect for the future or subsequently grant it again by configuring your settings for cookies accordingly. Alternatively, you can prevent the storage of cookies by making the appropriate settings in your browser software. Please note that the browser settings you make only affect the browser you are using. If personal data is processed following the storage of and access to the information on your terminal equipment, the provisions of the GDPR are relevant. Information on this can be found in the following sections of this privacy policy."},{tag:"h3",text:"4. Exercising your rights"},{tag:"p",text:"You can revoke consent to the use of cookies and manage your consent preferences at any time when you click on \u201CPrivacy Settings\u201D."},{tag:"h2",text:"Newsletter"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"You can subscribe to a newsletter on our website free of charge. When subscribing for the newsletter, the data from the input mask is transmitted to us."},{tag:"p",text:"We collect the following data from you in order to provide this service:"},{tag:"li",text:"Email address"},{tag:"p",text:"No data will be passed on to third parties in connection with data processing for the dispatch of newsletters. The data will be used exclusively for sending the newsletter."},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The user's email address is collected to deliver the newsletter to the recipient."},{tag:"p",text:"Additional personal data as part of the registration process is collected to prevent misuse of the services or email address."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The legal basis for the processing of data provided by the user after registration for the newsletter is Art. 6 (1) (a) GDPR if the user has given his consent."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"The data will be deleted as soon as it is no longer necessary to achieve the purpose for which it was collected. The user's email address will therefore be stored as long as the newsletter subscription is active."},{tag:"p",text:"The other personal data collected during the registration process is generally deleted after a period of seven days."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"The subscription for the newsletter can be cancelled by the data subject at any time. For this purpose, every newsletter contains an opt-out link."},{tag:"p",text:"Through this, it is also possible to withdraw the consent to the storage of personal data collected during the registration process."},{tag:"h2",text:"Contact via Email"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"You can contact us via the email address provided on our website. In this case, the personal data of the user transmitted with the email will be stored."},{tag:"p",text:"The data will be used exclusively for the processing of the conversation."},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"If you contact us via email, this also constitutes the necessary legitimate interest in the processing of the data."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The legal basis for the processing of data transmitted in the course of sending an e-mail is Art. 6 (1) (f) GDPR. Our legitimate interest is to optimally answer your request that you send by e-mail."},{tag:"p",text:"If the purpose of the email contact is to conclude a contract, the additional legal basis for the processing is Art. 6 (1) (b) GDPR."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"The data will be deleted as soon as it is no longer necessary to achieve the purpose for which it was collected. For personal data sent by email, this is the case when the respective conversation with the user has ended. The conversation ends when it can be concluded from the circumstances that the matter in question has been conclusively resolved."},{tag:"p",text:"The additional personal data collected during the sending process will be deleted after a period of seven days at the latest."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"You have the possibility to withdraw consent to the processing of their personal data at any time. If you contact us via email, you can object to the storage of his personal data at any time, by the following means:"},{tag:"p",text:"contact us by email, support@jina.ai"},{tag:"p",text:"In this case, all personal data stored while establishing contact will be deleted."},{tag:"h2",text:"Contact form"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"A contact form is available on our website, which can be used for electronic contact. If you make use of this option, the data entered in the contact form will be transmitted to us and stored."},{tag:"p",text:"When sending the message, the following data will also be stored:"},{tag:"li",text:"Email address"},{tag:"li",text:"Last name"},{tag:"li",text:"First name"},{tag:"li",text:"Job Title, Company Size, Company Name, and Country"},{tag:"li",text:"Date and time"},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The processing of the personal data from the form as well as if you contact us by mail serves us exclusively for the purpose of establishing contact."},{tag:"p",text:"The other personal data processed during the sending process serve to prevent misuse of the contact form and to ensure the security of our information technology systems."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The legal basis for the processing of data transmitted while sending an email is Art. 6 (1) (f) GDPR. Our legitimate interest is to provide you with the best possible response to the request you send to us via the contact form. If the purpose of the email contact is to conclude a contract, the additional legal basis for the processing is Art. 6 (1) (b) GDPR."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"The data will be deleted as soon as they are no longer necessary to achieve the purpose for which they were collected. For the personal data from the contact form and those sent by email, this is the case when the respective conversation with the user has ended. The conversation ends when it can be inferred from the circumstances that the facts in question have been conclusively clarified."},{tag:"p",text:"The additional personal data collected during the sending process will be deleted after a period of seven days at the latest."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"If you contact us via the contact form or via email, you can object to the storage of your personal data at any time, by the following means:"},{tag:"p",text:"contact us by email, support@jina.ai"},{tag:"p",text:"In this case, all personal data stored while establishing contact will be deleted."},{tag:"h2",text:"Application via Email and Form"},{tag:"p",text:"1. Description and scope of data processing"},{tag:"p",text:"There is a form on our website which can be used for electronic job applications. If an applicant makes use of this possibility, the data entered in the input mask will be transmitted to us and stored. The data is:"},{tag:"li",text:"Title"},{tag:"li",text:"Last name"},{tag:"li",text:"First name"},{tag:"li",text:"Email address"},{tag:"li",text:"Salary expectations"},{tag:"li",text:"Information on education and training"},{tag:"li",text:"Language proficiencies"},{tag:"li",text:"Curriculum Vitae"},{tag:"li",text:"Certificates"},{tag:"li",text:"Data that you send us during the application process"},{tag:"p",text:"Alternatively, you can send us your application by email. In this case, we collect your email address and the information you provide in the email."},{tag:"p",text:"After sending your application, you will receive confirmation of receipt of your application documents from us by email."},{tag:"p",text:"In addition, we offer an applicant/talent pool."},{tag:"p",text:"Your data will not be passed on to third parties. The data will be used exclusively for processing your application."},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The processing of personal data from the application form serves us solely to process your application. If you contact us by email, this also constitutes the necessary legitimate interest in the processing of the data."},{tag:"p",text:"The other personal data processed during the sending process serve to prevent misuse of the application form and to ensure the security of our information technology systems."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The legal basis for the processing of the data is the initiation of the contractual relationship at the request of the data subject, Art. 6 (1) (b) Alt. 1 GDPR and \xA7 26 (1) BDSG (Federal Act of Data Protection)."},{tag:"p",text:"The legal basis for the processing of data within the context of the applicant pool is the applicant's express consent, Art. 6 (1) (a) GDPR."},{tag:"h4",text:"4. Duration of storage"},{tag:"p",text:"After completion of the application procedure, the data will be stored for up to 6 months. Your data will be deleted after 6 months at the latest. In the case that you have given your consent for us to store your data for a further 12 months, the total storage period will be 18 months. In the event of a legal obligation, the data will be stored within the framework of the applicable provisions."},{tag:"p",text:"The additional personal data collected during the sending process will be deleted after a period of seven days at the latest."},{tag:"h2",text:"Corporate web profiles on social networks"},{tag:"p",text:"YouTube:"},{tag:"p",text:"YouTube LLC, 901 Cherry Ave., San Bruno, CA 94066, United States"},{tag:"p",text:"On our company profile we provide information and offer Youtube users the possibility of communication. If you carry out an action on our Youtube company profile (e.g. comments, contributions, likes etc.), you may make personal data (e.g. clear name or photo of your user profile) public. However, as we generally or to a large extent have no influence on the processing of your personal data by Youtube, we cannot make any binding statements regarding the purpose and scope of the processing of your data."},{tag:"p",text:"Our corporate profile in social networks is used for communication and information exchange with (potential) customers. We use the company's profile for:"},{tag:"li",text:"Products"},{tag:"li",text:"Community"},{tag:"p",text:"Publications on the company profile can contain the following content:"},{tag:"li",text:"Information about products"},{tag:"li",text:"Information about services"},{tag:"li",text:"Contact with customers"},{tag:"p",text:"Every user is free to publish personal data."},{tag:"p",text:"As far as we process your personal data in order to evaluate your online behavior, to offer you sweepstakes or to conduct lead campaigns, this is done on the basis of your express declaration of consent, Art. 6 (1) (a), Art. 7 GDPR. The legal basis for processing personal data for the purpose of communicating with customers and interested parties is Art. 6 (1) (f) GDPR. Thereby, our legitimate interest is to answer your request optimally or to be able to provide the requested information. If the aim of contacting you is to conclude a contract, the additional legal basis for the processing is Art. 6 (1) (b) GDPR."},{tag:"p",text:"The data generated on the company profile are not stored in our own systems."},{tag:"p",text:"You can object at any time to the processing of your personal data that we collect within the framework of your use of our Youtube corporate web profile and assert your rights as a data subject mentioned under IV. of this privacy policy. Please send us an informal email to support@jina.ai. For further information on the processing of your personal data by Youtube and the corresponding objection options, please click here:"},{tag:"p",text:'YouTube: <a href="https://policies.google.com/privacy?gl=DE&hl=en" style="color: white">https://policies.google.com/privacy?gl=DE&hl=en</a>'},{tag:"p",text:"Twitter:"},{tag:"p",text:"Twitter International Company, One Cumberland Place, Fenian Street, Dublin 2, Ireland"},{tag:"p",text:"On our company profile we provide information and offer Twitter users the possibility of communication. If you carry out an action on our Twitter company profile (e.g. comments, contributions, likes etc.), you may make personal data (e.g. clear name or photo of your user profile) public. However, as we generally or to a large extent have no influence on the processing of your personal data by Twitter, we cannot make any binding statements regarding the purpose and scope of the processing of your data."},{tag:"p",text:"Our corporate profile in social networks is used for communication and information exchange with (potential) customers. We use the company's profile for:"},{tag:"li",text:"Products"},{tag:"li",text:"Community"},{tag:"p",text:"Publications on the company profile can contain the following content:"},{tag:"li",text:"Information about products"},{tag:"li",text:"Information about services"},{tag:"li",text:"Contact with customers"},{tag:"p",text:"Every user is free to publish personal data."},{tag:"p",text:"As far as we process your personal data in order to evaluate your online behavior, to offer you sweepstakes or to conduct lead campaigns, this is done on the basis of your express declaration of consent, Art. 6 (1) (a), Art. 7 GDPR. The legal basis for processing personal data for the purpose of communicating with customers and interested parties is Art. 6 (1) (f) GDPR. Thereby, our legitimate interest is to answer your request optimally or to be able to provide the requested information. If the aim of contacting you is to conclude a contract, the additional legal basis for the processing is Art. 6 (1) (b) GDPR."},{tag:"p",text:"The data generated on the company profile are not stored in our own systems."},{tag:"p",text:"You can object at any time to the processing of your personal data that we collect within the framework of your use of our Twitter corporate web profile and assert your rights as a data subject mentioned under IV. of this privacy policy. Please send us an informal email to support@jina.ai. For further information on the processing of your personal data by Twitter and the corresponding objection options, please click here:"},{tag:"p",text:'Twitter: <a href="https://twitter.com/de/privacy" style="color: white">https://twitter.com/de/privacy</a>'},{tag:"h2",text:"Use of corporate profiles in professionally oriented networks"},{tag:"h3",text:"1. Scope of data processing"},{tag:"p",text:"We use corporate profiles on professionally oriented networks. We maintain a corporate presence on the following professionally oriented networks:"},{tag:"li",text:"LinkedIn"},{tag:"p",text:"On our site we provide information and offer users the possibility of communication."},{tag:"p",text:"The corporate profile is used for job applications, information, public relations, and active sourcing."},{tag:"p",text:"We do not have any information on the processing of your personal data by the companies jointly responsible for the corporate profile. Further information can be found in the privacy policy of:"},{tag:"p",text:"LinkedIn:"},{tag:"p",text:'LinkedIn:<a href="https://www.linkedin.com/legal/privacy-policy" style="color: white">https://www.linkedin.com/legal/privacy-policy</a>'},{tag:"p",text:"If you carry out an action on our company profile (e.g. comments, contributions, likes etc.), you may make personal data (e.g. clear name or photo of your user profile) public."},{tag:"h3",text:"2. Legal basis for data processing"},{tag:"p",text:"The legal basis for the processing of personal data for the purpose of communication with customers and interested parties is Art. 6 (1) (f) GDPR. Our legitimate interest is to answer your request optimally or to be able to provide the requested information. If the aim of contacting you is to conclude a contract, the additional legal basis for the processing is Art. 6 (1) (b) GDPR."},{tag:"h3",text:"3. Purpose of the data processing"},{tag:"p",text:"Our corporate web profile serves to inform users about our services. Every user is free to publish personal data."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"The data generated on the company profile are not stored in our own systems."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"You can object at any time to the processing of your personal data which we collect within the scope of your use of our corporate web profile and assert your rights as a data subject mentioned under IV. of this privacy policy. Please send us an informal email to the email address stated in this privacy policy."},{tag:"p",text:"You can find further information on objection and removal options here:"},{tag:"p",text:"LinkedIn:"},{tag:"p",text:'<a href="https://www.linkedin.com/legal/privacy-policy" style="color: white">https://www.linkedin.com/legal/privacy-policy</a>'},{tag:"h2",text:"Hosting"},{tag:"p",text:"The website is hosted on servers of a service provider commissioned by us."},{tag:"p",text:"Our service provider is:"},{tag:"p",text:"GitHub 88 Colin P Kelly Jr Street San Francisco, California 94107"},{tag:"p",text:"For further information on the processing of personal data by Github please see:"},{tag:"p",text:'<a href="https://docs.github.com/en/site-policy/privacy-policies/github-privacy-statement" style="color: white">https://docs.github.com/en/site-policy/privacy-policies/github-privacy-statement</a>'},{tag:"p",text:"The servers automatically collect and store information in so-called server log files, which your browser automatically transmits when you visit the website. The stored information is:"},{tag:"li",text:"Information about the browser type and the version used"},{tag:"li",text:"The user's operating system"},{tag:"li",text:"Date and time of access"},{tag:"li",text:"The Internet service provider of the user"},{tag:"li",text:"Websites from which the user's system accessed our website"},{tag:"li",text:"Websites the user's system accessed through our website"},{tag:"li",text:"IP address of the user's device"},{tag:"p",text:"This data will not be merged with other data sources. The data is collected on the basis of Art. 6 (1) (f) GDPR. The website operator has a legitimate interest in the technically error-free presentation and optimization of his website -and server log files are therefore recorded."},{tag:"p",text:"The server of the website is geographically located in the USA."},{tag:"p",text:"The Service Provider complies with the EU-U.S. Data Privacy Framework (EU-U.S. DPF) as set forth by the U.S. Department of Commerce and has certified that it adheres to the EU-U.S. Data Privacy Framework Principles (EU-U.S. DPF Principles) when processing personal data received from the European Union in reliance on the EU-U.S. DPF. More information can be found in at:"},{tag:"p",text:'<a href="https://www.dataprivacyframework.gov/s/participant-search/participant-detail?id=a2z3d0000001wwUAAQ&status=Active" style="color: white">https://www.dataprivacyframework.gov/s/participant-search/participant-detail?id=a2z3d0000001wwUAAQ&status=Active</a>'},{tag:"h2",text:"Geotargeting"},{tag:"p",text:'We use the IP address and other information provided by the user (e.g. the postal code used for registration or ordering) to approach regional target groups (so-called "geotargeting").'},{tag:"p",text:"The regional target group approach is used, for example, to automatically display regional offers or advertisements that often are more relevant to users. The legal basis for the use of the IP address and any other information provided by the user (e.g. postal code) is Art. 6 (1) (f) GDPR, based on our legitimate interest in ensuring a more precise target group approach and thus providing offers and advertising with greater relevance for our users."},{tag:"p",text:"Part of the IP address and the additional information provided by the user (e.g. postal code) are merely processed and not stored separately."},{tag:"p",text:"You can prevent geotargeting by, for example, using a VPN or proxy server that prevents accurate localization. In addition, depending on the browser you are using, you can also deactivate a location localization in the corresponding browser settings (as far as this is supported by the respective browser)."},{tag:"p",text:"We use geotargeting on our website for the following purposes:"},{tag:"li",text:"Products"},{tag:"h2",text:"Registration"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"We offer users the opportunity to register by providing personal data. The data is entered into a form and transmitted to us and stored. The following data is collected as part of the registration process:"},{tag:"li",text:"Email address"},{tag:"p",text:"As part of the registration process, your consent to the processing of this data is obtained."},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"A registration of the user is necessary for the fulfilment of a contract with the user or for the execution of pre-contractual measures."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The legal basis for the processing of the data is Art. 6 (1) (a) GDPR where you have provided consent."},{tag:"p",text:"The legal basis for the processing of registration data necessary to conclude or fulfil a contract with you is Art. 6 (1) (b) GDPR."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"The data will be deleted as soon as it is no longer necessary to achieve the purpose for which it was collected."},{tag:"p",text:"This is the case for the data collected during the registration process for the execution of a contract or for the implementation of pre-contractual measures if the data is no longer required for the execution of the contract. Even after the conclusion of the contract, it may be necessary to store personal data of the contractual partner in order to comply with contractual or legal obligations."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"As a user you have the possibility to cancel the registration at any time. You can request a change to the data stored about you at any time, by the following means:"},{tag:"p",text:"The user should reach out to our support team at support@jina.ai to delete their account or change their data."},{tag:"p",text:"If the data is necessary for the fulfilment of a contract or for the implementation of pre-contractual measures, a premature deletion of the data is only possible insofar as contractual or legal obligations do not stand in the way of a deletion."},{tag:"h2",text:"Content Delivery Networks"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"On our website we use functions of the content delivery network CloudFlare of CloudFlare Germany GmbH, Rosental 7, 80331 Munich, Germany (Hereinafter referred to as CloudFlare). A Content Delivery Network (CDN) is a network of regionally distributed servers connected via the Internet to deliver content, especially large media files such as videos. CloudFlare offers web optimization and security services that we use to improve the load times of our website and to protect it from misuse. When you visit our website you will be connected to the servers of CloudFlare, e.g. to retrieve content. This allows personal data to be stored and evaluated in server log files, the user's activity (e.g. which pages have been visited) and device and browser information (e.g. IP address and operating system). Further information on the collection and storage of data by CloudFlare can be found here:"},{tag:"p",text:'<a href="https://www.cloudflare.com/en-gb/privacypolicy/" style="color: white">https://www.cloudflare.com/en-gb/privacypolicy/</a>'},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The use of CloudFlare's features serves to deliver and accelerate online applications and content."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The data is collected on the basis of Art. 6 (1) (f) GDPR. The website operator has a legitimate interest in the technically error-free presentation and optimization of his website -and the server log files are therefore recorded."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"Your personal information will be retained for as long as necessary to fulfil the purposes described in this Privacy Policy or as required by law."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"Information about objection and removal options regarding CloudFlare can be found at:"},{tag:"p",text:'<a href="https://www.cloudflare.com/en-gb/privacypolicy/" style="color: white">https://www.cloudflare.com/en-gb/privacypolicy/</a>'},{tag:"h2",text:"Integrated third-party services"},{tag:"p",text:"We use various service providers to deliver the service we offer through the app."},{tag:"p",text:"Generally, where such services are essential to providing the basic service offered by the website, we have a legitimate interest in sharing your data with the relevant service providers in order to provide the relevant website service."},{tag:"p",text:"Where such services are required for additional services, enhanced functionalities, or additional purposes, your personal data will only be transferred to service providers if you provide consent."},{tag:"table",id:"Integrated third-party services",columns:[{name:"Service name",label:"Service name",align:"left",field:"service_name"},{name:"Company",label:"Company",align:"left",field:"company"},{name:"Location",label:"Location",align:"left",field:"location"},{name:"Purpose",label:"Purpose",align:"left",field:"purpose"},{name:"Reference",label:"Reference",align:"left",field:"reference"},{name:"Link",label:"Link",align:"left",field:"link"}],rows:[{service_name:"Google Tag Manager",company:"Google Ireland Ltd.",location:"Irland (USA)",purpose:"Tag configuration and integration of Google services",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://policies.google.com/privacy?gl=DE&hl=de https://business.safety.google/gdpr/"},{service_name:"Google Webfonts",company:"Google Ireland Ltd.",location:"Irland (USA)",purpose:"Fonts",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://policies.google.com/privacy?gl=DE&hl=de https://business.safety.google/gdpr/"},{service_name:"Google ReCaptcha",company:"Google Ireland Ltd.",location:"Irland (USA)",purpose:"Bot Protection",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://policies.google.com/privacy?gl=DE&hl=de https://business.safety.google/gdpr/"},{service_name:"Google Ads Remarketing",company:"Google Ireland Ltd.",location:"Irland (USA)",purpose:"Marketing / Tracking",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://policies.google.com/privacy?gl=DE&hl=de https://business.safety.google/gdpr/"},{service_name:"Google AdWords",company:"Google Ireland Ltd.",location:"Irland (USA)",purpose:"Marketing",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://policies.google.com/privacy?gl=DE&hl=de https://business.safety.google/gdpr/"},{service_name:"Google Analytics",company:"Google Ireland Ltd.",location:"Irland (USA)",purpose:"Analytic",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://policies.google.com/privacy?gl=DE&hl=de https://business.safety.google/gdpr/"},{service_name:"Hotjar",company:"Hotjar Ltd",location:"Malta*",purpose:"Tracking",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://www.hotjar.com/legal/policies/privacy/de/"},{service_name:"HubSpot",company:"HubSpot Inc.",location:"USA",purpose:"Customer surveys",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://legal.hubspot.com/de/privacy-policy"},{service_name:"LinkedIn",company:"LinkedIn Ireland Unlimited Company",location:"Irland (USA)",purpose:"Branding, Recruitment, Marketing and Community Building",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://www.linkedin.com/legal/privacy-policy?_l=de_DE https://de.linkedin.com/legal/l/dpa"},{service_name:"MailChimp",company:"The Rocket Science Group",location:"USA",purpose:"Email marketing, newsletter deployment, customer communication",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://mailchimp.com/en-gb/legal/cookies/#Why_do_we_use_cookies_and_other_tracking_technologies%3F https://mailchimp.com/en-gb/gdpr/"},{service_name:"Twitter",company:"Twitter International Company",location:"Irland (USA)",purpose:"Branding, Communication,Marketing and Community Building",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://twitter.com/de/privacy https://help.twitter.com/de/rules-and-policies/global-operations-and-data-transfer"},{service_name:"YouTube",company:"YouTube LLC",location:"USA",purpose:"Video embedding",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://policies.google.com/privacy?gl=DE&hl=de https://business.safety.google/gdpr/"},{service_name:"Usercentrics",company:"Usercentrics GmbH",location:"Deutschland*",purpose:"Consent management, compliance with legal requirements",reference:"Art. 6 para. 1 p. 1 lit. f GDPR",link:"https://usercentrics.com/de/datenschutzerklaerung/"},{service_name:"Discord",company:"Discord Inc.",location:"USA",purpose:"Community building, customer support, marketing",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://discord.com/privacy"},{service_name:"Github",company:"GitHub",location:"USA",purpose:"Community building, Facilitate downloads and use",reference:"Art. 6 para. 1 p. 1 lit. f GDPR",link:"https://docs.github.com/en/site-policy/privacy-policies/github-privacy-statement"},{service_name:"Meetup",company:"Meetup LLC",location:"Ireland",purpose:"Branding and community building",reference:"Art. 6 para. 1 p. 1 lit. f GDPR",link:"https://help.meetup.com/hc/en-us/articles/360044422391-Privacy-Policy/?urlkey=help&topic=help&__topic_subdomain=1"},{service_name:"WeChat Official Account",company:"WeChat International Pte. Ltd.	/ Tencent International Services Europe BV",location:"Singapore / Netherlands",purpose:"Branding, Recruitment, Marketing and Community Building",reference:"Art. 6 para. 1 p. 1 lit. f GDPR",link:"https://www.wechat.com/en/privacy_policy.html"}]},{tag:"h2",text:"Integration of Third-Party Services via External Service Providers"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"We integrate certain plugins on our website via external service providers in the form of content delivery networks. When you access our website, a connection is established to the servers of the providers used by us to retrieve content and store it in the cache of the user's browser. This allows personal data to be stored and evaluated in server log files, in particular device and browser information (e.g. IP address and operating system). We use the following services:"},{tag:"li",text:"Google Hosted Libraries"},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The use of the functions of these services serves the delivery and acceleration of online applications and content."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"This data is collected on the basis of Art. 6 (1) (f) GDPR. The website operator has a justified interest in the technically correct presentation and optimization of the website."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"Your personal information will be retained for as long as necessary to fulfil the purposes described in this Privacy Policy or as required by law."},{tag:"h3",text:"5. 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+import{e as A,bs as C,u as T,a6 as k,K as P,bt as m,a7 as r,a8 as i,a9 as o,az as t,aB as S,ai as a,ab as s,aa as n,ak as h,ac as y,ad as D,ae as G,bw as J,ah as c,af as b,j as R,bx as _}from"./index.ae19b4cb.js";import{Q as q}from"./QList.8bff8777.js";import{Q as F,a as L}from"./QTable.ea86ce71.js";import{Q as j}from"./QPage.785c0d26.js";import{_ as E}from"./plugin-vue_export-helper.21dcd24c.js";import"./QSelect.ec7f4034.js";import"./QChip.1a7b8095.js";import"./QItemLabel.737cbb7d.js";import"./QMenu.d7b6411c.js";import"./position-engine.2f7193db.js";import"./selection.10af5b4d.js";import"./format.988231da.js";import"./use-fullscreen.324b1ba3.js";const l={title:"Legal Information",subTitle:"Last Modified: Oct 26 2023",menus:[{label:"Terms and Conditions",link:"#terms-and-conditions"},{label:"Privacy Policy",link:"#privacy-policy"},{label:"Imprint",link:"#Imprint"}],content:[{tag:"h1",text:"Terms and Conditions",id:"terms-and-conditions"},{tag:"h2",text:"1. Scope and Subject Matter"},{tag:"p",text:'1.1 These terms and conditions (hereinafter referred to as "TCs") govern the legal relationship between you (the \u201CCustomer\u201D or \u201Cyou\u201D) and Jina AI GmbH, Leipziger Stra\xDFe 96, 10117 Berlin, Germany ("Jina AI", \u201Cwe\u201D or \u201Cus\u201D) when you access and use our services, including any content, functionality, software, application programming interface, tool, data, documentation, websites and services offered on or through Jina AI (the \u201CServices\u201D). These TCs shall apply exclusively; deviating Customer terms shall not apply except if we have expressly confirmed their application in writing.'},{tag:"p",text:"1.2 These TCs (as updated from time to time) shall also govern all future transactions between you and us."},{tag:"p",text:'1.3 The Services to be provided by Jina AI are set out in product descriptions (the \u201CProduct Descriptions\u201D as updated from time to time) in the online ordering pages (for Services ordered through our website, the \u201COnline Services\u201D) or a separate written order form which has been agreed between the Parties (together the "Order Form"). The Order Form has precedence over the terms of these TCs.'},{tag:"p",text:"1.4 The Order Form submitted by the Customer to Jina AI shall constitute a binding offer to enter into a contract with Jina AI on the provision of the Services identified in the Order Form. Jina AI can accept such offer (and thereby establish a binding contract) by providing the Customer with a corresponding order confirmation or by way of allowing the Customer the use of the Services online in case of Online Services."},{tag:"h2",text:"2. Registration and Access"},{tag:"p",text:"2.1 To use the Services Customers must register with Jina AI and create an account, providing all required data and information in an accurate and complete manner."},{tag:"p",text:"2.2 By registering, Customers agree to be fully responsible for all activities conducted through their account or using their access credentials."},{tag:"p",text:"2.3 Jina AI reserves the right, at its own discretion, to suspend or delete at any time and without notice, Customer accounts which it deems inappropriate, offensive or in violation of these TCs."},{tag:"h2",text:"3. Services of Jina AI"},{tag:"p",text:"3.1 Jina AI will provide the Services as specified in the Order Form and in accordance with the respective Product Description. Jina AI shall be entitled to determine the manner and means of performing and providing the Services at its own reasonable discretion, provided that the Services shall meet the material requirements as set out in the Product Description. Unless expressly agreed otherwise in the Order Form, the statutory terms for works contracts shall not apply to the Services and they shall not be subject to an acceptance procedure."},{tag:"p",text:"3.2 Unless expressly agreed otherwise in the Order Form, the Services are standard services which Jina AI makes available in a standard format to multiple Customers. Jina AI may from time to time improve, modify, extend and enhance the Services (while retaining their core functions as specified in the Product Description). In that case, Jina AI will update the Product Description accordingly and notify the Customer of such changes reasonably in advance of their implementation."},{tag:"p",text:"3.3 Dates and time periods set out in the Order Form or communicated otherwise by Jina AI are non-binding estimates unless it is expressly agreed between the parties in text form that they are binding."},{tag:"p",text:'3.4 Jina AI may temporarily suspend the Customer\u2019s access to the Services if and in so far as Jina AI reasonably considers such suspension to be required to stop or reduce a material risk to the Services or the Jina AI platforms or systems used to provide the Services (the "Jina AI Systems") or any Customer systems or data. Jina AI will inform the Customer of such suspension without undue delay and will reinstate the Customer\u2019s access to the Services as soon as the risk does no longer apply.'},{tag:"p",text:"3.5 The Services of Jina AI are designed only as a tool using artificial intelligence. No specific Output are owed by Jina AI to the user when using the Services. The Services do not claim to meet all Customer expectations for every situation. The Output made available to the user when using the Services therefore do not claim to be complete, accurate or true. Any of such Output must therefore be reviewed by the Customer for its use case and the Output does not replace the Customer's own considerations, evaluations and actions."},{tag:"h2",text:"4. Intellectual Property Rights"},{tag:"p",text:"4.1 All software, data bases, documents, information, algorithms, processes, prototypes, ideas, knowhow, patents, trademarks or other work results (\u201CIP\u201D) used by Jina AI to provide the Services or made available to the Customer by Jina AI are owned by Jina AI or its licensors (\u201CJina AI IP\u201D). Jina AI does not grant any licenses in the Jina AI IP or any other rights to use the Jina AI IP to the Customer."},{tag:"p",text:"4.2 Where Jina AI as part of its Services makes Jina AI IP available to the Customer, Jina AI grants the Customer (subject to the payment of the Service Charges, cf. Section 6 of these TCs) a non-exclusive, non-sublicensable, non-transferable, revocable and limited right to use such Jina AI IP strictly for the purpose of using the Services agreed in an Order Form and for the term set out in Section 11. Any other rights of the Customer in the Jina AI IP are excluded. Nothing in these TCs shall limit or exclude Jina AI's right to use the Jina AI IP or any other materials developed, used or provided by Jina AI under these TCs for its own business purposes or for other customers."},{tag:"p",text:"4.3 Where as an outcome of the Customer\u2019s use of the Services certain results (e.g. pictures, text, software, graphics, presentations, documents, data, works of art, or IP) are created through the Services (collectively, the \u201COutput\u201D), Jina AI (except as expressly stated otherwise herein) claims no rights to such Output and imposes no restrictions on the Customer regarding the use of the Output unless otherwise agreed in an agreement with the Customer. The Customer shall be responsible for such Output and its compliance with applicable law and applicable third party rights. In particular, Jina AI does not warrant that any Output is free of, or does not infringe, third party rights."},{tag:"p",text:"4.4 The Customer must ensure that any information, pictures, text, software, graphics, presentations, documents, work results, IP or other data the Customer provides in the course of using the Services (collectively \u201CInput\u201D), e.g. Input that the Customer uploads to Jina AI or processes through the Services, comply with all applicable laws and regulations, the terms of these TCs, and are not illegal, immoral or defamatory (e.g. do not include defamatory, pornographic, racist or violent content). The Customer confirms and commits that the Input and its use with the Services does not infringe any third party intellectual property or privacy rights and that the Customer is entitled to use the Input with the Services. If the Customer breaches its obligations under this Section 4.4, Jina AI may remove, delete or block the Input at its own discretion and, without prior notice, deny the Customer access to the Services."},{tag:"p",text:"4.5 Customers must not (i) reverse engineer, decompile, translate or otherwise attempt to discover the source code or underlying components of the Services or Jina AI\u2019s IP (except to the extent permitted under applicable mandatory law); (ii) use the Services in a way that infringes, misappropriates or violates any third party rights; (iii) use any Output from the Services to develop applications or services that compete with the Services offered by Jina AI; or (iv) use automated methods to extract information, data or result from the JINA-AI website or the Services, including by means of scraping, harvesting, or web data extraction."},{tag:"p",text:"4.6 Unless agreed otherwise (e.g. in these TCs) Jina AI will only store Input or Output on its servers to the extent required to provide the Services."},{tag:"p",text:"4.7 In the provision of the Services (and without prejudice to Section 4.2 above), Jina AI may use open source software components which may be subject to specific open sources license terms. Where relevant for the Customer, Jina AI will disclose such open source license terms to the Customer."},{tag:"h2",text:"5. Customer Obligations"},{tag:"p",text:"5.1 The Customer shall use the Services solely for the purposes established in the respective Order Form and Product Description."},{tag:"p",text:"5.2 The Customer shall reasonably support Jina AI in the provision of the Services as further set out in the Product Description. In addition, the Customer shall provide Jina AI with access to Customer's information, data, systems, personnel and premises as reasonably required by Jina AI for the provision of the Services. The Customer shall make decisions and provide feedback relating to the Services within a reasonable time period after receipt of a corresponding request by Jina AI."},{tag:"p",text:"5.3 Where to use the Services the Customer needs to connect to Jina AI Systems or platforms the Customer is responsible for establishing and maintaining the data connection between the interface of the relevant Jina AI Systems to the internet and the Customer\u2019s systems."},{tag:"p",text:"5.4 If the Customer fails to perform the Customer obligations, then the obligations of Jina AI which cannot be rendered without such Customer performance (or only by incurring disproportionate additional expenses) shall be suspended for the duration of such default and a reasonable start-up period. Additional expenses reasonably incurred by Jina AI shall be reimbursed by the Customer on a time and material basis applying the rates set out in the Order Form."},{tag:"h2",text:"6. Service Charges, Terms of Payment and Credits"},{tag:"p",text:'6.1 The Customer shall pay the fees for the Services as set out in the Order Form ("Service Charges"). Unless stated otherwise in the Order Form are exclusive of applicable VAT which the customer shall pay in addition to the Service Charges.'},{tag:"p",text:"6.2 Jina AI will invoice recurring lump sum Service Charges in advance prior to the beginning of the time period to which they relate (\u201DService Period\u201D). If applicable, Service Charges for time & material services will be invoiced monthly in arrears."},{tag:"p",text:"6.3 If applicable, expenses and disbursements shall be invoiced additionally in accordance with the principles set out in the Order Form. Where Service Charges are invoiced on a time & material basis, Jina AI will charge units of 15 minutes; travel time shall be chargeable as working time."},{tag:"p",text:"6.4 Unless otherwise agreed in the Order Form, invoices are due for payment within 14 days of receipt of the invoice by the Customer."},{tag:"p",text:"6.5 For certain Services the Customer receives from Jina AI a specific number of credits as set out in the Order Form (\u201CCredits\u201D). The Customer may use these Credits for obtaining Services during the respective Service Period. The Customer may roll over remaining Credits to the next Service Period, unless expressly agreed otherwise in the Order Form. If the Credits are used up, the Customer can purchase additional Credits; details are set out in the Order Form. The credits purchased by the client are not refundable nor exchangeable. The Credit System and the measurement of individual Credits may differ depending on the type of Service."},{tag:"h2",text:"7. Defects"},{tag:"p",text:"7.1 Services provided by Jina AI will essentially comply with the description in the Order Form and the Product Description. However, the Services are subject to continuous modification and improvement. The parties therefore agree that the Services may contain errors and malfunctions and that they may not comply in all aspects with general market standards, public statements, announcements or advertisements by Jina AI. Jina AI provides the Services to Customer \u201Cas is\u201D and except as expressly set out otherwise herein, the statutory liability for defects shall be excluded. The Customer acknowledges that the Services may not be fit for the purpose intended by the Customer, and that the Customer, being aware of this, uses the Services in its own responsibility and at its own risk."},{tag:"p",text:"7.2 If the Customer detects any defects in the Services, it shall notify Jina AI (in writing or text form) thereof without undue delay and shall provide a comprehensive description of the defects and the time and circumstances of their occurrence. Jina AI will use reasonable commercial efforts to (in its sole discretion) either remedy/correct the defect (if reasonable) or provide the affected Service (or part of the Service) again without defects and at no extra charge to the Customer. If an attempted remedy has failed for the third time, the Customer is entitled to reduce the Service Charge for the affected Service appropriately. Further claims for defects shall be excluded."},{tag:"p",text:"7.3 The Customer's rights due to defects are excluded, if the Customer has modified the Services or has not used the Services in accordance with the requirements set out in the Product Description or otherwise agreed between the parties, except if the Customer proves that the defect was not caused by such modification or non-compliance."},{tag:"p",text:"7.4 Jina AI may charge the Customer at the agreed rates for efforts and expenses incurred by Jina AI for the investigation or elimination of defects which were caused by the Customer or its delegates."},{tag:"p",text:"7.5 The limitation period for claims based on defects shall be 12 months from the occurrence of the defect, or (if the Service is subject to an acceptance) from Acceptance."},{tag:"h2",text:"8. Limitation of Liability"},{tag:"p",text:"8.1 Jina AI's liability for damages resulting from injury to life, limb or health as well as for intent, gross negligence and - insofar as applicable - in accordance with the German Product Liability Act (Produkthaftungsgesetz) shall be unlimited in accordance with the statutory provisions."},{tag:"p",text:`8.2 In cases of simple/normal negligence, Jina AI shall only be liable if essential contractual obligations ("cardinal obligations") have been breached and in these cases Jina AI's liability shall be limited to the damages which were reasonably foreseeable.`},{tag:"p",text:"8.3 Jina AI's liability pursuant to Section 8.2 shall be limited to a total maximum amount equal to 50% of the Service Charges the Customer has paid to Jina AI for the Services during the 12 months period immediately preceding the damaging event. Except in the cases set out in Section 8.1, Jina AI's liability for indirect and consequential damages (including loss of profit) shall be excluded entirely."},{tag:"p",text:"8.4 The limitations of liability set forth in this Section 8 shall apply to all claims for damages or compensation under or in relation to the Services irrespective of the legal grounds of such claims."},{tag:"p",text:"8.5 Any other liability of Jina AI shall be excluded."},{tag:"h2",text:"9. Confidentiality"},{tag:"p",text:"9.1 Each party agrees that all information received from the other party under these TCs which is (i) marked as confidential or (ii) from an objective perspective must be considered to be confidential, shall be maintained in confidence and shall not be disclosed to others. The receiving party agrees that without the prior written consent of the other party it will not use such information for any purpose other than the fulfillment of this contract."},{tag:"p",text:"9.2 Each party shall use no lesser standard of care to protect the confidentiality of information received from the other party than it uses to protect its own confidential information, and shall limit disclosure of such information to those of its group companies, personnel and consultants who have an actual need to know for purposes related to this contract and who have a written obligation to protect the confidentiality of such information."},{tag:"p",text:"9.3 Upon termination of the contract, each party will return to the other party such party's confidential information and data and will delete all copies of such information/data under its and its subcontractors' control (subject to applicable retention requirements)."},{tag:"p",text:"9.4 Jina AI shall, subject to applicable mandatory data protection requirements, be entitled to retain data uploaded to the Jina AI Systems or otherwise provided by the Customer or collected by Jina AI in the course of providing the Services and to use such data in anonymized/pseudonymized format for its business purposes including to improve its artificial intelligence applications."},{tag:"h2",text:"10. Data Protection"},{tag:"p",text:'10.1 Jina AI will comply with all applicable data protection requirements. Please see for further details the Jina AI Data Protection Policy under <a href="/legal/#privacy-policy" style="color: white">Privacy Policy</a>.'},{tag:"p",text:"10.2 Where Jina AI in providing the Services acts as a data processor pursuant to Art. 28 GDPR, Jina AI and Customer will enter into a data processing agreement in accordance with the requirements of Art. 28 GDPR."},{tag:"h2",text:"11. Term and Termination"},{tag:"p",text:"11.1 The contract between Jina AI and the Customer enters into force upon Jina AI's acceptance of the Order Form submitted by the Customer. Unless agreed otherwise in the Order Form, the contract continues to apply for an indefinite period of time. It can be terminated by each party in writing with a notice period of four (4) weeks to the end of a calendar quarter. Any ordinary termination is excluded during any minimum contract term the parties may have agreed in the Order Form."},{tag:"p",text:"11.2 Each party's statutory right to terminate this contract for good cause with immediate effect shall remain unaffected. A breach of contract shall only entitle a party to terminate the contract for good cause if the other party has breached a material obligation and \u2013 provided that the breach is curable \u2013 has failed to cure the breach within a reasonable grace period of at least twenty working days from receipt of a corresponding written warning notice served by the terminating party."},{tag:"h2",text:"12. Final Provisions"},{tag:"p",text:"12.1 Collateral agreements and amendments to these TCs must be made in writing. This also applies to a waiver of this written form requirement. Where these TCs establish a written form requirement, text form shall be sufficient unless expressly provided otherwise (e.g. by reference to Section 126 German Civil Code)."},{tag:"p",text:"12.2 Jina AI reserves the right to transfer, assign or dispose of by novation any or all rights or obligations under these T&Cs, taking the Customers\u2019 legitimate interests into account. The Customer may not assign to any third party any of its rights under the contract in whole or in part without the prior written consent of Jina AI."},{tag:"p",text:"12.3 Jina AI shall be entitled to involve subcontractors in the provision of the Services."},{tag:"p",text:"12.4 Unless agreed otherwise in the Order Form, the place of performance for Services shall be the business seat of Jina AI."},{tag:"p",text:"12.5 Offsetting and retention rights of the Customer shall be excluded. This shall not apply if its corresponding counterclaims have been confirmed by a final court order or acknowledged by Jina AI in writing."},{tag:"p",text:"12.6 Jina AI shall be entitled to update and change these TCs from time to time. In this case, Jina AI will inform the Customer of such changes with a notice period of at least six (6) weeks before such changes become effective. If the Customer does not object in writing to the changes within four (4) weeks from receipt of the notice, the changes shall be deemed approved. If the Customer objects to the changes, the changes will not become effective between Jina AI and the Customer but Jina AI shall, within four (4) weeks from receipt of the objection, be entitled to terminate this contract with a notice period of six (6) weeks to the end of a month."},{tag:"p",text:"12.7 German law shall apply, excluding its conflict of laws rules and the UNCISG. The courts competent for Berlin shall have exclusive jurisdiction over all matters relating to these TCs."},{tag:"p",text:"12.8 If any provision of these TCs should be invalid in whole or in part or if these TCs contain any omission, the effectiveness of the remaining provisions shall not be affected. The invalid or omitted provision shall be replaced with retroactive effect by an effective and enforceable provision which most closely legally and financially approximates to what the parties intended or would have intended if they had taken such invalidity into account when agreeing these TCs."},{tag:"h1",text:"Privacy Policy",id:"privacy-policy"},{tag:"h2",text:"Who we are"},{tag:"p",text:"The data controller responsible in accordance with the purposes of the General Data Protection Regulation (GDPR) of the European Union and other data protection regulations is:"},{tag:"p",text:"Jina AI GmbH"},{tag:"p",text:"Leipziger Str. 96"},{tag:"p",text:"10117 Berlin"},{tag:"p",text:"Germany"},{tag:"p",text:"030 224 88295"},{tag:"p",text:"support@jina.ai"},{tag:"p",text:"https://jina.ai/ "},{tag:"h2",text:"How to contact the data protection officer"},{tag:"p",text:"The designated data protection officer is:"},{tag:"p",text:"DataCo GmbH"},{tag:"p",text:"Dachauer Str. 65"},{tag:"p",text:"80335 Munich"},{tag:"p",text:"Germany"},{tag:"p",text:"+49 89 7400 45840"},{tag:"p",text:'<a href="https://www.dataguard.de" style="color: white">www.dataguard.de</a>'},{tag:"h2",text:"General information on data processing"},{tag:"p",text:"On this page, we provide you with information regarding the processing of your personal data on our website."},{tag:"p",text:"How we collect and use your personal data will depend on how you interact with us or the services you use. We only collect, use or share your personal data where we have a legitimate purpose and a legal basis for doing so."},{tag:"h2",text:"What do we mean by 'legal basis'?"},{tag:"p",text:"<b>Consent</b> (Art. 6(1)(a) GDPR) - You have given us your consent to process your personal data for the specific purpose we have explained to you. You have the right to withdraw your consent at any time. For further information on how to withdraw consent, please see the \u2018Exercising your rights\u2019 subsections in the subsequent sections of this Privacy Policy."},{tag:"p",text:"<b>Contract</b> (Art 6(1)(b) GDPR) - We need to use your data to fulfill a contract you have with us. Alternatively, it\u2019s necessary to use your data because we have asked you to, or you have taken yourself, specific steps before entering that contract."},{tag:"p",text:"<b>Legal Obligation</b> (Art 6(1)(c) GDPR) - We need to use your data to comply with the law."},{tag:"p",text:"<b>Vital Interests</b> (Art 6(1)(d) GDPR) - Processing your data is necessary to protect your vital interests or of another person. For example, to prevent you from serious physical harm."},{tag:"p",text:"<b>Public Task</b> (Art 6(1)(e) GDPR) - Using your data is necessary for the performance of a task carried out in the public interest, or because it is covered by a task set out in law, for example, for a statutory function."},{tag:"p",text:"<b>Legitimate Interests</b> (Art 6(1)(f) GDPR) - Processing your data is necessary to support a legitimate interest we or another party has, only where this is not outweighed by your own interests."},{tag:"p",text:"Please note where your data is processed under the performance of a contract or for a legal obligation, if you do not provide the data requested, we may be unable to provide you with our app."},{tag:"h2",text:"Data sharing and international transfers"},{tag:"p",text:"As explained throughout this Privacy Policy, we use various service providers to help us deliver our services and keep your data secure. When we use these service providers, it is necessary for us to share your personal data with them."},{tag:"p",text:"We have agreements in place with all our service providers that we share your data with that oblige them to protect your data."},{tag:"p",text:"Where your personal data is shared outside the EU, we ensure that your personal data is given an equivalent level of protection, either because the jurisdiction to which your data is transferred has an \u2018adequate\u2019 data protection standard according to the European Commission, or by using another safeguard such as an enhanced contractual agreement, i.e. Standard Contractual Clauses adopted by the European Commission (SCCs)."},{tag:"p",text:"For example, where we use US service providers, we either rely on SCCs or the EU-US Data Protection Framework, depending on the specific provider. You can request a copy of SCCs we have concluded with our service providers by sending an email to the email address provided in this Privacy Policy."},{tag:"h2",text:"Your rights"},{tag:"p",text:"When your personal data is processed, you are a data subject within the meaning of the GDPR and have the following rights:"},{tag:"h3",text:"1. Right of access (Art. 15 GDPR)"},{tag:"p",text:"You may request the data controller to confirm whether your personal data is processed by them."},{tag:"p",text:"If such processing occurs, you can request the following information from the data controller:"},{tag:"li",text:"Purposes of processing"},{tag:"li",text:"Categories of personal data being processed."},{tag:"li",text:"Recipients or categories of recipients to whom the personal data have been or will be disclosed."},{tag:"li",text:"Planned storage period or the criteria for determining this period"},{tag:"li",text:"The existence of the rights of rectification, erasure or restriction or opposition."},{tag:"li",text:"The existence of the right to lodge a complaint with a supervisory authority."},{tag:"li",text:"If applicable, origin of the data (if collected from a third party)."},{tag:"li",text:"If applicable, existence of automated decision-making including profiling with meaningful information about the logic involved, the scope and the effects to be expected."},{tag:"li",text:"If applicable, transfer of personal data to a third country or international organization."},{tag:"h3",text:"2. Right to rectification (Art. 16 GDPR)"},{tag:"p",text:"You have a right to rectification and/or modification of the data, if your processed personal data is incorrect or incomplete. The data controller must correct the data without delay."},{tag:"h3",text:"3. Right to the restriction of processing (Art. 18 GDPR)"},{tag:"p",text:"You may request the restriction of the processing of your personal data under the following conditions:"},{tag:"li",text:"If you challenge the accuracy of your personal data for a period that enables the data controller to verify the accuracy of your personal data."},{tag:"li",text:"The processing is unlawful, and you oppose the erasure of the personal data and instead request the restriction of their use instead."},{tag:"li",text:"The data controller or its representative no longer need the personal data for the purpose of processing, but you need it to assert, exercise or defend legal claims; or"},{tag:"li",text:"If you have objected to the processing pursuant and it is not yet certain whether the legitimate interests of the data controller override your interests."},{tag:"h3",text:'4. Right to erasure ("Right to be forgotten") (Art. 17 GDPR)'},{tag:"p",text:"If you request from the data controller to delete your personal data without undue delay, they are required to do so immediately if one of the following applies:"},{tag:"li",text:"Personal data concerning you is no longer necessary for the purposes for which they were collected or processed."},{tag:"li",text:"You withdraw your consent on which the processing is based pursuant to and where there is no other legal basis for processing the data."},{tag:"li",text:"You object to the processing of the data and there are no longer overriding legitimate grounds for processing, or you object pursuant to Art. 21 (2) GDPR."},{tag:"li",text:"Your personal data has been processed unlawfully."},{tag:"li",text:"The personal data must be deleted to comply with a legal obligation in Union law or Member State law to which the data controller is subject."},{tag:"li",text:"Your personal data was collected in relation to information society services offered pursuant to Art. 8 (1) GDPR."},{tag:"p",text:"The right to deletion does not exist if the processing is necessary"},{tag:"li",text:"to exercise the right to freedom of speech and information;"},{tag:"li",text:"to fulfill a legal obligation required by the law of the Union or Member States to which the data controller is subject, or to perform a task of public interest or in the exercise of public authority delegated to the representative."},{tag:"li",text:"for reasons of public interest in the field of public health."},{tag:"li",text:"for archival purposes of public interest, scientific or historical research purposes or for statistical purposes."},{tag:"li",text:"to enforce, exercise or defend legal claims."},{tag:"h3",text:"5. Right to data portability"},{tag:"p",text:"You have the right to receive your personal data given to the data controller in a structured and machine-readable format. In addition, you have the right to transfer this data to another person without hindrance by the data controller who was initially given the data."},{tag:"h3",text:"6. Right to object"},{tag:"p",text:"For reasons that arise from your particular situation, you have, at any time, the right to object to the processing of your personal data pursuant to Art. 6 (1) (e) or 6 (1) (f) GDPR; this also applies to profiling based on these provisions."},{tag:"p",text:"If the personal data relating to you are processed for direct marketing purposes, you have the right to object at any time to the processing of your personal data in regard to such advertising; this also applies to profiling associated with direct marketing."},{tag:"h3",text:"7. Right to complain to a supervisory authority"},{tag:"p",text:"Without prejudice to any other administrative or judicial remedy, you have the right to lodge a complaint with a supervisory authority if you consider that the processing of personal data concerning you infringes the GDPR. The supervisory authority to which the complaint has been lodged shall inform the complainant of the status and outcome of the complaint, including the possibility of a judicial remedy under Art. 78 GDPR. A list of the locally competent supervisory authorities in Germany can be found on the website of the Federal Commissioner for Data Protection at the following link:"},{tag:"p",text:'<a href="https://www.bfdi.bund.de/DE/Service/Anschriften/Laender/Laender-node.html" style="color: white">https://www.bfdi.bund.de/DE/Service/Anschriften/Laender/Laender-node.html</a>'},{tag:"h2",text:"Data processing when you load our website"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"Each time our website is accessed, our system automatically collects data and relevant information from the computer system of the calling device."},{tag:"p",text:"The following data is collected:"},{tag:"li",text:"Information about the browser type and the version used"},{tag:"li",text:"The user's operating system"},{tag:"li",text:"Date and time of access"},{tag:"p",text:"This data is stored in the log files of our system."},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The temporary storage of the IP address by the system is necessary for the delivery of the website to the computer of the user. For this purpose, the user\u2019s IP address must be kept for the duration of the session."},{tag:"p",text:"The storage in log files is done to ensure the functionality of the website. The data is also used to optimize the website and to ensure the security of our IT systems. An analysis of the data for marketing purposes does not take place."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The legal basis for the temporary storage of data and logfiles is Art. 6 (1) (f) GDPR."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"The data will be deleted as soon as it is no longer necessary for the purpose of its collection. The session is complete when the collection of data for the provision of the website is accomplished."},{tag:"p",text:"If the data is stored in log files, this is the case after seven days at the latest. Storage beyond this is possible. In this case, the IP addresses of the users are deleted or alienated so that an assignment of the calling client is not possible."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"The collection of data for the provision of the website and the storage of the data in log files is absolutely necessary for the operation of the website. The user can object to this. Whether the objection is successful is to be determined within the framework of a balancing of interests."},{tag:"h2",text:"Use of cookies"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"When you visit our website, we use technical tools for various functions, in particular cookies, which can be stored on your device. When you visit our website for the first time and at any time later, you have the choice of whether you generally permit the setting of cookies or which individual additional functions you would like to select. You can make changes in your browser settings or via our consent manager. Cookies are text files or information in a database that are stored on your hard drive and assigned to the browser you are using so that certain information can be passed to the entity that sets the cookie. We use technically necessary cookies, which are required for the technical structure of the website. Without these cookies, our website cannot be displayed (completely correctly) or the support functions are not possible."},{tag:"p",text:"The following data is stored and transmitted in the technical necessary cookies:"},{tag:"li",text:"Language settings"},{tag:"li",text:"Log-in information"},{tag:"li",text:"Entered search terms"},{tag:"li",text:"Frequency of page views"},{tag:"li",text:"Use of website functionalities"},{tag:"p",text:"We use cookies on our website that are not technically necessary. Technically unnecessary cookies are text files that are not only used for the functionality of the website, but also collect other data."},{tag:"p",text:"As a result, the following data will be processed:"},{tag:"li",text:"IP-address"},{tag:"li",text:"Internet user location"},{tag:"li",text:"Date and time of the website request"},{tag:"li",text:"Customization of advertisements to the user"},{tag:"li",text:"Tracking of the surfing behavior"},{tag:"li",text:"Linking the website visit with other social media platforms"},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The purpose of using technically necessary cookies is to ensure the functionality of our website. Some functions of our website cannot be offered without the use of cookies. For these, it is necessary that the browser is recognized even after a page change."},{tag:"p",text:"We need technical necessary cookies for the following purposes:"},{tag:"li",text:"Storage of language settings"},{tag:"li",text:"Storage of search queries"},{tag:"li",text:"Functionality of the website"},{tag:"p",text:"The use of technically not necessary cookies is carried out for the purpose of improving the quality of our website, its content, and thus our reach and profitability. By setting these cookies, we learn how the website is used and can thus constantly optimize our offer. These cookies serve us particularly for the following purposes:"},{tag:"li",text:"Improving the quality of our website and its content. Through the analysis cookies, we learn how the website is used and thus can constantly optimize our offer."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The regulations of the Telecommunications-Telemedia Data Protection Act (TTDSG) are relevant for the storage of information in the end user's terminal equipment and/or access to information already stored in the end user's terminal equipment. If the setting and reading of cookies is technically necessary, this is done to ensure the functionality of our website. In this case, the storage of and access to cookies on your terminal equipment is carried out on the basis of \xA7 25(2)(2) TTDSG. This storage of and access to the information in your terminal equipment serves to facilitate your use of our website and to be able to offer you our services as you have requested. Some functions of our website also do not work without the use of these cookies and could therefore not be offered. The cookies are generally deleted after the session ends (e.g. logging out or closing the browser) or after the expiry of a specified duration. Information on different storage periods for cookies can be found in the following sections of this data protection declaration."},{tag:"p",text:"As far as cookies are set that are not technically necessary, this is done on the basis of your expressed consent, which you can provide via the cookie banner. The basis for storing and accessing information in this case is \xA7 25(1) TTDSG in conjunction with. Art. 6(1)(1)(a), Art. 7 GDPR. You can withdraw your consent at any time with effect for the future or subsequently grant it again by configuring your settings for cookies accordingly. Alternatively, you can prevent the storage of cookies by making the appropriate settings in your browser software. Please note that the browser settings you make only affect the browser you are using. If personal data is processed following the storage of and access to the information on your terminal equipment, the provisions of the GDPR are relevant. Information on this can be found in the following sections of this privacy policy."},{tag:"h3",text:"4. Exercising your rights"},{tag:"p",text:"You can revoke consent to the use of cookies and manage your consent preferences at any time when you click on \u201CPrivacy Settings\u201D."},{tag:"h2",text:"Newsletter"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"You can subscribe to a newsletter on our website free of charge. When subscribing for the newsletter, the data from the input mask is transmitted to us."},{tag:"p",text:"We collect the following data from you in order to provide this service:"},{tag:"li",text:"Email address"},{tag:"p",text:"No data will be passed on to third parties in connection with data processing for the dispatch of newsletters. The data will be used exclusively for sending the newsletter."},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The user's email address is collected to deliver the newsletter to the recipient."},{tag:"p",text:"Additional personal data as part of the registration process is collected to prevent misuse of the services or email address."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The legal basis for the processing of data provided by the user after registration for the newsletter is Art. 6 (1) (a) GDPR if the user has given his consent."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"The data will be deleted as soon as it is no longer necessary to achieve the purpose for which it was collected. The user's email address will therefore be stored as long as the newsletter subscription is active."},{tag:"p",text:"The other personal data collected during the registration process is generally deleted after a period of seven days."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"The subscription for the newsletter can be cancelled by the data subject at any time. For this purpose, every newsletter contains an opt-out link."},{tag:"p",text:"Through this, it is also possible to withdraw the consent to the storage of personal data collected during the registration process."},{tag:"h2",text:"Contact via Email"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"You can contact us via the email address provided on our website. In this case, the personal data of the user transmitted with the email will be stored."},{tag:"p",text:"The data will be used exclusively for the processing of the conversation."},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"If you contact us via email, this also constitutes the necessary legitimate interest in the processing of the data."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The legal basis for the processing of data transmitted in the course of sending an e-mail is Art. 6 (1) (f) GDPR. Our legitimate interest is to optimally answer your request that you send by e-mail."},{tag:"p",text:"If the purpose of the email contact is to conclude a contract, the additional legal basis for the processing is Art. 6 (1) (b) GDPR."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"The data will be deleted as soon as it is no longer necessary to achieve the purpose for which it was collected. For personal data sent by email, this is the case when the respective conversation with the user has ended. The conversation ends when it can be concluded from the circumstances that the matter in question has been conclusively resolved."},{tag:"p",text:"The additional personal data collected during the sending process will be deleted after a period of seven days at the latest."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"You have the possibility to withdraw consent to the processing of their personal data at any time. If you contact us via email, you can object to the storage of his personal data at any time, by the following means:"},{tag:"p",text:"contact us by email, support@jina.ai"},{tag:"p",text:"In this case, all personal data stored while establishing contact will be deleted."},{tag:"h2",text:"Contact form"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"A contact form is available on our website, which can be used for electronic contact. If you make use of this option, the data entered in the contact form will be transmitted to us and stored."},{tag:"p",text:"When sending the message, the following data will also be stored:"},{tag:"li",text:"Email address"},{tag:"li",text:"Last name"},{tag:"li",text:"First name"},{tag:"li",text:"Job Title, Company Size, Company Name, and Country"},{tag:"li",text:"Date and time"},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The processing of the personal data from the form as well as if you contact us by mail serves us exclusively for the purpose of establishing contact."},{tag:"p",text:"The other personal data processed during the sending process serve to prevent misuse of the contact form and to ensure the security of our information technology systems."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The legal basis for the processing of data transmitted while sending an email is Art. 6 (1) (f) GDPR. Our legitimate interest is to provide you with the best possible response to the request you send to us via the contact form. If the purpose of the email contact is to conclude a contract, the additional legal basis for the processing is Art. 6 (1) (b) GDPR."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"The data will be deleted as soon as they are no longer necessary to achieve the purpose for which they were collected. For the personal data from the contact form and those sent by email, this is the case when the respective conversation with the user has ended. The conversation ends when it can be inferred from the circumstances that the facts in question have been conclusively clarified."},{tag:"p",text:"The additional personal data collected during the sending process will be deleted after a period of seven days at the latest."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"If you contact us via the contact form or via email, you can object to the storage of your personal data at any time, by the following means:"},{tag:"p",text:"contact us by email, support@jina.ai"},{tag:"p",text:"In this case, all personal data stored while establishing contact will be deleted."},{tag:"h2",text:"Application via Email and Form"},{tag:"p",text:"1. Description and scope of data processing"},{tag:"p",text:"There is a form on our website which can be used for electronic job applications. If an applicant makes use of this possibility, the data entered in the input mask will be transmitted to us and stored. The data is:"},{tag:"li",text:"Title"},{tag:"li",text:"Last name"},{tag:"li",text:"First name"},{tag:"li",text:"Email address"},{tag:"li",text:"Salary expectations"},{tag:"li",text:"Information on education and training"},{tag:"li",text:"Language proficiencies"},{tag:"li",text:"Curriculum Vitae"},{tag:"li",text:"Certificates"},{tag:"li",text:"Data that you send us during the application process"},{tag:"p",text:"Alternatively, you can send us your application by email. In this case, we collect your email address and the information you provide in the email."},{tag:"p",text:"After sending your application, you will receive confirmation of receipt of your application documents from us by email."},{tag:"p",text:"In addition, we offer an applicant/talent pool."},{tag:"p",text:"Your data will not be passed on to third parties. The data will be used exclusively for processing your application."},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The processing of personal data from the application form serves us solely to process your application. If you contact us by email, this also constitutes the necessary legitimate interest in the processing of the data."},{tag:"p",text:"The other personal data processed during the sending process serve to prevent misuse of the application form and to ensure the security of our information technology systems."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The legal basis for the processing of the data is the initiation of the contractual relationship at the request of the data subject, Art. 6 (1) (b) Alt. 1 GDPR and \xA7 26 (1) BDSG (Federal Act of Data Protection)."},{tag:"p",text:"The legal basis for the processing of data within the context of the applicant pool is the applicant's express consent, Art. 6 (1) (a) GDPR."},{tag:"h4",text:"4. Duration of storage"},{tag:"p",text:"After completion of the application procedure, the data will be stored for up to 6 months. Your data will be deleted after 6 months at the latest. In the case that you have given your consent for us to store your data for a further 12 months, the total storage period will be 18 months. In the event of a legal obligation, the data will be stored within the framework of the applicable provisions."},{tag:"p",text:"The additional personal data collected during the sending process will be deleted after a period of seven days at the latest."},{tag:"h2",text:"Corporate web profiles on social networks"},{tag:"p",text:"YouTube:"},{tag:"p",text:"YouTube LLC, 901 Cherry Ave., San Bruno, CA 94066, United States"},{tag:"p",text:"On our company profile we provide information and offer Youtube users the possibility of communication. If you carry out an action on our Youtube company profile (e.g. comments, contributions, likes etc.), you may make personal data (e.g. clear name or photo of your user profile) public. However, as we generally or to a large extent have no influence on the processing of your personal data by Youtube, we cannot make any binding statements regarding the purpose and scope of the processing of your data."},{tag:"p",text:"Our corporate profile in social networks is used for communication and information exchange with (potential) customers. We use the company's profile for:"},{tag:"li",text:"Products"},{tag:"li",text:"Community"},{tag:"p",text:"Publications on the company profile can contain the following content:"},{tag:"li",text:"Information about products"},{tag:"li",text:"Information about services"},{tag:"li",text:"Contact with customers"},{tag:"p",text:"Every user is free to publish personal data."},{tag:"p",text:"As far as we process your personal data in order to evaluate your online behavior, to offer you sweepstakes or to conduct lead campaigns, this is done on the basis of your express declaration of consent, Art. 6 (1) (a), Art. 7 GDPR. The legal basis for processing personal data for the purpose of communicating with customers and interested parties is Art. 6 (1) (f) GDPR. Thereby, our legitimate interest is to answer your request optimally or to be able to provide the requested information. If the aim of contacting you is to conclude a contract, the additional legal basis for the processing is Art. 6 (1) (b) GDPR."},{tag:"p",text:"The data generated on the company profile are not stored in our own systems."},{tag:"p",text:"You can object at any time to the processing of your personal data that we collect within the framework of your use of our Youtube corporate web profile and assert your rights as a data subject mentioned under IV. of this privacy policy. Please send us an informal email to support@jina.ai. For further information on the processing of your personal data by Youtube and the corresponding objection options, please click here:"},{tag:"p",text:'YouTube: <a href="https://policies.google.com/privacy?gl=DE&hl=en" style="color: white">https://policies.google.com/privacy?gl=DE&hl=en</a>'},{tag:"p",text:"Twitter:"},{tag:"p",text:"Twitter International Company, One Cumberland Place, Fenian Street, Dublin 2, Ireland"},{tag:"p",text:"On our company profile we provide information and offer Twitter users the possibility of communication. If you carry out an action on our Twitter company profile (e.g. comments, contributions, likes etc.), you may make personal data (e.g. clear name or photo of your user profile) public. However, as we generally or to a large extent have no influence on the processing of your personal data by Twitter, we cannot make any binding statements regarding the purpose and scope of the processing of your data."},{tag:"p",text:"Our corporate profile in social networks is used for communication and information exchange with (potential) customers. We use the company's profile for:"},{tag:"li",text:"Products"},{tag:"li",text:"Community"},{tag:"p",text:"Publications on the company profile can contain the following content:"},{tag:"li",text:"Information about products"},{tag:"li",text:"Information about services"},{tag:"li",text:"Contact with customers"},{tag:"p",text:"Every user is free to publish personal data."},{tag:"p",text:"As far as we process your personal data in order to evaluate your online behavior, to offer you sweepstakes or to conduct lead campaigns, this is done on the basis of your express declaration of consent, Art. 6 (1) (a), Art. 7 GDPR. The legal basis for processing personal data for the purpose of communicating with customers and interested parties is Art. 6 (1) (f) GDPR. Thereby, our legitimate interest is to answer your request optimally or to be able to provide the requested information. If the aim of contacting you is to conclude a contract, the additional legal basis for the processing is Art. 6 (1) (b) GDPR."},{tag:"p",text:"The data generated on the company profile are not stored in our own systems."},{tag:"p",text:"You can object at any time to the processing of your personal data that we collect within the framework of your use of our Twitter corporate web profile and assert your rights as a data subject mentioned under IV. of this privacy policy. Please send us an informal email to support@jina.ai. For further information on the processing of your personal data by Twitter and the corresponding objection options, please click here:"},{tag:"p",text:'Twitter: <a href="https://twitter.com/de/privacy" style="color: white">https://twitter.com/de/privacy</a>'},{tag:"h2",text:"Use of corporate profiles in professionally oriented networks"},{tag:"h3",text:"1. Scope of data processing"},{tag:"p",text:"We use corporate profiles on professionally oriented networks. We maintain a corporate presence on the following professionally oriented networks:"},{tag:"li",text:"LinkedIn"},{tag:"p",text:"On our site we provide information and offer users the possibility of communication."},{tag:"p",text:"The corporate profile is used for job applications, information, public relations, and active sourcing."},{tag:"p",text:"We do not have any information on the processing of your personal data by the companies jointly responsible for the corporate profile. Further information can be found in the privacy policy of:"},{tag:"p",text:"LinkedIn:"},{tag:"p",text:'LinkedIn:<a href="https://www.linkedin.com/legal/privacy-policy" style="color: white">https://www.linkedin.com/legal/privacy-policy</a>'},{tag:"p",text:"If you carry out an action on our company profile (e.g. comments, contributions, likes etc.), you may make personal data (e.g. clear name or photo of your user profile) public."},{tag:"h3",text:"2. Legal basis for data processing"},{tag:"p",text:"The legal basis for the processing of personal data for the purpose of communication with customers and interested parties is Art. 6 (1) (f) GDPR. Our legitimate interest is to answer your request optimally or to be able to provide the requested information. If the aim of contacting you is to conclude a contract, the additional legal basis for the processing is Art. 6 (1) (b) GDPR."},{tag:"h3",text:"3. Purpose of the data processing"},{tag:"p",text:"Our corporate web profile serves to inform users about our services. Every user is free to publish personal data."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"The data generated on the company profile are not stored in our own systems."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"You can object at any time to the processing of your personal data which we collect within the scope of your use of our corporate web profile and assert your rights as a data subject mentioned under IV. of this privacy policy. Please send us an informal email to the email address stated in this privacy policy."},{tag:"p",text:"You can find further information on objection and removal options here:"},{tag:"p",text:"LinkedIn:"},{tag:"p",text:'<a href="https://www.linkedin.com/legal/privacy-policy" style="color: white">https://www.linkedin.com/legal/privacy-policy</a>'},{tag:"h2",text:"Hosting"},{tag:"p",text:"The website is hosted on servers of a service provider commissioned by us."},{tag:"p",text:"Our service provider is:"},{tag:"p",text:"GitHub 88 Colin P Kelly Jr Street San Francisco, California 94107"},{tag:"p",text:"For further information on the processing of personal data by Github please see:"},{tag:"p",text:'<a href="https://docs.github.com/en/site-policy/privacy-policies/github-privacy-statement" style="color: white">https://docs.github.com/en/site-policy/privacy-policies/github-privacy-statement</a>'},{tag:"p",text:"The servers automatically collect and store information in so-called server log files, which your browser automatically transmits when you visit the website. The stored information is:"},{tag:"li",text:"Information about the browser type and the version used"},{tag:"li",text:"The user's operating system"},{tag:"li",text:"Date and time of access"},{tag:"li",text:"The Internet service provider of the user"},{tag:"li",text:"Websites from which the user's system accessed our website"},{tag:"li",text:"Websites the user's system accessed through our website"},{tag:"li",text:"IP address of the user's device"},{tag:"p",text:"This data will not be merged with other data sources. The data is collected on the basis of Art. 6 (1) (f) GDPR. The website operator has a legitimate interest in the technically error-free presentation and optimization of his website -and server log files are therefore recorded."},{tag:"p",text:"The server of the website is geographically located in the USA."},{tag:"p",text:"The Service Provider complies with the EU-U.S. Data Privacy Framework (EU-U.S. DPF) as set forth by the U.S. Department of Commerce and has certified that it adheres to the EU-U.S. Data Privacy Framework Principles (EU-U.S. DPF Principles) when processing personal data received from the European Union in reliance on the EU-U.S. DPF. More information can be found in at:"},{tag:"p",text:'<a href="https://www.dataprivacyframework.gov/s/participant-search/participant-detail?id=a2z3d0000001wwUAAQ&status=Active" style="color: white">https://www.dataprivacyframework.gov/s/participant-search/participant-detail?id=a2z3d0000001wwUAAQ&status=Active</a>'},{tag:"h2",text:"Geotargeting"},{tag:"p",text:'We use the IP address and other information provided by the user (e.g. the postal code used for registration or ordering) to approach regional target groups (so-called "geotargeting").'},{tag:"p",text:"The regional target group approach is used, for example, to automatically display regional offers or advertisements that often are more relevant to users. The legal basis for the use of the IP address and any other information provided by the user (e.g. postal code) is Art. 6 (1) (f) GDPR, based on our legitimate interest in ensuring a more precise target group approach and thus providing offers and advertising with greater relevance for our users."},{tag:"p",text:"Part of the IP address and the additional information provided by the user (e.g. postal code) are merely processed and not stored separately."},{tag:"p",text:"You can prevent geotargeting by, for example, using a VPN or proxy server that prevents accurate localization. In addition, depending on the browser you are using, you can also deactivate a location localization in the corresponding browser settings (as far as this is supported by the respective browser)."},{tag:"p",text:"We use geotargeting on our website for the following purposes:"},{tag:"li",text:"Products"},{tag:"h2",text:"Registration"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"We offer users the opportunity to register by providing personal data. The data is entered into a form and transmitted to us and stored. The following data is collected as part of the registration process:"},{tag:"li",text:"Email address"},{tag:"p",text:"As part of the registration process, your consent to the processing of this data is obtained."},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"A registration of the user is necessary for the fulfilment of a contract with the user or for the execution of pre-contractual measures."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The legal basis for the processing of the data is Art. 6 (1) (a) GDPR where you have provided consent."},{tag:"p",text:"The legal basis for the processing of registration data necessary to conclude or fulfil a contract with you is Art. 6 (1) (b) GDPR."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"The data will be deleted as soon as it is no longer necessary to achieve the purpose for which it was collected."},{tag:"p",text:"This is the case for the data collected during the registration process for the execution of a contract or for the implementation of pre-contractual measures if the data is no longer required for the execution of the contract. Even after the conclusion of the contract, it may be necessary to store personal data of the contractual partner in order to comply with contractual or legal obligations."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"As a user you have the possibility to cancel the registration at any time. You can request a change to the data stored about you at any time, by the following means:"},{tag:"p",text:"The user should reach out to our support team at support@jina.ai to delete their account or change their data."},{tag:"p",text:"If the data is necessary for the fulfilment of a contract or for the implementation of pre-contractual measures, a premature deletion of the data is only possible insofar as contractual or legal obligations do not stand in the way of a deletion."},{tag:"h2",text:"Content Delivery Networks"},{tag:"h3",text:"1. Description and scope of data processing"},{tag:"p",text:"On our website we use functions of the content delivery network CloudFlare of CloudFlare Germany GmbH, Rosental 7, 80331 Munich, Germany (Hereinafter referred to as CloudFlare). A Content Delivery Network (CDN) is a network of regionally distributed servers connected via the Internet to deliver content, especially large media files such as videos. CloudFlare offers web optimization and security services that we use to improve the load times of our website and to protect it from misuse. When you visit our website you will be connected to the servers of CloudFlare, e.g. to retrieve content. This allows personal data to be stored and evaluated in server log files, the user's activity (e.g. which pages have been visited) and device and browser information (e.g. IP address and operating system). Further information on the collection and storage of data by CloudFlare can be found here:"},{tag:"p",text:'<a href="https://www.cloudflare.com/en-gb/privacypolicy/" style="color: white">https://www.cloudflare.com/en-gb/privacypolicy/</a>'},{tag:"h3",text:"2. Purpose of data processing"},{tag:"p",text:"The use of CloudFlare's features serves to deliver and accelerate online applications and content."},{tag:"h3",text:"3. Legal basis for data processing"},{tag:"p",text:"The data is collected on the basis of Art. 6 (1) (f) GDPR. The website operator has a legitimate interest in the technically error-free presentation and optimization of his website -and the server log files are therefore recorded."},{tag:"h3",text:"4. Duration of storage"},{tag:"p",text:"Your personal information will be retained for as long as necessary to fulfil the purposes described in this Privacy Policy or as required by law."},{tag:"h3",text:"5. Exercising your rights"},{tag:"p",text:"Information about objection and removal options regarding CloudFlare can be found at:"},{tag:"p",text:'<a href="https://www.cloudflare.com/en-gb/privacypolicy/" style="color: white">https://www.cloudflare.com/en-gb/privacypolicy/</a>'},{tag:"h2",text:"Integrated third-party services"},{tag:"p",text:"We use various service providers to deliver the service we offer through the app."},{tag:"p",text:"Generally, where such services are essential to providing the basic service offered by the website, we have a legitimate interest in sharing your data with the relevant service providers in order to provide the relevant website service."},{tag:"p",text:"Where such services are required for additional services, enhanced functionalities, or additional purposes, your personal data will only be transferred to service providers if you provide consent."},{tag:"table",id:"Integrated third-party services",columns:[{name:"Service name",label:"Service name",align:"left",field:"service_name"},{name:"Company",label:"Company",align:"left",field:"company"},{name:"Location",label:"Location",align:"left",field:"location"},{name:"Purpose",label:"Purpose",align:"left",field:"purpose"},{name:"Reference",label:"Reference",align:"left",field:"reference"},{name:"Link",label:"Link",align:"left",field:"link"}],rows:[{service_name:"Google Tag Manager",company:"Google Ireland Ltd.",location:"Irland (USA)",purpose:"Tag configuration and integration of Google services",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://policies.google.com/privacy?gl=DE&hl=de https://business.safety.google/gdpr/"},{service_name:"Google Webfonts",company:"Google Ireland Ltd.",location:"Irland (USA)",purpose:"Fonts",reference:"Art. 6 para. 1 p. 1 lit. a GDPR",link:"https://policies.google.com/privacy?gl=DE&hl=de https://business.safety.google/gdpr/"},{service_name:"Google ReCaptcha",company:"Google Ireland Ltd.",location:"Irland (USA)",purpose:"Bot 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diff --git a/assets/MainLayout.cdce2c7a.js b/assets/MainLayout.702c6e21.js
similarity index 96%
rename from assets/MainLayout.cdce2c7a.js
rename to assets/MainLayout.702c6e21.js
index 39520e48796..dc966dea54a 100644
--- a/assets/MainLayout.cdce2c7a.js
+++ b/assets/MainLayout.702c6e21.js
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diff --git a/assets/NewsBadge.fdbfc6f6.js b/assets/NewsBadge.85969a48.js
similarity index 80%
rename from assets/NewsBadge.fdbfc6f6.js
rename to assets/NewsBadge.85969a48.js
index ea78087a81b..2d49673aa25 100644
--- a/assets/NewsBadge.fdbfc6f6.js
+++ b/assets/NewsBadge.85969a48.js
@@ -1 +1 @@
-import{Q as n}from"./QChip.dae6efcf.js";import{e as c,a6 as i,ab as r,a7 as o,ai as t,af as m,ak as u,ac as b,a9 as e}from"./index.2b6e3ac7.js";const k=c({__name:"NewsBadge",props:{news:{}},setup(d){const{t:a}=i({useScope:"global"});return(s,p)=>(e(),r(u,null,[s.news.featured?(e(),o(n,{key:0,label:t(a)("blog_tags.featured"),size:"sm",outline:"",square:"",class:"non-selectable no-border-radius",icon:"star"},null,8,["label"])):m("",!0),(e(!0),r(u,null,b(s.news.tags,(l,_)=>(e(),o(n,{key:l.id,size:"sm",outline:"",square:"",class:"non-selectable no-border-radius",label:t(a)(`blog_tags.${l.slug}`)},null,8,["label"]))),128))],64))}});export{k as _};
+import{Q as n}from"./QChip.1a7b8095.js";import{e as c,a6 as i,ab as r,a7 as o,ai as t,af as m,ak as u,ac as b,a9 as e}from"./index.ae19b4cb.js";const k=c({__name:"NewsBadge",props:{news:{}},setup(d){const{t:a}=i({useScope:"global"});return(s,p)=>(e(),r(u,null,[s.news.featured?(e(),o(n,{key:0,label:t(a)("blog_tags.featured"),size:"sm",outline:"",square:"",class:"non-selectable no-border-radius",icon:"star"},null,8,["label"])):m("",!0),(e(!0),r(u,null,b(s.news.tags,(l,_)=>(e(),o(n,{key:l.id,size:"sm",outline:"",square:"",class:"non-selectable no-border-radius",label:t(a)(`blog_tags.${l.slug}`)},null,8,["label"]))),128))],64))}});export{k as _};
diff --git a/assets/NewsPage.903087e6.js b/assets/NewsPage.3fc05989.js
similarity index 99%
rename from assets/NewsPage.903087e6.js
rename to assets/NewsPage.3fc05989.js
index 1f9fc4fcddb..93e420a24b3 100644
--- a/assets/NewsPage.903087e6.js
+++ b/assets/NewsPage.3fc05989.js
@@ -1,4 +1,4 @@
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diff --git a/assets/NewsVerticalCard.f5cd3c5b.js b/assets/NewsVerticalCard.2afaaf7a.js
similarity index 84%
rename from assets/NewsVerticalCard.f5cd3c5b.js
rename to assets/NewsVerticalCard.2afaaf7a.js
index a1cc7427acb..ca1720cd74c 100644
--- a/assets/NewsVerticalCard.f5cd3c5b.js
+++ b/assets/NewsVerticalCard.2afaaf7a.js
@@ -1 +1 @@
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diff --git a/assets/NewsroomPage.4a55792b.js b/assets/NewsroomPage.ec508005.js
similarity index 95%
rename from assets/NewsroomPage.4a55792b.js
rename to assets/NewsroomPage.ec508005.js
index 580d38d2bcf..05246b75dc5 100644
--- a/assets/NewsroomPage.4a55792b.js
+++ b/assets/NewsroomPage.ec508005.js
@@ -1 +1 @@
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diff --git a/assets/OpenDay.3a3b3b0d.js b/assets/OpenDay.5172c3be.js
similarity index 98%
rename from assets/OpenDay.3a3b3b0d.js
rename to assets/OpenDay.5172c3be.js
index 65edbb252d2..1660eff8b36 100644
--- a/assets/OpenDay.3a3b3b0d.js
+++ b/assets/OpenDay.5172c3be.js
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diff --git a/assets/QBtnDropdown.ecb3c5d9.js b/assets/QBtnDropdown.8a71b3aa.js
similarity index 94%
rename from assets/QBtnDropdown.ecb3c5d9.js
rename to assets/QBtnDropdown.8a71b3aa.js
index a2076415d92..c5c7a1f7a2c 100644
--- a/assets/QBtnDropdown.ecb3c5d9.js
+++ b/assets/QBtnDropdown.8a71b3aa.js
@@ -1 +1 @@
-import{k,aW as v,m as H,f as h,aX as V,h as r,w as m,K as j,i,aj as x,D as I,j as s,C as M,aY as O,aR as P}from"./index.2b6e3ac7.js";import{Q as _}from"./QBtnGroup.12934764.js";import{Q as R}from"./QMenu.d2069e37.js";const L=Object.keys(v),W=e=>L.reduce((o,t)=>{const l=e[t];return l!==void 0&&(o[t]=l),o},{});var K=k({name:"QBtnDropdown",props:{...v,...H,modelValue:Boolean,split:Boolean,dropdownIcon:String,contentClass:[Array,String,Object],contentStyle:[Array,String,Object],cover:Boolean,persistent:Boolean,noRouteDismiss:Boolean,autoClose:Boolean,menuAnchor:{type:String,default:"bottom end"},menuSelf:{type:String,default:"top end"},menuOffset:Array,disableMainBtn:Boolean,disableDropdown:Boolean,noIconAnimation:Boolean,toggleAriaLabel:String},emits:["update:modelValue","click","beforeShow","show","beforeHide","hide"],setup(e,{slots:o,emit:t}){const{proxy:l}=M(),u=h(e.modelValue),a=h(null),c=V(),f=r(()=>{const n={"aria-expanded":u.value===!0?"true":"false","aria-haspopup":"true","aria-controls":c,"aria-label":e.toggleAriaLabel||l.$q.lang.label[u.value===!0?"collapse":"expand"](e.label)};return(e.disable===!0||e.split===!1&&e.disableMainBtn===!0||e.disableDropdown===!0)&&(n["aria-disabled"]="true"),n}),B=r(()=>"q-btn-dropdown__arrow"+(u.value===!0&&e.noIconAnimation===!1?" rotate-180":"")+(e.split===!1?" q-btn-dropdown__arrow-container":"")),b=r(()=>O(e)),w=r(()=>W(e));m(()=>e.modelValue,n=>{a.value!==null&&a.value[n?"show":"hide"]()}),m(()=>e.split,d);function S(n){u.value=!0,t("beforeShow",n)}function C(n){t("show",n),t("update:modelValue",!0)}function q(n){u.value=!1,t("beforeHide",n)}function D(n){t("hide",n),t("update:modelValue",!1)}function A(n){t("click",n)}function y(n){P(n),d(),t("click",n)}function Q(n){a.value!==null&&a.value.toggle(n)}function g(n){a.value!==null&&a.value.show(n)}function d(n){a.value!==null&&a.value.hide(n)}return Object.assign(l,{show:g,hide:d,toggle:Q}),j(()=>{e.modelValue===!0&&g()}),()=>{const n=[i(x,{class:B.value,name:e.dropdownIcon||l.$q.iconSet.arrow.dropdown})];return e.disableDropdown!==!0&&n.push(i(R,{ref:a,id:c,class:e.contentClass,style:e.contentStyle,cover:e.cover,fit:!0,persistent:e.persistent,noRouteDismiss:e.noRouteDismiss,autoClose:e.autoClose,anchor:e.menuAnchor,self:e.menuSelf,offset:e.menuOffset,separateClosePopup:!0,transitionShow:e.transitionShow,transitionHide:e.transitionHide,transitionDuration:e.transitionDuration,onBeforeShow:S,onShow:C,onBeforeHide:q,onHide:D},o.default)),e.split===!1?i(s,{class:"q-btn-dropdown q-btn-dropdown--simple",...w.value,...f.value,disable:e.disable===!0||e.disableMainBtn===!0,noWrap:!0,round:!1,onClick:A},{default:()=>I(o.label,[]).concat(n),loading:o.loading}):i(_,{class:"q-btn-dropdown q-btn-dropdown--split no-wrap q-btn-item",rounded:e.rounded,square:e.square,...b.value,glossy:e.glossy,stretch:e.stretch},()=>[i(s,{class:"q-btn-dropdown--current",...w.value,disable:e.disable===!0||e.disableMainBtn===!0,noWrap:!0,round:!1,onClick:y},{default:o.label,loading:o.loading}),i(s,{class:"q-btn-dropdown__arrow-container q-anchor--skip",...f.value,...b.value,disable:e.disable===!0||e.disableDropdown===!0,rounded:e.rounded,color:e.color,textColor:e.textColor,dense:e.dense,size:e.size,padding:e.padding,ripple:e.ripple},()=>n)])}}});export{K as Q};
+import{k,aW as v,m as H,f as h,aX as V,h as r,w as m,K as j,i,aj as x,D as I,j as s,C as M,aY as O,aR as P}from"./index.ae19b4cb.js";import{Q as _}from"./QBtnGroup.d8d0cf5d.js";import{Q as R}from"./QMenu.d7b6411c.js";const L=Object.keys(v),W=e=>L.reduce((o,t)=>{const l=e[t];return l!==void 0&&(o[t]=l),o},{});var K=k({name:"QBtnDropdown",props:{...v,...H,modelValue:Boolean,split:Boolean,dropdownIcon:String,contentClass:[Array,String,Object],contentStyle:[Array,String,Object],cover:Boolean,persistent:Boolean,noRouteDismiss:Boolean,autoClose:Boolean,menuAnchor:{type:String,default:"bottom end"},menuSelf:{type:String,default:"top end"},menuOffset:Array,disableMainBtn:Boolean,disableDropdown:Boolean,noIconAnimation:Boolean,toggleAriaLabel:String},emits:["update:modelValue","click","beforeShow","show","beforeHide","hide"],setup(e,{slots:o,emit:t}){const{proxy:l}=M(),u=h(e.modelValue),a=h(null),c=V(),f=r(()=>{const n={"aria-expanded":u.value===!0?"true":"false","aria-haspopup":"true","aria-controls":c,"aria-label":e.toggleAriaLabel||l.$q.lang.label[u.value===!0?"collapse":"expand"](e.label)};return(e.disable===!0||e.split===!1&&e.disableMainBtn===!0||e.disableDropdown===!0)&&(n["aria-disabled"]="true"),n}),B=r(()=>"q-btn-dropdown__arrow"+(u.value===!0&&e.noIconAnimation===!1?" rotate-180":"")+(e.split===!1?" q-btn-dropdown__arrow-container":"")),b=r(()=>O(e)),w=r(()=>W(e));m(()=>e.modelValue,n=>{a.value!==null&&a.value[n?"show":"hide"]()}),m(()=>e.split,d);function S(n){u.value=!0,t("beforeShow",n)}function C(n){t("show",n),t("update:modelValue",!0)}function q(n){u.value=!1,t("beforeHide",n)}function D(n){t("hide",n),t("update:modelValue",!1)}function A(n){t("click",n)}function y(n){P(n),d(),t("click",n)}function Q(n){a.value!==null&&a.value.toggle(n)}function g(n){a.value!==null&&a.value.show(n)}function d(n){a.value!==null&&a.value.hide(n)}return Object.assign(l,{show:g,hide:d,toggle:Q}),j(()=>{e.modelValue===!0&&g()}),()=>{const n=[i(x,{class:B.value,name:e.dropdownIcon||l.$q.iconSet.arrow.dropdown})];return e.disableDropdown!==!0&&n.push(i(R,{ref:a,id:c,class:e.contentClass,style:e.contentStyle,cover:e.cover,fit:!0,persistent:e.persistent,noRouteDismiss:e.noRouteDismiss,autoClose:e.autoClose,anchor:e.menuAnchor,self:e.menuSelf,offset:e.menuOffset,separateClosePopup:!0,transitionShow:e.transitionShow,transitionHide:e.transitionHide,transitionDuration:e.transitionDuration,onBeforeShow:S,onShow:C,onBeforeHide:q,onHide:D},o.default)),e.split===!1?i(s,{class:"q-btn-dropdown q-btn-dropdown--simple",...w.value,...f.value,disable:e.disable===!0||e.disableMainBtn===!0,noWrap:!0,round:!1,onClick:A},{default:()=>I(o.label,[]).concat(n),loading:o.loading}):i(_,{class:"q-btn-dropdown q-btn-dropdown--split no-wrap q-btn-item",rounded:e.rounded,square:e.square,...b.value,glossy:e.glossy,stretch:e.stretch},()=>[i(s,{class:"q-btn-dropdown--current",...w.value,disable:e.disable===!0||e.disableMainBtn===!0,noWrap:!0,round:!1,onClick:y},{default:o.label,loading:o.loading}),i(s,{class:"q-btn-dropdown__arrow-container q-anchor--skip",...f.value,...b.value,disable:e.disable===!0||e.disableDropdown===!0,rounded:e.rounded,color:e.color,textColor:e.textColor,dense:e.dense,size:e.size,padding:e.padding,ripple:e.ripple},()=>n)])}}});export{K as Q};
diff --git a/assets/QBtnGroup.12934764.js b/assets/QBtnGroup.d8d0cf5d.js
similarity index 89%
rename from assets/QBtnGroup.12934764.js
rename to assets/QBtnGroup.d8d0cf5d.js
index f385f6782c8..5c7d0492abe 100644
--- a/assets/QBtnGroup.12934764.js
+++ b/assets/QBtnGroup.d8d0cf5d.js
@@ -1 +1 @@
-import{k as r,h as s,i as l,D as u}from"./index.2b6e3ac7.js";var d=r({name:"QBtnGroup",props:{unelevated:Boolean,outline:Boolean,flat:Boolean,rounded:Boolean,square:Boolean,push:Boolean,stretch:Boolean,glossy:Boolean,spread:Boolean},setup(o,{slots:n}){const t=s(()=>{const a=["unelevated","outline","flat","rounded","square","push","stretch","glossy"].filter(e=>o[e]===!0).map(e=>`q-btn-group--${e}`).join(" ");return`q-btn-group row no-wrap${a.length!==0?" "+a:""}`+(o.spread===!0?" q-btn-group--spread":" inline")});return()=>l("div",{class:t.value},u(n.default))}});export{d as Q};
+import{k as r,h as s,i as l,D as u}from"./index.ae19b4cb.js";var d=r({name:"QBtnGroup",props:{unelevated:Boolean,outline:Boolean,flat:Boolean,rounded:Boolean,square:Boolean,push:Boolean,stretch:Boolean,glossy:Boolean,spread:Boolean},setup(o,{slots:n}){const t=s(()=>{const a=["unelevated","outline","flat","rounded","square","push","stretch","glossy"].filter(e=>o[e]===!0).map(e=>`q-btn-group--${e}`).join(" ");return`q-btn-group row no-wrap${a.length!==0?" "+a:""}`+(o.spread===!0?" q-btn-group--spread":" inline")});return()=>l("div",{class:t.value},u(n.default))}});export{d as Q};
diff --git a/assets/QCarousel.9e51a2e1.js b/assets/QCarousel.7c089181.js
similarity index 98%
rename from assets/QCarousel.9e51a2e1.js
rename to assets/QCarousel.7c089181.js
index 78170119fd4..dfa9e070137 100644
--- a/assets/QCarousel.9e51a2e1.js
+++ b/assets/QCarousel.7c089181.js
@@ -1 +1 @@
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v=a.target;V(t,"temp",[[v,"touchmove","move","notPassiveCapture"],[v,"touchcancel","end","notPassiveCapture"],[v,"touchend","end","notPassiveCapture"]]),t.start(a)}},start(a,v){B.is.firefox===!0&&M(e,!0);const h=O(a);t.event={x:h.left,y:h.top,time:Date.now(),mouse:v===!0,dir:!1}},move(a){if(t.event===void 0)return;if(t.event.dir!==!1){L(a);return}const v=Date.now()-t.event.time;if(v===0)return;const h=O(a),y=h.left-t.event.x,u=Math.abs(y),b=h.top-t.event.y,s=Math.abs(b);if(t.event.mouse!==!0){if(u<t.sensitivity[1]&&s<t.sensitivity[1]){t.end(a);return}}else if(window.getSelection().toString()!==""){t.end(a);return}else if(u<t.sensitivity[2]&&s<t.sensitivity[2])return;const 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C=()=>{document.body.classList.remove("no-pointer-events--children")};w===!0?setTimeout(C,50):C()}),t.handler({evt:a,touch:t.event.mouse!==!0,mouse:t.event.mouse,direction:t.event.dir,duration:v,distance:{x:u,y:s}})):t.end(a)},end(a){t.event!==void 0&&(z(t,"temp"),B.is.firefox===!0&&M(e,!1),t.styleCleanup!==void 0&&t.styleCleanup(!0),a!==void 0&&t.event.dir!==!1&&L(a),t.event=void 0)}};if(e.__qtouchswipe=t,m.mouse===!0){const a=m.mouseCapture===!0||m.mousecapture===!0?"Capture":"";V(t,"main",[[e,"mousedown","mouseStart",`passive${a}`]])}B.has.touch===!0&&V(t,"main",[[e,"touchstart","touchStart",`passive${m.capture===!0?"Capture":""}`],[e,"touchmove","noop","notPassiveCapture"]])},updated(e,o){const l=e.__qtouchswipe;l!==void 0&&(o.oldValue!==o.value&&(typeof o.value!="function"&&l.end(),l.handler=o.value),l.direction=R(o.modifiers))},beforeUnmount(e){const o=e.__qtouchswipe;o!==void 0&&(z(o,"main"),z(o,"temp"),B.is.firefox===!0&&M(e,!1),o.styleCleanup!==void 0&&o.styleCleanup(),delete e.__qtouchswipe)}});const he={name:{required:!0},disable:Boolean},W={setup(e,{slots:o}){return()=>f("div",{class:"q-panel scroll",role:"tabpanel"},K(o.default))}},ye={modelValue:{required:!0},animated:Boolean,infinite:Boolean,swipeable:Boolean,vertical:Boolean,transitionPrev:String,transitionNext:String,transitionDuration:{type:[String,Number],default:300},keepAlive:Boolean,keepAliveInclude:[String,Array,RegExp],keepAliveExclude:[String,Array,RegExp],keepAliveMax:Number},be=["update:modelValue","beforeTransition","transition"];function xe(){const{props:e,emit:o,proxy:l}=X(),{getCacheWithFn:m}=ve();let i,t;const a=j(null),v=j(null);function h(n){const r=e.vertical===!0?"up":"left";P((l.$q.lang.rtl===!0?-1:1)*(n.direction===r?1:-1))}const y=d(()=>[[ge,h,void 0,{horizontal:e.vertical!==!0,vertical:e.vertical,mouse:!0}]]),u=d(()=>e.transitionPrev||`slide-${e.vertical===!0?"down":"right"}`),b=d(()=>e.transitionNext||`slide-${e.vertical===!0?"up":"left"}`),s=d(()=>`--q-transition-duration: 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Object.assign(l,{next:C,previous:D,goTo:T}),{panelIndex:a,panelDirectives:y,updatePanelsList:S,updatePanelIndex:$,getPanelContent:c,getEnabledPanels:E,getPanels:A,isValidPanelName:_,keepAliveProps:x,needsUniqueKeepAliveWrapper:w,goToPanelByOffset:P,goToPanel:T,nextPanel:C,previousPanel:D}}var Te=Y({name:"QCarouselSlide",props:{...he,imgSrc:String},setup(e,{slots:o}){const l=d(()=>e.imgSrc?{backgroundImage:`url("${e.imgSrc}")`}:{});return()=>f("div",{class:"q-carousel__slide",style:l.value},K(o.default))}});const Ce=["top","right","bottom","left"],Pe=["regular","flat","outline","push","unelevated"];var Ie=Y({name:"QCarousel",props:{...ae,...ye,...de,transitionPrev:{type:String,default:"fade"},transitionNext:{type:String,default:"fade"},height:String,padding:Boolean,controlColor:String,controlTextColor:String,controlType:{type:String,validator:e=>Pe.includes(e),default:"flat"},autoplay:[Number,Boolean],arrows:Boolean,prevIcon:String,nextIcon:String,navigation:Boolean,navigationPosition:{type:String,validator:e=>Ce.includes(e)},navigationIcon:String,navigationActiveIcon:String,thumbnails:Boolean},emits:[...fe,...be],setup(e,{slots:o}){const{proxy:{$q:l}}=X(),m=oe(e,l);let i=null,t;const{updatePanelsList:a,getPanelContent:v,panelDirectives:h,goToPanel:y,previousPanel:u,nextPanel:b,getEnabledPanels:s,panelIndex:p}=xe(),{inFullscreen:x}=me(),w=d(()=>x.value!==!0&&e.height!==void 0?{height:e.height}:{}),C=d(()=>e.vertical===!0?"vertical":"horizontal"),D=d(()=>`q-carousel q-panel-parent q-carousel--with${e.padding===!0?"":"out"}-padding`+(x.value===!0?" fullscreen":"")+(m.value===!0?" q-carousel--dark q-dark":"")+(e.arrows===!0?` q-carousel--arrows-${C.value}`:"")+(e.navigation===!0?` q-carousel--navigation-${E.value}`:"")),T=d(()=>{const c=[e.prevIcon||l.iconSet.carousel[e.vertical===!0?"up":"left"],e.nextIcon||l.iconSet.carousel[e.vertical===!0?"down":"right"]];return e.vertical===!1&&l.lang.rtl===!0?c.reverse():c}),_=d(()=>e.navigationIcon||l.iconSet.carousel.navigationIcon),I=d(()=>e.navigationActiveIcon||_.value),E=d(()=>e.navigationPosition||(e.vertical===!0?"right":"bottom")),k=d(()=>({color:e.controlColor,textColor:e.controlTextColor,round:!0,[e.controlType]:!0,dense:!0}));Q(()=>e.modelValue,()=>{e.autoplay&&P()}),Q(()=>e.autoplay,c=>{c?P():i!==null&&(clearTimeout(i),i=null)});function P(){const c=ue(e.autoplay)===!0?Math.abs(e.autoplay):5e3;i!==null&&clearTimeout(i),i=setTimeout(()=>{i=null,c>=0?b():u()},c)}ie(()=>{e.autoplay&&P()}),re(()=>{i!==null&&clearTimeout(i)});function $(c,S){return f("div",{class:`q-carousel__control q-carousel__navigation no-wrap absolute flex q-carousel__navigation--${c} q-carousel__navigation--${E.value}`+(e.controlColor!==void 0?` text-${e.controlColor}`:"")},[f("div",{class:"q-carousel__navigation-inner flex flex-center no-wrap"},s().map(S))])}function N(){const c=[];if(e.navigation===!0){const S=o["navigation-icon"]!==void 0?o["navigation-icon"]:n=>f(F,{key:"nav"+n.name,class:`q-carousel__navigation-icon q-carousel__navigation-icon--${n.active===!0?"":"in"}active`,...n.btnProps,onClick:n.onClick}),A=t-1;c.push($("buttons",(n,r)=>{const g=n.props.name,q=p.value===r;return S({index:r,maxIndex:A,name:g,active:q,btnProps:{icon:q===!0?I.value:_.value,size:"sm",...k.value},onClick:()=>{y(g)}})}))}else if(e.thumbnails===!0){const S=e.controlColor!==void 0?` text-${e.controlColor}`:"";c.push($("thumbnails",A=>{const n=A.props;return f("img",{key:"tmb#"+n.name,class:`q-carousel__thumbnail q-carousel__thumbnail--${n.name===e.modelValue?"":"in"}active`+S,src:n.imgSrc||n["img-src"],onClick:()=>{y(n.name)}})}))}return e.arrows===!0&&p.value>=0&&((e.infinite===!0||p.value>0)&&c.push(f("div",{key:"prev",class:`q-carousel__control q-carousel__arrow q-carousel__prev-arrow q-carousel__prev-arrow--${C.value} absolute flex flex-center`},[f(F,{icon:T.value[0],...k.value,onClick:u})])),(e.infinite===!0||p.value<t-1)&&c.push(f("div",{key:"next",class:`q-carousel__control q-carousel__arrow q-carousel__next-arrow q-carousel__next-arrow--${C.value} absolute flex flex-center`},[f(F,{icon:T.value[1],...k.value,onClick:b})]))),se(o.control,c)}return()=>(t=a(o),f("div",{class:D.value,style:w.value},[le("div",{class:"q-carousel__slides-container"},v(),"sl-cont",e.swipeable,()=>h.value)].concat(N())))}});export{Te as Q,Ie as a,ye as b,be as c,xe as d,he as u};
+import{b5 as H,N as B,aH as J,bi as G,z as V,bj as M,bc as O,E as L,y as z,f as j,h as d,w as Q,C as X,i as f,T as Z,bB as ee,D as K,J as te,bC as ne,k as Y,R as ae,S as oe,K as ie,x as re,$ as le,bD as ue,j as F,a4 as se}from"./index.ae19b4cb.js";import{g as R,s as U}from"./touch.3df10340.js";import{c as ce}from"./selection.10af5b4d.js";import{u as ve}from"./use-cache.b0833c75.js";import{u as de,a as fe,b as me}from"./use-fullscreen.324b1ba3.js";function pe(e){const o=[.06,6,50];return typeof e=="string"&&e.length&&e.split(":").forEach((l,m)=>{const i=parseFloat(l);i&&(o[m]=i)}),o}var ge=H({name:"touch-swipe",beforeMount(e,{value:o,arg:l,modifiers:m}){if(m.mouse!==!0&&B.has.touch!==!0)return;const i=m.mouseCapture===!0?"Capture":"",t={handler:o,sensitivity:pe(l),direction:R(m),noop:J,mouseStart(a){U(a,t)&&G(a)&&(V(t,"temp",[[document,"mousemove","move",`notPassive${i}`],[document,"mouseup","end","notPassiveCapture"]]),t.start(a,!0))},touchStart(a){if(U(a,t)){const 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Ie=Y({name:"QCarousel",props:{...ae,...ye,...de,transitionPrev:{type:String,default:"fade"},transitionNext:{type:String,default:"fade"},height:String,padding:Boolean,controlColor:String,controlTextColor:String,controlType:{type:String,validator:e=>Pe.includes(e),default:"flat"},autoplay:[Number,Boolean],arrows:Boolean,prevIcon:String,nextIcon:String,navigation:Boolean,navigationPosition:{type:String,validator:e=>Ce.includes(e)},navigationIcon:String,navigationActiveIcon:String,thumbnails:Boolean},emits:[...fe,...be],setup(e,{slots:o}){const{proxy:{$q:l}}=X(),m=oe(e,l);let i=null,t;const{updatePanelsList:a,getPanelContent:v,panelDirectives:h,goToPanel:y,previousPanel:u,nextPanel:b,getEnabledPanels:s,panelIndex:p}=xe(),{inFullscreen:x}=me(),w=d(()=>x.value!==!0&&e.height!==void 0?{height:e.height}:{}),C=d(()=>e.vertical===!0?"vertical":"horizontal"),D=d(()=>`q-carousel q-panel-parent q-carousel--with${e.padding===!0?"":"out"}-padding`+(x.value===!0?" fullscreen":"")+(m.value===!0?" q-carousel--dark q-dark":"")+(e.arrows===!0?` q-carousel--arrows-${C.value}`:"")+(e.navigation===!0?` q-carousel--navigation-${E.value}`:"")),T=d(()=>{const c=[e.prevIcon||l.iconSet.carousel[e.vertical===!0?"up":"left"],e.nextIcon||l.iconSet.carousel[e.vertical===!0?"down":"right"]];return e.vertical===!1&&l.lang.rtl===!0?c.reverse():c}),_=d(()=>e.navigationIcon||l.iconSet.carousel.navigationIcon),I=d(()=>e.navigationActiveIcon||_.value),E=d(()=>e.navigationPosition||(e.vertical===!0?"right":"bottom")),k=d(()=>({color:e.controlColor,textColor:e.controlTextColor,round:!0,[e.controlType]:!0,dense:!0}));Q(()=>e.modelValue,()=>{e.autoplay&&P()}),Q(()=>e.autoplay,c=>{c?P():i!==null&&(clearTimeout(i),i=null)});function P(){const c=ue(e.autoplay)===!0?Math.abs(e.autoplay):5e3;i!==null&&clearTimeout(i),i=setTimeout(()=>{i=null,c>=0?b():u()},c)}ie(()=>{e.autoplay&&P()}),re(()=>{i!==null&&clearTimeout(i)});function $(c,S){return f("div",{class:`q-carousel__control q-carousel__navigation no-wrap 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e.arrows===!0&&p.value>=0&&((e.infinite===!0||p.value>0)&&c.push(f("div",{key:"prev",class:`q-carousel__control q-carousel__arrow q-carousel__prev-arrow q-carousel__prev-arrow--${C.value} absolute flex flex-center`},[f(F,{icon:T.value[0],...k.value,onClick:u})])),(e.infinite===!0||p.value<t-1)&&c.push(f("div",{key:"next",class:`q-carousel__control q-carousel__arrow q-carousel__next-arrow q-carousel__next-arrow--${C.value} absolute flex flex-center`},[f(F,{icon:T.value[1],...k.value,onClick:b})]))),se(o.control,c)}return()=>(t=a(o),f("div",{class:D.value,style:w.value},[le("div",{class:"q-carousel__slides-container"},v(),"sl-cont",e.swipeable,()=>h.value)].concat(N())))}});export{Te as Q,Ie as a,ye as b,be as c,xe as d,he as u};
diff --git a/assets/QChatMessage.6c0b9515.js b/assets/QChatMessage.73c078ff.js
similarity index 96%
rename from assets/QChatMessage.6c0b9515.js
rename to assets/QChatMessage.73c078ff.js
index 23f9f37bb68..07e44400c0e 100644
--- a/assets/QChatMessage.6c0b9515.js
+++ b/assets/QChatMessage.73c078ff.js
@@ -1 +1 @@
-import{k as q,h as v,i as a,bB as C}from"./index.2b6e3ac7.js";var f=q({name:"QChatMessage",props:{sent:Boolean,label:String,bgColor:String,textColor:String,name:String,avatar:String,text:Array,stamp:String,size:String,labelHtml:Boolean,nameHtml:Boolean,textHtml:Boolean,stampHtml:Boolean},setup(e,{slots:s}){const m=v(()=>e.sent===!0?"sent":"received"),o=v(()=>`q-message-text-content q-message-text-content--${m.value}`+(e.textColor!==void 0?` text-${e.textColor}`:"")),g=v(()=>`q-message-text q-message-text--${m.value}`+(e.bgColor!==void 0?` text-${e.bgColor}`:"")),c=v(()=>"q-message-container row items-end no-wrap"+(e.sent===!0?" reverse":"")),d=v(()=>e.size!==void 0?`col-${e.size}`:""),r=v(()=>({msg:e.textHtml===!0?"innerHTML":"textContent",stamp:e.stampHtml===!0?"innerHTML":"textContent",name:e.nameHtml===!0?"innerHTML":"textContent",label:e.labelHtml===!0?"innerHTML":"textContent"}));function x(t){return s.stamp!==void 0?[t,a("div",{class:"q-message-stamp"},s.stamp())]:e.stamp?[t,a("div",{class:"q-message-stamp",[r.value.stamp]:e.stamp})]:[t]}function u(t,n){const i=n===!0?t.length>1?l=>l:l=>a("div",[l]):l=>a("div",{[r.value.msg]:l});return t.map((l,h)=>a("div",{key:h,class:g.value},[a("div",{class:o.value},x(i(l)))]))}return()=>{const t=[];s.avatar!==void 0?t.push(s.avatar()):e.avatar!==void 0&&t.push(a("img",{class:`q-message-avatar q-message-avatar--${m.value}`,src:e.avatar,"aria-hidden":"true"}));const n=[];s.name!==void 0?n.push(a("div",{class:`q-message-name q-message-name--${m.value}`},s.name())):e.name!==void 0&&n.push(a("div",{class:`q-message-name q-message-name--${m.value}`,[r.value.name]:e.name})),s.default!==void 0?n.push(u(C(s.default()),!0)):e.text!==void 0&&n.push(u(e.text)),t.push(a("div",{class:d.value},n));const i=[];return s.label!==void 0?i.push(a("div",{class:"q-message-label"},s.label())):e.label!==void 0&&i.push(a("div",{class:"q-message-label",[r.value.label]:e.label})),i.push(a("div",{class:c.value},t)),a("div",{class:`q-message q-message-${m.value}`},i)}}});export{f as Q};
+import{k as q,h as v,i as a,bB as C}from"./index.ae19b4cb.js";var f=q({name:"QChatMessage",props:{sent:Boolean,label:String,bgColor:String,textColor:String,name:String,avatar:String,text:Array,stamp:String,size:String,labelHtml:Boolean,nameHtml:Boolean,textHtml:Boolean,stampHtml:Boolean},setup(e,{slots:s}){const m=v(()=>e.sent===!0?"sent":"received"),o=v(()=>`q-message-text-content q-message-text-content--${m.value}`+(e.textColor!==void 0?` text-${e.textColor}`:"")),g=v(()=>`q-message-text q-message-text--${m.value}`+(e.bgColor!==void 0?` text-${e.bgColor}`:"")),c=v(()=>"q-message-container row items-end no-wrap"+(e.sent===!0?" reverse":"")),d=v(()=>e.size!==void 0?`col-${e.size}`:""),r=v(()=>({msg:e.textHtml===!0?"innerHTML":"textContent",stamp:e.stampHtml===!0?"innerHTML":"textContent",name:e.nameHtml===!0?"innerHTML":"textContent",label:e.labelHtml===!0?"innerHTML":"textContent"}));function x(t){return s.stamp!==void 0?[t,a("div",{class:"q-message-stamp"},s.stamp())]:e.stamp?[t,a("div",{class:"q-message-stamp",[r.value.stamp]:e.stamp})]:[t]}function u(t,n){const i=n===!0?t.length>1?l=>l:l=>a("div",[l]):l=>a("div",{[r.value.msg]:l});return t.map((l,h)=>a("div",{key:h,class:g.value},[a("div",{class:o.value},x(i(l)))]))}return()=>{const t=[];s.avatar!==void 0?t.push(s.avatar()):e.avatar!==void 0&&t.push(a("img",{class:`q-message-avatar q-message-avatar--${m.value}`,src:e.avatar,"aria-hidden":"true"}));const n=[];s.name!==void 0?n.push(a("div",{class:`q-message-name q-message-name--${m.value}`},s.name())):e.name!==void 0&&n.push(a("div",{class:`q-message-name q-message-name--${m.value}`,[r.value.name]:e.name})),s.default!==void 0?n.push(u(C(s.default()),!0)):e.text!==void 0&&n.push(u(e.text)),t.push(a("div",{class:d.value},n));const i=[];return s.label!==void 0?i.push(a("div",{class:"q-message-label"},s.label())):e.label!==void 0&&i.push(a("div",{class:"q-message-label",[r.value.label]:e.label})),i.push(a("div",{class:c.value},t)),a("div",{class:`q-message q-message-${m.value}`},i)}}});export{f as Q};
diff --git a/assets/QChip.dae6efcf.js b/assets/QChip.1a7b8095.js
similarity index 97%
rename from assets/QChip.dae6efcf.js
rename to assets/QChip.1a7b8095.js
index 3a9dc2de3f5..4ed36483172 100644
--- a/assets/QChip.dae6efcf.js
+++ b/assets/QChip.1a7b8095.js
@@ -1 +1 @@
-import{k as C,R as _,b8 as x,S as y,b9 as B,h as l,$ as R,i as a,aj as u,ba as I,bb as w,C as z,E as D}from"./index.2b6e3ac7.js";const Q={xs:8,sm:10,md:14,lg:20,xl:24};var $=C({name:"QChip",props:{..._,...x,dense:Boolean,icon:String,iconRight:String,iconRemove:String,iconSelected:String,label:[String,Number],color:String,textColor:String,modelValue:{type:Boolean,default:!0},selected:{type:Boolean,default:null},square:Boolean,outline:Boolean,clickable:Boolean,removable:Boolean,removeAriaLabel:String,tabindex:[String,Number],disable:Boolean,ripple:{type:[Boolean,Object],default:!0}},emits:["update:modelValue","update:selected","remove","click"],setup(e,{slots:b,emit:i}){const{proxy:{$q:n}}=z(),h=y(e,n),v=B(e,Q),m=l(()=>e.selected===!0||e.icon!==void 0),f=l(()=>e.selected===!0?e.iconSelected||n.iconSet.chip.selected:e.icon),q=l(()=>e.iconRemove||n.iconSet.chip.remove),c=l(()=>e.disable===!1&&(e.clickable===!0||e.selected!==null)),g=l(()=>{const t=e.outline===!0&&e.color||e.textColor;return"q-chip row inline no-wrap items-center"+(e.outline===!1&&e.color!==void 0?` bg-${e.color}`:"")+(t?` text-${t} q-chip--colored`:"")+(e.disable===!0?" disabled":"")+(e.dense===!0?" q-chip--dense":"")+(e.outline===!0?" q-chip--outline":"")+(e.selected===!0?" q-chip--selected":"")+(c.value===!0?" q-chip--clickable cursor-pointer non-selectable q-hoverable":"")+(e.square===!0?" q-chip--square":"")+(h.value===!0?" q-chip--dark q-dark":"")}),s=l(()=>{const t=e.disable===!0?{tabindex:-1,"aria-disabled":"true"}:{tabindex:e.tabindex||0},o={...t,role:"button","aria-hidden":"false","aria-label":e.removeAriaLabel||n.lang.label.remove};return{chip:t,remove:o}});function S(t){t.keyCode===13&&r(t)}function r(t){e.disable||(i("update:selected",!e.selected),i("click",t))}function d(t){(t.keyCode===void 0||t.keyCode===13)&&(D(t),e.disable===!1&&(i("update:modelValue",!1),i("remove")))}function k(){const t=[];c.value===!0&&t.push(a("div",{class:"q-focus-helper"})),m.value===!0&&t.push(a(u,{class:"q-chip__icon q-chip__icon--left",name:f.value}));const o=e.label!==void 0?[a("div",{class:"ellipsis"},[e.label])]:void 0;return t.push(a("div",{class:"q-chip__content col row no-wrap items-center q-anchor--skip"},I(b.default,o))),e.iconRight&&t.push(a(u,{class:"q-chip__icon q-chip__icon--right",name:e.iconRight})),e.removable===!0&&t.push(a(u,{class:"q-chip__icon q-chip__icon--remove cursor-pointer",name:q.value,...s.value.remove,onClick:d,onKeyup:d})),t}return()=>{if(e.modelValue===!1)return;const t={class:g.value,style:v.value};return c.value===!0&&Object.assign(t,s.value.chip,{onClick:r,onKeyup:S}),R("div",t,k(),"ripple",e.ripple!==!1&&e.disable!==!0,()=>[[w,e.ripple]])}}});export{$ as Q};
+import{k as C,R as _,b8 as x,S as y,b9 as B,h as l,$ as R,i as a,aj as u,ba as I,bb as w,C as z,E as D}from"./index.ae19b4cb.js";const Q={xs:8,sm:10,md:14,lg:20,xl:24};var $=C({name:"QChip",props:{..._,...x,dense:Boolean,icon:String,iconRight:String,iconRemove:String,iconSelected:String,label:[String,Number],color:String,textColor:String,modelValue:{type:Boolean,default:!0},selected:{type:Boolean,default:null},square:Boolean,outline:Boolean,clickable:Boolean,removable:Boolean,removeAriaLabel:String,tabindex:[String,Number],disable:Boolean,ripple:{type:[Boolean,Object],default:!0}},emits:["update:modelValue","update:selected","remove","click"],setup(e,{slots:b,emit:i}){const{proxy:{$q:n}}=z(),h=y(e,n),v=B(e,Q),m=l(()=>e.selected===!0||e.icon!==void 0),f=l(()=>e.selected===!0?e.iconSelected||n.iconSet.chip.selected:e.icon),q=l(()=>e.iconRemove||n.iconSet.chip.remove),c=l(()=>e.disable===!1&&(e.clickable===!0||e.selected!==null)),g=l(()=>{const t=e.outline===!0&&e.color||e.textColor;return"q-chip row inline no-wrap items-center"+(e.outline===!1&&e.color!==void 0?` bg-${e.color}`:"")+(t?` text-${t} q-chip--colored`:"")+(e.disable===!0?" disabled":"")+(e.dense===!0?" q-chip--dense":"")+(e.outline===!0?" q-chip--outline":"")+(e.selected===!0?" q-chip--selected":"")+(c.value===!0?" q-chip--clickable cursor-pointer non-selectable q-hoverable":"")+(e.square===!0?" q-chip--square":"")+(h.value===!0?" q-chip--dark q-dark":"")}),s=l(()=>{const t=e.disable===!0?{tabindex:-1,"aria-disabled":"true"}:{tabindex:e.tabindex||0},o={...t,role:"button","aria-hidden":"false","aria-label":e.removeAriaLabel||n.lang.label.remove};return{chip:t,remove:o}});function S(t){t.keyCode===13&&r(t)}function r(t){e.disable||(i("update:selected",!e.selected),i("click",t))}function d(t){(t.keyCode===void 0||t.keyCode===13)&&(D(t),e.disable===!1&&(i("update:modelValue",!1),i("remove")))}function k(){const t=[];c.value===!0&&t.push(a("div",{class:"q-focus-helper"})),m.value===!0&&t.push(a(u,{class:"q-chip__icon q-chip__icon--left",name:f.value}));const o=e.label!==void 0?[a("div",{class:"ellipsis"},[e.label])]:void 0;return t.push(a("div",{class:"q-chip__content col row no-wrap items-center q-anchor--skip"},I(b.default,o))),e.iconRight&&t.push(a(u,{class:"q-chip__icon q-chip__icon--right",name:e.iconRight})),e.removable===!0&&t.push(a(u,{class:"q-chip__icon q-chip__icon--remove cursor-pointer",name:q.value,...s.value.remove,onClick:d,onKeyup:d})),t}return()=>{if(e.modelValue===!1)return;const t={class:g.value,style:v.value};return c.value===!0&&Object.assign(t,s.value.chip,{onClick:r,onKeyup:S}),R("div",t,k(),"ripple",e.ripple!==!1&&e.disable!==!0,()=>[[w,e.ripple]])}}});export{$ as Q};
diff --git a/assets/QExpansionItem.6fccc081.js b/assets/QExpansionItem.b4d31658.js
similarity index 97%
rename from assets/QExpansionItem.6fccc081.js
rename to assets/QExpansionItem.b4d31658.js
index 426674c4dea..ff67fc8ef0e 100644
--- a/assets/QExpansionItem.6fccc081.js
+++ b/assets/QExpansionItem.b4d31658.js
@@ -1 +1 @@
-import{k as j,x as $,i as a,T as Z,a_ as J,a$ as N,l as W,R as p,n as ee,S as te,f as O,aX as Q,t as ne,h as v,w as k,ap as A,C as ae,ad as ie,Z as oe,b0 as le,D as ue,ae as _,aj as B,E as re}from"./index.2b6e3ac7.js";import{Q as H}from"./QItemLabel.4068d6dd.js";var se=j({name:"QSlideTransition",props:{appear:Boolean,duration:{type:Number,default:300}},emits:["show","hide"],setup(e,{slots:I,emit:T}){let r=!1,m,i,o=null,s=null,d,S;function b(){m&&m(),m=null,r=!1,o!==null&&(clearTimeout(o),o=null),s!==null&&(clearTimeout(s),s=null),i!==void 0&&i.removeEventListener("transitionend",d),d=null}function l(n,u,g){u!==void 0&&(n.style.height=`${u}px`),n.style.transition=`height ${e.duration}ms cubic-bezier(.25, .8, .50, 1)`,r=!0,m=g}function c(n,u){n.style.overflowY=null,n.style.height=null,n.style.transition=null,b(),u!==S&&T(u)}function y(n,u){let g=0;i=n,r===!0?(b(),g=n.offsetHeight===n.scrollHeight?0:void 0):(S="hide",n.style.overflowY="hidden"),l(n,g,u),o=setTimeout(()=>{o=null,n.style.height=`${n.scrollHeight}px`,d=f=>{s=null,(Object(f)!==f||f.target===n)&&c(n,"show")},n.addEventListener("transitionend",d),s=setTimeout(d,e.duration*1.1)},100)}function L(n,u){let g;i=n,r===!0?b():(S="show",n.style.overflowY="hidden",g=n.scrollHeight),l(n,g,u),o=setTimeout(()=>{o=null,n.style.height=0,d=f=>{s=null,(Object(f)!==f||f.target===n)&&c(n,"hide")},n.addEventListener("transitionend",d),s=setTimeout(d,e.duration*1.1)},100)}return $(()=>{r===!0&&b()}),()=>a(Z,{css:!1,appear:e.appear,onEnter:y,onLeave:L},I.default)}});const x=J({}),de=Object.keys(N);var fe=j({name:"QExpansionItem",props:{...N,...W,...p,icon:String,label:String,labelLines:[Number,String],caption:String,captionLines:[Number,String],dense:Boolean,toggleAriaLabel:String,expandIcon:String,expandedIcon:String,expandIconClass:[Array,String,Object],duration:Number,headerInsetLevel:Number,contentInsetLevel:Number,expandSeparator:Boolean,defaultOpened:Boolean,hideExpandIcon:Boolean,expandIconToggle:Boolean,switchToggleSide:Boolean,denseToggle:Boolean,group:String,popup:Boolean,headerStyle:[Array,String,Object],headerClass:[Array,String,Object]},emits:[...ee,"click","afterShow","afterHide"],setup(e,{slots:I,emit:T}){const{proxy:{$q:r}}=ae(),m=te(e,r),i=O(e.modelValue!==null?e.modelValue:e.defaultOpened),o=O(null),s=Q(),{show:d,hide:S,toggle:b}=ne({showing:i});let l,c;const y=v(()=>`q-expansion-item q-item-type q-expansion-item--${i.value===!0?"expanded":"collapsed"} q-expansion-item--${e.popup===!0?"popup":"standard"}`),L=v(()=>{if(e.contentInsetLevel===void 0)return null;const t=r.lang.rtl===!0?"Right":"Left";return{["padding"+t]:e.contentInsetLevel*56+"px"}}),n=v(()=>e.disable!==!0&&(e.href!==void 0||e.to!==void 0&&e.to!==null&&e.to!=="")),u=v(()=>{const t={};return de.forEach(h=>{t[h]=e[h]}),t}),g=v(()=>n.value===!0||e.expandIconToggle!==!0),f=v(()=>e.expandedIcon!==void 0&&i.value===!0?e.expandedIcon:e.expandIcon||r.iconSet.expansionItem[e.denseToggle===!0?"denseIcon":"icon"]),P=v(()=>e.disable!==!0&&(n.value===!0||e.expandIconToggle===!0)),R=v(()=>({expanded:i.value===!0,detailsId:e.targetUid,toggle:b,show:d,hide:S})),q=v(()=>{const t=e.toggleAriaLabel!==void 0?e.toggleAriaLabel:r.lang.label[i.value===!0?"collapse":"expand"](e.label);return{role:"button","aria-expanded":i.value===!0?"true":"false","aria-controls":s,"aria-label":t}});k(()=>e.group,t=>{c!==void 0&&c(),t!==void 0&&E()});function D(t){n.value!==!0&&b(t),T("click",t)}function G(t){t.keyCode===13&&C(t,!0)}function C(t,h){h!==!0&&o.value!==null&&o.value.focus(),b(t),re(t)}function K(){T("afterShow")}function M(){T("afterHide")}function E(){l===void 0&&(l=Q()),i.value===!0&&(x[e.group]=l);const t=k(i,w=>{w===!0?x[e.group]=l:x[e.group]===l&&delete x[e.group]}),h=k(()=>x[e.group],(w,X)=>{X===l&&w!==void 0&&w!==l&&S()});c=()=>{t(),h(),x[e.group]===l&&delete x[e.group],c=void 0}}function U(){const t={class:[`q-focusable relative-position cursor-pointer${e.denseToggle===!0&&e.switchToggleSide===!0?" items-end":""}`,e.expandIconClass],side:e.switchToggleSide!==!0,avatar:e.switchToggleSide},h=[a(B,{class:"q-expansion-item__toggle-icon"+(e.expandedIcon===void 0&&i.value===!0?" q-expansion-item__toggle-icon--rotated":""),name:f.value})];return P.value===!0&&(Object.assign(t,{tabindex:0,...q.value,onClick:C,onKeyup:G}),h.unshift(a("div",{ref:o,class:"q-expansion-item__toggle-focus q-icon q-focus-helper q-focus-helper--rounded",tabindex:-1}))),a(_,t,()=>h)}function Y(){let t;return I.header!==void 0?t=[].concat(I.header(R.value)):(t=[a(_,()=>[a(H,{lines:e.labelLines},()=>e.label||""),e.caption?a(H,{lines:e.captionLines,caption:!0},()=>e.caption):null])],e.icon&&t[e.switchToggleSide===!0?"push":"unshift"](a(_,{side:e.switchToggleSide===!0,avatar:e.switchToggleSide!==!0},()=>a(B,{name:e.icon})))),e.disable!==!0&&e.hideExpandIcon!==!0&&t[e.switchToggleSide===!0?"unshift":"push"](U()),t}function F(){const t={ref:"item",style:e.headerStyle,class:e.headerClass,dark:m.value,disable:e.disable,dense:e.dense,insetLevel:e.headerInsetLevel};return g.value===!0&&(t.clickable=!0,t.onClick=D,Object.assign(t,n.value===!0?u.value:q.value)),a(ie,t,Y)}function V(){return oe(a("div",{key:"e-content",class:"q-expansion-item__content relative-position",style:L.value,id:s},ue(I.default)),[[le,i.value]])}function z(){const t=[F(),a(se,{duration:e.duration,onShow:K,onHide:M},V)];return e.expandSeparator===!0&&t.push(a(A,{class:"q-expansion-item__border q-expansion-item__border--top absolute-top",dark:m.value}),a(A,{class:"q-expansion-item__border q-expansion-item__border--bottom absolute-bottom",dark:m.value})),t}return e.group!==void 0&&E(),$(()=>{c!==void 0&&c()}),()=>a("div",{class:y.value},[a("div",{class:"q-expansion-item__container relative-position"},z())])}});export{fe as Q};
+import{k as j,x as $,i as a,T as Z,a_ as J,a$ as N,l as W,R as p,n as ee,S as te,f as O,aX as Q,t as ne,h as v,w as k,ap as A,C as ae,ad as ie,Z as oe,b0 as le,D as ue,ae as _,aj as B,E as re}from"./index.ae19b4cb.js";import{Q as H}from"./QItemLabel.737cbb7d.js";var se=j({name:"QSlideTransition",props:{appear:Boolean,duration:{type:Number,default:300}},emits:["show","hide"],setup(e,{slots:I,emit:T}){let r=!1,m,i,o=null,s=null,d,S;function b(){m&&m(),m=null,r=!1,o!==null&&(clearTimeout(o),o=null),s!==null&&(clearTimeout(s),s=null),i!==void 0&&i.removeEventListener("transitionend",d),d=null}function l(n,u,g){u!==void 0&&(n.style.height=`${u}px`),n.style.transition=`height ${e.duration}ms cubic-bezier(.25, .8, .50, 1)`,r=!0,m=g}function c(n,u){n.style.overflowY=null,n.style.height=null,n.style.transition=null,b(),u!==S&&T(u)}function y(n,u){let g=0;i=n,r===!0?(b(),g=n.offsetHeight===n.scrollHeight?0:void 0):(S="hide",n.style.overflowY="hidden"),l(n,g,u),o=setTimeout(()=>{o=null,n.style.height=`${n.scrollHeight}px`,d=f=>{s=null,(Object(f)!==f||f.target===n)&&c(n,"show")},n.addEventListener("transitionend",d),s=setTimeout(d,e.duration*1.1)},100)}function L(n,u){let g;i=n,r===!0?b():(S="show",n.style.overflowY="hidden",g=n.scrollHeight),l(n,g,u),o=setTimeout(()=>{o=null,n.style.height=0,d=f=>{s=null,(Object(f)!==f||f.target===n)&&c(n,"hide")},n.addEventListener("transitionend",d),s=setTimeout(d,e.duration*1.1)},100)}return $(()=>{r===!0&&b()}),()=>a(Z,{css:!1,appear:e.appear,onEnter:y,onLeave:L},I.default)}});const x=J({}),de=Object.keys(N);var fe=j({name:"QExpansionItem",props:{...N,...W,...p,icon:String,label:String,labelLines:[Number,String],caption:String,captionLines:[Number,String],dense:Boolean,toggleAriaLabel:String,expandIcon:String,expandedIcon:String,expandIconClass:[Array,String,Object],duration:Number,headerInsetLevel:Number,contentInsetLevel:Number,expandSeparator:Boolean,defaultOpened:Boolean,hideExpandIcon:Boolean,expandIconToggle:Boolean,switchToggleSide:Boolean,denseToggle:Boolean,group:String,popup:Boolean,headerStyle:[Array,String,Object],headerClass:[Array,String,Object]},emits:[...ee,"click","afterShow","afterHide"],setup(e,{slots:I,emit:T}){const{proxy:{$q:r}}=ae(),m=te(e,r),i=O(e.modelValue!==null?e.modelValue:e.defaultOpened),o=O(null),s=Q(),{show:d,hide:S,toggle:b}=ne({showing:i});let l,c;const y=v(()=>`q-expansion-item q-item-type q-expansion-item--${i.value===!0?"expanded":"collapsed"} q-expansion-item--${e.popup===!0?"popup":"standard"}`),L=v(()=>{if(e.contentInsetLevel===void 0)return null;const t=r.lang.rtl===!0?"Right":"Left";return{["padding"+t]:e.contentInsetLevel*56+"px"}}),n=v(()=>e.disable!==!0&&(e.href!==void 0||e.to!==void 0&&e.to!==null&&e.to!=="")),u=v(()=>{const t={};return de.forEach(h=>{t[h]=e[h]}),t}),g=v(()=>n.value===!0||e.expandIconToggle!==!0),f=v(()=>e.expandedIcon!==void 0&&i.value===!0?e.expandedIcon:e.expandIcon||r.iconSet.expansionItem[e.denseToggle===!0?"denseIcon":"icon"]),P=v(()=>e.disable!==!0&&(n.value===!0||e.expandIconToggle===!0)),R=v(()=>({expanded:i.value===!0,detailsId:e.targetUid,toggle:b,show:d,hide:S})),q=v(()=>{const t=e.toggleAriaLabel!==void 0?e.toggleAriaLabel:r.lang.label[i.value===!0?"collapse":"expand"](e.label);return{role:"button","aria-expanded":i.value===!0?"true":"false","aria-controls":s,"aria-label":t}});k(()=>e.group,t=>{c!==void 0&&c(),t!==void 0&&E()});function D(t){n.value!==!0&&b(t),T("click",t)}function G(t){t.keyCode===13&&C(t,!0)}function C(t,h){h!==!0&&o.value!==null&&o.value.focus(),b(t),re(t)}function K(){T("afterShow")}function M(){T("afterHide")}function E(){l===void 0&&(l=Q()),i.value===!0&&(x[e.group]=l);const t=k(i,w=>{w===!0?x[e.group]=l:x[e.group]===l&&delete x[e.group]}),h=k(()=>x[e.group],(w,X)=>{X===l&&w!==void 0&&w!==l&&S()});c=()=>{t(),h(),x[e.group]===l&&delete x[e.group],c=void 0}}function U(){const t={class:[`q-focusable relative-position cursor-pointer${e.denseToggle===!0&&e.switchToggleSide===!0?" items-end":""}`,e.expandIconClass],side:e.switchToggleSide!==!0,avatar:e.switchToggleSide},h=[a(B,{class:"q-expansion-item__toggle-icon"+(e.expandedIcon===void 0&&i.value===!0?" q-expansion-item__toggle-icon--rotated":""),name:f.value})];return P.value===!0&&(Object.assign(t,{tabindex:0,...q.value,onClick:C,onKeyup:G}),h.unshift(a("div",{ref:o,class:"q-expansion-item__toggle-focus q-icon q-focus-helper q-focus-helper--rounded",tabindex:-1}))),a(_,t,()=>h)}function Y(){let t;return I.header!==void 0?t=[].concat(I.header(R.value)):(t=[a(_,()=>[a(H,{lines:e.labelLines},()=>e.label||""),e.caption?a(H,{lines:e.captionLines,caption:!0},()=>e.caption):null])],e.icon&&t[e.switchToggleSide===!0?"push":"unshift"](a(_,{side:e.switchToggleSide===!0,avatar:e.switchToggleSide!==!0},()=>a(B,{name:e.icon})))),e.disable!==!0&&e.hideExpandIcon!==!0&&t[e.switchToggleSide===!0?"unshift":"push"](U()),t}function F(){const t={ref:"item",style:e.headerStyle,class:e.headerClass,dark:m.value,disable:e.disable,dense:e.dense,insetLevel:e.headerInsetLevel};return g.value===!0&&(t.clickable=!0,t.onClick=D,Object.assign(t,n.value===!0?u.value:q.value)),a(ie,t,Y)}function V(){return oe(a("div",{key:"e-content",class:"q-expansion-item__content relative-position",style:L.value,id:s},ue(I.default)),[[le,i.value]])}function z(){const t=[F(),a(se,{duration:e.duration,onShow:K,onHide:M},V)];return e.expandSeparator===!0&&t.push(a(A,{class:"q-expansion-item__border q-expansion-item__border--top absolute-top",dark:m.value}),a(A,{class:"q-expansion-item__border q-expansion-item__border--bottom absolute-bottom",dark:m.value})),t}return e.group!==void 0&&E(),$(()=>{c!==void 0&&c()}),()=>a("div",{class:y.value},[a("div",{class:"q-expansion-item__container relative-position"},z())])}});export{fe as Q};
diff --git a/assets/QForm.c9a41b4c.js b/assets/QForm.c9044a42.js
similarity index 94%
rename from assets/QForm.c9a41b4c.js
rename to assets/QForm.c9044a42.js
index 67b0c36f376..0e8dbf66810 100644
--- a/assets/QForm.c9a41b4c.js
+++ b/assets/QForm.c9044a42.js
@@ -1 +1 @@
-import{k as F,f as P,a1 as q,aJ as A,aK as V,K as B,i as I,D as R,C as D,bV as K,E as p,J as Q,be as j,bW as k}from"./index.2b6e3ac7.js";var M=F({name:"QForm",props:{autofocus:Boolean,noErrorFocus:Boolean,noResetFocus:Boolean,greedy:Boolean,onSubmit:Function},emits:["reset","validationSuccess","validationError"],setup(r,{slots:C,emit:f}){const E=D(),s=P(null);let u=0;const i=[];function d(e){const a=typeof e=="boolean"?e:r.noErrorFocus!==!0,l=++u,x=(t,o)=>{f("validation"+(t===!0?"Success":"Error"),o)},h=t=>{const o=t.validate();return typeof o.then=="function"?o.then(n=>({valid:n,comp:t}),n=>({valid:!1,comp:t,err:n})):Promise.resolve({valid:o,comp:t})};return(r.greedy===!0?Promise.all(i.map(h)).then(t=>t.filter(o=>o.valid!==!0)):i.reduce((t,o)=>t.then(()=>h(o).then(n=>{if(n.valid===!1)return Promise.reject(n)})),Promise.resolve()).catch(t=>[t])).then(t=>{if(t===void 0||t.length===0)return l===u&&x(!0),!0;if(l===u){const{comp:o,err:n}=t[0];if(n!==void 0&&console.error(n),x(!1,o),a===!0){const g=t.find(({comp:S})=>typeof S.focus=="function"&&K(S.$)===!1);g!==void 0&&g.comp.focus()}}return!1})}function v(){u++,i.forEach(e=>{typeof e.resetValidation=="function"&&e.resetValidation()})}function m(e){e!==void 0&&p(e);const a=u+1;d().then(l=>{a===u&&l===!0&&(r.onSubmit!==void 0?f("submit",e):e!==void 0&&e.target!==void 0&&typeof e.target.submit=="function"&&e.target.submit())})}function b(e){e!==void 0&&p(e),f("reset"),Q(()=>{v(),r.autofocus===!0&&r.noResetFocus!==!0&&c()})}function c(){j(()=>{if(s.value===null)return;const e=s.value.querySelector("[autofocus][tabindex], [data-autofocus][tabindex]")||s.value.querySelector("[autofocus] [tabindex], [data-autofocus] [tabindex]")||s.value.querySelector("[autofocus], [data-autofocus]")||Array.prototype.find.call(s.value.querySelectorAll("[tabindex]"),a=>a.tabIndex>-1);e!=null&&e.focus({preventScroll:!0})})}q(k,{bindComponent(e){i.push(e)},unbindComponent(e){const a=i.indexOf(e);a>-1&&i.splice(a,1)}});let y=!1;return A(()=>{y=!0}),V(()=>{y===!0&&r.autofocus===!0&&c()}),B(()=>{r.autofocus===!0&&c()}),Object.assign(E.proxy,{validate:d,resetValidation:v,submit:m,reset:b,focus:c,getValidationComponents:()=>i}),()=>I("form",{class:"q-form",ref:s,onSubmit:m,onReset:b},R(C.default))}});export{M as Q};
+import{k as F,f as P,a1 as q,aJ as A,aK as V,K as B,i as I,D as R,C as D,bV as K,E as p,J as Q,be as j,bW as k}from"./index.ae19b4cb.js";var M=F({name:"QForm",props:{autofocus:Boolean,noErrorFocus:Boolean,noResetFocus:Boolean,greedy:Boolean,onSubmit:Function},emits:["reset","validationSuccess","validationError"],setup(r,{slots:C,emit:f}){const E=D(),s=P(null);let u=0;const i=[];function d(e){const a=typeof e=="boolean"?e:r.noErrorFocus!==!0,l=++u,x=(t,o)=>{f("validation"+(t===!0?"Success":"Error"),o)},h=t=>{const o=t.validate();return typeof o.then=="function"?o.then(n=>({valid:n,comp:t}),n=>({valid:!1,comp:t,err:n})):Promise.resolve({valid:o,comp:t})};return(r.greedy===!0?Promise.all(i.map(h)).then(t=>t.filter(o=>o.valid!==!0)):i.reduce((t,o)=>t.then(()=>h(o).then(n=>{if(n.valid===!1)return Promise.reject(n)})),Promise.resolve()).catch(t=>[t])).then(t=>{if(t===void 0||t.length===0)return l===u&&x(!0),!0;if(l===u){const{comp:o,err:n}=t[0];if(n!==void 0&&console.error(n),x(!1,o),a===!0){const g=t.find(({comp:S})=>typeof S.focus=="function"&&K(S.$)===!1);g!==void 0&&g.comp.focus()}}return!1})}function v(){u++,i.forEach(e=>{typeof e.resetValidation=="function"&&e.resetValidation()})}function m(e){e!==void 0&&p(e);const a=u+1;d().then(l=>{a===u&&l===!0&&(r.onSubmit!==void 0?f("submit",e):e!==void 0&&e.target!==void 0&&typeof e.target.submit=="function"&&e.target.submit())})}function b(e){e!==void 0&&p(e),f("reset"),Q(()=>{v(),r.autofocus===!0&&r.noResetFocus!==!0&&c()})}function c(){j(()=>{if(s.value===null)return;const e=s.value.querySelector("[autofocus][tabindex], [data-autofocus][tabindex]")||s.value.querySelector("[autofocus] [tabindex], [data-autofocus] [tabindex]")||s.value.querySelector("[autofocus], [data-autofocus]")||Array.prototype.find.call(s.value.querySelectorAll("[tabindex]"),a=>a.tabIndex>-1);e!=null&&e.focus({preventScroll:!0})})}q(k,{bindComponent(e){i.push(e)},unbindComponent(e){const a=i.indexOf(e);a>-1&&i.splice(a,1)}});let y=!1;return A(()=>{y=!0}),V(()=>{y===!0&&r.autofocus===!0&&c()}),B(()=>{r.autofocus===!0&&c()}),Object.assign(E.proxy,{validate:d,resetValidation:v,submit:m,reset:b,focus:c,getValidationComponents:()=>i}),()=>I("form",{class:"q-form",ref:s,onSubmit:m,onReset:b},R(C.default))}});export{M as Q};
diff --git a/assets/QImg.366b6afd.js b/assets/QImg.27db20fc.js
similarity index 98%
rename from assets/QImg.366b6afd.js
rename to assets/QImg.27db20fc.js
index 767c1aa7ab3..224dc2c82ce 100644
--- a/assets/QImg.366b6afd.js
+++ b/assets/QImg.27db20fc.js
@@ -1 +1 @@
-import{h as g,k as j,f as o,w as I,x as Q,i as a,T as $,D,aZ as E}from"./index.2b6e3ac7.js";const F={ratio:[String,Number]};function H(e,r){return g(()=>{const u=Number(e.ratio||(r!==void 0?r.value:void 0));return isNaN(u)!==!0&&u>0?{paddingBottom:`${100/u}%`}:null})}const L=16/9;var O=j({name:"QImg",props:{...F,src:String,srcset:String,sizes:String,alt:String,crossorigin:String,decoding:String,referrerpolicy:String,draggable:Boolean,loading:{type:String,default:"lazy"},fetchpriority:{type:String,default:"auto"},width:String,height:String,initialRatio:{type:[Number,String],default:L},placeholderSrc:String,fit:{type:String,default:"cover"},position:{type:String,default:"50% 50%"},imgClass:String,imgStyle:Object,noSpinner:Boolean,noNativeMenu:Boolean,noTransition:Boolean,spinnerColor:String,spinnerSize:String},emits:["load","error"],setup(e,{slots:r,emit:u}){const h=o(e.initialRatio),S=H(e,h);let t=null,d=!1;const l=[o(null),o(m())],n=o(0),s=o(!1),c=o(!1),w=g(()=>`q-img q-img--${e.noNativeMenu===!0?"no-":""}menu`),C=g(()=>({width:e.width,height:e.height})),T=g(()=>`q-img__image ${e.imgClass!==void 0?e.imgClass+" ":""}q-img__image--with${e.noTransition===!0?"out":""}-transition`),z=g(()=>({...e.imgStyle,objectFit:e.fit,objectPosition:e.position}));I(()=>y(),_);function y(){return e.src||e.srcset||e.sizes?{src:e.src,srcset:e.srcset,sizes:e.sizes}:null}function m(){return e.placeholderSrc!==void 0?{src:e.placeholderSrc}:null}function _(i){t!==null&&(clearTimeout(t),t=null),c.value=!1,i===null?(s.value=!1,l[n.value^1].value=m()):s.value=!0,l[n.value].value=i}function k({target:i}){d!==!0&&(t!==null&&(clearTimeout(t),t=null),h.value=i.naturalHeight===0?.5:i.naturalWidth/i.naturalHeight,b(i,1))}function b(i,f){d===!0||f===1e3||(i.complete===!0?N(i):t=setTimeout(()=>{t=null,b(i,f+1)},50))}function N(i){d!==!0&&(n.value=n.value^1,l[n.value].value=null,s.value=!1,c.value=!1,u("load",i.currentSrc||i.src))}function B(i){t!==null&&(clearTimeout(t),t=null),s.value=!1,c.value=!0,l[n.value].value=null,l[n.value^1].value=m(),u("error",i)}function q(i){const f=l[i].value,v={key:"img_"+i,class:T.value,style:z.value,crossorigin:e.crossorigin,decoding:e.decoding,referrerpolicy:e.referrerpolicy,height:e.height,width:e.width,loading:e.loading,fetchpriority:e.fetchpriority,"aria-hidden":"true",draggable:e.draggable,...f};return n.value===i?(v.class+=" q-img__image--waiting",Object.assign(v,{onLoad:k,onError:B})):v.class+=" q-img__image--loaded",a("div",{class:"q-img__container absolute-full",key:"img"+i},a("img",v))}function R(){return s.value!==!0?a("div",{key:"content",class:"q-img__content absolute-full q-anchor--skip"},D(r[c.value===!0?"error":"default"])):a("div",{key:"loading",class:"q-img__loading absolute-full flex flex-center"},r.loading!==void 0?r.loading():e.noSpinner===!0?void 0:[a(E,{color:e.spinnerColor,size:e.spinnerSize})])}return _(y()),Q(()=>{d=!0,t!==null&&(clearTimeout(t),t=null)}),()=>{const i=[];return S.value!==null&&i.push(a("div",{key:"filler",style:S.value})),c.value!==!0&&(l[0].value!==null&&i.push(q(0)),l[1].value!==null&&i.push(q(1))),i.push(a($,{name:"q-transition--fade"},R)),a("div",{class:w.value,style:C.value,role:"img","aria-label":e.alt},i)}}});export{O as Q,H as a,F as u};
+import{h as g,k as j,f as o,w as I,x as Q,i as a,T as $,D,aZ as E}from"./index.ae19b4cb.js";const F={ratio:[String,Number]};function H(e,r){return g(()=>{const u=Number(e.ratio||(r!==void 0?r.value:void 0));return isNaN(u)!==!0&&u>0?{paddingBottom:`${100/u}%`}:null})}const L=16/9;var O=j({name:"QImg",props:{...F,src:String,srcset:String,sizes:String,alt:String,crossorigin:String,decoding:String,referrerpolicy:String,draggable:Boolean,loading:{type:String,default:"lazy"},fetchpriority:{type:String,default:"auto"},width:String,height:String,initialRatio:{type:[Number,String],default:L},placeholderSrc:String,fit:{type:String,default:"cover"},position:{type:String,default:"50% 50%"},imgClass:String,imgStyle:Object,noSpinner:Boolean,noNativeMenu:Boolean,noTransition:Boolean,spinnerColor:String,spinnerSize:String},emits:["load","error"],setup(e,{slots:r,emit:u}){const h=o(e.initialRatio),S=H(e,h);let t=null,d=!1;const l=[o(null),o(m())],n=o(0),s=o(!1),c=o(!1),w=g(()=>`q-img q-img--${e.noNativeMenu===!0?"no-":""}menu`),C=g(()=>({width:e.width,height:e.height})),T=g(()=>`q-img__image ${e.imgClass!==void 0?e.imgClass+" ":""}q-img__image--with${e.noTransition===!0?"out":""}-transition`),z=g(()=>({...e.imgStyle,objectFit:e.fit,objectPosition:e.position}));I(()=>y(),_);function y(){return e.src||e.srcset||e.sizes?{src:e.src,srcset:e.srcset,sizes:e.sizes}:null}function m(){return e.placeholderSrc!==void 0?{src:e.placeholderSrc}:null}function _(i){t!==null&&(clearTimeout(t),t=null),c.value=!1,i===null?(s.value=!1,l[n.value^1].value=m()):s.value=!0,l[n.value].value=i}function k({target:i}){d!==!0&&(t!==null&&(clearTimeout(t),t=null),h.value=i.naturalHeight===0?.5:i.naturalWidth/i.naturalHeight,b(i,1))}function b(i,f){d===!0||f===1e3||(i.complete===!0?N(i):t=setTimeout(()=>{t=null,b(i,f+1)},50))}function N(i){d!==!0&&(n.value=n.value^1,l[n.value].value=null,s.value=!1,c.value=!1,u("load",i.currentSrc||i.src))}function B(i){t!==null&&(clearTimeout(t),t=null),s.value=!1,c.value=!0,l[n.value].value=null,l[n.value^1].value=m(),u("error",i)}function q(i){const f=l[i].value,v={key:"img_"+i,class:T.value,style:z.value,crossorigin:e.crossorigin,decoding:e.decoding,referrerpolicy:e.referrerpolicy,height:e.height,width:e.width,loading:e.loading,fetchpriority:e.fetchpriority,"aria-hidden":"true",draggable:e.draggable,...f};return n.value===i?(v.class+=" q-img__image--waiting",Object.assign(v,{onLoad:k,onError:B})):v.class+=" q-img__image--loaded",a("div",{class:"q-img__container absolute-full",key:"img"+i},a("img",v))}function R(){return s.value!==!0?a("div",{key:"content",class:"q-img__content absolute-full q-anchor--skip"},D(r[c.value===!0?"error":"default"])):a("div",{key:"loading",class:"q-img__loading absolute-full flex flex-center"},r.loading!==void 0?r.loading():e.noSpinner===!0?void 0:[a(E,{color:e.spinnerColor,size:e.spinnerSize})])}return _(y()),Q(()=>{d=!0,t!==null&&(clearTimeout(t),t=null)}),()=>{const i=[];return S.value!==null&&i.push(a("div",{key:"filler",style:S.value})),c.value!==!0&&(l[0].value!==null&&i.push(q(0)),l[1].value!==null&&i.push(q(1))),i.push(a($,{name:"q-transition--fade"},R)),a("div",{class:w.value,style:C.value,role:"img","aria-label":e.alt},i)}}});export{O as Q,H as a,F as u};
diff --git a/assets/QItemLabel.4068d6dd.js b/assets/QItemLabel.737cbb7d.js
similarity index 90%
rename from assets/QItemLabel.4068d6dd.js
rename to assets/QItemLabel.737cbb7d.js
index 728c017b496..15021791451 100644
--- a/assets/QItemLabel.4068d6dd.js
+++ b/assets/QItemLabel.737cbb7d.js
@@ -1 +1 @@
-import{k as o,h as t,i as r,D as s}from"./index.2b6e3ac7.js";var v=o({name:"QItemLabel",props:{overline:Boolean,caption:Boolean,header:Boolean,lines:[Number,String]},setup(e,{slots:a}){const l=t(()=>parseInt(e.lines,10)),i=t(()=>"q-item__label"+(e.overline===!0?" q-item__label--overline text-overline":"")+(e.caption===!0?" q-item__label--caption text-caption":"")+(e.header===!0?" q-item__label--header":"")+(l.value===1?" ellipsis":"")),n=t(()=>e.lines!==void 0&&l.value>1?{overflow:"hidden",display:"-webkit-box","-webkit-box-orient":"vertical","-webkit-line-clamp":l.value}:null);return()=>r("div",{style:n.value,class:i.value},s(a.default))}});export{v as Q};
+import{k as o,h as t,i as r,D as s}from"./index.ae19b4cb.js";var v=o({name:"QItemLabel",props:{overline:Boolean,caption:Boolean,header:Boolean,lines:[Number,String]},setup(e,{slots:a}){const l=t(()=>parseInt(e.lines,10)),i=t(()=>"q-item__label"+(e.overline===!0?" q-item__label--overline text-overline":"")+(e.caption===!0?" q-item__label--caption text-caption":"")+(e.header===!0?" q-item__label--header":"")+(l.value===1?" ellipsis":"")),n=t(()=>e.lines!==void 0&&l.value>1?{overflow:"hidden",display:"-webkit-box","-webkit-box-orient":"vertical","-webkit-line-clamp":l.value}:null);return()=>r("div",{style:n.value,class:i.value},s(a.default))}});export{v as Q};
diff --git a/assets/QList.77d2e514.js b/assets/QList.8bff8777.js
similarity index 88%
rename from assets/QList.77d2e514.js
rename to assets/QList.8bff8777.js
index 1318f0f6861..5e272fb2f9b 100644
--- a/assets/QList.77d2e514.js
+++ b/assets/QList.8bff8777.js
@@ -1 +1 @@
-import{k as o,R as n,S as d,h as l,i,D as u,C as c}from"./index.2b6e3ac7.js";var q=o({name:"QList",props:{...n,bordered:Boolean,dense:Boolean,separator:Boolean,padding:Boolean,tag:{type:String,default:"div"}},setup(e,{slots:a}){const t=c(),s=d(e,t.proxy.$q),r=l(()=>"q-list"+(e.bordered===!0?" q-list--bordered":"")+(e.dense===!0?" q-list--dense":"")+(e.separator===!0?" q-list--separator":"")+(s.value===!0?" q-list--dark":"")+(e.padding===!0?" q-list--padding":""));return()=>i(e.tag,{class:r.value},u(a.default))}});export{q as Q};
+import{k as o,R as n,S as d,h as l,i,D as u,C as c}from"./index.ae19b4cb.js";var q=o({name:"QList",props:{...n,bordered:Boolean,dense:Boolean,separator:Boolean,padding:Boolean,tag:{type:String,default:"div"}},setup(e,{slots:a}){const t=c(),s=d(e,t.proxy.$q),r=l(()=>"q-list"+(e.bordered===!0?" q-list--bordered":"")+(e.dense===!0?" q-list--dense":"")+(e.separator===!0?" q-list--separator":"")+(s.value===!0?" q-list--dark":"")+(e.padding===!0?" q-list--padding":""));return()=>i(e.tag,{class:r.value},u(a.default))}});export{q as Q};
diff --git a/assets/QMenu.d2069e37.js b/assets/QMenu.d7b6411c.js
similarity index 95%
rename from assets/QMenu.d2069e37.js
rename to assets/QMenu.d7b6411c.js
index b2b9ce219bf..61c9f0703a8 100644
--- a/assets/QMenu.d2069e37.js
+++ b/assets/QMenu.d7b6411c.js
@@ -1 +1 @@
-import{k as ae,l as ne,R as se,m as ue,n as le,f as w,h as u,S as ie,p as re,q as ce,s as fe,t as de,v as ve,w as D,F as ge,bc as he,G as me,bd as M,B as ye,i as R,D as Pe,T as Te,x as ke,C as be,be as Ce,bf as Se,bg as xe,bh as qe,E as Oe}from"./index.2b6e3ac7.js";import{u as Be,v as A,a as Ee,b as Fe,c as we,r as H,s as De,p as K,d as Me}from"./position-engine.7fb36afb.js";var He=ae({name:"QMenu",inheritAttrs:!1,props:{...Be,...ne,...se,...ue,persistent:Boolean,autoClose:Boolean,separateClosePopup:Boolean,noRouteDismiss:Boolean,noRefocus:Boolean,noFocus:Boolean,fit:Boolean,cover:Boolean,square:Boolean,anchor:{type:String,validator:A},self:{type:String,validator:A},offset:{type:Array,validator:Ee},scrollTarget:{default:void 0},touchPosition:Boolean,maxHeight:{type:String,default:null},maxWidth:{type:String,default:null}},emits:[...le,"click","escapeKey"],setup(t,{slots:Q,emit:c,attrs:d}){let n=null,f,l,v;const T=be(),{proxy:g}=T,{$q:o}=g,a=w(null),s=w(!1),W=u(()=>t.persistent!==!0&&t.noRouteDismiss!==!0),_=ie(t,o),{registerTick:j,removeTick:G}=re(),{registerTimeout:k}=ce(),{transitionProps:I,transitionStyle:L}=fe(t),{localScrollTarget:b,changeScrollEvent:U,unconfigureScrollTarget:$}=Fe(t,E),{anchorEl:i,canShow:z}=we({showing:s}),{hide:C}=de({showing:s,canShow:z,handleShow:Y,handleHide:Z,hideOnRouteChange:W,processOnMount:!0}),{showPortal:S,hidePortal:x,renderPortal:J}=ve(T,a,ee,"menu"),h={anchorEl:i,innerRef:a,onClickOutside(e){if(t.persistent!==!0&&s.value===!0)return C(e),(e.type==="touchstart"||e.target.classList.contains("q-dialog__backdrop"))&&Oe(e),!0}},q=u(()=>K(t.anchor||(t.cover===!0?"center middle":"bottom start"),o.lang.rtl)),N=u(()=>t.cover===!0?q.value:K(t.self||"top start",o.lang.rtl)),V=u(()=>(t.square===!0?" q-menu--square":"")+(_.value===!0?" q-menu--dark q-dark":"")),X=u(()=>t.autoClose===!0?{onClick:p}:{}),O=u(()=>s.value===!0&&t.persistent!==!0);D(O,e=>{e===!0?(xe(y),Me(h)):(M(y),H(h))});function m(){Ce(()=>{let e=a.value;e&&e.contains(document.activeElement)!==!0&&(e=e.querySelector("[autofocus][tabindex], [data-autofocus][tabindex]")||e.querySelector("[autofocus] [tabindex], [data-autofocus] [tabindex]")||e.querySelector("[autofocus], [data-autofocus]")||e,e.focus({preventScroll:!0}))})}function Y(e){if(n=t.noRefocus===!1?document.activeElement:null,ge(F),S(),E(),f=void 0,e!==void 0&&(t.touchPosition||t.contextMenu)){const P=he(e);if(P.left!==void 0){const{top:te,left:oe}=i.value.getBoundingClientRect();f={left:P.left-oe,top:P.top-te}}}l===void 0&&(l=D(()=>o.screen.width+"|"+o.screen.height+"|"+t.self+"|"+t.anchor+"|"+o.lang.rtl,r)),t.noFocus!==!0&&document.activeElement.blur(),j(()=>{r(),t.noFocus!==!0&&m()}),k(()=>{o.platform.is.ios===!0&&(v=t.autoClose,a.value.click()),r(),S(!0),c("show",e)},t.transitionDuration)}function Z(e){G(),x(),B(!0),n!==null&&(e===void 0||e.qClickOutside!==!0)&&(((e&&e.type.indexOf("key")===0?n.closest('[tabindex]:not([tabindex^="-"])'):void 0)||n).focus(),n=null),k(()=>{x(!0),c("hide",e)},t.transitionDuration)}function B(e){f=void 0,l!==void 0&&(l(),l=void 0),(e===!0||s.value===!0)&&(me(F),$(),H(h),M(y)),e!==!0&&(n=null)}function E(){(i.value!==null||t.scrollTarget!==void 0)&&(b.value=ye(i.value,t.scrollTarget),U(b.value,r))}function p(e){v!==!0?(Se(g,e),c("click",e)):v=!1}function F(e){O.value===!0&&t.noFocus!==!0&&qe(a.value,e.target)!==!0&&m()}function y(e){c("escapeKey"),C(e)}function r(){De({targetEl:a.value,offset:t.offset,anchorEl:i.value,anchorOrigin:q.value,selfOrigin:N.value,absoluteOffset:f,fit:t.fit,cover:t.cover,maxHeight:t.maxHeight,maxWidth:t.maxWidth})}function ee(){return R(Te,I.value,()=>s.value===!0?R("div",{role:"menu",...d,ref:a,tabindex:-1,class:["q-menu q-position-engine scroll"+V.value,d.class],style:[d.style,L.value],...X.value},Pe(Q.default)):null)}return ke(B),Object.assign(g,{focus:m,updatePosition:r}),J}});export{He as Q};
+import{k as ae,l as ne,R as se,m as ue,n as le,f as w,h as u,S as ie,p as re,q as ce,s as fe,t as de,v as ve,w as D,F as ge,bc as he,G as me,bd as M,B as ye,i as R,D as Pe,T as Te,x as ke,C as be,be as Ce,bf as Se,bg as xe,bh as qe,E as Oe}from"./index.ae19b4cb.js";import{u as Be,v as A,a as Ee,b as Fe,c as we,r as H,s as De,p as K,d as Me}from"./position-engine.2f7193db.js";var He=ae({name:"QMenu",inheritAttrs:!1,props:{...Be,...ne,...se,...ue,persistent:Boolean,autoClose:Boolean,separateClosePopup:Boolean,noRouteDismiss:Boolean,noRefocus:Boolean,noFocus:Boolean,fit:Boolean,cover:Boolean,square:Boolean,anchor:{type:String,validator:A},self:{type:String,validator:A},offset:{type:Array,validator:Ee},scrollTarget:{default:void 0},touchPosition:Boolean,maxHeight:{type:String,default:null},maxWidth:{type:String,default:null}},emits:[...le,"click","escapeKey"],setup(t,{slots:Q,emit:c,attrs:d}){let n=null,f,l,v;const T=be(),{proxy:g}=T,{$q:o}=g,a=w(null),s=w(!1),W=u(()=>t.persistent!==!0&&t.noRouteDismiss!==!0),_=ie(t,o),{registerTick:j,removeTick:G}=re(),{registerTimeout:k}=ce(),{transitionProps:I,transitionStyle:L}=fe(t),{localScrollTarget:b,changeScrollEvent:U,unconfigureScrollTarget:$}=Fe(t,E),{anchorEl:i,canShow:z}=we({showing:s}),{hide:C}=de({showing:s,canShow:z,handleShow:Y,handleHide:Z,hideOnRouteChange:W,processOnMount:!0}),{showPortal:S,hidePortal:x,renderPortal:J}=ve(T,a,ee,"menu"),h={anchorEl:i,innerRef:a,onClickOutside(e){if(t.persistent!==!0&&s.value===!0)return C(e),(e.type==="touchstart"||e.target.classList.contains("q-dialog__backdrop"))&&Oe(e),!0}},q=u(()=>K(t.anchor||(t.cover===!0?"center middle":"bottom start"),o.lang.rtl)),N=u(()=>t.cover===!0?q.value:K(t.self||"top start",o.lang.rtl)),V=u(()=>(t.square===!0?" q-menu--square":"")+(_.value===!0?" q-menu--dark q-dark":"")),X=u(()=>t.autoClose===!0?{onClick:p}:{}),O=u(()=>s.value===!0&&t.persistent!==!0);D(O,e=>{e===!0?(xe(y),Me(h)):(M(y),H(h))});function m(){Ce(()=>{let e=a.value;e&&e.contains(document.activeElement)!==!0&&(e=e.querySelector("[autofocus][tabindex], [data-autofocus][tabindex]")||e.querySelector("[autofocus] [tabindex], [data-autofocus] [tabindex]")||e.querySelector("[autofocus], [data-autofocus]")||e,e.focus({preventScroll:!0}))})}function Y(e){if(n=t.noRefocus===!1?document.activeElement:null,ge(F),S(),E(),f=void 0,e!==void 0&&(t.touchPosition||t.contextMenu)){const P=he(e);if(P.left!==void 0){const{top:te,left:oe}=i.value.getBoundingClientRect();f={left:P.left-oe,top:P.top-te}}}l===void 0&&(l=D(()=>o.screen.width+"|"+o.screen.height+"|"+t.self+"|"+t.anchor+"|"+o.lang.rtl,r)),t.noFocus!==!0&&document.activeElement.blur(),j(()=>{r(),t.noFocus!==!0&&m()}),k(()=>{o.platform.is.ios===!0&&(v=t.autoClose,a.value.click()),r(),S(!0),c("show",e)},t.transitionDuration)}function Z(e){G(),x(),B(!0),n!==null&&(e===void 0||e.qClickOutside!==!0)&&(((e&&e.type.indexOf("key")===0?n.closest('[tabindex]:not([tabindex^="-"])'):void 0)||n).focus(),n=null),k(()=>{x(!0),c("hide",e)},t.transitionDuration)}function B(e){f=void 0,l!==void 0&&(l(),l=void 0),(e===!0||s.value===!0)&&(me(F),$(),H(h),M(y)),e!==!0&&(n=null)}function E(){(i.value!==null||t.scrollTarget!==void 0)&&(b.value=ye(i.value,t.scrollTarget),U(b.value,r))}function p(e){v!==!0?(Se(g,e),c("click",e)):v=!1}function F(e){O.value===!0&&t.noFocus!==!0&&qe(a.value,e.target)!==!0&&m()}function y(e){c("escapeKey"),C(e)}function r(){De({targetEl:a.value,offset:t.offset,anchorEl:i.value,anchorOrigin:q.value,selfOrigin:N.value,absoluteOffset:f,fit:t.fit,cover:t.cover,maxHeight:t.maxHeight,maxWidth:t.maxWidth})}function ee(){return R(Te,I.value,()=>s.value===!0?R("div",{role:"menu",...d,ref:a,tabindex:-1,class:["q-menu q-position-engine scroll"+V.value,d.class],style:[d.style,L.value],...X.value},Pe(Q.default)):null)}return ke(B),Object.assign(g,{focus:m,updatePosition:r}),J}});export{He as Q};
diff --git a/assets/QPage.9d7ab03a.js b/assets/QPage.785c0d26.js
similarity index 92%
rename from assets/QPage.9d7ab03a.js
rename to assets/QPage.785c0d26.js
index 48858f20b2b..5027cabf60e 100644
--- a/assets/QPage.9d7ab03a.js
+++ b/assets/QPage.785c0d26.js
@@ -1 +1 @@
-import{k as g,U as r,V as t,h as s,i as h,D as p,X as d,a2 as y,C as f}from"./index.2b6e3ac7.js";var m=g({name:"QPage",props:{padding:Boolean,styleFn:Function},setup(a,{slots:i}){const{proxy:{$q:o}}=f(),e=r(d,t);if(e===t)return console.error("QPage needs to be a deep child of QLayout"),t;if(r(y,t)===t)return console.error("QPage needs to be child of QPageContainer"),t;const c=s(()=>{const n=(e.header.space===!0?e.header.size:0)+(e.footer.space===!0?e.footer.size:0);if(typeof a.styleFn=="function"){const l=e.isContainer.value===!0?e.containerHeight.value:o.screen.height;return a.styleFn(n,l)}return{minHeight:e.isContainer.value===!0?e.containerHeight.value-n+"px":o.screen.height===0?n!==0?`calc(100vh - ${n}px)`:"100vh":o.screen.height-n+"px"}}),u=s(()=>`q-page${a.padding===!0?" q-layout-padding":""}`);return()=>h("main",{class:u.value,style:c.value},p(i.default))}});export{m as Q};
+import{k as g,U as r,V as t,h as s,i as h,D as p,X as d,a2 as y,C as f}from"./index.ae19b4cb.js";var m=g({name:"QPage",props:{padding:Boolean,styleFn:Function},setup(a,{slots:i}){const{proxy:{$q:o}}=f(),e=r(d,t);if(e===t)return console.error("QPage needs to be a deep child of QLayout"),t;if(r(y,t)===t)return console.error("QPage needs to be child of QPageContainer"),t;const c=s(()=>{const n=(e.header.space===!0?e.header.size:0)+(e.footer.space===!0?e.footer.size:0);if(typeof a.styleFn=="function"){const l=e.isContainer.value===!0?e.containerHeight.value:o.screen.height;return a.styleFn(n,l)}return{minHeight:e.isContainer.value===!0?e.containerHeight.value-n+"px":o.screen.height===0?n!==0?`calc(100vh - ${n}px)`:"100vh":o.screen.height-n+"px"}}),u=s(()=>`q-page${a.padding===!0?" q-layout-padding":""}`);return()=>h("main",{class:u.value,style:c.value},p(i.default))}});export{m as Q};
diff --git a/assets/QParallax.33781c83.js b/assets/QParallax.bd31f995.js
similarity index 96%
rename from assets/QParallax.33781c83.js
rename to assets/QParallax.bd31f995.js
index ba5e2706fbd..ed7bc1fd1fb 100644
--- a/assets/QParallax.33781c83.js
+++ b/assets/QParallax.bd31f995.js
@@ -1 +1 @@
-import{k as _,f as g,w as P,K as B,x as F,i as w,D as I,bz as q,B as O,L as Q,bA as A}from"./index.2b6e3ac7.js";function H(e){let a=!1,u,r;function l(){r=arguments,a!==!0&&(a=!0,u=requestAnimationFrame(()=>{e.apply(this,r),r=void 0,a=!1}))}return l.cancel=()=>{window.cancelAnimationFrame(u),a=!1},l}const{passive:b}=Q;var D=_({name:"QParallax",props:{src:String,height:{type:Number,default:500},speed:{type:Number,default:1,validator:e=>e>=0&&e<=1},scrollTarget:{default:void 0},onScroll:Function},setup(e,{slots:a,emit:u}){const r=g(0),l=g(null),T=g(null),z=g(null);let i,t,E,f,s,o;P(()=>e.height,()=>{i===!0&&c()}),P(()=>e.scrollTarget,()=>{i===!0&&(S(),x())});let v=n=>{r.value=n,e.onScroll!==void 0&&u("scroll",n)};function c(){let n,d,h;o===window?(n=0,h=d=window.innerHeight):(n=A(o).top,d=q(o),h=n+d);const y=A(l.value).top,R=y+e.height;if(s!==void 0||R>n&&y<h){const L=(h-y)/(e.height+d);m((E-e.height)*L*e.speed),v(L)}}let m=n=>{t.style.transform=`translate3d(-50%,${Math.round(n)}px,0)`};function p(){E=t.naturalHeight||t.videoHeight||q(t),i===!0&&c()}function x(){i=!0,o=O(l.value,e.scrollTarget),o.addEventListener("scroll",c,b),window.addEventListener("resize",f,b),c()}function S(){i===!0&&(i=!1,o.removeEventListener("scroll",c,b),window.removeEventListener("resize",f,b),o=void 0,m.cancel(),v.cancel(),f.cancel())}return B(()=>{m=H(m),v=H(v),f=H(p),t=a.media!==void 0?T.value.children[0]:z.value,t.onload=t.onloadstart=t.loadedmetadata=p,p(),t.style.display="initial",window.IntersectionObserver!==void 0?(s=new IntersectionObserver(n=>{(n[0].isIntersecting===!0?x:S)()}),s.observe(l.value)):x()}),F(()=>{S(),s!==void 0&&s.disconnect(),t.onload=t.onloadstart=t.loadedmetadata=null}),()=>w("div",{ref:l,class:"q-parallax",style:{height:`${e.height}px`}},[w("div",{ref:T,class:"q-parallax__media absolute-full"},a.media!==void 0?a.media():[w("img",{ref:z,src:e.src})]),w("div",{class:"q-parallax__content absolute-full column flex-center"},a.content!==void 0?a.content({percentScrolled:r.value}):I(a.default))])}});export{D as Q};
+import{k as _,f as g,w as P,K as B,x as F,i as w,D as I,bz as q,B as O,L as Q,bA as A}from"./index.ae19b4cb.js";function H(e){let a=!1,u,r;function l(){r=arguments,a!==!0&&(a=!0,u=requestAnimationFrame(()=>{e.apply(this,r),r=void 0,a=!1}))}return l.cancel=()=>{window.cancelAnimationFrame(u),a=!1},l}const{passive:b}=Q;var D=_({name:"QParallax",props:{src:String,height:{type:Number,default:500},speed:{type:Number,default:1,validator:e=>e>=0&&e<=1},scrollTarget:{default:void 0},onScroll:Function},setup(e,{slots:a,emit:u}){const r=g(0),l=g(null),T=g(null),z=g(null);let i,t,E,f,s,o;P(()=>e.height,()=>{i===!0&&c()}),P(()=>e.scrollTarget,()=>{i===!0&&(S(),x())});let v=n=>{r.value=n,e.onScroll!==void 0&&u("scroll",n)};function c(){let n,d,h;o===window?(n=0,h=d=window.innerHeight):(n=A(o).top,d=q(o),h=n+d);const y=A(l.value).top,R=y+e.height;if(s!==void 0||R>n&&y<h){const L=(h-y)/(e.height+d);m((E-e.height)*L*e.speed),v(L)}}let m=n=>{t.style.transform=`translate3d(-50%,${Math.round(n)}px,0)`};function p(){E=t.naturalHeight||t.videoHeight||q(t),i===!0&&c()}function x(){i=!0,o=O(l.value,e.scrollTarget),o.addEventListener("scroll",c,b),window.addEventListener("resize",f,b),c()}function S(){i===!0&&(i=!1,o.removeEventListener("scroll",c,b),window.removeEventListener("resize",f,b),o=void 0,m.cancel(),v.cancel(),f.cancel())}return B(()=>{m=H(m),v=H(v),f=H(p),t=a.media!==void 0?T.value.children[0]:z.value,t.onload=t.onloadstart=t.loadedmetadata=p,p(),t.style.display="initial",window.IntersectionObserver!==void 0?(s=new IntersectionObserver(n=>{(n[0].isIntersecting===!0?x:S)()}),s.observe(l.value)):x()}),F(()=>{S(),s!==void 0&&s.disconnect(),t.onload=t.onloadstart=t.loadedmetadata=null}),()=>w("div",{ref:l,class:"q-parallax",style:{height:`${e.height}px`}},[w("div",{ref:T,class:"q-parallax__media absolute-full"},a.media!==void 0?a.media():[w("img",{ref:z,src:e.src})]),w("div",{class:"q-parallax__content absolute-full column flex-center"},a.content!==void 0?a.content({percentScrolled:r.value}):I(a.default))])}});export{D as Q};
diff --git a/assets/QResizeObserver.131f6516.js b/assets/QResizeObserver.8b038ac4.js
similarity index 95%
rename from assets/QResizeObserver.131f6516.js
rename to assets/QResizeObserver.8b038ac4.js
index d979c0e5131..4561fa58659 100644
--- a/assets/QResizeObserver.131f6516.js
+++ b/assets/QResizeObserver.8b038ac4.js
@@ -1 +1 @@
-import{f as g,a3 as z,K as d,k as y,x as f,aH as w,J as v,i as R,C as x,L as b}from"./index.2b6e3ac7.js";function O(){const r=g(!z.value);return r.value===!1&&d(()=>{r.value=!0}),r}const m=typeof ResizeObserver!="undefined",h=m===!0?{}:{style:"display:block;position:absolute;top:0;left:0;right:0;bottom:0;height:100%;width:100%;overflow:hidden;pointer-events:none;z-index:-1;",url:"about:blank"};var E=y({name:"QResizeObserver",props:{debounce:{type:[String,Number],default:100}},emits:["resize"],setup(r,{emit:p}){let i=null,t,o={width:-1,height:-1};function s(e){e===!0||r.debounce===0||r.debounce==="0"?u():i===null&&(i=setTimeout(u,r.debounce))}function u(){if(i!==null&&(clearTimeout(i),i=null),t){const{offsetWidth:e,offsetHeight:n}=t;(e!==o.width||n!==o.height)&&(o={width:e,height:n},p("resize",o))}}const{proxy:l}=x();if(m===!0){let e;const n=a=>{t=l.$el.parentNode,t?(e=new ResizeObserver(s),e.observe(t),u()):a!==!0&&v(()=>{n(!0)})};return d(()=>{n()}),f(()=>{i!==null&&clearTimeout(i),e!==void 0&&(e.disconnect!==void 0?e.disconnect():t&&e.unobserve(t))}),w}else{let a=function(){i!==null&&(clearTimeout(i),i=null),n!==void 0&&(n.removeEventListener!==void 0&&n.removeEventListener("resize",s,b.passive),n=void 0)},c=function(){a(),t&&t.contentDocument&&(n=t.contentDocument.defaultView,n.addEventListener("resize",s,b.passive),u())};const e=O();let n;return d(()=>{v(()=>{t=l.$el,t&&c()})}),f(a),l.trigger=s,()=>{if(e.value===!0)return R("object",{style:h.style,tabindex:-1,type:"text/html",data:h.url,"aria-hidden":"true",onLoad:c})}}}});export{E as Q};
+import{f as g,a3 as z,K as d,k as y,x as f,aH as w,J as v,i as R,C as x,L as b}from"./index.ae19b4cb.js";function O(){const r=g(!z.value);return r.value===!1&&d(()=>{r.value=!0}),r}const m=typeof ResizeObserver!="undefined",h=m===!0?{}:{style:"display:block;position:absolute;top:0;left:0;right:0;bottom:0;height:100%;width:100%;overflow:hidden;pointer-events:none;z-index:-1;",url:"about:blank"};var E=y({name:"QResizeObserver",props:{debounce:{type:[String,Number],default:100}},emits:["resize"],setup(r,{emit:p}){let i=null,t,o={width:-1,height:-1};function s(e){e===!0||r.debounce===0||r.debounce==="0"?u():i===null&&(i=setTimeout(u,r.debounce))}function u(){if(i!==null&&(clearTimeout(i),i=null),t){const{offsetWidth:e,offsetHeight:n}=t;(e!==o.width||n!==o.height)&&(o={width:e,height:n},p("resize",o))}}const{proxy:l}=x();if(m===!0){let e;const n=a=>{t=l.$el.parentNode,t?(e=new ResizeObserver(s),e.observe(t),u()):a!==!0&&v(()=>{n(!0)})};return d(()=>{n()}),f(()=>{i!==null&&clearTimeout(i),e!==void 0&&(e.disconnect!==void 0?e.disconnect():t&&e.unobserve(t))}),w}else{let a=function(){i!==null&&(clearTimeout(i),i=null),n!==void 0&&(n.removeEventListener!==void 0&&n.removeEventListener("resize",s,b.passive),n=void 0)},c=function(){a(),t&&t.contentDocument&&(n=t.contentDocument.defaultView,n.addEventListener("resize",s,b.passive),u())};const e=O();let n;return d(()=>{v(()=>{t=l.$el,t&&c()})}),f(a),l.trigger=s,()=>{if(e.value===!0)return R("object",{style:h.style,tabindex:-1,type:"text/html",data:h.url,"aria-hidden":"true",onLoad:c})}}}});export{E as Q};
diff --git a/assets/QResponsive.15f7afc8.js b/assets/QResponsive.d028432b.js
similarity index 66%
rename from assets/QResponsive.15f7afc8.js
rename to assets/QResponsive.d028432b.js
index bda0178efe1..97b115f19c2 100644
--- a/assets/QResponsive.15f7afc8.js
+++ b/assets/QResponsive.d028432b.js
@@ -1 +1 @@
-import{u as t,a as i}from"./QImg.366b6afd.js";import{k as r,i as s,D as l}from"./index.2b6e3ac7.js";var v=r({name:"QResponsive",props:t,setup(e,{slots:o}){const a=i(e);return()=>s("div",{class:"q-responsive"},[s("div",{class:"q-responsive__filler overflow-hidden"},[s("div",{style:a.value})]),s("div",{class:"q-responsive__content absolute-full fit"},l(o.default))])}});export{v as Q};
+import{u as t,a as i}from"./QImg.27db20fc.js";import{k as r,i as s,D as l}from"./index.ae19b4cb.js";var v=r({name:"QResponsive",props:t,setup(e,{slots:o}){const a=i(e);return()=>s("div",{class:"q-responsive"},[s("div",{class:"q-responsive__filler overflow-hidden"},[s("div",{style:a.value})]),s("div",{class:"q-responsive__content absolute-full fit"},l(o.default))])}});export{v as Q};
diff --git a/assets/QScrollArea.e4f81404.js b/assets/QScrollArea.ce7c28a8.js
similarity index 98%
rename from assets/QScrollArea.e4f81404.js
rename to assets/QScrollArea.ce7c28a8.js
index 2318d3cb5cc..6fff87c2f3b 100644
--- a/assets/QScrollArea.e4f81404.js
+++ b/assets/QScrollArea.ce7c28a8.js
@@ -1 +1 @@
-import{k as N,w as O,K as re,x as I,aH as ie,B as ne,C as K,L as ue,b1 as ce,b2 as se,R as ve,f as v,S as he,h as i,aI as fe,aJ as de,aK as be,i as d,a4 as me,Z as Q,b3 as B,b4 as C}from"./index.2b6e3ac7.js";import{Q as R}from"./QResizeObserver.131f6516.js";import{T as k}from"./TouchPan.2038ddce.js";import{b as P}from"./format.988231da.js";const{passive:x}=ue,ze=["both","horizontal","vertical"];var Se=N({name:"QScrollObserver",props:{axis:{type:String,validator:a=>ze.includes(a),default:"vertical"},debounce:[String,Number],scrollTarget:{default:void 0}},emits:["scroll"],setup(a,{emit:M}){const n={position:{top:0,left:0},direction:"down",directionChanged:!1,delta:{top:0,left:0},inflectionPoint:{top:0,left:0}};let c=null,u,m;O(()=>a.scrollTarget,()=>{f(),e()});function o(){c!==null&&c();const z=Math.max(0,ce(u)),s=se(u),h={top:z-n.position.top,left:s-n.position.left};if(a.axis==="vertical"&&h.top===0||a.axis==="horizontal"&&h.left===0)return;const p=Math.abs(h.top)>=Math.abs(h.left)?h.top<0?"up":"down":h.left<0?"left":"right";n.position={top:z,left:s},n.directionChanged=n.direction!==p,n.delta=h,n.directionChanged===!0&&(n.direction=p,n.inflectionPoint=n.position),M("scroll",{...n})}function e(){u=ne(m,a.scrollTarget),u.addEventListener("scroll",y,x),y(!0)}function f(){u!==void 0&&(u.removeEventListener("scroll",y,x),u=void 0)}function y(z){if(z===!0||a.debounce===0||a.debounce==="0")o();else if(c===null){const[s,h]=a.debounce?[setTimeout(o,a.debounce),clearTimeout]:[requestAnimationFrame(o),cancelAnimationFrame];c=()=>{h(s),c=null}}}const{proxy:b}=K();return O(()=>b.$q.lang.rtl,o),re(()=>{m=b.$el.parentNode,e()}),I(()=>{c!==null&&c(),f()}),Object.assign(b,{trigger:y,getPosition:()=>n}),ie}});const F=["vertical","horizontal"],H={vertical:{offset:"offsetY",scroll:"scrollTop",dir:"down",dist:"y"},horizontal:{offset:"offsetX",scroll:"scrollLeft",dir:"right",dist:"x"}},L={prevent:!0,mouse:!0,mouseAllDir:!0},V=a=>a>=250?50:Math.ceil(a/5);var _e=N({name:"QScrollArea",props:{...ve,thumbStyle:Object,verticalThumbStyle:Object,horizontalThumbStyle:Object,barStyle:[Array,String,Object],verticalBarStyle:[Array,String,Object],horizontalBarStyle:[Array,String,Object],contentStyle:[Array,String,Object],contentActiveStyle:[Array,String,Object],delay:{type:[String,Number],default:1e3},visible:{type:Boolean,default:null},tabindex:[String,Number],onScroll:Function},setup(a,{slots:M,emit:n}){const c=v(!1),u=v(!1),m=v(!1),o={vertical:v(0),horizontal:v(0)},e={vertical:{ref:v(null),position:v(0),size:v(0)},horizontal:{ref:v(null),position:v(0),size:v(0)}},{proxy:f}=K(),y=he(a,f.$q);let b=null,z;const s=v(null),h=i(()=>"q-scrollarea"+(y.value===!0?" q-scrollarea--dark":""));e.vertical.percentage=i(()=>{const t=e.vertical.size.value-o.vertical.value;if(t<=0)return 0;const l=P(e.vertical.position.value/t,0,1);return Math.round(l*1e4)/1e4}),e.vertical.thumbHidden=i(()=>(a.visible===null?m.value:a.visible)!==!0&&c.value===!1&&u.value===!1||e.vertical.size.value<=o.vertical.value+1),e.vertical.thumbStart=i(()=>e.vertical.percentage.value*(o.vertical.value-e.vertical.thumbSize.value)),e.vertical.thumbSize=i(()=>Math.round(P(o.vertical.value*o.vertical.value/e.vertical.size.value,V(o.vertical.value),o.vertical.value))),e.vertical.style=i(()=>({...a.thumbStyle,...a.verticalThumbStyle,top:`${e.vertical.thumbStart.value}px`,height:`${e.vertical.thumbSize.value}px`})),e.vertical.thumbClass=i(()=>"q-scrollarea__thumb q-scrollarea__thumb--v absolute-right"+(e.vertical.thumbHidden.value===!0?" q-scrollarea__thumb--invisible":"")),e.vertical.barClass=i(()=>"q-scrollarea__bar q-scrollarea__bar--v absolute-right"+(e.vertical.thumbHidden.value===!0?" q-scrollarea__bar--invisible":"")),e.horizontal.percentage=i(()=>{const t=e.horizontal.size.value-o.horizontal.value;if(t<=0)return 0;const l=P(Math.abs(e.horizontal.position.value)/t,0,1);return Math.round(l*1e4)/1e4}),e.horizontal.thumbHidden=i(()=>(a.visible===null?m.value:a.visible)!==!0&&c.value===!1&&u.value===!1||e.horizontal.size.value<=o.horizontal.value+1),e.horizontal.thumbStart=i(()=>e.horizontal.percentage.value*(o.horizontal.value-e.horizontal.thumbSize.value)),e.horizontal.thumbSize=i(()=>Math.round(P(o.horizontal.value*o.horizontal.value/e.horizontal.size.value,V(o.horizontal.value),o.horizontal.value))),e.horizontal.style=i(()=>({...a.thumbStyle,...a.horizontalThumbStyle,[f.$q.lang.rtl===!0?"right":"left"]:`${e.horizontal.thumbStart.value}px`,width:`${e.horizontal.thumbSize.value}px`})),e.horizontal.thumbClass=i(()=>"q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom"+(e.horizontal.thumbHidden.value===!0?" q-scrollarea__thumb--invisible":"")),e.horizontal.barClass=i(()=>"q-scrollarea__bar q-scrollarea__bar--h absolute-bottom"+(e.horizontal.thumbHidden.value===!0?" q-scrollarea__bar--invisible":""));const p=i(()=>e.vertical.thumbHidden.value===!0&&e.horizontal.thumbHidden.value===!0?a.contentStyle:a.contentActiveStyle),J=[[k,t=>{j(t,"vertical")},void 0,{vertical:!0,...L}]],U=[[k,t=>{j(t,"horizontal")},void 0,{horizontal:!0,...L}]];function w(){const t={};return F.forEach(l=>{const r=e[l];t[l+"Position"]=r.position.value,t[l+"Percentage"]=r.percentage.value,t[l+"Size"]=r.size.value,t[l+"ContainerSize"]=o[l].value}),t}const A=fe(()=>{const t=w();t.ref=f,n("scroll",t)},0);function $(t,l,r){if(F.includes(t)===!1){console.error("[QScrollArea]: wrong first param of setScrollPosition (vertical/horizontal)");return}(t==="vertical"?B:C)(s.value,l,r)}function X({height:t,width:l}){let r=!1;o.vertical.value!==t&&(o.vertical.value=t,r=!0),o.horizontal.value!==l&&(o.horizontal.value=l,r=!0),r===!0&&T()}function Y({position:t}){let l=!1;e.vertical.position.value!==t.top&&(e.vertical.position.value=t.top,l=!0),e.horizontal.position.value!==t.left&&(e.horizontal.position.value=t.left,l=!0),l===!0&&T()}function Z({height:t,width:l}){e.horizontal.size.value!==l&&(e.horizontal.size.value=l,T()),e.vertical.size.value!==t&&(e.vertical.size.value=t,T())}function j(t,l){const r=e[l];if(t.isFirst===!0){if(r.thumbHidden.value===!0)return;z=r.position.value,u.value=!0}else if(u.value!==!0)return;t.isFinal===!0&&(u.value=!1);const g=H[l],q=o[l].value,le=(r.size.value-q)/(q-r.thumbSize.value),ae=t.distance[g.dist],oe=z+(t.direction===g.dir?1:-1)*ae*le;E(oe,l)}function D(t,l){const r=e[l];if(r.thumbHidden.value!==!0){const g=t[H[l].offset];if(g<r.thumbStart.value||g>r.thumbStart.value+r.thumbSize.value){const q=g-r.thumbSize.value/2;E(q/o[l].value*r.size.value,l)}r.ref.value!==null&&r.ref.value.dispatchEvent(new MouseEvent(t.type,t))}}function G(t){D(t,"vertical")}function W(t){D(t,"horizontal")}function T(){c.value=!0,b!==null&&clearTimeout(b),b=setTimeout(()=>{b=null,c.value=!1},a.delay),a.onScroll!==void 0&&A()}function E(t,l){s.value[H[l].scroll]=t}let S=null;function ee(){S!==null&&clearTimeout(S),S=setTimeout(()=>{S=null,m.value=!0},f.$q.platform.is.ios?50:0)}function te(){S!==null&&(clearTimeout(S),S=null),m.value=!1}let _=null;return O(()=>f.$q.lang.rtl,t=>{s.value!==null&&C(s.value,Math.abs(e.horizontal.position.value)*(t===!0?-1:1))}),de(()=>{_={top:e.vertical.position.value,left:e.horizontal.position.value}}),be(()=>{if(_===null)return;const t=s.value;t!==null&&(C(t,_.left),B(t,_.top))}),I(A.cancel),Object.assign(f,{getScrollTarget:()=>s.value,getScroll:w,getScrollPosition:()=>({top:e.vertical.position.value,left:e.horizontal.position.value}),getScrollPercentage:()=>({top:e.vertical.percentage.value,left:e.horizontal.percentage.value}),setScrollPosition:$,setScrollPercentage(t,l,r){$(t,l*(e[t].size.value-o[t].value)*(t==="horizontal"&&f.$q.lang.rtl===!0?-1:1),r)}}),()=>d("div",{class:h.value,onMouseenter:ee,onMouseleave:te},[d("div",{ref:s,class:"q-scrollarea__container scroll relative-position fit hide-scrollbar",tabindex:a.tabindex!==void 0?a.tabindex:void 0},[d("div",{class:"q-scrollarea__content absolute",style:p.value},me(M.default,[d(R,{debounce:0,onResize:Z})])),d(Se,{axis:"both",onScroll:Y})]),d(R,{debounce:0,onResize:X}),d("div",{class:e.vertical.barClass.value,style:[a.barStyle,a.verticalBarStyle],"aria-hidden":"true",onMousedown:G}),d("div",{class:e.horizontal.barClass.value,style:[a.barStyle,a.horizontalBarStyle],"aria-hidden":"true",onMousedown:W}),Q(d("div",{ref:e.vertical.ref,class:e.vertical.thumbClass.value,style:e.vertical.style.value,"aria-hidden":"true"}),J),Q(d("div",{ref:e.horizontal.ref,class:e.horizontal.thumbClass.value,style:e.horizontal.style.value,"aria-hidden":"true"}),U)])}});export{Se as Q,_e as a};
+import{k as N,w as O,K as re,x as I,aH as ie,B as ne,C as K,L as ue,b1 as ce,b2 as se,R as ve,f as v,S as he,h as i,aI as fe,aJ as de,aK as be,i as d,a4 as me,Z as Q,b3 as B,b4 as C}from"./index.ae19b4cb.js";import{Q as R}from"./QResizeObserver.8b038ac4.js";import{T as k}from"./TouchPan.a03d231e.js";import{b as P}from"./format.988231da.js";const{passive:x}=ue,ze=["both","horizontal","vertical"];var Se=N({name:"QScrollObserver",props:{axis:{type:String,validator:a=>ze.includes(a),default:"vertical"},debounce:[String,Number],scrollTarget:{default:void 0}},emits:["scroll"],setup(a,{emit:M}){const n={position:{top:0,left:0},direction:"down",directionChanged:!1,delta:{top:0,left:0},inflectionPoint:{top:0,left:0}};let c=null,u,m;O(()=>a.scrollTarget,()=>{f(),e()});function o(){c!==null&&c();const z=Math.max(0,ce(u)),s=se(u),h={top:z-n.position.top,left:s-n.position.left};if(a.axis==="vertical"&&h.top===0||a.axis==="horizontal"&&h.left===0)return;const p=Math.abs(h.top)>=Math.abs(h.left)?h.top<0?"up":"down":h.left<0?"left":"right";n.position={top:z,left:s},n.directionChanged=n.direction!==p,n.delta=h,n.directionChanged===!0&&(n.direction=p,n.inflectionPoint=n.position),M("scroll",{...n})}function e(){u=ne(m,a.scrollTarget),u.addEventListener("scroll",y,x),y(!0)}function f(){u!==void 0&&(u.removeEventListener("scroll",y,x),u=void 0)}function y(z){if(z===!0||a.debounce===0||a.debounce==="0")o();else if(c===null){const[s,h]=a.debounce?[setTimeout(o,a.debounce),clearTimeout]:[requestAnimationFrame(o),cancelAnimationFrame];c=()=>{h(s),c=null}}}const{proxy:b}=K();return O(()=>b.$q.lang.rtl,o),re(()=>{m=b.$el.parentNode,e()}),I(()=>{c!==null&&c(),f()}),Object.assign(b,{trigger:y,getPosition:()=>n}),ie}});const F=["vertical","horizontal"],H={vertical:{offset:"offsetY",scroll:"scrollTop",dir:"down",dist:"y"},horizontal:{offset:"offsetX",scroll:"scrollLeft",dir:"right",dist:"x"}},L={prevent:!0,mouse:!0,mouseAllDir:!0},V=a=>a>=250?50:Math.ceil(a/5);var _e=N({name:"QScrollArea",props:{...ve,thumbStyle:Object,verticalThumbStyle:Object,horizontalThumbStyle:Object,barStyle:[Array,String,Object],verticalBarStyle:[Array,String,Object],horizontalBarStyle:[Array,String,Object],contentStyle:[Array,String,Object],contentActiveStyle:[Array,String,Object],delay:{type:[String,Number],default:1e3},visible:{type:Boolean,default:null},tabindex:[String,Number],onScroll:Function},setup(a,{slots:M,emit:n}){const c=v(!1),u=v(!1),m=v(!1),o={vertical:v(0),horizontal:v(0)},e={vertical:{ref:v(null),position:v(0),size:v(0)},horizontal:{ref:v(null),position:v(0),size:v(0)}},{proxy:f}=K(),y=he(a,f.$q);let b=null,z;const s=v(null),h=i(()=>"q-scrollarea"+(y.value===!0?" q-scrollarea--dark":""));e.vertical.percentage=i(()=>{const t=e.vertical.size.value-o.vertical.value;if(t<=0)return 0;const l=P(e.vertical.position.value/t,0,1);return Math.round(l*1e4)/1e4}),e.vertical.thumbHidden=i(()=>(a.visible===null?m.value:a.visible)!==!0&&c.value===!1&&u.value===!1||e.vertical.size.value<=o.vertical.value+1),e.vertical.thumbStart=i(()=>e.vertical.percentage.value*(o.vertical.value-e.vertical.thumbSize.value)),e.vertical.thumbSize=i(()=>Math.round(P(o.vertical.value*o.vertical.value/e.vertical.size.value,V(o.vertical.value),o.vertical.value))),e.vertical.style=i(()=>({...a.thumbStyle,...a.verticalThumbStyle,top:`${e.vertical.thumbStart.value}px`,height:`${e.vertical.thumbSize.value}px`})),e.vertical.thumbClass=i(()=>"q-scrollarea__thumb q-scrollarea__thumb--v absolute-right"+(e.vertical.thumbHidden.value===!0?" q-scrollarea__thumb--invisible":"")),e.vertical.barClass=i(()=>"q-scrollarea__bar q-scrollarea__bar--v absolute-right"+(e.vertical.thumbHidden.value===!0?" q-scrollarea__bar--invisible":"")),e.horizontal.percentage=i(()=>{const t=e.horizontal.size.value-o.horizontal.value;if(t<=0)return 0;const l=P(Math.abs(e.horizontal.position.value)/t,0,1);return Math.round(l*1e4)/1e4}),e.horizontal.thumbHidden=i(()=>(a.visible===null?m.value:a.visible)!==!0&&c.value===!1&&u.value===!1||e.horizontal.size.value<=o.horizontal.value+1),e.horizontal.thumbStart=i(()=>e.horizontal.percentage.value*(o.horizontal.value-e.horizontal.thumbSize.value)),e.horizontal.thumbSize=i(()=>Math.round(P(o.horizontal.value*o.horizontal.value/e.horizontal.size.value,V(o.horizontal.value),o.horizontal.value))),e.horizontal.style=i(()=>({...a.thumbStyle,...a.horizontalThumbStyle,[f.$q.lang.rtl===!0?"right":"left"]:`${e.horizontal.thumbStart.value}px`,width:`${e.horizontal.thumbSize.value}px`})),e.horizontal.thumbClass=i(()=>"q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom"+(e.horizontal.thumbHidden.value===!0?" q-scrollarea__thumb--invisible":"")),e.horizontal.barClass=i(()=>"q-scrollarea__bar q-scrollarea__bar--h absolute-bottom"+(e.horizontal.thumbHidden.value===!0?" q-scrollarea__bar--invisible":""));const p=i(()=>e.vertical.thumbHidden.value===!0&&e.horizontal.thumbHidden.value===!0?a.contentStyle:a.contentActiveStyle),J=[[k,t=>{j(t,"vertical")},void 0,{vertical:!0,...L}]],U=[[k,t=>{j(t,"horizontal")},void 0,{horizontal:!0,...L}]];function w(){const t={};return F.forEach(l=>{const r=e[l];t[l+"Position"]=r.position.value,t[l+"Percentage"]=r.percentage.value,t[l+"Size"]=r.size.value,t[l+"ContainerSize"]=o[l].value}),t}const A=fe(()=>{const t=w();t.ref=f,n("scroll",t)},0);function $(t,l,r){if(F.includes(t)===!1){console.error("[QScrollArea]: wrong first param of setScrollPosition (vertical/horizontal)");return}(t==="vertical"?B:C)(s.value,l,r)}function X({height:t,width:l}){let r=!1;o.vertical.value!==t&&(o.vertical.value=t,r=!0),o.horizontal.value!==l&&(o.horizontal.value=l,r=!0),r===!0&&T()}function Y({position:t}){let l=!1;e.vertical.position.value!==t.top&&(e.vertical.position.value=t.top,l=!0),e.horizontal.position.value!==t.left&&(e.horizontal.position.value=t.left,l=!0),l===!0&&T()}function Z({height:t,width:l}){e.horizontal.size.value!==l&&(e.horizontal.size.value=l,T()),e.vertical.size.value!==t&&(e.vertical.size.value=t,T())}function j(t,l){const r=e[l];if(t.isFirst===!0){if(r.thumbHidden.value===!0)return;z=r.position.value,u.value=!0}else if(u.value!==!0)return;t.isFinal===!0&&(u.value=!1);const g=H[l],q=o[l].value,le=(r.size.value-q)/(q-r.thumbSize.value),ae=t.distance[g.dist],oe=z+(t.direction===g.dir?1:-1)*ae*le;E(oe,l)}function D(t,l){const r=e[l];if(r.thumbHidden.value!==!0){const g=t[H[l].offset];if(g<r.thumbStart.value||g>r.thumbStart.value+r.thumbSize.value){const q=g-r.thumbSize.value/2;E(q/o[l].value*r.size.value,l)}r.ref.value!==null&&r.ref.value.dispatchEvent(new MouseEvent(t.type,t))}}function G(t){D(t,"vertical")}function W(t){D(t,"horizontal")}function T(){c.value=!0,b!==null&&clearTimeout(b),b=setTimeout(()=>{b=null,c.value=!1},a.delay),a.onScroll!==void 0&&A()}function E(t,l){s.value[H[l].scroll]=t}let S=null;function ee(){S!==null&&clearTimeout(S),S=setTimeout(()=>{S=null,m.value=!0},f.$q.platform.is.ios?50:0)}function te(){S!==null&&(clearTimeout(S),S=null),m.value=!1}let _=null;return O(()=>f.$q.lang.rtl,t=>{s.value!==null&&C(s.value,Math.abs(e.horizontal.position.value)*(t===!0?-1:1))}),de(()=>{_={top:e.vertical.position.value,left:e.horizontal.position.value}}),be(()=>{if(_===null)return;const t=s.value;t!==null&&(C(t,_.left),B(t,_.top))}),I(A.cancel),Object.assign(f,{getScrollTarget:()=>s.value,getScroll:w,getScrollPosition:()=>({top:e.vertical.position.value,left:e.horizontal.position.value}),getScrollPercentage:()=>({top:e.vertical.percentage.value,left:e.horizontal.percentage.value}),setScrollPosition:$,setScrollPercentage(t,l,r){$(t,l*(e[t].size.value-o[t].value)*(t==="horizontal"&&f.$q.lang.rtl===!0?-1:1),r)}}),()=>d("div",{class:h.value,onMouseenter:ee,onMouseleave:te},[d("div",{ref:s,class:"q-scrollarea__container scroll relative-position fit hide-scrollbar",tabindex:a.tabindex!==void 0?a.tabindex:void 0},[d("div",{class:"q-scrollarea__content absolute",style:p.value},me(M.default,[d(R,{debounce:0,onResize:Z})])),d(Se,{axis:"both",onScroll:Y})]),d(R,{debounce:0,onResize:X}),d("div",{class:e.vertical.barClass.value,style:[a.barStyle,a.verticalBarStyle],"aria-hidden":"true",onMousedown:G}),d("div",{class:e.horizontal.barClass.value,style:[a.barStyle,a.horizontalBarStyle],"aria-hidden":"true",onMousedown:W}),Q(d("div",{ref:e.vertical.ref,class:e.vertical.thumbClass.value,style:e.vertical.style.value,"aria-hidden":"true"}),J),Q(d("div",{ref:e.horizontal.ref,class:e.horizontal.thumbClass.value,style:e.horizontal.style.value,"aria-hidden":"true"}),U)])}});export{Se as Q,_e as a};
diff --git a/assets/QSelect.ada2cea3.js b/assets/QSelect.ec7f4034.js
similarity index 99%
rename from assets/QSelect.ada2cea3.js
rename to assets/QSelect.ec7f4034.js
index c7814d26676..edca5772358 100644
--- a/assets/QSelect.ada2cea3.js
+++ b/assets/QSelect.ec7f4034.js
@@ -1 +1 @@
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diff --git a/assets/QSpace.1a54f452.js b/assets/QSpace.e72a2bc7.js
similarity index 55%
rename from assets/QSpace.1a54f452.js
rename to assets/QSpace.e72a2bc7.js
index 03d9243a2b1..ab5a7f0bdef 100644
--- a/assets/QSpace.1a54f452.js
+++ b/assets/QSpace.e72a2bc7.js
@@ -1 +1 @@
-import{i as a,k as e}from"./index.2b6e3ac7.js";const s=a("div",{class:"q-space"});var c=e({name:"QSpace",setup(){return()=>s}});export{c as Q};
+import{i as a,k as e}from"./index.ae19b4cb.js";const s=a("div",{class:"q-space"});var c=e({name:"QSpace",setup(){return()=>s}});export{c as Q};
diff --git a/assets/QTable.c2f82dde.js b/assets/QTable.ea86ce71.js
similarity index 99%
rename from assets/QTable.c2f82dde.js
rename to assets/QTable.ea86ce71.js
index 4197aaa48f5..61001f03803 100644
--- a/assets/QTable.c2f82dde.js
+++ b/assets/QTable.ea86ce71.js
@@ -1 +1 @@
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Ft=Q({name:"QMarkupTable",props:{...be,dense:Boolean,flat:Boolean,bordered:Boolean,square:Boolean,wrapCells:Boolean,separator:{type:String,default:"horizontal",validator:e=>Ot.includes(e)}},setup(e,{slots:l}){const r=H(),g=me(e,r.proxy.$q),i=u(()=>`q-markup-table q-table__container q-table__card q-table--${e.separator}-separator`+(g.value===!0?" q-table--dark q-table__card--dark q-dark":"")+(e.dense===!0?" q-table--dense":"")+(e.flat===!0?" q-table--flat":"")+(e.bordered===!0?" q-table--bordered":"")+(e.square===!0?" q-table--square":"")+(e.wrapCells===!1?" q-table--no-wrap":""));return()=>n("div",{class:i.value},[n("table",{class:"q-table"},N(l.default))])}});function je(e,l){return n("div",e,[n("table",{class:"q-table"},l)])}const Dt={list:qt,table:Ft},Lt=["list","table","__qtable"];var Mt=Q({name:"QVirtualScroll",props:{...Pt,type:{type:String,default:"list",validator:e=>Lt.includes(e)},items:{type:Array,default:()=>[]},itemsFn:Function,itemsSize:Number,scrollTarget:{default:void 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$t=Q({name:"QLinearProgress",props:{...be,...St,value:{type:Number,default:0},buffer:Number,color:String,trackColor:String,reverse:Boolean,stripe:Boolean,indeterminate:Boolean,query:Boolean,rounded:Boolean,animationSpeed:{type:[String,Number],default:2100},instantFeedback:Boolean},setup(e,{slots:l}){const{proxy:r}=H(),g=me(e,r.$q),i=yt(e,Vt),f=u(()=>e.indeterminate===!0||e.query===!0),s=u(()=>e.reverse!==e.query),d=u(()=>({...i.value!==null?i.value:{},"--q-linear-progress-speed":`${e.animationSpeed}ms`})),c=u(()=>"q-linear-progress"+(e.color!==void 0?` text-${e.color}`:"")+(e.reverse===!0||e.query===!0?" q-linear-progress--reverse":"")+(e.rounded===!0?" rounded-borders":"")),h=u(()=>Oe(e.buffer!==void 0?e.buffer:1,s.value,r.$q)),a=u(()=>`with${e.instantFeedback===!0?"out":""}-transition`),m=u(()=>`q-linear-progress__track absolute-full q-linear-progress__track--${a.value} q-linear-progress__track--${g.value===!0?"dark":"light"}`+(e.trackColor!==void 0?` 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diff --git a/assets/QTabs.41a4e3c1.js b/assets/QTabs.f5653f56.js
similarity index 98%
rename from assets/QTabs.41a4e3c1.js
rename to assets/QTabs.f5653f56.js
index 329801005b1..7765532d05f 100644
--- a/assets/QTabs.41a4e3c1.js
+++ b/assets/QTabs.f5653f56.js
@@ -1 +1 @@
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diff --git a/assets/QTooltip.334e385b.js b/assets/QTooltip.5338ff56.js
similarity index 94%
rename from assets/QTooltip.334e385b.js
rename to assets/QTooltip.5338ff56.js
index 0dde8890c3b..71d2f4b74d8 100644
--- a/assets/QTooltip.334e385b.js
+++ b/assets/QTooltip.5338ff56.js
@@ -1 +1 @@
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+import{k as ee,l as te,m as oe,n as ae,f as O,h as f,p as ne,q as ie,s as le,t as se,v as re,w as C,x as E,y as k,z as x,B as ue,i as H,T as ce,C as de,D as fe,E as ve}from"./index.ae19b4cb.js";import{u as he,v as q,a as me,b as ge,c as ye,r as A,s as Te,p as D,d as pe}from"./position-engine.2f7193db.js";import{c as M}from"./selection.10af5b4d.js";var we=ee({name:"QTooltip",inheritAttrs:!1,props:{...he,...te,...oe,maxHeight:{type:String,default:null},maxWidth:{type:String,default:null},transitionShow:{default:"jump-down"},transitionHide:{default:"jump-up"},anchor:{type:String,default:"bottom middle",validator:q},self:{type:String,default:"top middle",validator:q},offset:{type:Array,default:()=>[14,14],validator:me},scrollTarget:{default:void 0},delay:{type:Number,default:0},hideDelay:{type:Number,default:0}},emits:[...ae],setup(e,{slots:j,emit:y,attrs:v}){let i,l;const h=de(),{proxy:{$q:o}}=h,s=O(null),c=O(!1),L=f(()=>D(e.anchor,o.lang.rtl)),Q=f(()=>D(e.self,o.lang.rtl)),W=f(()=>e.persistent!==!0),{registerTick:B,removeTick:N}=ne(),{registerTimeout:d}=ie(),{transitionProps:R,transitionStyle:_}=le(e),{localScrollTarget:T,changeScrollEvent:z,unconfigureScrollTarget:I}=ge(e,P),{anchorEl:a,canShow:U,anchorEvents:r}=ye({showing:c,configureAnchorEl:X}),{show:V,hide:m}=se({showing:c,canShow:U,handleShow:F,handleHide:G,hideOnRouteChange:W,processOnMount:!0});Object.assign(r,{delayShow:J,delayHide:K});const{showPortal:p,hidePortal:b,renderPortal:$}=re(h,s,Z,"tooltip");if(o.platform.is.mobile===!0){const t={anchorEl:a,innerRef:s,onClickOutside(n){return m(n),n.target.classList.contains("q-dialog__backdrop")&&ve(n),!0}},g=f(()=>e.modelValue===null&&e.persistent!==!0&&c.value===!0);C(g,n=>{(n===!0?pe:A)(t)}),E(()=>{A(t)})}function F(t){p(),B(()=>{l=new MutationObserver(()=>u()),l.observe(s.value,{attributes:!1,childList:!0,characterData:!0,subtree:!0}),u(),P()}),i===void 0&&(i=C(()=>o.screen.width+"|"+o.screen.height+"|"+e.self+"|"+e.anchor+"|"+o.lang.rtl,u)),d(()=>{p(!0),y("show",t)},e.transitionDuration)}function G(t){N(),b(),S(),d(()=>{b(!0),y("hide",t)},e.transitionDuration)}function S(){l!==void 0&&(l.disconnect(),l=void 0),i!==void 0&&(i(),i=void 0),I(),k(r,"tooltipTemp")}function u(){Te({targetEl:s.value,offset:e.offset,anchorEl:a.value,anchorOrigin:L.value,selfOrigin:Q.value,maxHeight:e.maxHeight,maxWidth:e.maxWidth})}function J(t){if(o.platform.is.mobile===!0){M(),document.body.classList.add("non-selectable");const g=a.value,n=["touchmove","touchcancel","touchend","click"].map(w=>[g,w,"delayHide","passiveCapture"]);x(r,"tooltipTemp",n)}d(()=>{V(t)},e.delay)}function K(t){o.platform.is.mobile===!0&&(k(r,"tooltipTemp"),M(),setTimeout(()=>{document.body.classList.remove("non-selectable")},10)),d(()=>{m(t)},e.hideDelay)}function X(){if(e.noParentEvent===!0||a.value===null)return;const t=o.platform.is.mobile===!0?[[a.value,"touchstart","delayShow","passive"]]:[[a.value,"mouseenter","delayShow","passive"],[a.value,"mouseleave","delayHide","passive"]];x(r,"anchor",t)}function P(){if(a.value!==null||e.scrollTarget!==void 0){T.value=ue(a.value,e.scrollTarget);const t=e.noParentEvent===!0?u:m;z(T.value,t)}}function Y(){return c.value===!0?H("div",{...v,ref:s,class:["q-tooltip q-tooltip--style q-position-engine no-pointer-events",v.class],style:[v.style,_.value],role:"tooltip"},fe(j.default)):null}function Z(){return H(ce,R.value,Y)}return E(S),Object.assign(h.proxy,{updatePosition:u}),$}});export{we as Q};
diff --git a/assets/TouchPan.2038ddce.js b/assets/TouchPan.a03d231e.js
similarity index 97%
rename from assets/TouchPan.2038ddce.js
rename to assets/TouchPan.a03d231e.js
index 7ea6fb144bd..9e350d03565 100644
--- a/assets/TouchPan.2038ddce.js
+++ b/assets/TouchPan.a03d231e.js
@@ -1 +1 @@
-import{b5 as D,N as m,aH as X,bi as Y,z as h,bj as y,I as w,aR as C,bc as g,y as b,E as F}from"./index.2b6e3ac7.js";import{g as _,s as M}from"./touch.3df10340.js";import{c as P}from"./selection.e82f8124.js";function E(a,r,n){const l=g(a);let e,t=l.left-r.event.x,i=l.top-r.event.y,u=Math.abs(t),s=Math.abs(i);const o=r.direction;o.horizontal===!0&&o.vertical!==!0?e=t<0?"left":"right":o.horizontal!==!0&&o.vertical===!0?e=i<0?"up":"down":o.up===!0&&i<0?(e="up",u>s&&(o.left===!0&&t<0?e="left":o.right===!0&&t>0&&(e="right"))):o.down===!0&&i>0?(e="down",u>s&&(o.left===!0&&t<0?e="left":o.right===!0&&t>0&&(e="right"))):o.left===!0&&t<0?(e="left",u<s&&(o.up===!0&&i<0?e="up":o.down===!0&&i>0&&(e="down"))):o.right===!0&&t>0&&(e="right",u<s&&(o.up===!0&&i<0?e="up":o.down===!0&&i>0&&(e="down")));let v=!1;if(e===void 0&&n===!1){if(r.event.isFirst===!0||r.event.lastDir===void 0)return{};e=r.event.lastDir,v=!0,e==="left"||e==="right"?(l.left-=t,u=0,t=0):(l.top-=i,s=0,i=0)}return{synthetic:v,payload:{evt:a,touch:r.event.mouse!==!0,mouse:r.event.mouse===!0,position:l,direction:e,isFirst:r.event.isFirst,isFinal:n===!0,duration:Date.now()-r.event.time,distance:{x:u,y:s},offset:{x:t,y:i},delta:{x:l.left-r.event.lastX,y:l.top-r.event.lastY}}}}let S=0;var L=D({name:"touch-pan",beforeMount(a,{value:r,modifiers:n}){if(n.mouse!==!0&&m.has.touch!==!0)return;function l(t,i){n.mouse===!0&&i===!0?F(t):(n.stop===!0&&C(t),n.prevent===!0&&w(t))}const e={uid:"qvtp_"+S++,handler:r,modifiers:n,direction:_(n),noop:X,mouseStart(t){M(t,e)&&Y(t)&&(h(e,"temp",[[document,"mousemove","move","notPassiveCapture"],[document,"mouseup","end","passiveCapture"]]),e.start(t,!0))},touchStart(t){if(M(t,e)){const i=t.target;h(e,"temp",[[i,"touchmove","move","notPassiveCapture"],[i,"touchcancel","end","passiveCapture"],[i,"touchend","end","passiveCapture"]]),e.start(t)}},start(t,i){if(m.is.firefox===!0&&y(a,!0),e.lastEvt=t,i===!0||n.stop===!0){if(e.direction.all!==!0&&(i!==!0||e.modifiers.mouseAllDir!==!0&&e.modifiers.mousealldir!==!0)){const o=t.type.indexOf("mouse")>-1?new MouseEvent(t.type,t):new TouchEvent(t.type,t);t.defaultPrevented===!0&&w(o),t.cancelBubble===!0&&C(o),Object.assign(o,{qKeyEvent:t.qKeyEvent,qClickOutside:t.qClickOutside,qAnchorHandled:t.qAnchorHandled,qClonedBy:t.qClonedBy===void 0?[e.uid]:t.qClonedBy.concat(e.uid)}),e.initialEvent={target:t.target,event:o}}C(t)}const{left:u,top:s}=g(t);e.event={x:u,y:s,time:Date.now(),mouse:i===!0,detected:!1,isFirst:!0,isFinal:!1,lastX:u,lastY:s}},move(t){if(e.event===void 0)return;const i=g(t),u=i.left-e.event.x,s=i.top-e.event.y;if(u===0&&s===0)return;e.lastEvt=t;const o=e.event.mouse===!0,v=()=>{l(t,o);let d;n.preserveCursor!==!0&&n.preservecursor!==!0&&(d=document.documentElement.style.cursor||"",document.documentElement.style.cursor="grabbing"),o===!0&&document.body.classList.add("no-pointer-events--children"),document.body.classList.add("non-selectable"),P(),e.styleCleanup=p=>{if(e.styleCleanup=void 0,d!==void 0&&(document.documentElement.style.cursor=d),document.body.classList.remove("non-selectable"),o===!0){const q=()=>{document.body.classList.remove("no-pointer-events--children")};p!==void 0?setTimeout(()=>{q(),p()},50):q()}else p!==void 0&&p()}};if(e.event.detected===!0){e.event.isFirst!==!0&&l(t,e.event.mouse);const{payload:d,synthetic:p}=E(t,e,!1);d!==void 0&&(e.handler(d)===!1?e.end(t):(e.styleCleanup===void 0&&e.event.isFirst===!0&&v(),e.event.lastX=d.position.left,e.event.lastY=d.position.top,e.event.lastDir=p===!0?void 0:d.direction,e.event.isFirst=!1));return}if(e.direction.all===!0||o===!0&&(e.modifiers.mouseAllDir===!0||e.modifiers.mousealldir===!0)){v(),e.event.detected=!0,e.move(t);return}const c=Math.abs(u),f=Math.abs(s);c!==f&&(e.direction.horizontal===!0&&c>f||e.direction.vertical===!0&&c<f||e.direction.up===!0&&c<f&&s<0||e.direction.down===!0&&c<f&&s>0||e.direction.left===!0&&c>f&&u<0||e.direction.right===!0&&c>f&&u>0?(e.event.detected=!0,e.move(t)):e.end(t,!0))},end(t,i){if(e.event!==void 0){if(b(e,"temp"),m.is.firefox===!0&&y(a,!1),i===!0)e.styleCleanup!==void 0&&e.styleCleanup(),e.event.detected!==!0&&e.initialEvent!==void 0&&e.initialEvent.target.dispatchEvent(e.initialEvent.event);else if(e.event.detected===!0){e.event.isFirst===!0&&e.handler(E(t===void 0?e.lastEvt:t,e).payload);const{payload:u}=E(t===void 0?e.lastEvt:t,e,!0),s=()=>{e.handler(u)};e.styleCleanup!==void 0?e.styleCleanup(s):s()}e.event=void 0,e.initialEvent=void 0,e.lastEvt=void 0}}};if(a.__qtouchpan=e,n.mouse===!0){const t=n.mouseCapture===!0||n.mousecapture===!0?"Capture":"";h(e,"main",[[a,"mousedown","mouseStart",`passive${t}`]])}m.has.touch===!0&&h(e,"main",[[a,"touchstart","touchStart",`passive${n.capture===!0?"Capture":""}`],[a,"touchmove","noop","notPassiveCapture"]])},updated(a,r){const n=a.__qtouchpan;n!==void 0&&(r.oldValue!==r.value&&(typeof value!="function"&&n.end(),n.handler=r.value),n.direction=_(r.modifiers))},beforeUnmount(a){const r=a.__qtouchpan;r!==void 0&&(r.event!==void 0&&r.end(),b(r,"main"),b(r,"temp"),m.is.firefox===!0&&y(a,!1),r.styleCleanup!==void 0&&r.styleCleanup(),delete a.__qtouchpan)}});export{L as T};
+import{b5 as D,N as m,aH as X,bi as Y,z as h,bj as y,I as w,aR as C,bc as g,y as b,E as F}from"./index.ae19b4cb.js";import{g as _,s as M}from"./touch.3df10340.js";import{c as P}from"./selection.10af5b4d.js";function E(a,r,n){const l=g(a);let e,t=l.left-r.event.x,i=l.top-r.event.y,u=Math.abs(t),s=Math.abs(i);const o=r.direction;o.horizontal===!0&&o.vertical!==!0?e=t<0?"left":"right":o.horizontal!==!0&&o.vertical===!0?e=i<0?"up":"down":o.up===!0&&i<0?(e="up",u>s&&(o.left===!0&&t<0?e="left":o.right===!0&&t>0&&(e="right"))):o.down===!0&&i>0?(e="down",u>s&&(o.left===!0&&t<0?e="left":o.right===!0&&t>0&&(e="right"))):o.left===!0&&t<0?(e="left",u<s&&(o.up===!0&&i<0?e="up":o.down===!0&&i>0&&(e="down"))):o.right===!0&&t>0&&(e="right",u<s&&(o.up===!0&&i<0?e="up":o.down===!0&&i>0&&(e="down")));let v=!1;if(e===void 0&&n===!1){if(r.event.isFirst===!0||r.event.lastDir===void 0)return{};e=r.event.lastDir,v=!0,e==="left"||e==="right"?(l.left-=t,u=0,t=0):(l.top-=i,s=0,i=0)}return{synthetic:v,payload:{evt:a,touch:r.event.mouse!==!0,mouse:r.event.mouse===!0,position:l,direction:e,isFirst:r.event.isFirst,isFinal:n===!0,duration:Date.now()-r.event.time,distance:{x:u,y:s},offset:{x:t,y:i},delta:{x:l.left-r.event.lastX,y:l.top-r.event.lastY}}}}let S=0;var L=D({name:"touch-pan",beforeMount(a,{value:r,modifiers:n}){if(n.mouse!==!0&&m.has.touch!==!0)return;function l(t,i){n.mouse===!0&&i===!0?F(t):(n.stop===!0&&C(t),n.prevent===!0&&w(t))}const e={uid:"qvtp_"+S++,handler:r,modifiers:n,direction:_(n),noop:X,mouseStart(t){M(t,e)&&Y(t)&&(h(e,"temp",[[document,"mousemove","move","notPassiveCapture"],[document,"mouseup","end","passiveCapture"]]),e.start(t,!0))},touchStart(t){if(M(t,e)){const i=t.target;h(e,"temp",[[i,"touchmove","move","notPassiveCapture"],[i,"touchcancel","end","passiveCapture"],[i,"touchend","end","passiveCapture"]]),e.start(t)}},start(t,i){if(m.is.firefox===!0&&y(a,!0),e.lastEvt=t,i===!0||n.stop===!0){if(e.direction.all!==!0&&(i!==!0||e.modifiers.mouseAllDir!==!0&&e.modifiers.mousealldir!==!0)){const o=t.type.indexOf("mouse")>-1?new MouseEvent(t.type,t):new TouchEvent(t.type,t);t.defaultPrevented===!0&&w(o),t.cancelBubble===!0&&C(o),Object.assign(o,{qKeyEvent:t.qKeyEvent,qClickOutside:t.qClickOutside,qAnchorHandled:t.qAnchorHandled,qClonedBy:t.qClonedBy===void 0?[e.uid]:t.qClonedBy.concat(e.uid)}),e.initialEvent={target:t.target,event:o}}C(t)}const{left:u,top:s}=g(t);e.event={x:u,y:s,time:Date.now(),mouse:i===!0,detected:!1,isFirst:!0,isFinal:!1,lastX:u,lastY:s}},move(t){if(e.event===void 0)return;const i=g(t),u=i.left-e.event.x,s=i.top-e.event.y;if(u===0&&s===0)return;e.lastEvt=t;const o=e.event.mouse===!0,v=()=>{l(t,o);let d;n.preserveCursor!==!0&&n.preservecursor!==!0&&(d=document.documentElement.style.cursor||"",document.documentElement.style.cursor="grabbing"),o===!0&&document.body.classList.add("no-pointer-events--children"),document.body.classList.add("non-selectable"),P(),e.styleCleanup=p=>{if(e.styleCleanup=void 0,d!==void 0&&(document.documentElement.style.cursor=d),document.body.classList.remove("non-selectable"),o===!0){const q=()=>{document.body.classList.remove("no-pointer-events--children")};p!==void 0?setTimeout(()=>{q(),p()},50):q()}else p!==void 0&&p()}};if(e.event.detected===!0){e.event.isFirst!==!0&&l(t,e.event.mouse);const{payload:d,synthetic:p}=E(t,e,!1);d!==void 0&&(e.handler(d)===!1?e.end(t):(e.styleCleanup===void 0&&e.event.isFirst===!0&&v(),e.event.lastX=d.position.left,e.event.lastY=d.position.top,e.event.lastDir=p===!0?void 0:d.direction,e.event.isFirst=!1));return}if(e.direction.all===!0||o===!0&&(e.modifiers.mouseAllDir===!0||e.modifiers.mousealldir===!0)){v(),e.event.detected=!0,e.move(t);return}const c=Math.abs(u),f=Math.abs(s);c!==f&&(e.direction.horizontal===!0&&c>f||e.direction.vertical===!0&&c<f||e.direction.up===!0&&c<f&&s<0||e.direction.down===!0&&c<f&&s>0||e.direction.left===!0&&c>f&&u<0||e.direction.right===!0&&c>f&&u>0?(e.event.detected=!0,e.move(t)):e.end(t,!0))},end(t,i){if(e.event!==void 0){if(b(e,"temp"),m.is.firefox===!0&&y(a,!1),i===!0)e.styleCleanup!==void 0&&e.styleCleanup(),e.event.detected!==!0&&e.initialEvent!==void 0&&e.initialEvent.target.dispatchEvent(e.initialEvent.event);else if(e.event.detected===!0){e.event.isFirst===!0&&e.handler(E(t===void 0?e.lastEvt:t,e).payload);const{payload:u}=E(t===void 0?e.lastEvt:t,e,!0),s=()=>{e.handler(u)};e.styleCleanup!==void 0?e.styleCleanup(s):s()}e.event=void 0,e.initialEvent=void 0,e.lastEvt=void 0}}};if(a.__qtouchpan=e,n.mouse===!0){const t=n.mouseCapture===!0||n.mousecapture===!0?"Capture":"";h(e,"main",[[a,"mousedown","mouseStart",`passive${t}`]])}m.has.touch===!0&&h(e,"main",[[a,"touchstart","touchStart",`passive${n.capture===!0?"Capture":""}`],[a,"touchmove","noop","notPassiveCapture"]])},updated(a,r){const n=a.__qtouchpan;n!==void 0&&(r.oldValue!==r.value&&(typeof value!="function"&&n.end(),n.handler=r.value),n.direction=_(r.modifiers))},beforeUnmount(a){const r=a.__qtouchpan;r!==void 0&&(r.event!==void 0&&r.end(),b(r,"main"),b(r,"temp"),m.is.firefox===!0&&y(a,!1),r.styleCleanup!==void 0&&r.styleCleanup(),delete a.__qtouchpan)}});export{L as T};
diff --git a/assets/addressbar-color.39c07217.js b/assets/addressbar-color.39c07217.js
new file mode 100644
index 00000000000..061ea0383e2
--- /dev/null
+++ b/assets/addressbar-color.39c07217.js
@@ -0,0 +1 @@
+import{g as a,A as s}from"./index.ae19b4cb.js";var e=()=>{const r=a("primary");r&&s.set(r)};export{e as default};
diff --git a/assets/addressbar-color.84ac271b.js b/assets/addressbar-color.84ac271b.js
deleted file mode 100644
index 37d55dcbd26..00000000000
--- a/assets/addressbar-color.84ac271b.js
+++ /dev/null
@@ -1 +0,0 @@
-import{g as a,A as s}from"./index.2b6e3ac7.js";var e=()=>{const r=a("primary");r&&s.set(r)};export{e as default};
diff --git a/assets/blogs.fa81a92f.js b/assets/blogs.0b845204.js
similarity index 98%
rename from assets/blogs.fa81a92f.js
rename to assets/blogs.0b845204.js
index f411158c23b..ce1beb25854 100644
--- a/assets/blogs.fa81a92f.js
+++ b/assets/blogs.0b845204.js
@@ -1 +1 @@
-import{k as b,R as w,m as y,S as _,s as v,h as m,i as g,T as S,C as A,aZ as C,e as T,a7 as h,a8 as p,ae as j,a9 as d,az as x,ab as B,ac as I,at as N,bE as f,aa as k,ak as L,aV as $}from"./index.2b6e3ac7.js";import{Q}from"./QImg.366b6afd.js";import{_ as P}from"./plugin-vue_export-helper.21dcd24c.js";var O=b({name:"QInnerLoading",props:{...w,...y,showing:Boolean,color:String,size:{type:[String,Number],default:42},label:String,labelClass:String,labelStyle:[String,Array,Object]},setup(e,{slots:t}){const l=A(),a=_(e,l.proxy.$q),{transitionProps:n,transitionStyle:s}=v(e),i=m(()=>"q-inner-loading absolute-full column flex-center"+(a.value===!0?" q-inner-loading--dark":"")),u=m(()=>"q-inner-loading__label"+(e.labelClass!==void 0?` ${e.labelClass}`:""));function c(){const r=[g(C,{size:e.size,color:e.color})];return e.label!==void 0&&r.push(g("div",{class:u.value,style:e.labelStyle},[e.label])),r}function o(){return e.showing===!0?g("div",{class:i.value,style:s.value},t.default!==void 0?t.default():c()):null}return()=>g(S,n.value,o)}});const z=T({__name:"AvatarsComponent",props:{authors:{}},setup(e){return(t,l)=>(d(),h(j,{avatar:""},{default:p(()=>[x("div",{style:f([{height:"30px"},`width: ${t.authors.length*30-(t.authors.length-1)*5}px`]),class:"relative-position"},[(d(!0),B(L,null,I(t.authors,(a,n)=>(d(),h(N,{size:"30px",color:"grey-9",key:a.id,style:f(`left: ${n*25}px;`),class:"overlapping"},{default:p(()=>[k(Q,{src:a.profileImage},null,8,["src"])]),_:2},1032,["style"]))),128))],4)]),_:1}))}});var F=P(z,[["__scopeId","data-v-363418f9"]]);const R=$("news",{state:()=>({authors:[],blogs:{all:[],featured:[],press:[],events:[],insights:[],"knowledge-base":[],releases:[],"tech-blog":[]},blogsMeta:{pagination:{limit:0,next:0,page:0,pages:0,prev:0,total:0}},allBlogs:[],updatedAt:void 0}),actions:{async getNews(e,t="authors,tags"){const l=`https://jina-ai-gmbh.ghost.io/ghost/api/content/posts/slug/${e}/?${new URLSearchParams({key:"2652cf20335454671600707967",include:t})}`,a=await fetch(l,{headers:{"Content-Type":"application/json; charset=UTF-8"}}),{posts:n}=await a.json();return n.length>0?n.map(s=>({id:s.id,url:s.url,html:s.html,excerpt:s.excerpt,featureImage:s.feature_image,publishedAt:s.published_at,updatedAt:s.updated_at,title:s.title,slug:s.slug,readingTime:s.reading_time,featured:s.featured,primaryTag:s.primary_tag,authors:s.authors.map(i=>({id:i.id,name:i.name,bio:i.bio,location:i.location,profileImage:i.profile_image,slug:i.slug,url:i.url,twitter:i.twitter})),tags:s.tags.map(i=>({id:i.id,name:i.name,slug:i.slug,url:i.url,visibility:i.visibility}))}))[0]:null},async getNewsList({filter:e,include:t="authors,tags",page:l,limit:a=6}){let n={include:t,limit:String(a),key:"2652cf20335454671600707967"};e!==void 0&&(n=Object.assign(n,{filter:e})),l!==void 0&&(n=Object.assign(n,{page:String(l)}));const s="https://jina-ai-gmbh.ghost.io/ghost/api/content/posts/?"+new URLSearchParams(n),i=await fetch(s,{headers:{"Content-Type":"application/json; charset=UTF-8"}}),{posts:u,meta:c}=await i.json();return{posts:u.map(o=>({id:o.id,url:o.url,html:o.html,excerpt:o.excerpt,featureImage:o.feature_image,publishedAt:o.published_at,updatedAt:o.updated_at,title:o.title,slug:o.slug,readingTime:o.reading_time,featured:o.featured,primaryTag:o.primary_tag,authors:o.authors.map(r=>({id:r.id,name:r.name,bio:r.bio,location:r.location,profileImage:r.profile_image,slug:r.slug,url:r.url,twitter:r.twitter})),tags:o.tags.map(r=>({id:r.id,name:r.name,slug:r.slug,url:r.url,visibility:r.visibility}))})),meta:c}},async getNewsBy({authors:e,tag:t="all",page:l=1,limit:a=6}){const n=[];e&&e.length>0&&n.push(`authors.slug:[${e.join(",")}]`),t!=="all"&&(t==="featured"?n.push("featured:true"):n.push(`tag:${t}`));const{posts:s,meta:i}=await this.getNewsList({filter:n.join("+"),page:l,limit:a});this.blogs[t]=s,this.blogsMeta=i},async getNewsBySlug(e,t="authors,tags"){return await this.getNews(e,t)},async getSuggestionNews(e,t){const{posts:l}=await this.getNewsList({limit:e,filter:t,page:1});return l},async getAllNews(){let e={limit:"all"};if(this.allBlogs.length>0&&this.updatedAt){e=Object.assign(e,{filter:`updated_at:>${this.updatedAt}`});const{posts:t}=await this.getNewsList(e);t.reverse().forEach(l=>{const a=this.allBlogs.findIndex(n=>n.id===l.id);a!==-1?this.allBlogs[a]=l:this.allBlogs.unshift(l)})}else{const{posts:t}=await this.getNewsList(e);this.allBlogs=t}this.allBlogs=[...this.allBlogs.sort((t,l)=>new Date(l.publishedAt).getTime()-new Date(t.publishedAt).getTime())],this.updatedAt=new Date().toISOString()},async getAuthors(){const e="https://jina-ai-gmbh.ghost.io/ghost/api/content/authors/?"+new URLSearchParams({key:"2652cf20335454671600707967",limit:"all"}),t=await fetch(e,{headers:{"Content-Type":"application/json; charset=UTF-8"}}),{authors:l}=await t.json();this.authors=l.map(a=>({id:a.id,name:a.name,bio:a.bio,location:a.location,profileImage:a.profile_image,slug:a.slug,url:a.url,twitter:a.twitter}))}},persist:!0});export{F as A,O as Q,R as u};
+import{k as b,R as w,m as y,S as _,s as v,h as m,i as g,T as S,C as A,aZ as C,e as T,a7 as h,a8 as p,ae as j,a9 as d,az as x,ab as B,ac as I,at as N,bE as f,aa as k,ak as L,aV as $}from"./index.ae19b4cb.js";import{Q}from"./QImg.27db20fc.js";import{_ as P}from"./plugin-vue_export-helper.21dcd24c.js";var O=b({name:"QInnerLoading",props:{...w,...y,showing:Boolean,color:String,size:{type:[String,Number],default:42},label:String,labelClass:String,labelStyle:[String,Array,Object]},setup(e,{slots:t}){const l=A(),a=_(e,l.proxy.$q),{transitionProps:n,transitionStyle:s}=v(e),i=m(()=>"q-inner-loading absolute-full column flex-center"+(a.value===!0?" q-inner-loading--dark":"")),u=m(()=>"q-inner-loading__label"+(e.labelClass!==void 0?` ${e.labelClass}`:""));function c(){const r=[g(C,{size:e.size,color:e.color})];return e.label!==void 0&&r.push(g("div",{class:u.value,style:e.labelStyle},[e.label])),r}function o(){return e.showing===!0?g("div",{class:i.value,style:s.value},t.default!==void 0?t.default():c()):null}return()=>g(S,n.value,o)}});const z=T({__name:"AvatarsComponent",props:{authors:{}},setup(e){return(t,l)=>(d(),h(j,{avatar:""},{default:p(()=>[x("div",{style:f([{height:"30px"},`width: ${t.authors.length*30-(t.authors.length-1)*5}px`]),class:"relative-position"},[(d(!0),B(L,null,I(t.authors,(a,n)=>(d(),h(N,{size:"30px",color:"grey-9",key:a.id,style:f(`left: ${n*25}px;`),class:"overlapping"},{default:p(()=>[k(Q,{src:a.profileImage},null,8,["src"])]),_:2},1032,["style"]))),128))],4)]),_:1}))}});var F=P(z,[["__scopeId","data-v-363418f9"]]);const R=$("news",{state:()=>({authors:[],blogs:{all:[],featured:[],press:[],events:[],insights:[],"knowledge-base":[],releases:[],"tech-blog":[]},blogsMeta:{pagination:{limit:0,next:0,page:0,pages:0,prev:0,total:0}},allBlogs:[],updatedAt:void 0}),actions:{async getNews(e,t="authors,tags"){const l=`https://jina-ai-gmbh.ghost.io/ghost/api/content/posts/slug/${e}/?${new URLSearchParams({key:"2652cf20335454671600707967",include:t})}`,a=await fetch(l,{headers:{"Content-Type":"application/json; charset=UTF-8"}}),{posts:n}=await a.json();return n.length>0?n.map(s=>({id:s.id,url:s.url,html:s.html,excerpt:s.excerpt,featureImage:s.feature_image,publishedAt:s.published_at,updatedAt:s.updated_at,title:s.title,slug:s.slug,readingTime:s.reading_time,featured:s.featured,primaryTag:s.primary_tag,authors:s.authors.map(i=>({id:i.id,name:i.name,bio:i.bio,location:i.location,profileImage:i.profile_image,slug:i.slug,url:i.url,twitter:i.twitter})),tags:s.tags.map(i=>({id:i.id,name:i.name,slug:i.slug,url:i.url,visibility:i.visibility}))}))[0]:null},async getNewsList({filter:e,include:t="authors,tags",page:l,limit:a=6}){let n={include:t,limit:String(a),key:"2652cf20335454671600707967"};e!==void 0&&(n=Object.assign(n,{filter:e})),l!==void 0&&(n=Object.assign(n,{page:String(l)}));const s="https://jina-ai-gmbh.ghost.io/ghost/api/content/posts/?"+new URLSearchParams(n),i=await fetch(s,{headers:{"Content-Type":"application/json; charset=UTF-8"}}),{posts:u,meta:c}=await i.json();return{posts:u.map(o=>({id:o.id,url:o.url,html:o.html,excerpt:o.excerpt,featureImage:o.feature_image,publishedAt:o.published_at,updatedAt:o.updated_at,title:o.title,slug:o.slug,readingTime:o.reading_time,featured:o.featured,primaryTag:o.primary_tag,authors:o.authors.map(r=>({id:r.id,name:r.name,bio:r.bio,location:r.location,profileImage:r.profile_image,slug:r.slug,url:r.url,twitter:r.twitter})),tags:o.tags.map(r=>({id:r.id,name:r.name,slug:r.slug,url:r.url,visibility:r.visibility}))})),meta:c}},async getNewsBy({authors:e,tag:t="all",page:l=1,limit:a=6}){const n=[];e&&e.length>0&&n.push(`authors.slug:[${e.join(",")}]`),t!=="all"&&(t==="featured"?n.push("featured:true"):n.push(`tag:${t}`));const{posts:s,meta:i}=await this.getNewsList({filter:n.join("+"),page:l,limit:a});this.blogs[t]=s,this.blogsMeta=i},async getNewsBySlug(e,t="authors,tags"){return await this.getNews(e,t)},async getSuggestionNews(e,t){const{posts:l}=await this.getNewsList({limit:e,filter:t,page:1});return l},async getAllNews(){let e={limit:"all"};if(this.allBlogs.length>0&&this.updatedAt){e=Object.assign(e,{filter:`updated_at:>${this.updatedAt}`});const{posts:t}=await this.getNewsList(e);t.reverse().forEach(l=>{const a=this.allBlogs.findIndex(n=>n.id===l.id);a!==-1?this.allBlogs[a]=l:this.allBlogs.unshift(l)})}else{const{posts:t}=await this.getNewsList(e);this.allBlogs=t}this.allBlogs=[...this.allBlogs.sort((t,l)=>new Date(l.publishedAt).getTime()-new Date(t.publishedAt).getTime())],this.updatedAt=new Date().toISOString()},async getAuthors(){const e="https://jina-ai-gmbh.ghost.io/ghost/api/content/authors/?"+new URLSearchParams({key:"2652cf20335454671600707967",limit:"all"}),t=await fetch(e,{headers:{"Content-Type":"application/json; charset=UTF-8"}}),{authors:l}=await t.json();this.authors=l.map(a=>({id:a.id,name:a.name,bio:a.bio,location:a.location,profileImage:a.profile_image,slug:a.slug,url:a.url,twitter:a.twitter}))}},persist:!0});export{F as A,O as Q,R as u};
diff --git a/assets/copy-to-clipboard.1e057f62.js b/assets/copy-to-clipboard.58aec584.js
similarity index 85%
rename from assets/copy-to-clipboard.1e057f62.js
rename to assets/copy-to-clipboard.58aec584.js
index 274790fa8e5..090ac614ecc 100644
--- a/assets/copy-to-clipboard.1e057f62.js
+++ b/assets/copy-to-clipboard.58aec584.js
@@ -1 +1 @@
-import{F as r,G as a}from"./index.2b6e3ac7.js";function c(o){const e=document.createElement("textarea");e.value=o,e.contentEditable="true",e.style.position="fixed";const t=()=>{};r(t),document.body.appendChild(e),e.focus(),e.select();const n=document.execCommand("copy");return e.remove(),a(t),n}function s(o){return navigator.clipboard!==void 0?navigator.clipboard.writeText(o):new Promise((e,t)=>{const n=c(o);n?e(!0):t(n)})}export{s as c};
+import{F as r,G as a}from"./index.ae19b4cb.js";function c(o){const e=document.createElement("textarea");e.value=o,e.contentEditable="true",e.style.position="fixed";const t=()=>{};r(t),document.body.appendChild(e),e.focus(),e.select();const n=document.execCommand("copy");return e.remove(),a(t),n}function s(o){return navigator.clipboard!==void 0?navigator.clipboard.writeText(o):new Promise((e,t)=>{const n=c(o);n?e(!0):t(n)})}export{s as c};
diff --git a/assets/data.json b/assets/data.json
index 21346816414..463cc2260ce 100644
--- a/assets/data.json
+++ b/assets/data.json
@@ -17,8 +17,8 @@
   },
   "jobs": [
     {
-      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n✉️ Recommendation letter \n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.\n\n- Next, candidates will be invited to a Team Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
-      "additional": "<div><br></div><div><br></div><div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><b style=\"font-size: 1em\">✉️ </b><span style=\"font-size: 1em\">Recommendation letter </span></div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;30-minute screening call&nbsp;specifically on Zoom with one of our global recruiters.</div><div><br></div><div>- Next, candidates will be invited to a&nbsp;Team Peer Interview.&nbsp;During the interview, which will last&nbsp;1 hour,&nbsp;the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;15-minute call&nbsp;with our recruiters to discuss the terms of the offer.</div>",
+      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n✉️ Recommendation letter \n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.\n\n- Next, candidates will be invited to a Team Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
+      "additional": "<div><br></div><div><br></div><div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><b style=\"font-size: 1em\">✉️ </b><span style=\"font-size: 1em\">Recommendation letter </span></div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;30-minute screening call&nbsp;specifically on Zoom with one of our global recruiters.</div><div><br></div><div>- Next, candidates will be invited to a&nbsp;Team Peer Interview.&nbsp;During the interview, which will last&nbsp;1 hour,&nbsp;the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;15-minute call&nbsp;with our recruiters to discuss the terms of the offer.</div>",
       "categories": {
         "location": "Berlin",
         "team": "Internship Programme",
@@ -38,8 +38,8 @@
       "applyUrl": "https://jobs.lever.co/jina-ai/d17e522f-4095-4e22-91a0-523938132664/apply"
     },
     {
-      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n✉️ Recommendation letter \n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.\n\n- Next, candidates will be invited to a Team Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
-      "additional": "<div><br></div><div><br></div><div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><b style=\"font-size: 1em\">✉️ </b><span style=\"font-size: 1em\">Recommendation letter </span></div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;30-minute screening call&nbsp;specifically on Zoom with one of our global recruiters.</div><div><br></div><div>- Next, candidates will be invited to a&nbsp;Team Peer Interview.&nbsp;During the interview, which will last&nbsp;1 hour,&nbsp;the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;15-minute call&nbsp;with our recruiters to discuss the terms of the offer.</div>",
+      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n✉️ Recommendation letter \n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.\n\n- Next, candidates will be invited to a Team Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
+      "additional": "<div><br></div><div><br></div><div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><b style=\"font-size: 1em\">✉️ </b><span style=\"font-size: 1em\">Recommendation letter </span></div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;30-minute screening call&nbsp;specifically on Zoom with one of our global recruiters.</div><div><br></div><div>- Next, candidates will be invited to a&nbsp;Team Peer Interview.&nbsp;During the interview, which will last&nbsp;1 hour,&nbsp;the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;15-minute call&nbsp;with our recruiters to discuss the terms of the offer.</div>",
       "categories": {
         "location": "Berlin",
         "team": "Internship Programme",
@@ -59,8 +59,8 @@
       "applyUrl": "https://jobs.lever.co/jina-ai/c3335e56-dfb0-40d7-871d-f1a87ccb0e8d/apply"
     },
     {
-      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n✉️ Recommendation letter \n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.\n\n- Next, candidates will be invited to a Team Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
-      "additional": "<div><br></div><div><br></div><div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><b style=\"font-size: 1em\">✉️ </b><span style=\"font-size: 1em\">Recommendation letter </span></div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;30-minute screening call&nbsp;specifically on Zoom with one of our global recruiters.</div><div><br></div><div>- Next, candidates will be invited to a&nbsp;Team Peer Interview.&nbsp;During the interview, which will last&nbsp;1 hour,&nbsp;the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;15-minute call&nbsp;with our recruiters to discuss the terms of the offer.</div>",
+      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n✉️ Recommendation letter \n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.\n\n- Next, candidates will be invited to a Team Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
+      "additional": "<div><br></div><div><br></div><div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><b style=\"font-size: 1em\">✉️ </b><span style=\"font-size: 1em\">Recommendation letter </span></div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;30-minute screening call&nbsp;specifically on Zoom with one of our global recruiters.</div><div><br></div><div>- Next, candidates will be invited to a&nbsp;Team Peer Interview.&nbsp;During the interview, which will last&nbsp;1 hour,&nbsp;the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;15-minute call&nbsp;with our recruiters to discuss the terms of the offer.</div>",
       "categories": {
         "location": "Berlin",
         "team": "Internship Programme",
@@ -80,8 +80,8 @@
       "applyUrl": "https://jobs.lever.co/jina-ai/f79464ed-0537-413c-81fe-6710bf83d569/apply"
     },
     {
-      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n✉️ Recommendation letter \n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.\n\n- Next, candidates will be invited to a Team Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
-      "additional": "<div><br></div><div><br></div><div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><b style=\"font-size: 1em\">✉️ </b><span style=\"font-size: 1em\">Recommendation letter </span></div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;30-minute screening call&nbsp;specifically on Zoom with one of our global recruiters.</div><div><br></div><div>- Next, candidates will be invited to a&nbsp;Team Peer Interview.&nbsp;During the interview, which will last&nbsp;1 hour,&nbsp;the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;15-minute call&nbsp;with our recruiters to discuss the terms of the offer.</div>",
+      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n✉️ Recommendation letter \n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.\n\n- Next, candidates will be invited to a Team Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
+      "additional": "<div><br></div><div><br></div><div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><b style=\"font-size: 1em\">✉️ </b><span style=\"font-size: 1em\">Recommendation letter </span></div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;30-minute screening call&nbsp;specifically on Zoom with one of our global recruiters.</div><div><br></div><div>- Next, candidates will be invited to a&nbsp;Team Peer Interview.&nbsp;During the interview, which will last&nbsp;1 hour,&nbsp;the team will examine your fundamental knowledge and experience as well as your motivation to join Jina AI; If you are applying for an Engineering Internship, one should also expect a live-coding challenge in 10 to 15 minutes.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;15-minute call&nbsp;with our recruiters to discuss the terms of the offer.</div>",
       "categories": {
         "location": "Berlin",
         "team": "Internship Programme",
@@ -132,8 +132,8 @@
       "applyUrl": "https://jobs.lever.co/jina-ai/7a1f8cdc-196d-483d-9b8b-f3734c8394f6/apply"
     },
     {
-      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary & stock options\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters. For engineering candidates, after this interview candidates will receive an email and be asked to complete an offline code challenge. On average the candidates can finish it in 30 minutes.\n\n- Next, candidates will be invited to schedule a 45min Peer Interview, followed by a 45min Team Peer Interview. \n\n- Finally, candidates will be invited to schedule a 30-minute interview with COO.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
-      "additional": "<div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary &amp; stock options</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;<b>30-minute screening call</b>&nbsp;specifically on Zoom with one of our global recruiters. For engineering candidates, after this interview candidates will receive an email and be asked to complete an offline code challenge. On average the candidates can finish it in 30 minutes.</div><div><br></div><div>- Next, candidates will be invited to schedule&nbsp;a <b>45min&nbsp;Peer Interview,&nbsp;</b>followed by a <b>45min Team Peer Interview. </b></div><div><br></div><div><span style=\"font-size: 16px\">- </span>Finally, candidates will be invited to schedule a&nbsp;<b>30-minute interview</b>&nbsp;with COO.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;<b>15-minute call</b>&nbsp;with our recruiters to discuss the terms of the offer.</div>",
+      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary & stock options\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters. For engineering candidates, after this interview candidates will receive an email and be asked to complete an offline code challenge. On average the candidates can finish it in 30 minutes.\n\n- Next, candidates will be invited to schedule a 45min Peer Interview, followed by a 45min Team Peer Interview. \n\n- Finally, candidates will be invited to schedule a 30-minute interview with COO.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
+      "additional": "<div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary &amp; stock options</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;<b>30-minute screening call</b>&nbsp;specifically on Zoom with one of our global recruiters. For engineering candidates, after this interview candidates will receive an email and be asked to complete an offline code challenge. On average the candidates can finish it in 30 minutes.</div><div><br></div><div>- Next, candidates will be invited to schedule&nbsp;a <b>45min&nbsp;Peer Interview,&nbsp;</b>followed by a <b>45min Team Peer Interview. </b></div><div><br></div><div><span style=\"font-size: 16px\">- </span>Finally, candidates will be invited to schedule a&nbsp;<b>30-minute interview</b>&nbsp;with COO.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;<b>15-minute call</b>&nbsp;with our recruiters to discuss the terms of the offer.</div>",
       "categories": {
         "commitment": "Internship",
         "location": "Berlin",
@@ -163,8 +163,8 @@
       "applyUrl": "https://jobs.lever.co/jina-ai/e417d0d5-4204-4a83-ae58-ead9a69f282b/apply"
     },
     {
-      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.\n\n- Next, candidates will be invited to a Technical Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and coding skills as well as your motivation to join Jina AI; one should also expect a live-coding challenge in 10 to 15 minutes.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
-      "additional": "<div><br></div><div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;<b>30-minute screening call</b>&nbsp;specifically on Zoom with one of our global recruiters.</div><div><br></div><div>- Next, candidates will be invited to a&nbsp;<b>Technical Peer Interview.&nbsp;</b>During the interview, which will last&nbsp;<b>1 hour</b>,<b>&nbsp;</b>the team will examine your fundamental knowledge and coding skills as well as your motivation to join Jina AI; one should also expect a live-coding challenge in 10 to 15 minutes.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;<b>15-minute call</b>&nbsp;with our recruiters to discuss the terms of the offer.</div>",
+      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.\n\n- Next, candidates will be invited to a Technical Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and coding skills as well as your motivation to join Jina AI; one should also expect a live-coding challenge in 10 to 15 minutes.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
+      "additional": "<div><br></div><div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;<b>30-minute screening call</b>&nbsp;specifically on Zoom with one of our global recruiters.</div><div><br></div><div>- Next, candidates will be invited to a&nbsp;<b>Technical Peer Interview.&nbsp;</b>During the interview, which will last&nbsp;<b>1 hour</b>,<b>&nbsp;</b>the team will examine your fundamental knowledge and coding skills as well as your motivation to join Jina AI; one should also expect a live-coding challenge in 10 to 15 minutes.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;<b>15-minute call</b>&nbsp;with our recruiters to discuss the terms of the offer.</div>",
       "categories": {
         "commitment": "Internship",
         "location": "Berlin",
@@ -225,8 +225,8 @@
       "applyUrl": "https://jobs.lever.co/jina-ai/336de671-c918-4dd1-9757-aff42558d7a7/apply"
     },
     {
-      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.\n\n- Next, candidates will be invited to a Technical Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and coding skills as well as your motivation to join Jina AI; one should also expect a live-coding challenge in 10 to 15 minutes.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
-      "additional": "<div><br></div><div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;<b>30-minute screening call</b>&nbsp;specifically on Zoom with one of our global recruiters.</div><div><br></div><div>- Next, candidates will be invited to a&nbsp;<b>Technical Peer Interview.&nbsp;</b>During the interview, which will last&nbsp;<b>1 hour</b>,<b>&nbsp;</b>the team will examine your fundamental knowledge and coding skills as well as your motivation to join Jina AI; one should also expect a live-coding challenge in 10 to 15 minutes.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;<b>15-minute call</b>&nbsp;with our recruiters to discuss the terms of the offer.</div>",
+      "additionalPlain": "😊 Benefits & Perks\n\n💰 Competitive salary\n🌎 Multi-cultural & diverse team\n🎓 Numerous opportunities to present/attend top AI/OSS/industry conference\n🦄 Rapid career development opportunities alongside the company\n🏢 Central office in downtown Berlin, Shenzhen, Beijing\n⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options\n💻 Macbooks & top-notch equipment\n\n\n💼 Hiring Process\n\nCandidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. \n\n- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.\n\n- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.\n\n- Next, candidates will be invited to a Technical Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and coding skills as well as your motivation to join Jina AI; one should also expect a live-coding challenge in 10 to 15 minutes.\n\nWe will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.",
+      "additional": "<div><br></div><div><span style=\"font-size: 24px\">😊 Benefits &amp; Perks</span></div><div><br></div><div>💰 Competitive salary</div><div>🌎 Multi-cultural &amp; diverse team</div><div>🎓 Numerous opportunities to present/attend top AI/OSS/industry conference</div><div>🦄 Rapid career development opportunities alongside the company</div><div>🏢 Central office in downtown Berlin, Shenzhen, Beijing</div><div>⛱️ Free snacks &amp; drinks, monthly team events, flexible working hours, home office options</div><div>💻 Macbooks &amp; top-notch equipment</div><div><br></div><div><br></div><div><span style=\"font-size: 24px\">💼 Hiring Process</span></div><div><br></div><div>Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.&nbsp;</div><div><br></div><div>- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.</div><div><br></div><div>- Qualified candidates will be invited to schedule a&nbsp;<b>30-minute screening call</b>&nbsp;specifically on Zoom with one of our global recruiters.</div><div><br></div><div>- Next, candidates will be invited to a&nbsp;<b>Technical Peer Interview.&nbsp;</b>During the interview, which will last&nbsp;<b>1 hour</b>,<b>&nbsp;</b>the team will examine your fundamental knowledge and coding skills as well as your motivation to join Jina AI; one should also expect a live-coding challenge in 10 to 15 minutes.</div><div><br></div><div>We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another&nbsp;<b>15-minute call</b>&nbsp;with our recruiters to discuss the terms of the offer.</div>",
       "categories": {
         "commitment": "Internship",
         "location": "Beijing",
diff --git a/assets/embedding.ed2c7731.js b/assets/embedding.507e019a.js
similarity index 97%
rename from assets/embedding.ed2c7731.js
rename to assets/embedding.507e019a.js
index e82a6ec3c5e..d02f4061f97 100644
--- a/assets/embedding.ed2c7731.js
+++ b/assets/embedding.507e019a.js
@@ -1 +1 @@
-import{k as a,h as s,i as n,D as i,aV as c}from"./index.2b6e3ac7.js";var h=a({name:"QToolbar",props:{inset:Boolean},setup(t,{slots:r}){const e=s(()=>"q-toolbar row no-wrap items-center"+(t.inset===!0?" q-toolbar--inset":""));return()=>n("div",{class:e.value,role:"toolbar"},i(r.default))}});const o="https://embeddings-dashboard-api.jina.ai";var p=(t=>(t.CONSUME="consume",t.PURCHASE="purchase",t.TRIAL="trial",t))(p||{});const l=c("embedding",{state:()=>({apiKey:"",models:[],products:[]}),persist:{paths:["apiKey"]},getters:{},actions:{async getApiKey(){try{const t=await fetch(`${o}/api/v1/api_key`,{method:"POST"});if(!t.ok)throw new Error(`getApiKey error! Status: ${t.status}`);const r=await t.json();return this.apiKey=r.api_key,!0}catch(t){return console.error("getApiKey error:",t),!1}},async getTokens(t){try{const r=await fetch(`${o}/api/v1/api_key/user?api_key=${t}`);if(!r.ok)throw new Error(`getTokens error! Status: ${r.status}`);return(await r.json()).wallet.total_balance}catch(r){console.error("getTokens error:",r)}},async getModels(){try{const t=await fetch(`${o}/api/v1/models`);if(!t.ok)throw new Error(`getModels error! Status: ${t.status}`);const r=await t.json();this.models=r}catch(t){console.error("getModels error:",t)}},async getProducts(){try{const t=await fetch(`${o}/api/v1/product`);if(!t.ok)throw new Error(`getProducts error! Status: ${t.status}`);const r=await t.json();this.products=r}catch(t){console.error("getProducts error:",t)}},async getUsage(t){try{const r=await fetch(`${o}/api/v1/billing/transaction`,{headers:{Authorization:`Bearer ${t}`}});if(!r.ok)throw new Error(`getUsage error! Status: ${r.status}`);return await r.json()}catch(r){console.error("getUsage error:",r)}},async checkoutWithStripe(t,r){try{const e=await fetch(`${o}/api/v1/checkout_session`,{headers:{Authorization:`Bearer ${t}`,"Content-Type":"application/json"},method:"POST",body:JSON.stringify(r),mode:"cors",credentials:"include"});if(!e.ok)throw new Error(`checkoutWithStripe error! Status: ${e.status}`);return await e.json()}catch(e){console.error("checkoutWithStripe error:",e)}}}});export{h as Q,p as T,l as u};
+import{k as a,h as s,i as n,D as i,aV as c}from"./index.ae19b4cb.js";var h=a({name:"QToolbar",props:{inset:Boolean},setup(t,{slots:r}){const e=s(()=>"q-toolbar row no-wrap items-center"+(t.inset===!0?" q-toolbar--inset":""));return()=>n("div",{class:e.value,role:"toolbar"},i(r.default))}});const o="https://embeddings-dashboard-api.jina.ai";var p=(t=>(t.CONSUME="consume",t.PURCHASE="purchase",t.TRIAL="trial",t))(p||{});const l=c("embedding",{state:()=>({apiKey:"",models:[],products:[]}),persist:{paths:["apiKey"]},getters:{},actions:{async getApiKey(){try{const t=await fetch(`${o}/api/v1/api_key`,{method:"POST"});if(!t.ok)throw new Error(`getApiKey error! Status: ${t.status}`);const r=await t.json();return this.apiKey=r.api_key,!0}catch(t){return console.error("getApiKey error:",t),!1}},async getTokens(t){try{const r=await fetch(`${o}/api/v1/api_key/user?api_key=${t}`);if(!r.ok)throw new Error(`getTokens error! Status: ${r.status}`);return(await r.json()).wallet.total_balance}catch(r){console.error("getTokens error:",r)}},async getModels(){try{const t=await fetch(`${o}/api/v1/models`);if(!t.ok)throw new Error(`getModels error! Status: ${t.status}`);const r=await t.json();this.models=r}catch(t){console.error("getModels error:",t)}},async getProducts(){try{const t=await fetch(`${o}/api/v1/product`);if(!t.ok)throw new Error(`getProducts error! Status: ${t.status}`);const r=await t.json();this.products=r}catch(t){console.error("getProducts error:",t)}},async getUsage(t){try{const r=await fetch(`${o}/api/v1/billing/transaction`,{headers:{Authorization:`Bearer ${t}`}});if(!r.ok)throw new Error(`getUsage error! Status: ${r.status}`);return await r.json()}catch(r){console.error("getUsage error:",r)}},async checkoutWithStripe(t,r){try{const e=await fetch(`${o}/api/v1/checkout_session`,{headers:{Authorization:`Bearer ${t}`,"Content-Type":"application/json"},method:"POST",body:JSON.stringify(r),mode:"cors",credentials:"include"});if(!e.ok)throw new Error(`checkoutWithStripe error! Status: ${e.status}`);return await e.json()}catch(e){console.error("checkoutWithStripe error:",e)}}}});export{h as Q,p as T,l as u};
diff --git a/assets/i18n.8b0aa42c.js b/assets/i18n.08ec4503.js
similarity index 99%
rename from assets/i18n.8b0aa42c.js
rename to assets/i18n.08ec4503.js
index e8d3f1b4d32..e74b3285028 100644
--- a/assets/i18n.8b0aa42c.js
+++ b/assets/i18n.08ec4503.js
@@ -1,4 +1,4 @@
-import{b as a,c as t}from"./index.2b6e3ac7.js";var s={SEO_TAG_LINE:e=>{const{normalize:n}=e;return n(["Your Portal to Multimodal AI"])},PRODUCT_DESCRIPTION:e=>{const{normalize:n}=e;return n(["Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. We aim to democratize access to the limitless potential of AI-generated creativity and innovation, empowering individuals and businesses alike."])},notice:e=>{const{normalize:n}=e;return n(['\u{1F389} Our first book, "Neural Search \u2014 From Prototype to Production with Jina" is officially out today!'])},purchase_now:e=>{const{normalize:n}=e;return n(["Purchase now"])},copy:e=>{const{normalize:n}=e;return n(["Copy"])},copy_to_clipboard_success:e=>{const{normalize:n}=e;return n(["Copied to clipboard"])},open_day:{title:e=>{const{normalize:n}=e;return n(["Open Day"])},description:e=>{const{normalize:n}=e;return n(["An exclusive opportunity to gain an insider's view of Jina AI."])},organization:e=>{const{normalize:n}=e;return n(["Organization"])},group_size:e=>{const{normalize:n}=e;return n(["Number of visitors"])},organization_website:e=>{const{normalize:n}=e;return n(["Organization website"])},organization_website_placeholder:e=>{const{normalize:n}=e;return n(["URL for your organization's homepage or LinkedIn profile"])},preferred_products:e=>{const{normalize:n}=e;return n(["Which products are you interested in?"])},preferred_date:e=>{const{normalize:n}=e;return n(["Preferred date"])},preferred_language:e=>{const{normalize:n}=e;return n(["Preferred language"])},subtitle:e=>{const{normalize:n}=e;return n(["A Glimpse into the Future of Multimodal AI"])},introduction:e=>{const{normalize:n}=e;return n(["Jina AI is delighted to open our doors to esteemed entities and organizations interested in the progress and future of Artificial Intelligence. We extend this exclusive opportunity for those in politics, NGOs, NPOs, and investment sectors to gain an insider's view of our operations and visions here at our Berlin headquarters."])},vision_title:e=>{const{normalize:n}=e;return n(["Our Vision for the Future"])},vision:e=>{const{normalize:n}=e;return n(["Join us for a comprehensive overview of the AI landscape as we see it. Our discussion will focus on the potential of Large Language Models, multimodal AI, and the impact of open-source technology in shaping the future of global innovation."])},experience:e=>{const{normalize:n}=e;return n(["We've arranged an immersive three-hour tour for our guests, available in German, English, French, Spanish, Chinese, and Russian. The tour covers an in-depth look into our advancements in multimodal AI, our perspective on the AI landscape, followed by a detailed examination of specific projects. We'll conclude with a group discussion to facilitate the exchange of ideas and insights. A lunch option is also available upon request."])},experience_title:e=>{const{normalize:n}=e;return n(["An Insider's Journey"])},impact_title:e=>{const{normalize:n}=e;return n(["Impact and Influence"])},impact:e=>{const{normalize:n}=e;return n(["Understand how our contributions to the open-source community and our work in multimodal AI technology are establishing Jina AI as an influential player in AI innovation. We aim to play a significant role in decision-making processes, ensuring that the advancement of AI technology benefits all."])},engage_title:e=>{const{normalize:n}=e;return n(["Engage with Us"])},engage:e=>{const{normalize:n}=e;return n(["We highly encourage an interactive dialogue throughout the day. The exchange of thoughts and perspectives is invaluable to us. Potential collaborations stemming from these discussions could significantly contribute to a more integrated and innovative future."])},tutor_title:e=>{const{normalize:n}=e;return n(["An Exclusive Deep Dive into"])},tutor_subtitle:e=>{const{normalize:n}=e;return n(["A meticulously curated three-hour tour, bringing you closer to the heart of Jina AI's groundbreaking work in multimodal AI technology."])},one_hour:e=>{const{normalize:n}=e;return n(["1 hour"])},motivation_to_attend_v2:e=>{const{normalize:n}=e;return n(["Why are you interested in our Open Day?"])},motivation_placeholder_v2:e=>{const{normalize:n}=e;return n(["Sharing your motivations will help us improve your experience."])},motivation_min_length_v1:e=>{const{normalize:n}=e;return n(["Please provide a more detailed motivation."])}},internship_faq:{question1:e=>{const{normalize:n}=e;return n(["Who can apply for the Jina AI internship program?"])},answer1:e=>{const{normalize:n}=e;return n(["Undergraduate, Masters, and Ph.D. students from all over the world, with interest in fields such as research, engineering, marketing, and sales, are encouraged to apply. We also welcome non-technical internships in marketing, sales, executive assistance, and more. We are seeking passionate individuals ready to pioneer multimodal AI with us."])},question2:e=>{const{normalize:n}=e;return n(["Where will the internship take place?"])},answer2:e=>{const{normalize:n}=e;return n(["Internships must be carried out onsite at one of our offices, which are located in Berlin, Beijing, and Shenzhen."])},question3:e=>{const{normalize:n}=e;return n(["Does Jina AI assist with visa processes?"])},answer3:e=>{const{normalize:n}=e;return n(["Yes, Jina AI offers reasonable assistance in the visa process for successful applicants."])},question4:e=>{const{normalize:n}=e;return n(["Does Jina AI provide any allowances or benefits for interns?"])},answer4:e=>{const{normalize:n}=e;return n(["Yes, Jina AI provides a reasonable amount of living cost coverage for interns during the internship period."])},question5:e=>{const{normalize:n}=e;return n(["Can I work on my Master's thesis during the internship at Jina AI?"])},answer5:e=>{const{normalize:n}=e;return n(["Yes, it is possible to work on your Master's thesis during your internship at Jina AI, typically applicable to students at German universities. However, you must have prior communication and agreement from your university's supervisor. Note that we do not help students find advisors."])},question6:e=>{const{normalize:n}=e;return n(["What does the application process involve?"])},answer6:e=>{const{normalize:n}=e;return n(["The application process includes submitting your application form, a resume, a cover letter expressing your interest and motivation, and any relevant professional links such as GitHub or LinkedIn. We evaluate candidates based on their performance during the interview and their performance in their university."])},question7:e=>{const{normalize:n}=e;return n(["Does Jina AI provide any letter of recommendation post-internship?"])},answer7:e=>{const{normalize:n}=e;return n(["Yes, successful interns may receive a letter of recommendation at the end of their internship, signed by our CEO."])},question8:e=>{const{normalize:n}=e;return n(["What is the duration of the internship?"])},answer8:e=>{const{normalize:n}=e;return n(["The duration of the internship varies based on the role and project. However, it typically ranges from three to six months."])},question9:e=>{const{normalize:n}=e;return n(["Can I apply if I don't have prior experience in AI?"])},answer9:e=>{const{normalize:n}=e;return n(["Yes, we welcome applications from all academic backgrounds. We value your passion and commitment to learn as much as prior experience."])},question10:e=>{const{normalize:n}=e;return n(["Is this a paid internship?"])},answer10:e=>{const{normalize:n}=e;return n(["Yes, our internship program offers competitive remuneration."])},question11:e=>{const{normalize:n}=e;return n(["What opportunities will I have as a Jina AI intern?"])},answer11:e=>{const{normalize:n}=e;return n(["As a Jina AI intern, you'll get hands-on experience working on challenging projects, learn from industry experts, be part of a vibrant community, and have the opportunity to make real contributions to our pioneering work in multimodal AI."])}},open_day_faq:{question1:e=>{const{normalize:n}=e;return n(["What languages do you offer for the tour?"])},answer1:e=>{const{normalize:n}=e;return n(["We offer tours in German, English, French, Spanish, Chinese, and Russian."])},question2:e=>{const{normalize:n}=e;return n(["What is the duration of the tour?"])},answer2:e=>{const{normalize:n}=e;return n(["The tour typically lasts for approximately three hours."])},question3:e=>{const{normalize:n}=e;return n(["Is lunch provided?"])},answer3:e=>{const{normalize:n}=e;return n(["Lunch is optional and can be arranged upon request."])},question4:e=>{const{normalize:n}=e;return n(["Can individuals register for the Open Day?"])},answer4:e=>{const{normalize:n}=e;return n(["Our Open Day is designed primarily for professional groups, such as politicians, NGOs, NPOs, and investors. However, we occasionally make exceptions based on the individual's profile."])},question5:e=>{const{normalize:n}=e;return n(["How many people can a group consist of for the Open Day?"])},answer5:e=>{const{normalize:n}=e;return n(["We can accommodate a variety of group sizes. Please indicate the size of your group in the registration form, and we will confirm the details with you."])},question6:e=>{const{normalize:n}=e;return n(["How can I specify areas of interest for the tour?"])},answer6:e=>{const{normalize:n}=e;return n(["There's a section in the registration form where you can specify your areas of interest or any special requests. We will do our best to tailor the tour according to your needs."])},question7:e=>{const{normalize:n}=e;return n(["Are tours available at your Beijing or Shenzhen offices?"])},answer7:e=>{const{normalize:n}=e;return n(["At this time, we only offer tours at our Berlin headquarter located in Kreuzberg. Our Beijing and Shenzhen offices are not currently open for tours."])}},header:{news:e=>{const{normalize:n}=e;return n(["News"])},open_day:e=>{const{normalize:n}=e;return n(["Open day"])},for_power_users:e=>{const{normalize:n}=e;return n(["For Power Users"])},for_power_users_description:e=>{const{normalize:n}=e;return n(["Utilize our streamlined multimodal tools to enhance your productivity."])},power_users_others:e=>{const{normalize:n}=e;return n(["More power user tools"])},for_developers:e=>{const{normalize:n}=e;return n(["For Developers"])},for_developers_description:e=>{const{normalize:n}=e;return n(["Experience a comprehensive open-source multimodal AI stack designed for developers."])},developers_others:e=>{const{normalize:n}=e;return n(["More developer tools"])},for_enterprise:e=>{const{normalize:n}=e;return n(["For Enterprises"])},for_enterprise_description:e=>{const{normalize:n}=e;return n(["Discover scalable multimodal AI strategies tailored to meet business needs."])},enterprise_others:e=>{const{normalize:n}=e;return n(["More enterprise solutions"])},internship1:e=>{const{normalize:n}=e;return n(["Intern program"])},company:e=>{const{normalize:n}=e;return n(["Company"])},about_us:e=>{const{normalize:n}=e;return n(["About us"])},contact_us:e=>{const{normalize:n}=e;return n(["Contact sales"])},jobs:e=>{const{normalize:n}=e;return n(["Join us"])},join_discord:e=>{const{normalize:n}=e;return n(["Join our Discord community"])}},footer:{power_users:e=>{const{normalize:n}=e;return n(["Power Users"])},developers:e=>{const{normalize:n}=e;return n(["Developers"])},enterprise:e=>{const{normalize:n}=e;return n(["Enterprise"])},address_beijing:e=>{const{normalize:n}=e;return n(["Beijing, China"])},address_shenzhen:e=>{const{normalize:n}=e;return n(["Shenzhen, China"])},address_berlin:e=>{const{normalize:n}=e;return n(["Berlin, Germany (HQ)"])},offices:e=>{const{normalize:n}=e;return n(["Offices"])},docs:e=>{const{normalize:n}=e;return n(["Docs"])},company:e=>{const{normalize:n}=e;return n(["Company"])},all_rights_reserved:e=>{const{normalize:n}=e;return n(["All rights reserved."])},tc:e=>{const{normalize:n}=e;return n(["Terms and Conditions"])},privacy_policy:e=>{const{normalize:n}=e;return n(["Privacy Policy"])},privacy_settings:e=>{const{normalize:n}=e;return n(["Privacy Settings"])}},prompt_perfect:{description:e=>{const{normalize:n}=e;return n(["Premier tool for prompt engineering"])},intro:e=>{const{normalize:n}=e;return n(["Premier tool for prompt engineering"])},intro1:e=>{const{normalize:n}=e;return n(["The premier tool for prompt engineering"])},original_title:e=>{const{normalize:n}=e;return n(["Original prompt"])},optimized_title:e=>{const{normalize:n}=e;return n(["Optimized prompt"])},original:e=>{const{normalize:n}=e;return n(["Your role is to be my brainstorming partner."])},optimized:e=>{const{normalize:n}=e;return n(["Your task is to be my brainstorming partner and provide creative ideas and suggestions for a given topic or problem. Your response should include original, unique, and relevant ideas that could help solve the problem or further explore the topic in an interesting way. Please note that your response should also take into account any specific requirements or constraints of the task."])},text_model:e=>{const{normalize:n}=e;return n(["Text models"])},image_model:e=>{const{normalize:n}=e;return n(["Image models"])}},jina_chat:{description:e=>{const{normalize:n}=e;return n(["More modality, longer memory, less cost"])},example_1:e=>{const{normalize:n}=e;return n(["Who are you?"])},example_2:e=>{const{normalize:n}=e;return n(["I'm a LLM chat service made by Jina AI"])}},scenex:{intro1:e=>{const{normalize:n}=e;return n(["Leading AI solution for image captions and video summaries"])},description:e=>{const{normalize:n}=e;return n(["Explore image storytelling beyond pixels"])},example1:e=>{const{normalize:n}=e;return n(["This video appears to be a nature footage featuring a charming white bunny and a butterfly in a grassy field. The bunny is seen interacting with the butterfly in different ways, showcasing their unique relationship. The natural surroundings provide a picturesque backdrop, enhancing the beauty of this simple yet captivating scene."])},caption_image_title:e=>{const{normalize:n}=e;return n(["Caption Image"])},caption_image_desc:e=>{const{normalize:n}=e;return n(["Generate a textual description of the image."])},json_image_title:e=>{const{normalize:n}=e;return n(["Extract JSON from Image"])},json_image_desc:e=>{const{normalize:n}=e;return n(["Generate a structured JSON format from the image using a predefined schema. This allows for specific data extraction from the image."])},visual_q_a_title:e=>{const{normalize:n}=e;return n(["Visual Q&A"])},visual_q_a_desc:e=>{const{normalize:n}=e;return n(["Answer a query based on the image's content."])},summarize_video_title:e=>{const{normalize:n}=e;return n(["Summarize Video"])},summarize_video_desc:e=>{const{normalize:n}=e;return n(["Generate a concise summary of the video, highlighting key events."])},generate_story_title:e=>{const{normalize:n}=e;return n(["Generate Story"])},generate_story_desc:e=>{const{normalize:n}=e;return n(["Craft a story inspired by the image, often featuring dialogues or monologues of its characters."])}},rationale:{description:e=>{const{normalize:n}=e;return n(["Ultimate AI decision-making tools"])},intro:e=>{const{normalize:n}=e;return n(["See two sides of the coin, make rational decisions"])},decision:e=>{const{normalize:n}=e;return n(["Decision"])}},best_banner:{description:e=>{const{normalize:n}=e;return n(["Blog to banner, without the prompts!"])},example_title:e=>{const{normalize:n}=e;return n(["Alice's Adventures in Wonderland - Chapter 1"])},example_description:e=>{const{normalize:n}=e;return n(["Alice was beginning to get very tired of sitting by her sister on the bank, and of having nothing to do: once or twice she had peeped into the book her sister was reading, but it had no pictures or conversations in it, \u201Cand what is the use of a book,\u201D thought Alice \u201Cwithout pictures or conversations?\u201D So she was considering in her own mind (as well as she could, for the hot day made her feel very sleepy and stupid), whether the pleasure of making a daisy-chain would be worth the trouble of getting up and picking the daisies, when suddenly a White Rabbit with pink eyes ran close by her."])}},doc_array:{description:e=>{const{normalize:n}=e;return n(["The data structure for multimodal data"])}},jina:{description:e=>{const{normalize:n}=e;return n(["Build multimodal AI applications on the cloud"])}},finetuner:{description:e=>{const{normalize:n}=e;return n(["Fine-tune embeddings on domain specific data for better search quality"])},intro:e=>{const{normalize:n}=e;return n(["On-prem embedding-tuning for your company on your data"])}},hub:{description:e=>{const{normalize:n}=e;return n(["Share and discover building blocks for multimodal AI applications"])}},clip_as_service:{description:e=>{const{normalize:n}=e;return n(["Embed images and sentences into fixed-length vectors with CLIP"])}},dalle_flow:{description:e=>{const{normalize:n}=e;return n(["A human-in-the-Loop workflow for creating HD images from text"])}},disco_art:{description:e=>{const{normalize:n}=e;return n(["Create compelling Disco Diffusion artworks in one line of code"])}},think_gpt:{description:e=>{const{normalize:n}=e;return n(["Agent techniques to augment your LLM and push it beyond its limits"])}},jcloud:{description:e=>{const{normalize:n}=e;return n(["Deploy a local project as a cloud service. 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Start with a free trial!"])},researcher_desc:e=>{const{normalize:n}=e;return n(["To understand how our large language models were trained from scratch for embedding tasks, check out our latest research and publications. Meet our team at the EMNLP, ACL, SIGIR, NeurIPS, and ICML conferences."])},include_experiment:e=>{const{normalize:n}=e;return n(["Includes our experimental and archived projects in the solution."])},your_portal_to:e=>{const{normalize:n}=e;return n(["Your Portal to"])},copy:e=>{const{normalize:n}=e;return n(["Copy"])},require_full_question:e=>{const{normalize:n}=e;return n(["Please describe your problem with more details."])},proposing_solution:e=>{const{normalize:n}=e;return n(["Proposing a solution based on Jina AI products..."])},mentioned_products:e=>{const{normalize:n}=e;return n(["Mentioned products:"])},copied_to_clipboard:e=>{const{normalize:n}=e;return n(["Copied to clipboard"])},checkout_our_solution_for_you:e=>{const{normalize:n}=e;return n(["Find out our solution tailored for you"])},ask_how_your_question:e=>{const{normalize:n}=e;return n(["Please describe your problem"])},how_to:e=>{const{normalize:n}=e;return n(["How to"])},powered_by_promptperfect:e=>{const{normalize:n}=e;return n([`Powered by PromptPerfect's "Prompt optimization" and "Prompt as a service" feature`])},error:e=>{const{normalize:n,interpolate:r,named:o}=e;return n(["There was a problem with the fetch operation: ",r(o("message"))])},find_your_portal:e=>{const{normalize:n}=e;return n(["Find Your Portal"])},opensource:e=>{const{normalize:n}=e;return n(["Open Source"])},mmstack:e=>{const{normalize:n}=e;return n(["Multimodal Stack"])},mmstack_desc:e=>{const{normalize:n}=e;return n(["The developer-friendly, cloud-native, and production-ready stack for building multimodal AI applications."])},llm:e=>{const{normalize:n}=e;return n(["LLM embedding models"])},llm_desc:e=>{const{normalize:n}=e;return n(["We provide a collection of high-performance sentence embedding models, boasting between 35 million to 6 billion parameters. They're excellent for enhancing neural search, reranking, sentence similarity, recommendations, etc. Get ready to elevate your AI experience!"])},parameters:e=>{const{normalize:n}=e;return n(["Parameters"])},download_pdf:e=>{const{normalize:n}=e;return n(["Download PDF"])},multimodal_ai:e=>{const{normalize:n}=e;return n(["Multimodal AI"])},multimodal:e=>{const{normalize:n}=e;return n(["Multimodal"])},contact_sales:e=>{const{normalize:n}=e;return n(["Contact sales"])},join_community:e=>{const{normalize:n}=e;return n(["Join community"])},trusted_by:e=>{const{normalize:n}=e;return n(["TRUSTED BY"])},newsroom:e=>{const{normalize:n}=e;return n(["Newsroom"])},read_more:e=>{const{normalize:n}=e;return n(["Read more"])},for:e=>{const{normalize:n}=e;return n(["For"])},power_users:e=>{const{normalize:n}=e;return n(["Power Users"])},researchers:e=>{const{normalize:n}=e;return n(["Researchers"])},power_users_desc:e=>{const{normalize:n}=e;return n(["Experience powerful, user-friendly multimodal AI apps. No coding, no fuss, just results."])},developers:e=>{const{normalize:n}=e;return n(["Developers"])},developers_desc:e=>{const{normalize:n}=e;return n(["Unleash the full power of multimodal AI with cutting-edge cloud-native technologies and open-source infrastructure."])},sdk:e=>{const{normalize:n}=e;return n(["SDK"])},starter_kit:e=>{const{normalize:n}=e;return n(["Starter Kit"])},sdk_desc:e=>{const{normalize:n}=e;return n(["Want to build high-level AIGC applications using PromptPerfect, SceneXplain, BestBanner, JinaChat, Rationale APIs? We've got you covered! Try our easy-to-use SDK and get started in minutes."])},sdk_docs:e=>{const{normalize:n}=e;return n(["Read docs"])},sdk_example:e=>{const{normalize:n}=e;return n(["Example"])},build_python:e=>{const{normalize:n}=e;return n(["Build with Python"])},build_js:e=>{const{normalize:n}=e;return n(["Build with JavaScript"])},enterprise:e=>{const{normalize:n}=e;return n(["Enterprise"])},enterprise_desc:e=>{const{normalize:n}=e;return n(["Boost your business with scalable, secure, and bespoke multimodal AI solutions."])},embedding_paper_title:e=>{const{normalize:n}=e;return n(["Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models"])},embedding_paper_desc:e=>{const{normalize:n}=e;return n(["Jina Embeddings constitutes a set of high-performance sentence embedding models adept at translating various textual inputs into numerical representations, thereby capturing the semantic essence of the text. While these models are not exclusively designed for text generation, they excel in applications such as dense retrieval and semantic textual similarity. This paper details the development of Jina Embeddings, starting with the creation of a high-quality pairwise and triplet dataset. It underlines the crucial role of data cleaning in dataset preparation, gives in-depth insights into the model training process, and concludes with a comprehensive performance evaluation using the Massive Textual Embedding Benchmark (MTEB)."])}},about_us_page:{employees:e=>{const{normalize:n}=e;return n(["Employees"])},approach:e=>{const{normalize:n}=e;return n(["Our Approach"])},approach_content1:e=>{const{normalize:n}=e;return n(["In the rapidly evolving world of AI, strategies need to be both nimble and forward-thinking. While our core offering remains centered on enterprises, the AI landscape has shifted in ways that necessitate a rethinking of our approach to customer acquisition. Here's why introducing power users as the entry point of our funnel isn't just innovative, but crucial for our sustained growth in the enterprise sector."])},approach_content2:e=>{const{normalize:n}=e;return n(["At Jina AI, our strategy is to be proactive rather than reactive. The inclusion of power users as the funnel's entry point ensures we're not only capturing current market trends but are also strategically poised for future enterprise growth. Our commitment to enterprises remains unwavering; however, our approach to reaching them is innovative, robust, and, above all, forward-thinking."])},approach_new_paradigm:e=>{const{normalize:n}=e;return n(["Prompt-based Technology: A New Paradigm"])},approach_miss_mark:e=>{const{normalize:n}=e;return n(["Why Traditional MLOps Miss the Mark"])},approach_connect_dots:e=>{const{normalize:n}=e;return n(["Connecting the Dots: Power Users to Enterprises"])},approach_new_paradigm_description:e=>{const{normalize:n}=e;return n([`2023 heralded a significant change: the rise of prompt-based technology. By simplifying the AI development process, it has democratized access to AI tools. Now, those without extensive programming experience\u2014termed as 'power users'\u2014can engage in AI development without the steep learning curves associated with tools like Pytorch, Docker, or Kubernetes.
+import{b as a,c as t}from"./index.ae19b4cb.js";var s={SEO_TAG_LINE:e=>{const{normalize:n}=e;return n(["Your Portal to Multimodal AI"])},PRODUCT_DESCRIPTION:e=>{const{normalize:n}=e;return n(["Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. 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We extend this exclusive opportunity for those in politics, NGOs, NPOs, and investment sectors to gain an insider's view of our operations and visions here at our Berlin headquarters."])},vision_title:e=>{const{normalize:n}=e;return n(["Our Vision for the Future"])},vision:e=>{const{normalize:n}=e;return n(["Join us for a comprehensive overview of the AI landscape as we see it. Our discussion will focus on the potential of Large Language Models, multimodal AI, and the impact of open-source technology in shaping the future of global innovation."])},experience:e=>{const{normalize:n}=e;return n(["We've arranged an immersive three-hour tour for our guests, available in German, English, French, Spanish, Chinese, and Russian. The tour covers an in-depth look into our advancements in multimodal AI, our perspective on the AI landscape, followed by a detailed examination of specific projects. We'll conclude with a group discussion to facilitate the exchange of ideas and insights. A lunch option is also available upon request."])},experience_title:e=>{const{normalize:n}=e;return n(["An Insider's Journey"])},impact_title:e=>{const{normalize:n}=e;return n(["Impact and Influence"])},impact:e=>{const{normalize:n}=e;return n(["Understand how our contributions to the open-source community and our work in multimodal AI technology are establishing Jina AI as an influential player in AI innovation. We aim to play a significant role in decision-making processes, ensuring that the advancement of AI technology benefits all."])},engage_title:e=>{const{normalize:n}=e;return n(["Engage with Us"])},engage:e=>{const{normalize:n}=e;return n(["We highly encourage an interactive dialogue throughout the day. The exchange of thoughts and perspectives is invaluable to us. 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We are seeking passionate individuals ready to pioneer multimodal AI with us."])},question2:e=>{const{normalize:n}=e;return n(["Where will the internship take place?"])},answer2:e=>{const{normalize:n}=e;return n(["Internships must be carried out onsite at one of our offices, which are located in Berlin, Beijing, and Shenzhen."])},question3:e=>{const{normalize:n}=e;return n(["Does Jina AI assist with visa processes?"])},answer3:e=>{const{normalize:n}=e;return n(["Yes, Jina AI offers reasonable assistance in the visa process for successful applicants."])},question4:e=>{const{normalize:n}=e;return n(["Does Jina AI provide any allowances or benefits for interns?"])},answer4:e=>{const{normalize:n}=e;return n(["Yes, Jina AI provides a reasonable amount of living cost coverage for interns during the internship period."])},question5:e=>{const{normalize:n}=e;return n(["Can I work on my Master's thesis during the internship at Jina AI?"])},answer5:e=>{const{normalize:n}=e;return n(["Yes, it is possible to work on your Master's thesis during your internship at Jina AI, typically applicable to students at German universities. However, you must have prior communication and agreement from your university's supervisor. Note that we do not help students find advisors."])},question6:e=>{const{normalize:n}=e;return n(["What does the application process involve?"])},answer6:e=>{const{normalize:n}=e;return n(["The application process includes submitting your application form, a resume, a cover letter expressing your interest and motivation, and any relevant professional links such as GitHub or LinkedIn. We evaluate candidates based on their performance during the interview and their performance in their university."])},question7:e=>{const{normalize:n}=e;return n(["Does Jina AI provide any letter of recommendation post-internship?"])},answer7:e=>{const{normalize:n}=e;return n(["Yes, successful interns may receive a letter of recommendation at the end of their internship, signed by our CEO."])},question8:e=>{const{normalize:n}=e;return n(["What is the duration of the internship?"])},answer8:e=>{const{normalize:n}=e;return n(["The duration of the internship varies based on the role and project. However, it typically ranges from three to six months."])},question9:e=>{const{normalize:n}=e;return n(["Can I apply if I don't have prior experience in AI?"])},answer9:e=>{const{normalize:n}=e;return n(["Yes, we welcome applications from all academic backgrounds. We value your passion and commitment to learn as much as prior experience."])},question10:e=>{const{normalize:n}=e;return n(["Is this a paid internship?"])},answer10:e=>{const{normalize:n}=e;return n(["Yes, our internship program offers competitive remuneration."])},question11:e=>{const{normalize:n}=e;return n(["What opportunities will I have as a Jina AI intern?"])},answer11:e=>{const{normalize:n}=e;return n(["As a Jina AI intern, you'll get hands-on experience working on challenging projects, learn from industry experts, be part of a vibrant community, and have the opportunity to make real contributions to our pioneering work in multimodal AI."])}},open_day_faq:{question1:e=>{const{normalize:n}=e;return n(["What languages do you offer for the tour?"])},answer1:e=>{const{normalize:n}=e;return n(["We offer tours in German, English, French, Spanish, Chinese, and Russian."])},question2:e=>{const{normalize:n}=e;return n(["What is the duration of the tour?"])},answer2:e=>{const{normalize:n}=e;return n(["The tour typically lasts for approximately three hours."])},question3:e=>{const{normalize:n}=e;return n(["Is lunch provided?"])},answer3:e=>{const{normalize:n}=e;return n(["Lunch is optional and can be arranged upon request."])},question4:e=>{const{normalize:n}=e;return n(["Can individuals register for the Open Day?"])},answer4:e=>{const{normalize:n}=e;return n(["Our Open Day is designed primarily for professional groups, such as politicians, NGOs, NPOs, and investors. However, we occasionally make exceptions based on the individual's profile."])},question5:e=>{const{normalize:n}=e;return n(["How many people can a group consist of for the Open Day?"])},answer5:e=>{const{normalize:n}=e;return n(["We can accommodate a variety of group sizes. Please indicate the size of your group in the registration form, and we will confirm the details with you."])},question6:e=>{const{normalize:n}=e;return n(["How can I specify areas of interest for the tour?"])},answer6:e=>{const{normalize:n}=e;return n(["There's a section in the registration form where you can specify your areas of interest or any special requests. We will do our best to tailor the tour according to your needs."])},question7:e=>{const{normalize:n}=e;return n(["Are tours available at your Beijing or Shenzhen offices?"])},answer7:e=>{const{normalize:n}=e;return n(["At this time, we only offer tours at our Berlin headquarter located in Kreuzberg. Our Beijing and Shenzhen offices are not currently open for tours."])}},header:{news:e=>{const{normalize:n}=e;return n(["News"])},open_day:e=>{const{normalize:n}=e;return n(["Open day"])},for_power_users:e=>{const{normalize:n}=e;return n(["For Power Users"])},for_power_users_description:e=>{const{normalize:n}=e;return n(["Utilize our streamlined multimodal tools to enhance your productivity."])},power_users_others:e=>{const{normalize:n}=e;return n(["More power user tools"])},for_developers:e=>{const{normalize:n}=e;return n(["For Developers"])},for_developers_description:e=>{const{normalize:n}=e;return n(["Experience a comprehensive open-source multimodal AI stack designed for developers."])},developers_others:e=>{const{normalize:n}=e;return n(["More developer tools"])},for_enterprise:e=>{const{normalize:n}=e;return n(["For Enterprises"])},for_enterprise_description:e=>{const{normalize:n}=e;return n(["Discover scalable multimodal AI strategies tailored to meet business needs."])},enterprise_others:e=>{const{normalize:n}=e;return n(["More enterprise solutions"])},internship1:e=>{const{normalize:n}=e;return n(["Intern program"])},company:e=>{const{normalize:n}=e;return n(["Company"])},about_us:e=>{const{normalize:n}=e;return n(["About us"])},contact_us:e=>{const{normalize:n}=e;return n(["Contact sales"])},jobs:e=>{const{normalize:n}=e;return n(["Join us"])},join_discord:e=>{const{normalize:n}=e;return n(["Join our Discord community"])}},footer:{power_users:e=>{const{normalize:n}=e;return n(["Power Users"])},developers:e=>{const{normalize:n}=e;return n(["Developers"])},enterprise:e=>{const{normalize:n}=e;return n(["Enterprise"])},address_beijing:e=>{const{normalize:n}=e;return n(["Beijing, China"])},address_shenzhen:e=>{const{normalize:n}=e;return n(["Shenzhen, China"])},address_berlin:e=>{const{normalize:n}=e;return n(["Berlin, Germany (HQ)"])},offices:e=>{const{normalize:n}=e;return n(["Offices"])},docs:e=>{const{normalize:n}=e;return n(["Docs"])},company:e=>{const{normalize:n}=e;return n(["Company"])},all_rights_reserved:e=>{const{normalize:n}=e;return n(["All rights reserved."])},tc:e=>{const{normalize:n}=e;return n(["Terms and Conditions"])},privacy_policy:e=>{const{normalize:n}=e;return n(["Privacy Policy"])},privacy_settings:e=>{const{normalize:n}=e;return n(["Privacy Settings"])}},prompt_perfect:{description:e=>{const{normalize:n}=e;return n(["Premier tool for prompt engineering"])},intro:e=>{const{normalize:n}=e;return n(["Premier tool for prompt engineering"])},intro1:e=>{const{normalize:n}=e;return n(["The premier tool for prompt engineering"])},original_title:e=>{const{normalize:n}=e;return n(["Original prompt"])},optimized_title:e=>{const{normalize:n}=e;return n(["Optimized prompt"])},original:e=>{const{normalize:n}=e;return n(["Your role is to be my brainstorming partner."])},optimized:e=>{const{normalize:n}=e;return n(["Your task is to be my brainstorming partner and provide creative ideas and suggestions for a given topic or problem. Your response should include original, unique, and relevant ideas that could help solve the problem or further explore the topic in an interesting way. Please note that your response should also take into account any specific requirements or constraints of the task."])},text_model:e=>{const{normalize:n}=e;return n(["Text models"])},image_model:e=>{const{normalize:n}=e;return n(["Image models"])}},jina_chat:{description:e=>{const{normalize:n}=e;return n(["More modality, longer memory, less cost"])},example_1:e=>{const{normalize:n}=e;return n(["Who are you?"])},example_2:e=>{const{normalize:n}=e;return n(["I'm a LLM chat service made by Jina AI"])}},scenex:{intro1:e=>{const{normalize:n}=e;return n(["Leading AI solution for image captions and video summaries"])},description:e=>{const{normalize:n}=e;return n(["Explore image storytelling beyond pixels"])},example1:e=>{const{normalize:n}=e;return n(["This video appears to be a nature footage featuring a charming white bunny and a butterfly in a grassy field. The bunny is seen interacting with the butterfly in different ways, showcasing their unique relationship. The natural surroundings provide a picturesque backdrop, enhancing the beauty of this simple yet captivating scene."])},caption_image_title:e=>{const{normalize:n}=e;return n(["Caption Image"])},caption_image_desc:e=>{const{normalize:n}=e;return n(["Generate a textual description of the image."])},json_image_title:e=>{const{normalize:n}=e;return n(["Extract JSON from Image"])},json_image_desc:e=>{const{normalize:n}=e;return n(["Generate a structured JSON format from the image using a predefined schema. This allows for specific data extraction from the image."])},visual_q_a_title:e=>{const{normalize:n}=e;return n(["Visual Q&A"])},visual_q_a_desc:e=>{const{normalize:n}=e;return n(["Answer a query based on the image's content."])},summarize_video_title:e=>{const{normalize:n}=e;return n(["Summarize Video"])},summarize_video_desc:e=>{const{normalize:n}=e;return n(["Generate a concise summary of the video, highlighting key events."])},generate_story_title:e=>{const{normalize:n}=e;return n(["Generate Story"])},generate_story_desc:e=>{const{normalize:n}=e;return n(["Craft a story inspired by the image, often featuring dialogues or monologues of its characters."])}},rationale:{description:e=>{const{normalize:n}=e;return n(["Ultimate AI decision-making tools"])},intro:e=>{const{normalize:n}=e;return n(["See two sides of the coin, make rational decisions"])},decision:e=>{const{normalize:n}=e;return n(["Decision"])}},best_banner:{description:e=>{const{normalize:n}=e;return n(["Blog to banner, without the prompts!"])},example_title:e=>{const{normalize:n}=e;return n(["Alice's Adventures in Wonderland - Chapter 1"])},example_description:e=>{const{normalize:n}=e;return n(["Alice was beginning to get very tired of sitting by her sister on the bank, and of having nothing to do: once or twice she had peeped into the book her sister was reading, but it had no pictures or conversations in it, \u201Cand what is the use of a book,\u201D thought Alice \u201Cwithout pictures or conversations?\u201D So she was considering in her own mind (as well as she could, for the hot day made her feel very sleepy and stupid), whether the pleasure of making a daisy-chain would be worth the trouble of getting up and picking the daisies, when suddenly a White Rabbit with pink eyes ran close by her."])}},doc_array:{description:e=>{const{normalize:n}=e;return n(["The data structure for multimodal data"])}},jina:{description:e=>{const{normalize:n}=e;return n(["Build multimodal AI applications on the cloud"])}},finetuner:{description:e=>{const{normalize:n}=e;return n(["Fine-tune embeddings on domain specific data for better search quality"])},intro:e=>{const{normalize:n}=e;return n(["On-prem embedding-tuning for your company on your data"])}},hub:{description:e=>{const{normalize:n}=e;return n(["Share and discover building blocks for multimodal AI applications"])}},clip_as_service:{description:e=>{const{normalize:n}=e;return n(["Embed images and sentences into fixed-length vectors with CLIP"])}},dalle_flow:{description:e=>{const{normalize:n}=e;return n(["A human-in-the-Loop workflow for creating HD images from text"])}},disco_art:{description:e=>{const{normalize:n}=e;return n(["Create compelling Disco Diffusion artworks in one line of code"])}},think_gpt:{description:e=>{const{normalize:n}=e;return n(["Agent techniques to augment your LLM and push it beyond its limits"])}},jcloud:{description:e=>{const{normalize:n}=e;return n(["Deploy a local project as a cloud service. Radically easy, no nasty surprises."])}},"dev-gpt":{description:e=>{const{normalize:n}=e;return n(["Your virtual development team"])}},langchain_serve:{description:e=>{const{normalize:n}=e;return n(["Langchain apps on production with Jina & FastAPI"])}},vectordb:{description:e=>{const{normalize:n}=e;return n(["A Python vector database you just need - no more, no less"])}},open_gpt:{description:e=>{const{normalize:n}=e;return n(["An open-source cloud-native of large multimodal models serving framework"])}},jerboa:{description:e=>{const{normalize:n}=e;return n(["An experimental finetuner for open-source LLMs"])}},finetuner_plus:{description:e=>{const{normalize:n}=e;return n(["Empower your enterprise with on-premise finetuning solutions"])}},inference:{description:e=>{const{normalize:n}=e;return n(["State-of-the-art multimodal models available for inference"])}},cloud:{description:e=>{const{normalize:n}=e;return n(["Cloud hosting platform for multimodal AI applications"])}},semantic:{description:e=>{const{normalize:n}=e;return n(["Bridging the semantic gap in your existing search infrastructure"])}},searchscape:{description:e=>{const{normalize:n}=e;return n(["Navigate, interact, refine: reimagine product discovery"])}},landing_page:{finding_faq:e=>{const{normalize:n}=e;return n(["Generating answer based on the FAQ knowledge below"])},embeddings:e=>{const{normalize:n}=e;return n(["Embeddings"])},new:e=>{const{normalize:n}=e;return n(["New"])},"on-premises":e=>{const{normalize:n}=e;return n(["On-premises"])},"on-prem-deploy":e=>{const{normalize:n}=e;return n(["On-premises deployment"])},also_available_on1:e=>{const{normalize:n}=e;return n(["Available on the marketplaces of your enterprise cloud"])},coming_soon:e=>{const{normalize:n}=e;return n(["Coming soon"])},try_our_saas:e=>{const{normalize:n}=e;return n(["Try our hosted solution, a drop-in replacement for OpenAI's embedding API."])},also_available_on:e=>{const{normalize:n}=e;return n(["Available on the marketplaces"])},our_publications:e=>{const{normalize:n}=e;return n(["Our Publications"])},embedding_desc:e=>{const{normalize:n}=e;return n(["The only open-source embedding model that supports 8192-token context length, putting it on par with OpenAI's proprietary Ada 22 model, in both capabilities and performance on the Massive Text Embedding Benchmark (MTEB)."])},enterprise_desc_v2:e=>{const{normalize:n}=e;return n(["Try our world-class embedding models to improve your search and RAG systems. Start with a free trial!"])},researcher_desc:e=>{const{normalize:n}=e;return n(["To understand how our large language models were trained from scratch for embedding tasks, check out our latest research and publications. Meet our team at the EMNLP, ACL, SIGIR, NeurIPS, and ICML conferences."])},include_experiment:e=>{const{normalize:n}=e;return n(["Includes our experimental and archived projects in the solution."])},your_portal_to:e=>{const{normalize:n}=e;return n(["Your Portal to"])},copy:e=>{const{normalize:n}=e;return n(["Copy"])},require_full_question:e=>{const{normalize:n}=e;return n(["Please describe your problem with more details."])},proposing_solution:e=>{const{normalize:n}=e;return n(["Proposing a solution based on Jina AI products..."])},mentioned_products:e=>{const{normalize:n}=e;return n(["Mentioned products:"])},copied_to_clipboard:e=>{const{normalize:n}=e;return n(["Copied to clipboard"])},checkout_our_solution_for_you:e=>{const{normalize:n}=e;return n(["Find out our solution tailored for you"])},ask_how_your_question:e=>{const{normalize:n}=e;return n(["Please describe your problem"])},how_to:e=>{const{normalize:n}=e;return n(["How to"])},powered_by_promptperfect:e=>{const{normalize:n}=e;return n([`Powered by PromptPerfect's "Prompt optimization" and "Prompt as a service" feature`])},error:e=>{const{normalize:n,interpolate:r,named:o}=e;return n(["There was a problem with the fetch operation: ",r(o("message"))])},find_your_portal:e=>{const{normalize:n}=e;return n(["Find Your Portal"])},opensource:e=>{const{normalize:n}=e;return n(["Open Source"])},mmstack:e=>{const{normalize:n}=e;return n(["Multimodal Stack"])},mmstack_desc:e=>{const{normalize:n}=e;return n(["The developer-friendly, cloud-native, and production-ready stack for building multimodal AI applications."])},llm:e=>{const{normalize:n}=e;return n(["LLM embedding models"])},llm_desc:e=>{const{normalize:n}=e;return n(["We provide a collection of high-performance sentence embedding models, boasting between 35 million to 6 billion parameters. They're excellent for enhancing neural search, reranking, sentence similarity, recommendations, etc. Get ready to elevate your AI experience!"])},parameters:e=>{const{normalize:n}=e;return n(["Parameters"])},download_pdf:e=>{const{normalize:n}=e;return n(["Download PDF"])},multimodal_ai:e=>{const{normalize:n}=e;return n(["Multimodal AI"])},multimodal:e=>{const{normalize:n}=e;return n(["Multimodal"])},contact_sales:e=>{const{normalize:n}=e;return n(["Contact sales"])},join_community:e=>{const{normalize:n}=e;return n(["Join community"])},trusted_by:e=>{const{normalize:n}=e;return n(["TRUSTED BY"])},newsroom:e=>{const{normalize:n}=e;return n(["Newsroom"])},read_more:e=>{const{normalize:n}=e;return n(["Read more"])},for:e=>{const{normalize:n}=e;return n(["For"])},power_users:e=>{const{normalize:n}=e;return n(["Power Users"])},researchers:e=>{const{normalize:n}=e;return n(["Researchers"])},power_users_desc:e=>{const{normalize:n}=e;return n(["Experience powerful, user-friendly multimodal AI apps. No coding, no fuss, just results."])},developers:e=>{const{normalize:n}=e;return n(["Developers"])},developers_desc:e=>{const{normalize:n}=e;return n(["Unleash the full power of multimodal AI with cutting-edge cloud-native technologies and open-source infrastructure."])},sdk:e=>{const{normalize:n}=e;return n(["SDK"])},starter_kit:e=>{const{normalize:n}=e;return n(["Starter Kit"])},sdk_desc:e=>{const{normalize:n}=e;return n(["Want to build high-level AIGC applications using PromptPerfect, SceneXplain, BestBanner, JinaChat, Rationale APIs? We've got you covered! Try our easy-to-use SDK and get started in minutes."])},sdk_docs:e=>{const{normalize:n}=e;return n(["Read docs"])},sdk_example:e=>{const{normalize:n}=e;return n(["Example"])},build_python:e=>{const{normalize:n}=e;return n(["Build with Python"])},build_js:e=>{const{normalize:n}=e;return n(["Build with JavaScript"])},enterprise:e=>{const{normalize:n}=e;return n(["Enterprise"])},enterprise_desc:e=>{const{normalize:n}=e;return n(["Boost your business with scalable, secure, and bespoke multimodal AI solutions."])},embedding_paper_title:e=>{const{normalize:n}=e;return n(["Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models"])},embedding_paper_desc:e=>{const{normalize:n}=e;return n(["Jina Embeddings constitutes a set of high-performance sentence embedding models adept at translating various textual inputs into numerical representations, thereby capturing the semantic essence of the text. While these models are not exclusively designed for text generation, they excel in applications such as dense retrieval and semantic textual similarity. This paper details the development of Jina Embeddings, starting with the creation of a high-quality pairwise and triplet dataset. It underlines the crucial role of data cleaning in dataset preparation, gives in-depth insights into the model training process, and concludes with a comprehensive performance evaluation using the Massive Textual Embedding Benchmark (MTEB)."])}},about_us_page:{employees:e=>{const{normalize:n}=e;return n(["Employees"])},approach:e=>{const{normalize:n}=e;return n(["Our Approach"])},approach_content1:e=>{const{normalize:n}=e;return n(["In the rapidly evolving world of AI, strategies need to be both nimble and forward-thinking. While our core offering remains centered on enterprises, the AI landscape has shifted in ways that necessitate a rethinking of our approach to customer acquisition. Here's why introducing power users as the entry point of our funnel isn't just innovative, but crucial for our sustained growth in the enterprise sector."])},approach_content2:e=>{const{normalize:n}=e;return n(["At Jina AI, our strategy is to be proactive rather than reactive. The inclusion of power users as the funnel's entry point ensures we're not only capturing current market trends but are also strategically poised for future enterprise growth. Our commitment to enterprises remains unwavering; however, our approach to reaching them is innovative, robust, and, above all, forward-thinking."])},approach_new_paradigm:e=>{const{normalize:n}=e;return n(["Prompt-based Technology: A New Paradigm"])},approach_miss_mark:e=>{const{normalize:n}=e;return n(["Why Traditional MLOps Miss the Mark"])},approach_connect_dots:e=>{const{normalize:n}=e;return n(["Connecting the Dots: Power Users to Enterprises"])},approach_new_paradigm_description:e=>{const{normalize:n}=e;return n([`2023 heralded a significant change: the rise of prompt-based technology. By simplifying the AI development process, it has democratized access to AI tools. Now, those without extensive programming experience\u2014termed as 'power users'\u2014can engage in AI development without the steep learning curves associated with tools like Pytorch, Docker, or Kubernetes.
 
 Drawing a parallel, this is akin to the evolution of personal computing. Initially, only tech experts operated computers. But with the advent of user-friendly interfaces, a broader audience could participate. Today, with prompt-based technology, we're witnessing a similar democratization in AI.`])},approach_miss_mark_description:e=>{const{normalize:n}=e;return n(["While the influx of power users is significant, traditional MLOps tools are ill-equipped to cater to their needs. These tools are reminiscent of using a tractor to navigate city streets\u2014they're heavy and often excessive. The new-gen developers demand agile, intuitive tools that complement their rapid development pace."])},approach_connect_dots_description:e=>{const{normalize:n}=e;return n(["So, why is a power user focus essential for our enterprise-centric model? Because it\u2019s about establishing early relationships. By catering to power users now, we're building bridges to the enterprises they'll influence in the future. It\u2019s a strategic play\u2014a long-term investment to ensure our enterprise offering remains top-of-mind when these power users ascend to decision-making roles within organizations."])},title:e=>{const{normalize:n}=e;return n(["About Jina AI"])},title0:e=>{const{normalize:n}=e;return n(["The Future"])},title1:e=>{const{normalize:n}=e;return n(["Starts"])},title2:e=>{const{normalize:n}=e;return n(["Here"])},description:e=>{const{normalize:n}=e;return n(["The future starts here."])},subtitle:e=>{const{normalize:n}=e;return n(["Revolutionizing content creation through AI-generated solutions to unlock infinite possibilities. Shaping the future of AI-generated content and enhancing human creativity."])},stats:e=>{const{normalize:n}=e;return n(["Pioneering the Future of Multimodal AI"])},founded:e=>{const{normalize:n}=e;return n(["Founded"])},founded_in:e=>{const{normalize:n}=e;return n(["Founded in"])},empower_developers:e=>{const{normalize:n}=e;return n(["Developers Empowered"])},technologies:e=>{const{normalize:n}=e;return n(["Technologies"])},users:e=>{const{normalize:n}=e;return n(["Users Registered"])},value:e=>{const{normalize:n}=e;return n(["Our Value"])},value_content:e=>{const{normalize:n}=e;return n([`At Jina AI, we believe in the power of open-source technology to accelerate innovation, foster collaboration, and empower communities. We're not just advocates - we are active contributors, investing significantly in the open-source community.
 
diff --git a/assets/index.2b6e3ac7.js b/assets/index.ae19b4cb.js
similarity index 97%
rename from assets/index.2b6e3ac7.js
rename to assets/index.ae19b4cb.js
index c0ce31d9d58..68668f8a3e6 100644
--- a/assets/index.2b6e3ac7.js
+++ b/assets/index.ae19b4cb.js
@@ -142,4 +142,4 @@ const generate = async () => {
 generate();
 
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diff --git a/assets/position-engine.7fb36afb.js b/assets/position-engine.2f7193db.js
similarity index 98%
rename from assets/position-engine.7fb36afb.js
rename to assets/position-engine.2f7193db.js
index 56b037cb73f..0d5cf2a9da3 100644
--- a/assets/position-engine.7fb36afb.js
+++ b/assets/position-engine.2f7193db.js
@@ -1 +1 @@
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0&&(m.maxWidth=h.maxWidth+"px",r.width>h.maxWidth&&(m.minWidth=m.maxWidth)),Object.assign(i.style,m),i.scrollTop!==n&&(i.scrollTop=n),i.scrollLeft!==p&&(i.scrollLeft=p)}function C(t,l,i,e,a){const s=i.bottom,o=i.right,c=J(),d=window.innerHeight-c,u=document.body.clientWidth;if(t.top<0||t.top+s>d)if(a.vertical==="center")t.top=l[e.vertical]>d/2?Math.max(0,d-s):0,t.maxHeight=Math.min(s,d);else if(l[e.vertical]>d/2){const f=Math.min(d,e.vertical==="center"?l.center:e.vertical===a.vertical?l.bottom:l.top);t.maxHeight=Math.min(s,f),t.top=Math.max(0,f-s)}else t.top=Math.max(0,e.vertical==="center"?l.center:e.vertical===a.vertical?l.top:l.bottom),t.maxHeight=Math.min(s,d-t.top);if(t.left<0||t.left+o>u)if(t.maxWidth=Math.min(o,u),a.horizontal==="middle")t.left=l[e.horizontal]>u/2?Math.max(0,u-o):0;else if(l[e.horizontal]>u/2){const f=Math.min(u,e.horizontal==="middle"?l.middle:e.horizontal===a.horizontal?l.right:l.left);t.maxWidth=Math.min(o,f),t.left=Math.max(0,f-t.maxWidth)}else 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diff --git a/assets/prism.7035d23b.js b/assets/prism.4adcbfb5.js
similarity index 85%
rename from assets/prism.7035d23b.js
rename to assets/prism.4adcbfb5.js
index 371b6b3053d..d54f0b98907 100644
--- a/assets/prism.7035d23b.js
+++ b/assets/prism.4adcbfb5.js
@@ -1 +1 @@
-import{b as t,_}from"./index.2b6e3ac7.js";var a=t(async()=>{await _(()=>import("./prism-bash.f7256737.js"),[]),await _(()=>import("./prism-python.97b4fd77.js"),[]),await _(()=>import("./prism-csharp.609116a7.js"),[]),await _(()=>import("./prism-ruby.d01b091c.js"),[]),await _(()=>import("./prism-rust.565b489f.js"),[]),await _(()=>import("./prism-java.45134ac5.js"),[]),await _(()=>import("./prism-go.62561c56.js"),[])});export{a as default};
+import{b as t,_}from"./index.ae19b4cb.js";var a=t(async()=>{await _(()=>import("./prism-bash.f7256737.js"),[]),await _(()=>import("./prism-python.97b4fd77.js"),[]),await _(()=>import("./prism-csharp.609116a7.js"),[]),await _(()=>import("./prism-ruby.d01b091c.js"),[]),await _(()=>import("./prism-rust.565b489f.js"),[]),await _(()=>import("./prism-java.45134ac5.js"),[]),await _(()=>import("./prism-go.62561c56.js"),[])});export{a as default};
diff --git a/assets/quasar-lang-pack.f7786d22.js b/assets/quasar-lang-pack.223b3de1.js
similarity index 95%
rename from assets/quasar-lang-pack.f7786d22.js
rename to assets/quasar-lang-pack.223b3de1.js
index b3c5c4ea657..15728dbff4b 100644
--- a/assets/quasar-lang-pack.f7786d22.js
+++ b/assets/quasar-lang-pack.223b3de1.js
@@ -1 +1 @@
-import{b as m,Q as a,_}from"./index.2b6e3ac7.js";const o={"../../node_modules/quasar/lang/ar-TN.mjs":()=>_(()=>import("./ar-TN.da1c2ae9.js"),[]),"../../node_modules/quasar/lang/ar.mjs":()=>_(()=>import("./ar.4424b2ca.js"),[]),"../../node_modules/quasar/lang/az-Latn.mjs":()=>_(()=>import("./az-Latn.76e916af.js"),[]),"../../node_modules/quasar/lang/bg.mjs":()=>_(()=>import("./bg.34308bda.js"),[]),"../../node_modules/quasar/lang/bn.mjs":()=>_(()=>import("./bn.0dc88bb7.js"),[]),"../../node_modules/quasar/lang/ca.mjs":()=>_(()=>import("./ca.e544b008.js"),[]),"../../node_modules/quasar/lang/cs.mjs":()=>_(()=>import("./cs.b2a4ae35.js"),[]),"../../node_modules/quasar/lang/da.mjs":()=>_(()=>import("./da.3285a81d.js"),[]),"../../node_modules/quasar/lang/de-CH.mjs":()=>_(()=>import("./de-CH.f7dd13ff.js"),[]),"../../node_modules/quasar/lang/de-DE.mjs":()=>_(()=>import("./de-DE.462aa26f.js"),[]),"../../node_modules/quasar/lang/de.mjs":()=>_(()=>import("./de.70e8e1d6.js"),[]),"../../node_modules/quasar/lang/el.mjs":()=>_(()=>import("./el.e6abd5bb.js"),[]),"../../node_modules/quasar/lang/en-GB.mjs":()=>_(()=>import("./en-GB.53603fc5.js"),[]),"../../node_modules/quasar/lang/en-US.mjs":()=>_(()=>import("./index.2b6e3ac7.js").then(function(r){return r.c7}),["assets/index.2b6e3ac7.js","assets/index.9fe6336f.css"]),"../../node_modules/quasar/lang/eo.mjs":()=>_(()=>import("./eo.dbb48655.js"),[]),"../../node_modules/quasar/lang/es.mjs":()=>_(()=>import("./es.49f2e1b3.js"),[]),"../../node_modules/quasar/lang/et.mjs":()=>_(()=>import("./et.a8730c6b.js"),[]),"../../node_modules/quasar/lang/eu.mjs":()=>_(()=>import("./eu.7d38efce.js"),[]),"../../node_modules/quasar/lang/fa-IR.mjs":()=>_(()=>import("./fa-IR.cd71a812.js"),[]),"../../node_modules/quasar/lang/fa.mjs":()=>_(()=>import("./fa.1c4f124f.js"),[]),"../../node_modules/quasar/lang/fi.mjs":()=>_(()=>import("./fi.efe68fec.js"),[]),"../../node_modules/quasar/lang/fr.mjs":()=>_(()=>import("./fr.a4be8ef1.js"),[]),"../../node_modules/quasar/lang/gn.mjs":()=>_(()=>import("./gn.a2c26bf8.js"),[]),"../../node_modules/quasar/lang/he.mjs":()=>_(()=>import("./he.ec08790e.js"),[]),"../../node_modules/quasar/lang/hi.mjs":()=>_(()=>import("./hi.113132da.js"),[]),"../../node_modules/quasar/lang/hr.mjs":()=>_(()=>import("./hr.85daf05b.js"),[]),"../../node_modules/quasar/lang/hu.mjs":()=>_(()=>import("./hu.003b71b2.js"),[]),"../../node_modules/quasar/lang/id.mjs":()=>_(()=>import("./id.e067b78c.js"),[]),"../../node_modules/quasar/lang/is.mjs":()=>_(()=>import("./is.8f591d92.js"),[]),"../../node_modules/quasar/lang/it.mjs":()=>_(()=>import("./it.8a166729.js"),[]),"../../node_modules/quasar/lang/ja.mjs":()=>_(()=>import("./ja.a95d536a.js"),[]),"../../node_modules/quasar/lang/kk.mjs":()=>_(()=>import("./kk.2764dcd9.js"),[]),"../../node_modules/quasar/lang/km.mjs":()=>_(()=>import("./km.3b96b328.js"),[]),"../../node_modules/quasar/lang/ko-KR.mjs":()=>_(()=>import("./ko-KR.073a03c6.js"),[]),"../../node_modules/quasar/lang/kur-CKB.mjs":()=>_(()=>import("./kur-CKB.41ee161f.js"),[]),"../../node_modules/quasar/lang/lt.mjs":()=>_(()=>import("./lt.dbd27467.js"),[]),"../../node_modules/quasar/lang/lu.mjs":()=>_(()=>import("./lu.86586a88.js"),[]),"../../node_modules/quasar/lang/lv.mjs":()=>_(()=>import("./lv.9d077723.js"),[]),"../../node_modules/quasar/lang/mk.mjs":()=>_(()=>import("./mk.9f534988.js"),[]),"../../node_modules/quasar/lang/ml.mjs":()=>_(()=>import("./ml.e618c433.js"),[]),"../../node_modules/quasar/lang/mm.mjs":()=>_(()=>import("./mm.9fb291cc.js"),[]),"../../node_modules/quasar/lang/ms.mjs":()=>_(()=>import("./ms.207a15ad.js"),[]),"../../node_modules/quasar/lang/my.mjs":()=>_(()=>import("./my.0ad1b622.js"),[]),"../../node_modules/quasar/lang/nb-NO.mjs":()=>_(()=>import("./nb-NO.0e72dba2.js"),[]),"../../node_modules/quasar/lang/nl.mjs":()=>_(()=>import("./nl.93314d9a.js"),[]),"../../node_modules/quasar/lang/pl.mjs":()=>_(()=>import("./pl.ce3cad59.js"),[]),"../../node_modules/quasar/lang/pt-BR.mjs":()=>_(()=>import("./pt-BR.694fe516.js"),[]),"../../node_modules/quasar/lang/pt.mjs":()=>_(()=>import("./pt.d2dd73a5.js"),[]),"../../node_modules/quasar/lang/ro.mjs":()=>_(()=>import("./ro.4216b410.js"),[]),"../../node_modules/quasar/lang/ru.mjs":()=>_(()=>import("./ru.f960bf45.js"),[]),"../../node_modules/quasar/lang/sk.mjs":()=>_(()=>import("./sk.6b4495ea.js"),[]),"../../node_modules/quasar/lang/sl.mjs":()=>_(()=>import("./sl.6365d64c.js"),[]),"../../node_modules/quasar/lang/sm.mjs":()=>_(()=>import("./sm.0aac1705.js"),[]),"../../node_modules/quasar/lang/sr-CYR.mjs":()=>_(()=>import("./sr-CYR.47d2a59a.js"),[]),"../../node_modules/quasar/lang/sr.mjs":()=>_(()=>import("./sr.bc648137.js"),[]),"../../node_modules/quasar/lang/sv.mjs":()=>_(()=>import("./sv.4a40c1a2.js"),[]),"../../node_modules/quasar/lang/ta.mjs":()=>_(()=>import("./ta.1c8cf5a1.js"),[]),"../../node_modules/quasar/lang/th.mjs":()=>_(()=>import("./th.05577c5f.js"),[]),"../../node_modules/quasar/lang/tr.mjs":()=>_(()=>import("./tr.e317d4ca.js"),[]),"../../node_modules/quasar/lang/ug.mjs":()=>_(()=>import("./ug.9694c105.js"),[]),"../../node_modules/quasar/lang/uk.mjs":()=>_(()=>import("./uk.b80d3112.js"),[]),"../../node_modules/quasar/lang/uz-Cyrl.mjs":()=>_(()=>import("./uz-Cyrl.945aa89e.js"),[]),"../../node_modules/quasar/lang/uz-Latn.mjs":()=>_(()=>import("./uz-Latn.c988920c.js"),[]),"../../node_modules/quasar/lang/vi.mjs":()=>_(()=>import("./vi.69524d61.js"),[]),"../../node_modules/quasar/lang/zh-CN.mjs":()=>_(()=>import("./zh-CN.868d3f1f.js"),[]),"../../node_modules/quasar/lang/zh-TW.mjs":()=>_(()=>import("./zh-TW.bbb73372.js"),[])};var t=m(async()=>{const r="en-US";try{o[`../../node_modules/quasar/lang/${r}.mjs`]().then(s=>{a.lang.set(s.default)})}catch{}});export{t as default};
+import{b as m,Q as a,_}from"./index.ae19b4cb.js";const o={"../../node_modules/quasar/lang/ar-TN.mjs":()=>_(()=>import("./ar-TN.da1c2ae9.js"),[]),"../../node_modules/quasar/lang/ar.mjs":()=>_(()=>import("./ar.4424b2ca.js"),[]),"../../node_modules/quasar/lang/az-Latn.mjs":()=>_(()=>import("./az-Latn.76e916af.js"),[]),"../../node_modules/quasar/lang/bg.mjs":()=>_(()=>import("./bg.34308bda.js"),[]),"../../node_modules/quasar/lang/bn.mjs":()=>_(()=>import("./bn.0dc88bb7.js"),[]),"../../node_modules/quasar/lang/ca.mjs":()=>_(()=>import("./ca.e544b008.js"),[]),"../../node_modules/quasar/lang/cs.mjs":()=>_(()=>import("./cs.b2a4ae35.js"),[]),"../../node_modules/quasar/lang/da.mjs":()=>_(()=>import("./da.3285a81d.js"),[]),"../../node_modules/quasar/lang/de-CH.mjs":()=>_(()=>import("./de-CH.f7dd13ff.js"),[]),"../../node_modules/quasar/lang/de-DE.mjs":()=>_(()=>import("./de-DE.462aa26f.js"),[]),"../../node_modules/quasar/lang/de.mjs":()=>_(()=>import("./de.70e8e1d6.js"),[]),"../../node_modules/quasar/lang/el.mjs":()=>_(()=>import("./el.e6abd5bb.js"),[]),"../../node_modules/quasar/lang/en-GB.mjs":()=>_(()=>import("./en-GB.53603fc5.js"),[]),"../../node_modules/quasar/lang/en-US.mjs":()=>_(()=>import("./index.ae19b4cb.js").then(function(r){return r.c7}),["assets/index.ae19b4cb.js","assets/index.9fe6336f.css"]),"../../node_modules/quasar/lang/eo.mjs":()=>_(()=>import("./eo.dbb48655.js"),[]),"../../node_modules/quasar/lang/es.mjs":()=>_(()=>import("./es.49f2e1b3.js"),[]),"../../node_modules/quasar/lang/et.mjs":()=>_(()=>import("./et.a8730c6b.js"),[]),"../../node_modules/quasar/lang/eu.mjs":()=>_(()=>import("./eu.7d38efce.js"),[]),"../../node_modules/quasar/lang/fa-IR.mjs":()=>_(()=>import("./fa-IR.cd71a812.js"),[]),"../../node_modules/quasar/lang/fa.mjs":()=>_(()=>import("./fa.1c4f124f.js"),[]),"../../node_modules/quasar/lang/fi.mjs":()=>_(()=>import("./fi.efe68fec.js"),[]),"../../node_modules/quasar/lang/fr.mjs":()=>_(()=>import("./fr.a4be8ef1.js"),[]),"../../node_modules/quasar/lang/gn.mjs":()=>_(()=>import("./gn.a2c26bf8.js"),[]),"../../node_modules/quasar/lang/he.mjs":()=>_(()=>import("./he.ec08790e.js"),[]),"../../node_modules/quasar/lang/hi.mjs":()=>_(()=>import("./hi.113132da.js"),[]),"../../node_modules/quasar/lang/hr.mjs":()=>_(()=>import("./hr.85daf05b.js"),[]),"../../node_modules/quasar/lang/hu.mjs":()=>_(()=>import("./hu.003b71b2.js"),[]),"../../node_modules/quasar/lang/id.mjs":()=>_(()=>import("./id.e067b78c.js"),[]),"../../node_modules/quasar/lang/is.mjs":()=>_(()=>import("./is.8f591d92.js"),[]),"../../node_modules/quasar/lang/it.mjs":()=>_(()=>import("./it.8a166729.js"),[]),"../../node_modules/quasar/lang/ja.mjs":()=>_(()=>import("./ja.a95d536a.js"),[]),"../../node_modules/quasar/lang/kk.mjs":()=>_(()=>import("./kk.2764dcd9.js"),[]),"../../node_modules/quasar/lang/km.mjs":()=>_(()=>import("./km.3b96b328.js"),[]),"../../node_modules/quasar/lang/ko-KR.mjs":()=>_(()=>import("./ko-KR.073a03c6.js"),[]),"../../node_modules/quasar/lang/kur-CKB.mjs":()=>_(()=>import("./kur-CKB.41ee161f.js"),[]),"../../node_modules/quasar/lang/lt.mjs":()=>_(()=>import("./lt.dbd27467.js"),[]),"../../node_modules/quasar/lang/lu.mjs":()=>_(()=>import("./lu.86586a88.js"),[]),"../../node_modules/quasar/lang/lv.mjs":()=>_(()=>import("./lv.9d077723.js"),[]),"../../node_modules/quasar/lang/mk.mjs":()=>_(()=>import("./mk.9f534988.js"),[]),"../../node_modules/quasar/lang/ml.mjs":()=>_(()=>import("./ml.e618c433.js"),[]),"../../node_modules/quasar/lang/mm.mjs":()=>_(()=>import("./mm.9fb291cc.js"),[]),"../../node_modules/quasar/lang/ms.mjs":()=>_(()=>import("./ms.207a15ad.js"),[]),"../../node_modules/quasar/lang/my.mjs":()=>_(()=>import("./my.0ad1b622.js"),[]),"../../node_modules/quasar/lang/nb-NO.mjs":()=>_(()=>import("./nb-NO.0e72dba2.js"),[]),"../../node_modules/quasar/lang/nl.mjs":()=>_(()=>import("./nl.93314d9a.js"),[]),"../../node_modules/quasar/lang/pl.mjs":()=>_(()=>import("./pl.ce3cad59.js"),[]),"../../node_modules/quasar/lang/pt-BR.mjs":()=>_(()=>import("./pt-BR.694fe516.js"),[]),"../../node_modules/quasar/lang/pt.mjs":()=>_(()=>import("./pt.d2dd73a5.js"),[]),"../../node_modules/quasar/lang/ro.mjs":()=>_(()=>import("./ro.4216b410.js"),[]),"../../node_modules/quasar/lang/ru.mjs":()=>_(()=>import("./ru.f960bf45.js"),[]),"../../node_modules/quasar/lang/sk.mjs":()=>_(()=>import("./sk.6b4495ea.js"),[]),"../../node_modules/quasar/lang/sl.mjs":()=>_(()=>import("./sl.6365d64c.js"),[]),"../../node_modules/quasar/lang/sm.mjs":()=>_(()=>import("./sm.0aac1705.js"),[]),"../../node_modules/quasar/lang/sr-CYR.mjs":()=>_(()=>import("./sr-CYR.47d2a59a.js"),[]),"../../node_modules/quasar/lang/sr.mjs":()=>_(()=>import("./sr.bc648137.js"),[]),"../../node_modules/quasar/lang/sv.mjs":()=>_(()=>import("./sv.4a40c1a2.js"),[]),"../../node_modules/quasar/lang/ta.mjs":()=>_(()=>import("./ta.1c8cf5a1.js"),[]),"../../node_modules/quasar/lang/th.mjs":()=>_(()=>import("./th.05577c5f.js"),[]),"../../node_modules/quasar/lang/tr.mjs":()=>_(()=>import("./tr.e317d4ca.js"),[]),"../../node_modules/quasar/lang/ug.mjs":()=>_(()=>import("./ug.9694c105.js"),[]),"../../node_modules/quasar/lang/uk.mjs":()=>_(()=>import("./uk.b80d3112.js"),[]),"../../node_modules/quasar/lang/uz-Cyrl.mjs":()=>_(()=>import("./uz-Cyrl.945aa89e.js"),[]),"../../node_modules/quasar/lang/uz-Latn.mjs":()=>_(()=>import("./uz-Latn.c988920c.js"),[]),"../../node_modules/quasar/lang/vi.mjs":()=>_(()=>import("./vi.69524d61.js"),[]),"../../node_modules/quasar/lang/zh-CN.mjs":()=>_(()=>import("./zh-CN.868d3f1f.js"),[]),"../../node_modules/quasar/lang/zh-TW.mjs":()=>_(()=>import("./zh-TW.bbb73372.js"),[])};var t=m(async()=>{const r="en-US";try{o[`../../node_modules/quasar/lang/${r}.mjs`]().then(s=>{a.lang.set(s.default)})}catch{}});export{t as default};
diff --git a/assets/register.a0e90567.js b/assets/register.7136f5fa.js
similarity index 99%
rename from assets/register.a0e90567.js
rename to assets/register.7136f5fa.js
index 320cb3412ea..50e16d3e3bc 100644
--- a/assets/register.a0e90567.js
+++ b/assets/register.7136f5fa.js
@@ -1,4 +1,4 @@
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9",YR="\xF9",WR="\u2963",JR="\u21BF",QR="\u21BE",KR="\u2580",XR="\u231C",nL="\u231C",rL="\u230F",eL="\u25F8",tL="\u016A",oL="\u016B",sL="\xA8",cL="_",iL="\u23DF",aL="\u23B5",lL="\u23DD",uL="\u22C3",fL="\u228E",pL="\u0172",hL="\u0173",dL="\u{1D54C}",gL="\u{1D566}",mL="\u2912",vL="\u2191",bL="\u2191",xL="\u21D1",kL="\u21C5",_L="\u2195",wL="\u2195",yL="\u21D5",AL="\u296E",EL="\u21BF",CL="\u21BE",SL="\u228E",DL="\u2196",qL="\u2197",FL="\u03C5",TL="\u03D2",IL="\u03D2",BL="\u03A5",RL="\u03C5",LL="\u21A5",PL="\u22A5",ML="\u21C8",UL="\u231D",zL="\u231D",NL="\u230E",OL="\u016E",$L="\u016F",VL="\u25F9",HL="\u{1D4B0}",GL="\u{1D4CA}",jL="\u22F0",ZL="\u0168",YL="\u0169",WL="\u25B5",JL="\u25B4",QL="\u21C8",KL="\xDC",XL="\xFC",n3="\u29A7",r3="\u299C",e3="\u03F5",t3="\u03F0",o3="\u2205",s3="\u03D5",c3="\u03D6",i3="\u221D",a3="\u2195",l3="\u21D5",u3="\u03F1",f3="\u03C2",p3="\u228A\uFE00",h3="\u2ACB\uFE00",d3="\u228B\uFE00",g3="\u2ACC\uFE00",m3="\u03D1",v3="\u22B2",b3="\u22B3",x3="\u2AE8",k3="\u2AEB",_3="\u2AE9",w3="\u0412",y3="\u0432",A3="\u22A2",E3="\u22A8",C3="\u22A9",S3="\u22AB",D3="\u2AE6",q3="\u22BB",F3="\u2228",T3="\u22C1",I3="\u225A",B3="\u22EE",R3="|",L3="\u2016",P3="|",M3="\u2016",U3="\u2223",z3="|",N3="\u2758",O3="\u2240",$3="\u200A",V3="\u{1D519}",H3="\u{1D533}",G3="\u22B2",j3="\u2282\u20D2",Z3="\u2283\u20D2",Y3="\u{1D54D}",W3="\u{1D567}",J3="\u221D",Q3="\u22B3",K3="\u{1D4B1}",X3="\u{1D4CB}",nP="\u2ACB\uFE00",rP="\u228A\uFE00",eP="\u2ACC\uFE00",tP="\u228B\uFE00",oP="\u22AA",sP="\u299A",cP="\u0174",iP="\u0175",aP="\u2A5F",lP="\u2227",uP="\u22C0",fP="\u2259",pP="\u2118",hP="\u{1D51A}",dP="\u{1D534}",gP="\u{1D54E}",mP="\u{1D568}",vP="\u2118",bP="\u2240",xP="\u2240",kP="\u{1D4B2}",_P="\u{1D4CC}",wP="\u22C2",yP="\u25EF",AP="\u22C3",EP="\u25BD",CP="\u{1D51B}",SP="\u{1D535}",DP="\u27F7",qP="\u27FA",FP="\u039E",TP="\u03BE",IP="\u27F5",BP="\u27F8",RP="\u27FC",LP="\u22FB",PP="\u2A00",MP="\u{1D54F}",UP="\u{1D569}",zP="\u2A01",NP="\u2A02",OP="\u27F6",$P="\u27F9",VP="\u{1D4B3}",HP="\u{1D4CD}",GP="\u2A06",jP="\u2A04",ZP="\u25B3",YP="\u22C1",WP="\u22C0",JP="\xDD",QP="\xFD",KP="\u042F",XP="\u044F",nM="\u0176",rM="\u0177",eM="\u042B",tM="\u044B",oM="\xA5",sM="\u{1D51C}",cM="\u{1D536}",iM="\u0407",aM="\u0457",lM="\u{1D550}",uM="\u{1D56A}",fM="\u{1D4B4}",pM="\u{1D4CE}",hM="\u042E",dM="\u044E",gM="\xFF",mM="\u0178",vM="\u0179",bM="\u017A",xM="\u017D",kM="\u017E",_M="\u0417",wM="\u0437",yM="\u017B",AM="\u017C",EM="\u2128",CM="\u200B",SM="\u0396",DM="\u03B6",qM="\u{1D537}",FM="\u2128",TM="\u0416",IM="\u0436",BM="\u21DD",RM="\u{1D56B}",LM="\u2124",PM="\u{1D4B5}",MM="\u{1D4CF}",UM="\u200D",zM="\u200C";var NM={Aacute:_e,aacute:we,Abreve:ye,abreve:Ae,ac:Ee,acd:Ce,acE:Se,Acirc:De,acirc:qe,acute:Fe,Acy:Te,acy:Ie,AElig:Be,aelig:Re,af:Le,Afr:Pe,afr:Me,Agrave:Ue,agrave:ze,alefsym:Ne,aleph:Oe,Alpha:$e,alpha:Ve,Amacr:He,amacr:Ge,amalg:je,amp:Ze,AMP:Ye,andand:We,And:Je,and:Qe,andd:Ke,andslope:Xe,andv:nt,ang:rt,ange:et,angle:tt,angmsdaa:ot,angmsdab:st,angmsdac:ct,angmsdad:it,angmsdae:at,angmsdaf:lt,angmsdag:ut,angmsdah:ft,angmsd:pt,angrt:ht,angrtvb:dt,angrtvbd:gt,angsph:mt,angst:vt,angzarr:bt,Aogon:xt,aogon:kt,Aopf:_t,aopf:wt,apacir:yt,ap:At,apE:Et,ape:Ct,apid:St,apos:Dt,ApplyFunction:qt,approx:Ft,approxeq:Tt,Aring:It,aring:Bt,Ascr:Rt,ascr:Lt,Assign:Pt,ast:Mt,asymp:Ut,asympeq:zt,Atilde:Nt,atilde:Ot,Auml:$t,auml:Vt,awconint:Ht,awint:Gt,backcong:jt,backepsilon:Zt,backprime:Yt,backsim:Wt,backsimeq:Jt,Backslash:Qt,Barv:Kt,barvee:Xt,barwed:no,Barwed:ro,barwedge:eo,bbrk:to,bbrktbrk:oo,bcong:so,Bcy:co,bcy:io,bdquo:ao,becaus:lo,because:uo,Because:fo,bemptyv:po,bepsi:ho,bernou:go,Bernoullis:mo,Beta:vo,beta:bo,beth:xo,between:ko,Bfr:_o,bfr:wo,bigcap:yo,bigcirc:Ao,bigcup:Eo,bigodot:Co,bigoplus:So,bigotimes:Do,bigsqcup:qo,bigstar:Fo,bigtriangledown:To,bigtriangleup:Io,biguplus:Bo,bigvee:Ro,bigwedge:Lo,bkarow:Po,blacklozenge:Mo,blacksquare:Uo,blacktriangle:zo,blacktriangledown:No,blacktriangleleft:Oo,blacktriangleright:$o,blank:Vo,blk12:Ho,blk14:Go,blk34:jo,block:Zo,bne:Yo,bnequiv:Wo,bNot:Jo,bnot:Qo,Bopf:Ko,bopf:Xo,bot:ns,bottom:rs,bowtie:es,boxbox:ts,boxdl:os,boxdL:ss,boxDl:cs,boxDL:is,boxdr:as,boxdR:ls,boxDr:us,boxDR:fs,boxh:ps,boxH:hs,boxhd:ds,boxHd:gs,boxhD:ms,boxHD:vs,boxhu:bs,boxHu:xs,boxhU:ks,boxHU:_s,boxminus:ws,boxplus:ys,boxtimes:As,boxul:Es,boxuL:Cs,boxUl:Ss,boxUL:Ds,boxur:qs,boxuR:Fs,boxUr:Ts,boxUR:Is,boxv:Bs,boxV:Rs,boxvh:Ls,boxvH:Ps,boxVh:Ms,boxVH:Us,boxvl:zs,boxvL:Ns,boxVl:Os,boxVL:$s,boxvr:Vs,boxvR:Hs,boxVr:Gs,boxVR:js,bprime:Zs,breve:Ys,Breve:Ws,brvbar:Js,bscr:Qs,Bscr:Ks,bsemi:Xs,bsim:nc,bsime:rc,bsolb:ec,bsol:tc,bsolhsub:oc,bull:sc,bullet:cc,bump:ic,bumpE:ac,bumpe:lc,Bumpeq:uc,bumpeq:fc,Cacute:pc,cacute:hc,capand:dc,capbrcup:gc,capcap:mc,cap:vc,Cap:bc,capcup:xc,capdot:kc,CapitalDifferentialD:_c,caps:wc,caret:yc,caron:Ac,Cayleys:Ec,ccaps:Cc,Ccaron:Sc,ccaron:Dc,Ccedil:qc,ccedil:Fc,Ccirc:Tc,ccirc:Ic,Cconint:Bc,ccups:Rc,ccupssm:Lc,Cdot:Pc,cdot:Mc,cedil:Uc,Cedilla:zc,cemptyv:Nc,cent:Oc,centerdot:$c,CenterDot:Vc,cfr:Hc,Cfr:Gc,CHcy:jc,chcy:Zc,check:Yc,checkmark:Wc,Chi:Jc,chi:Qc,circ:Kc,circeq:Xc,circlearrowleft:ni,circlearrowright:ri,circledast:ei,circledcirc:ti,circleddash:oi,CircleDot:si,circledR:ci,circledS:ii,CircleMinus:ai,CirclePlus:li,CircleTimes:ui,cir:fi,cirE:pi,cire:hi,cirfnint:di,cirmid:gi,cirscir:mi,ClockwiseContourIntegral:vi,CloseCurlyDoubleQuote:bi,CloseCurlyQuote:xi,clubs:ki,clubsuit:_i,colon:wi,Colon:yi,Colone:Ai,colone:Ei,coloneq:Ci,comma:Si,commat:Di,comp:qi,compfn:Fi,complement:Ti,complexes:Ii,cong:Bi,congdot:Ri,Congruent:Li,conint:Pi,Conint:Mi,ContourIntegral:Ui,copf:zi,Copf:Ni,coprod:Oi,Coproduct:$i,copy:Vi,COPY:Hi,copysr:Gi,CounterClockwiseContourIntegral:ji,crarr:Zi,cross:Yi,Cross:Wi,Cscr:Ji,cscr:Qi,csub:Ki,csube:Xi,csup:na,csupe:ra,ctdot:ea,cudarrl:ta,cudarrr:oa,cuepr:sa,cuesc:ca,cularr:ia,cularrp:aa,cupbrcap:la,cupcap:ua,CupCap:fa,cup:pa,Cup:ha,cupcup:da,cupdot:ga,cupor:ma,cups:va,curarr:ba,curarrm:xa,curlyeqprec:ka,curlyeqsucc:_a,curlyvee:wa,curlywedge:ya,curren:Aa,curvearrowleft:Ea,curvearrowright:Ca,cuvee:Sa,cuwed:Da,cwconint:qa,cwint:Fa,cylcty:Ta,dagger:Ia,Dagger:Ba,daleth:Ra,darr:La,Darr:Pa,dArr:Ma,dash:Ua,Dashv:za,dashv:Na,dbkarow:Oa,dblac:$a,Dcaron:Va,dcaron:Ha,Dcy:Ga,dcy:ja,ddagger:Za,ddarr:Ya,DD:Wa,dd:Ja,DDotrahd:Qa,ddotseq:Ka,deg:Xa,Del:nl,Delta:rl,delta:el,demptyv:tl,dfisht:ol,Dfr:sl,dfr:cl,dHar:il,dharl:al,dharr:ll,DiacriticalAcute:ul,DiacriticalDot:fl,DiacriticalDoubleAcute:pl,DiacriticalGrave:hl,DiacriticalTilde:dl,diam:gl,diamond:ml,Diamond:vl,diamondsuit:bl,diams:xl,die:kl,DifferentialD:_l,digamma:wl,disin:yl,div:Al,divide:El,divideontimes:Cl,divonx:Sl,DJcy:Dl,djcy:ql,dlcorn:Fl,dlcrop:Tl,dollar:Il,Dopf:Bl,dopf:Rl,Dot:Ll,dot:Pl,DotDot:Ml,doteq:Ul,doteqdot:zl,DotEqual:Nl,dotminus:Ol,dotplus:$l,dotsquare:Vl,doublebarwedge:Hl,DoubleContourIntegral:Gl,DoubleDot:jl,DoubleDownArrow:Zl,DoubleLeftArrow:Yl,DoubleLeftRightArrow:Wl,DoubleLeftTee:Jl,DoubleLongLeftArrow:Ql,DoubleLongLeftRightArrow:Kl,DoubleLongRightArrow:Xl,DoubleRightArrow:nu,DoubleRightTee:ru,DoubleUpArrow:eu,DoubleUpDownArrow:tu,DoubleVerticalBar:ou,DownArrowBar:su,downarrow:cu,DownArrow:iu,Downarrow:au,DownArrowUpArrow:lu,DownBreve:uu,downdownarrows:fu,downharpoonleft:pu,downharpoonright:hu,DownLeftRightVector:du,DownLeftTeeVector:gu,DownLeftVectorBar:mu,DownLeftVector:vu,DownRightTeeVector:bu,DownRightVectorBar:xu,DownRightVector:ku,DownTeeArrow:_u,DownTee:wu,drbkarow:yu,drcorn:Au,drcrop:Eu,Dscr:Cu,dscr:Su,DScy:Du,dscy:qu,dsol:Fu,Dstrok:Tu,dstrok:Iu,dtdot:Bu,dtri:Ru,dtrif:Lu,duarr:Pu,duhar:Mu,dwangle:Uu,DZcy:zu,dzcy:Nu,dzigrarr:Ou,Eacute:$u,eacute:Vu,easter:Hu,Ecaron:Gu,ecaron:ju,Ecirc:Zu,ecirc:Yu,ecir:Wu,ecolon:Ju,Ecy:Qu,ecy:Ku,eDDot:Xu,Edot:nf,edot:rf,eDot:ef,ee:tf,efDot:of,Efr:sf,efr:cf,eg:af,Egrave:lf,egrave:uf,egs:ff,egsdot:pf,el:hf,Element:df,elinters:gf,ell:mf,els:vf,elsdot:bf,Emacr:xf,emacr:kf,empty:_f,emptyset:wf,EmptySmallSquare:yf,emptyv:Af,EmptyVerySmallSquare:Ef,emsp13:Cf,emsp14:Sf,emsp:Df,ENG:qf,eng:Ff,ensp:Tf,Eogon:If,eogon:Bf,Eopf:Rf,eopf:Lf,epar:Pf,eparsl:Mf,eplus:Uf,epsi:zf,Epsilon:Nf,epsilon:Of,epsiv:$f,eqcirc:Vf,eqcolon:Hf,eqsim:Gf,eqslantgtr:jf,eqslantless:Zf,Equal:Yf,equals:Wf,EqualTilde:Jf,equest:Qf,Equilibrium:Kf,equiv:Xf,equivDD:np,eqvparsl:rp,erarr:ep,erDot:tp,escr:op,Escr:sp,esdot:cp,Esim:ip,esim:ap,Eta:lp,eta:up,ETH:fp,eth:pp,Euml:hp,euml:dp,euro:gp,excl:mp,exist:vp,Exists:bp,expectation:xp,exponentiale:kp,ExponentialE:_p,fallingdotseq:wp,Fcy:yp,fcy:Ap,female:Ep,ffilig:Cp,fflig:Sp,ffllig:Dp,Ffr:qp,ffr:Fp,filig:Tp,FilledSmallSquare:Ip,FilledVerySmallSquare:Bp,fjlig:Rp,flat:Lp,fllig:Pp,fltns:Mp,fnof:Up,Fopf:zp,fopf:Np,forall:Op,ForAll:$p,fork:Vp,forkv:Hp,Fouriertrf:Gp,fpartint:jp,frac12:Zp,frac13:Yp,frac14:Wp,frac15:Jp,frac16:Qp,frac18:Kp,frac23:Xp,frac25:nh,frac34:rh,frac35:eh,frac38:th,frac45:oh,frac56:sh,frac58:ch,frac78:ih,frasl:ah,frown:lh,fscr:uh,Fscr:fh,gacute:ph,Gamma:hh,gamma:dh,Gammad:gh,gammad:mh,gap:vh,Gbreve:bh,gbreve:xh,Gcedil:kh,Gcirc:_h,gcirc:wh,Gcy:yh,gcy:Ah,Gdot:Eh,gdot:Ch,ge:Sh,gE:Dh,gEl:qh,gel:Fh,geq:Th,geqq:Ih,geqslant:Bh,gescc:Rh,ges:Lh,gesdot:Ph,gesdoto:Mh,gesdotol:Uh,gesl:zh,gesles:Nh,Gfr:Oh,gfr:$h,gg:Vh,Gg:Hh,ggg:Gh,gimel:jh,GJcy:Zh,gjcy:Yh,gla:Wh,gl:Jh,glE:Qh,glj:Kh,gnap:Xh,gnapprox:nd,gne:rd,gnE:ed,gneq:td,gneqq:od,gnsim:sd,Gopf:cd,gopf:id,grave:ad,GreaterEqual:ld,GreaterEqualLess:ud,GreaterFullEqual:fd,GreaterGreater:pd,GreaterLess:hd,GreaterSlantEqual:dd,GreaterTilde:gd,Gscr:md,gscr:vd,gsim:bd,gsime:xd,gsiml:kd,gtcc:_d,gtcir:wd,gt:yd,GT:Ad,Gt:Ed,gtdot:Cd,gtlPar:Sd,gtquest:Dd,gtrapprox:qd,gtrarr:Fd,gtrdot:Td,gtreqless:Id,gtreqqless:Bd,gtrless:Rd,gtrsim:Ld,gvertneqq:Pd,gvnE:Md,Hacek:Ud,hairsp:zd,half:Nd,hamilt:Od,HARDcy:$d,hardcy:Vd,harrcir:Hd,harr:Gd,hArr:jd,harrw:Zd,Hat:Yd,hbar:Wd,Hcirc:Jd,hcirc:Qd,hearts:Kd,heartsuit:Xd,hellip:ng,hercon:rg,hfr:eg,Hfr:tg,HilbertSpace:og,hksearow:sg,hkswarow:cg,hoarr:ig,homtht:ag,hookleftarrow:lg,hookrightarrow:ug,hopf:fg,Hopf:pg,horbar:hg,HorizontalLine:dg,hscr:gg,Hscr:mg,hslash:vg,Hstrok:bg,hstrok:xg,HumpDownHump:kg,HumpEqual:_g,hybull:wg,hyphen:yg,Iacute:Ag,iacute:Eg,ic:Cg,Icirc:Sg,icirc:Dg,Icy:qg,icy:Fg,Idot:Tg,IEcy:Ig,iecy:Bg,iexcl:Rg,iff:Lg,ifr:Pg,Ifr:Mg,Igrave:Ug,igrave:zg,ii:Ng,iiiint:Og,iiint:$g,iinfin:Vg,iiota:Hg,IJlig:Gg,ijlig:jg,Imacr:Zg,imacr:Yg,image:Wg,ImaginaryI:Jg,imagline:Qg,imagpart:Kg,imath:Xg,Im:n0,imof:r0,imped:e0,Implies:t0,incare:o0,in:"\u2208",infin:s0,infintie:c0,inodot:i0,intcal:a0,int:l0,Int:u0,integers:f0,Integral:p0,intercal:h0,Intersection:d0,intlarhk:g0,intprod:m0,InvisibleComma:v0,InvisibleTimes:b0,IOcy:x0,iocy:k0,Iogon:_0,iogon:w0,Iopf:y0,iopf:A0,Iota:E0,iota:C0,iprod:S0,iquest:D0,iscr:q0,Iscr:F0,isin:T0,isindot:I0,isinE:B0,isins:R0,isinsv:L0,isinv:P0,it:M0,Itilde:U0,itilde:z0,Iukcy:N0,iukcy:O0,Iuml:$0,iuml:V0,Jcirc:H0,jcirc:G0,Jcy:j0,jcy:Z0,Jfr:Y0,jfr:W0,jmath:J0,Jopf:Q0,jopf:K0,Jscr:X0,jscr:nm,Jsercy:rm,jsercy:em,Jukcy:tm,jukcy:om,Kappa:sm,kappa:cm,kappav:im,Kcedil:am,kcedil:lm,Kcy:um,kcy:fm,Kfr:pm,kfr:hm,kgreen:dm,KHcy:gm,khcy:mm,KJcy:vm,kjcy:bm,Kopf:xm,kopf:km,Kscr:_m,kscr:wm,lAarr:ym,Lacute:Am,lacute:Em,laemptyv:Cm,lagran:Sm,Lambda:Dm,lambda:qm,lang:Fm,Lang:Tm,langd:Im,langle:Bm,lap:Rm,Laplacetrf:Lm,laquo:Pm,larrb:Mm,larrbfs:Um,larr:zm,Larr:Nm,lArr:Om,larrfs:$m,larrhk:Vm,larrlp:Hm,larrpl:Gm,larrsim:jm,larrtl:Zm,latail:Ym,lAtail:Wm,lat:Jm,late:Qm,lates:Km,lbarr:Xm,lBarr:nv,lbbrk:rv,lbrace:ev,lbrack:tv,lbrke:ov,lbrksld:sv,lbrkslu:cv,Lcaron:iv,lcaron:av,Lcedil:lv,lcedil:uv,lceil:fv,lcub:pv,Lcy:hv,lcy:dv,ldca:gv,ldquo:mv,ldquor:vv,ldrdhar:bv,ldrushar:xv,ldsh:kv,le:_v,lE:wv,LeftAngleBracket:yv,LeftArrowBar:Av,leftarrow:Ev,LeftArrow:Cv,Leftarrow:Sv,LeftArrowRightArrow:Dv,leftarrowtail:qv,LeftCeiling:Fv,LeftDoubleBracket:Tv,LeftDownTeeVector:Iv,LeftDownVectorBar:Bv,LeftDownVector:Rv,LeftFloor:Lv,leftharpoondown:Pv,leftharpoonup:Mv,leftleftarrows:Uv,leftrightarrow:zv,LeftRightArrow:Nv,Leftrightarrow:Ov,leftrightarrows:$v,leftrightharpoons:Vv,leftrightsquigarrow:Hv,LeftRightVector:Gv,LeftTeeArrow:jv,LeftTee:Zv,LeftTeeVector:Yv,leftthreetimes:Wv,LeftTriangleBar:Jv,LeftTriangle:Qv,LeftTriangleEqual:Kv,LeftUpDownVector:Xv,LeftUpTeeVector:nb,LeftUpVectorBar:rb,LeftUpVector:eb,LeftVectorBar:tb,LeftVector:ob,lEg:sb,leg:cb,leq:ib,leqq:ab,leqslant:lb,lescc:ub,les:fb,lesdot:pb,lesdoto:hb,lesdotor:db,lesg:gb,lesges:mb,lessapprox:vb,lessdot:bb,lesseqgtr:xb,lesseqqgtr:kb,LessEqualGreater:_b,LessFullEqual:wb,LessGreater:yb,lessgtr:Ab,LessLess:Eb,lesssim:Cb,LessSlantEqual:Sb,LessTilde:Db,lfisht:qb,lfloor:Fb,Lfr:Tb,lfr:Ib,lg:Bb,lgE:Rb,lHar:Lb,lhard:Pb,lharu:Mb,lharul:Ub,lhblk:zb,LJcy:Nb,ljcy:Ob,llarr:$b,ll:Vb,Ll:Hb,llcorner:Gb,Lleftarrow:jb,llhard:Zb,lltri:Yb,Lmidot:Wb,lmidot:Jb,lmoustache:Qb,lmoust:Kb,lnap:Xb,lnapprox:nx,lne:rx,lnE:ex,lneq:tx,lneqq:ox,lnsim:sx,loang:cx,loarr:ix,lobrk:ax,longleftarrow:lx,LongLeftArrow:ux,Longleftarrow:fx,longleftrightarrow:px,LongLeftRightArrow:hx,Longleftrightarrow:dx,longmapsto:gx,longrightarrow:mx,LongRightArrow:vx,Longrightarrow:bx,looparrowleft:xx,looparrowright:kx,lopar:_x,Lopf:wx,lopf:yx,loplus:Ax,lotimes:Ex,lowast:Cx,lowbar:Sx,LowerLeftArrow:Dx,LowerRightArrow:qx,loz:Fx,lozenge:Tx,lozf:Ix,lpar:Bx,lparlt:Rx,lrarr:Lx,lrcorner:Px,lrhar:Mx,lrhard:Ux,lrm:zx,lrtri:Nx,lsaquo:Ox,lscr:$x,Lscr:Vx,lsh:Hx,Lsh:Gx,lsim:jx,lsime:Zx,lsimg:Yx,lsqb:Wx,lsquo:Jx,lsquor:Qx,Lstrok:Kx,lstrok:Xx,ltcc:nk,ltcir:rk,lt:ek,LT:tk,Lt:ok,ltdot:sk,lthree:ck,ltimes:ik,ltlarr:ak,ltquest:lk,ltri:uk,ltrie:fk,ltrif:pk,ltrPar:hk,lurdshar:dk,luruhar:gk,lvertneqq:mk,lvnE:vk,macr:bk,male:xk,malt:kk,maltese:_k,Map:"\u2905",map:wk,mapsto:yk,mapstodown:Ak,mapstoleft:Ek,mapstoup:Ck,marker:Sk,mcomma:Dk,Mcy:qk,mcy:Fk,mdash:Tk,mDDot:Ik,measuredangle:Bk,MediumSpace:Rk,Mellintrf:Lk,Mfr:Pk,mfr:Mk,mho:Uk,micro:zk,midast:Nk,midcir:Ok,mid:$k,middot:Vk,minusb:Hk,minus:Gk,minusd:jk,minusdu:Zk,MinusPlus:Yk,mlcp:Wk,mldr:Jk,mnplus:Qk,models:Kk,Mopf:Xk,mopf:n_,mp:r_,mscr:e_,Mscr:t_,mstpos:o_,Mu:s_,mu:c_,multimap:i_,mumap:a_,nabla:l_,Nacute:u_,nacute:f_,nang:p_,nap:h_,napE:d_,napid:g_,napos:m_,napprox:v_,natural:b_,naturals:x_,natur:k_,nbsp:__,nbump:w_,nbumpe:y_,ncap:A_,Ncaron:E_,ncaron:C_,Ncedil:S_,ncedil:D_,ncong:q_,ncongdot:F_,ncup:T_,Ncy:I_,ncy:B_,ndash:R_,nearhk:L_,nearr:P_,neArr:M_,nearrow:U_,ne:z_,nedot:N_,NegativeMediumSpace:O_,NegativeThickSpace:$_,NegativeThinSpace:V_,NegativeVeryThinSpace:H_,nequiv:G_,nesear:j_,nesim:Z_,NestedGreaterGreater:Y_,NestedLessLess:W_,NewLine:J_,nexist:Q_,nexists:K_,Nfr:X_,nfr:nw,ngE:rw,nge:ew,ngeq:tw,ngeqq:ow,ngeqslant:sw,nges:cw,nGg:iw,ngsim:aw,nGt:lw,ngt:uw,ngtr:fw,nGtv:pw,nharr:hw,nhArr:dw,nhpar:gw,ni:mw,nis:vw,nisd:bw,niv:xw,NJcy:kw,njcy:_w,nlarr:ww,nlArr:yw,nldr:Aw,nlE:Ew,nle:Cw,nleftarrow:Sw,nLeftarrow:Dw,nleftrightarrow:qw,nLeftrightarrow:Fw,nleq:Tw,nleqq:Iw,nleqslant:Bw,nles:Rw,nless:Lw,nLl:Pw,nlsim:Mw,nLt:Uw,nlt:zw,nltri:Nw,nltrie:Ow,nLtv:$w,nmid:Vw,NoBreak:Hw,NonBreakingSpace:Gw,nopf:jw,Nopf:Zw,Not:Yw,not:Ww,NotCongruent:Jw,NotCupCap:Qw,NotDoubleVerticalBar:Kw,NotElement:Xw,NotEqual:n1,NotEqualTilde:r1,NotExists:e1,NotGreater:t1,NotGreaterEqual:o1,NotGreaterFullEqual:s1,NotGreaterGreater:c1,NotGreaterLess:i1,NotGreaterSlantEqual:a1,NotGreaterTilde:l1,NotHumpDownHump:u1,NotHumpEqual:f1,notin:p1,notindot:h1,notinE:d1,notinva:g1,notinvb:m1,notinvc:v1,NotLeftTriangleBar:b1,NotLeftTriangle:x1,NotLeftTriangleEqual:k1,NotLess:_1,NotLessEqual:w1,NotLessGreater:y1,NotLessLess:A1,NotLessSlantEqual:E1,NotLessTilde:C1,NotNestedGreaterGreater:S1,NotNestedLessLess:D1,notni:q1,notniva:F1,notnivb:T1,notnivc:I1,NotPrecedes:B1,NotPrecedesEqual:R1,NotPrecedesSlantEqual:L1,NotReverseElement:P1,NotRightTriangleBar:M1,NotRightTriangle:U1,NotRightTriangleEqual:z1,NotSquareSubset:N1,NotSquareSubsetEqual:O1,NotSquareSuperset:$1,NotSquareSupersetEqual:V1,NotSubset:H1,NotSubsetEqual:G1,NotSucceeds:j1,NotSucceedsEqual:Z1,NotSucceedsSlantEqual:Y1,NotSucceedsTilde:W1,NotSuperset:J1,NotSupersetEqual:Q1,NotTilde:K1,NotTildeEqual:X1,NotTildeFullEqual:ny,NotTildeTilde:ry,NotVerticalBar:ey,nparallel:ty,npar:oy,nparsl:sy,npart:cy,npolint:iy,npr:ay,nprcue:ly,nprec:uy,npreceq:fy,npre:py,nrarrc:hy,nrarr:dy,nrArr:gy,nrarrw:my,nrightarrow:vy,nRightarrow:by,nrtri:xy,nrtrie:ky,nsc:_y,nsccue:wy,nsce:yy,Nscr:Ay,nscr:Ey,nshortmid:Cy,nshortparallel:Sy,nsim:Dy,nsime:qy,nsimeq:Fy,nsmid:Ty,nspar:Iy,nsqsube:By,nsqsupe:Ry,nsub:Ly,nsubE:Py,nsube:My,nsubset:Uy,nsubseteq:zy,nsubseteqq:Ny,nsucc:Oy,nsucceq:$y,nsup:Vy,nsupE:Hy,nsupe:Gy,nsupset:jy,nsupseteq:Zy,nsupseteqq:Yy,ntgl:Wy,Ntilde:Jy,ntilde:Qy,ntlg:Ky,ntriangleleft:Xy,ntrianglelefteq:nA,ntriangleright:rA,ntrianglerighteq:eA,Nu:tA,nu:oA,num:sA,numero:cA,numsp:iA,nvap:aA,nvdash:lA,nvDash:uA,nVdash:fA,nVDash:pA,nvge:hA,nvgt:dA,nvHarr:gA,nvinfin:mA,nvlArr:vA,nvle:bA,nvlt:xA,nvltrie:kA,nvrArr:_A,nvrtrie:wA,nvsim:yA,nwarhk:AA,nwarr:EA,nwArr:CA,nwarrow:SA,nwnear:DA,Oacute:qA,oacute:FA,oast:TA,Ocirc:IA,ocirc:BA,ocir:RA,Ocy:LA,ocy:PA,odash:MA,Odblac:UA,odblac:zA,odiv:NA,odot:OA,odsold:$A,OElig:VA,oelig:HA,ofcir:GA,Ofr:jA,ofr:ZA,ogon:YA,Ograve:WA,ograve:JA,ogt:QA,ohbar:KA,ohm:XA,oint:nE,olarr:rE,olcir:eE,olcross:tE,oline:oE,olt:sE,Omacr:cE,omacr:iE,Omega:aE,omega:lE,Omicron:uE,omicron:fE,omid:pE,ominus:hE,Oopf:dE,oopf:gE,opar:mE,OpenCurlyDoubleQuote:vE,OpenCurlyQuote:bE,operp:xE,oplus:kE,orarr:_E,Or:wE,or:yE,ord:AE,order:EE,orderof:CE,ordf:SE,ordm:DE,origof:qE,oror:FE,orslope:TE,orv:IE,oS:BE,Oscr:RE,oscr:LE,Oslash:PE,oslash:ME,osol:UE,Otilde:zE,otilde:NE,otimesas:OE,Otimes:$E,otimes:VE,Ouml:HE,ouml:GE,ovbar:jE,OverBar:ZE,OverBrace:YE,OverBracket:WE,OverParenthesis:JE,para:QE,parallel:KE,par:XE,parsim:nC,parsl:rC,part:eC,PartialD:tC,Pcy:oC,pcy:sC,percnt:cC,period:iC,permil:aC,perp:lC,pertenk:uC,Pfr:fC,pfr:pC,Phi:hC,phi:dC,phiv:gC,phmmat:mC,phone:vC,Pi:bC,pi:xC,pitchfork:kC,piv:_C,planck:wC,planckh:yC,plankv:AC,plusacir:EC,plusb:CC,pluscir:SC,plus:DC,plusdo:qC,plusdu:FC,pluse:TC,PlusMinus:IC,plusmn:BC,plussim:RC,plustwo:LC,pm:PC,Poincareplane:MC,pointint:UC,popf:zC,Popf:NC,pound:OC,prap:$C,Pr:VC,pr:HC,prcue:GC,precapprox:jC,prec:ZC,preccurlyeq:YC,Precedes:WC,PrecedesEqual:JC,PrecedesSlantEqual:QC,PrecedesTilde:KC,preceq:XC,precnapprox:nS,precneqq:rS,precnsim:eS,pre:tS,prE:oS,precsim:sS,prime:cS,Prime:iS,primes:aS,prnap:lS,prnE:uS,prnsim:fS,prod:pS,Product:hS,profalar:dS,profline:gS,profsurf:mS,prop:vS,Proportional:bS,Proportion:xS,propto:kS,prsim:_S,prurel:wS,Pscr:yS,pscr:AS,Psi:ES,psi:CS,puncsp:SS,Qfr:DS,qfr:qS,qint:FS,qopf:TS,Qopf:IS,qprime:BS,Qscr:RS,qscr:LS,quaternions:PS,quatint:MS,quest:US,questeq:zS,quot:NS,QUOT:OS,rAarr:$S,race:VS,Racute:HS,racute:GS,radic:jS,raemptyv:ZS,rang:YS,Rang:WS,rangd:JS,range:QS,rangle:KS,raquo:XS,rarrap:nD,rarrb:rD,rarrbfs:eD,rarrc:tD,rarr:oD,Rarr:sD,rArr:cD,rarrfs:iD,rarrhk:aD,rarrlp:lD,rarrpl:uD,rarrsim:fD,Rarrtl:pD,rarrtl:hD,rarrw:dD,ratail:gD,rAtail:mD,ratio:vD,rationals:bD,rbarr:xD,rBarr:kD,RBarr:_D,rbbrk:wD,rbrace:yD,rbrack:AD,rbrke:ED,rbrksld:CD,rbrkslu:SD,Rcaron:DD,rcaron:qD,Rcedil:FD,rcedil:TD,rceil:ID,rcub:BD,Rcy:RD,rcy:LD,rdca:PD,rdldhar:MD,rdquo:UD,rdquor:zD,rdsh:ND,real:OD,realine:$D,realpart:VD,reals:HD,Re:GD,rect:jD,reg:ZD,REG:YD,ReverseElement:WD,ReverseEquilibrium:JD,ReverseUpEquilibrium:QD,rfisht:KD,rfloor:XD,rfr:n2,Rfr:r2,rHar:e2,rhard:t2,rharu:o2,rharul:s2,Rho:c2,rho:i2,rhov:a2,RightAngleBracket:l2,RightArrowBar:u2,rightarrow:f2,RightArrow:p2,Rightarrow:h2,RightArrowLeftArrow:d2,rightarrowtail:g2,RightCeiling:m2,RightDoubleBracket:v2,RightDownTeeVector:b2,RightDownVectorBar:x2,RightDownVector:k2,RightFloor:_2,rightharpoondown:w2,rightharpoonup:y2,rightleftarrows:A2,rightleftharpoons:E2,rightrightarrows:C2,rightsquigarrow:S2,RightTeeArrow:D2,RightTee:q2,RightTeeVector:F2,rightthreetimes:T2,RightTriangleBar:I2,RightTriangle:B2,RightTriangleEqual:R2,RightUpDownVector:L2,RightUpTeeVector:P2,RightUpVectorBar:M2,RightUpVector:U2,RightVectorBar:z2,RightVector:N2,ring:O2,risingdotseq:$2,rlarr:V2,rlhar:H2,rlm:G2,rmoustache:j2,rmoust:Z2,rnmid:Y2,roang:W2,roarr:J2,robrk:Q2,ropar:K2,ropf:X2,Ropf:nq,roplus:rq,rotimes:eq,RoundImplies:tq,rpar:oq,rpargt:sq,rppolint:cq,rrarr:iq,Rrightarrow:aq,rsaquo:lq,rscr:uq,Rscr:fq,rsh:pq,Rsh:hq,rsqb:dq,rsquo:gq,rsquor:mq,rthree:vq,rtimes:bq,rtri:xq,rtrie:kq,rtrif:_q,rtriltri:wq,RuleDelayed:yq,ruluhar:Aq,rx:Eq,Sacute:Cq,sacute:Sq,sbquo:Dq,scap:qq,Scaron:Fq,scaron:Tq,Sc:Iq,sc:Bq,sccue:Rq,sce:Lq,scE:Pq,Scedil:Mq,scedil:Uq,Scirc:zq,scirc:Nq,scnap:Oq,scnE:$q,scnsim:Vq,scpolint:Hq,scsim:Gq,Scy:jq,scy:Zq,sdotb:Yq,sdot:Wq,sdote:Jq,searhk:Qq,searr:Kq,seArr:Xq,searrow:nF,sect:rF,semi:eF,seswar:tF,setminus:oF,setmn:sF,sext:cF,Sfr:iF,sfr:aF,sfrown:lF,sharp:uF,SHCHcy:fF,shchcy:pF,SHcy:hF,shcy:dF,ShortDownArrow:gF,ShortLeftArrow:mF,shortmid:vF,shortparallel:bF,ShortRightArrow:xF,ShortUpArrow:kF,shy:_F,Sigma:wF,sigma:yF,sigmaf:AF,sigmav:EF,sim:CF,simdot:SF,sime:DF,simeq:qF,simg:FF,simgE:TF,siml:IF,simlE:BF,simne:RF,simplus:LF,simrarr:PF,slarr:MF,SmallCircle:UF,smallsetminus:zF,smashp:NF,smeparsl:OF,smid:$F,smile:VF,smt:HF,smte:GF,smtes:jF,SOFTcy:ZF,softcy:YF,solbar:WF,solb:JF,sol:QF,Sopf:KF,sopf:XF,spades:nT,spadesuit:rT,spar:eT,sqcap:tT,sqcaps:oT,sqcup:sT,sqcups:cT,Sqrt:iT,sqsub:aT,sqsube:lT,sqsubset:uT,sqsubseteq:fT,sqsup:pT,sqsupe:hT,sqsupset:dT,sqsupseteq:gT,square:mT,Square:vT,SquareIntersection:bT,SquareSubset:xT,SquareSubsetEqual:kT,SquareSuperset:_T,SquareSupersetEqual:wT,SquareUnion:yT,squarf:AT,squ:ET,squf:CT,srarr:ST,Sscr:DT,sscr:qT,ssetmn:FT,ssmile:TT,sstarf:IT,Star:BT,star:RT,starf:LT,straightepsilon:PT,straightphi:MT,strns:UT,sub:zT,Sub:NT,subdot:OT,subE:$T,sube:VT,subedot:HT,submult:GT,subnE:jT,subne:ZT,subplus:YT,subrarr:WT,subset:JT,Subset:QT,subseteq:KT,subseteqq:XT,SubsetEqual:nI,subsetneq:rI,subsetneqq:eI,subsim:tI,subsub:oI,subsup:sI,succapprox:cI,succ:iI,succcurlyeq:aI,Succeeds:lI,SucceedsEqual:uI,SucceedsSlantEqual:fI,SucceedsTilde:pI,succeq:hI,succnapprox:dI,succneqq:gI,succnsim:mI,succsim:vI,SuchThat:bI,sum:xI,Sum:kI,sung:_I,sup1:wI,sup2:yI,sup3:AI,sup:EI,Sup:CI,supdot:SI,supdsub:DI,supE:qI,supe:FI,supedot:TI,Superset:II,SupersetEqual:BI,suphsol:RI,suphsub:LI,suplarr:PI,supmult:MI,supnE:UI,supne:zI,supplus:NI,supset:OI,Supset:$I,supseteq:VI,supseteqq:HI,supsetneq:GI,supsetneqq:jI,supsim:ZI,supsub:YI,supsup:WI,swarhk:JI,swarr:QI,swArr:KI,swarrow:XI,swnwar:nB,szlig:rB,Tab:eB,target:tB,Tau:oB,tau:sB,tbrk:cB,Tcaron:iB,tcaron:aB,Tcedil:lB,tcedil:uB,Tcy:fB,tcy:pB,tdot:hB,telrec:dB,Tfr:gB,tfr:mB,there4:vB,therefore:bB,Therefore:xB,Theta:kB,theta:_B,thetasym:wB,thetav:yB,thickapprox:AB,thicksim:EB,ThickSpace:CB,ThinSpace:SB,thinsp:DB,thkap:qB,thksim:FB,THORN:TB,thorn:IB,tilde:BB,Tilde:RB,TildeEqual:LB,TildeFullEqual:PB,TildeTilde:MB,timesbar:UB,timesb:zB,times:NB,timesd:OB,tint:$B,toea:VB,topbot:HB,topcir:GB,top:jB,Topf:ZB,topf:YB,topfork:WB,tosa:JB,tprime:QB,trade:KB,TRADE:XB,triangle:nR,triangledown:rR,triangleleft:eR,trianglelefte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diff --git a/assets/selection.e82f8124.js b/assets/selection.10af5b4d.js
similarity index 80%
rename from assets/selection.e82f8124.js
rename to assets/selection.10af5b4d.js
index d5daa94add4..569184cf87e 100644
--- a/assets/selection.e82f8124.js
+++ b/assets/selection.10af5b4d.js
@@ -1 +1 @@
-import{P as o}from"./index.2b6e3ac7.js";function i(){if(window.getSelection!==void 0){const e=window.getSelection();e.empty!==void 0?e.empty():e.removeAllRanges!==void 0&&(e.removeAllRanges(),o.is.mobile!==!0&&e.addRange(document.createRange()))}else document.selection!==void 0&&document.selection.empty()}export{i as c};
+import{P as o}from"./index.ae19b4cb.js";function i(){if(window.getSelection!==void 0){const e=window.getSelection();e.empty!==void 0?e.empty():e.removeAllRanges!==void 0&&(e.removeAllRanges(),o.is.mobile!==!0&&e.addRange(document.createRange()))}else document.selection!==void 0&&document.selection.empty()}export{i as c};
diff --git a/assets/use-fullscreen.92026c44.js b/assets/use-fullscreen.324b1ba3.js
similarity index 94%
rename from assets/use-fullscreen.92026c44.js
rename to assets/use-fullscreen.324b1ba3.js
index 1d94ef8669d..9682244d461 100644
--- a/assets/use-fullscreen.92026c44.js
+++ b/assets/use-fullscreen.324b1ba3.js
@@ -1 +1 @@
-import{f as v,bN as F,w as f,o as b,K as x,x as y,bO as p,C as h}from"./index.2b6e3ac7.js";let s=0;const C={fullscreen:Boolean,noRouteFullscreenExit:Boolean},E=["update:fullscreen","fullscreen"];function g(){const d=h(),{props:r,emit:m,proxy:e}=d;let n,u,c;const l=v(!1);F(d)===!0&&f(()=>e.$route.fullPath,()=>{r.noRouteFullscreenExit!==!0&&t()}),f(()=>r.fullscreen,o=>{l.value!==o&&a()}),f(l,o=>{m("update:fullscreen",o),m("fullscreen",o)});function a(){l.value===!0?t():i()}function i(){l.value!==!0&&(l.value=!0,c=e.$el.parentNode,c.replaceChild(u,e.$el),document.body.appendChild(e.$el),s++,s===1&&document.body.classList.add("q-body--fullscreen-mixin"),n={handler:t},p.add(n))}function t(){l.value===!0&&(n!==void 0&&(p.remove(n),n=void 0),c.replaceChild(e.$el,u),l.value=!1,s=Math.max(0,s-1),s===0&&(document.body.classList.remove("q-body--fullscreen-mixin"),e.$el.scrollIntoView!==void 0&&setTimeout(()=>{e.$el.scrollIntoView()})))}return b(()=>{u=document.createElement("span")}),x(()=>{r.fullscreen===!0&&i()}),y(t),Object.assign(e,{toggleFullscreen:a,setFullscreen:i,exitFullscreen:t}),{inFullscreen:l,toggleFullscreen:a}}export{E as a,g as b,C as u};
+import{f as v,bN as F,w as f,o as b,K as x,x as y,bO as p,C as h}from"./index.ae19b4cb.js";let s=0;const C={fullscreen:Boolean,noRouteFullscreenExit:Boolean},E=["update:fullscreen","fullscreen"];function g(){const d=h(),{props:r,emit:m,proxy:e}=d;let n,u,c;const l=v(!1);F(d)===!0&&f(()=>e.$route.fullPath,()=>{r.noRouteFullscreenExit!==!0&&t()}),f(()=>r.fullscreen,o=>{l.value!==o&&a()}),f(l,o=>{m("update:fullscreen",o),m("fullscreen",o)});function a(){l.value===!0?t():i()}function i(){l.value!==!0&&(l.value=!0,c=e.$el.parentNode,c.replaceChild(u,e.$el),document.body.appendChild(e.$el),s++,s===1&&document.body.classList.add("q-body--fullscreen-mixin"),n={handler:t},p.add(n))}function t(){l.value===!0&&(n!==void 0&&(p.remove(n),n=void 0),c.replaceChild(e.$el,u),l.value=!1,s=Math.max(0,s-1),s===0&&(document.body.classList.remove("q-body--fullscreen-mixin"),e.$el.scrollIntoView!==void 0&&setTimeout(()=>{e.$el.scrollIntoView()})))}return b(()=>{u=document.createElement("span")}),x(()=>{r.fullscreen===!0&&i()}),y(t),Object.assign(e,{toggleFullscreen:a,setFullscreen:i,exitFullscreen:t}),{inFullscreen:l,toggleFullscreen:a}}export{E as a,g as b,C as u};
diff --git a/assets/useMetaTags.dca8d813.js b/assets/useMetaTags.f561479d.js
similarity index 91%
rename from assets/useMetaTags.dca8d813.js
rename to assets/useMetaTags.f561479d.js
index 58d0face1b3..cfee3c7e144 100644
--- a/assets/useMetaTags.dca8d813.js
+++ b/assets/useMetaTags.f561479d.js
@@ -1 +1 @@
-import{a6 as r,bX as a}from"./index.2b6e3ac7.js";const p=t=>{const{t:e}=r({useScope:"global"});a({title:e(`${t.page}.title`),meta:[{name:"title",content:e(`${t.page}.title`)},{property:"og:title",content:e(`${t.page}.title`)},{property:"twitter:title",content:e(`${t.page}.title`)},{name:"description",content:e(`${t.page}.description`)},{property:"og:description",content:e(`${t.page}.description`)},{property:"twitter:description",content:e(`${t.page}.description`)},{property:"og:url",content:`https://jina.ai/${t.url}`},{property:"og:image",content:`https://jina.ai/${t.banner}`},{property:"twitter:url",content:`https://jina.ai/${t.url}`},{property:"twitter:image",content:`https://jina.ai/${t.banner}`}]})};export{p as u};
+import{a6 as r,bX as a}from"./index.ae19b4cb.js";const p=t=>{const{t:e}=r({useScope:"global"});a({title:e(`${t.page}.title`),meta:[{name:"title",content:e(`${t.page}.title`)},{property:"og:title",content:e(`${t.page}.title`)},{property:"twitter:title",content:e(`${t.page}.title`)},{name:"description",content:e(`${t.page}.description`)},{property:"og:description",content:e(`${t.page}.description`)},{property:"twitter:description",content:e(`${t.page}.description`)},{property:"og:url",content:`https://jina.ai/${t.url}`},{property:"og:image",content:`https://jina.ai/${t.banner}`},{property:"twitter:url",content:`https://jina.ai/${t.url}`},{property:"twitter:image",content:`https://jina.ai/${t.banner}`}]})};export{p as u};
diff --git a/contact-sales/index.html b/contact-sales/index.html
index f1543d6acb3..aacbacb1601 100644
--- a/contact-sales/index.html
+++ b/contact-sales/index.html
@@ -1,6 +1,6 @@
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draggable="false" src="/assets/logo-Holidu.145e3007.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div></div><div data-v-69ac199c="" class="row q-py-xl justify-center bg-dark"><div data-v-69ac199c="" class="col-10 q-py-xl q-my-xl"><div data-v-69ac199c="" class="text-h2 text-center q-py-xl">Impact Snapshots</div><div data-v-69ac199c="" class="q-scrollarea q-scrollarea--dark full-width" style="height: 300px;"><div class="q-scrollarea__container scroll relative-position fit hide-scrollbar"><div class="q-scrollarea__content absolute"><div data-v-69ac199c="" class="q-list q-list--dark row justify-start"><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Enable high-accuracy search within 3D mesh data using point cloud information.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Design a content-based search engine for short animation films.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Enhance e-commerce conversion rates by fine-tuning embedding models.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Execute prompt tuning to boost efficiency for a business consulting company.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Pioneer game scene understanding and automatic annotation for a leading gaming enterprise.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Implement real-time input expansion for a chatbot company, enhancing user experience.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Revolutionize legal tech by enabling efficient search within lengthy legal documents.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Support a high-throughput generative art service for large-scale operations.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Carry out process mining and modeling using advanced language models.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Leverage computer vision to improve digital accessibility of government websites.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Fine-tune LLM for a consulting firm to optimize finance data analysis.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Advance marketing strategies by fine-tuning text-to-image models for style transferring.</div></div></div></div></div></div><div class="q-scrollarea__bar q-scrollarea__bar--v absolute-right" aria-hidden="true"></div><div class="q-scrollarea__bar q-scrollarea__bar--h absolute-bottom q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--v absolute-right" aria-hidden="true" style="top: 0px; height: 98px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="left: 0px; width: 667px;"></div></div></div></div></div></div><div data-v-69ac199c="" class="row q-px-lg q-mt-xl q-pb-md non-selectable justify-center"><div data-v-69ac199c="" class="text-h2">FAQ</div></div><div data-v-69ac199c="" class="q-pa-xl row items-start q-gutter-xl justify-center"><div data-v-69ac199c="" class="q-list q-list--dark col-11 col-md-8"><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="1907398a-e0cc-4374-8648-9c8b25fe29e2" aria-label="Expand &quot;What does Jina AI specialize in?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What does Jina AI specialize in?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="1907398a-e0cc-4374-8648-9c8b25fe29e2" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Jina AI specializes in multimodal AI technologies, including embedding-tuning, embedding-serving, prompt-tuning, and prompt-serving. We leverage advanced tools like Kubernetes and serverless architectures to create robust, scalable, and production-ready solutions.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="4118a240-c7e8-4ce6-a9c4-a168fb89a4c7" aria-label="Expand &quot;What types of AI does Jina AI work with?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What types of AI does Jina AI work with?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="4118a240-c7e8-4ce6-a9c4-a168fb89a4c7" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Our expertise spans a broad spectrum, encompassing large language models, text, image, video, audio understanding, neural search, and generative art.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f5abbed4-def2-45ca-b716-e84e607c45e2" aria-label="Expand &quot;Are your solutions scalable and production-ready?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Are your solutions scalable and production-ready?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f5abbed4-def2-45ca-b716-e84e607c45e2" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Yes, our solutions are designed to be scalable and ready for production. We build our solutions using cloud-native technologies that allow for efficient scaling and reliable performance in production environments.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="23e0102f-5803-4ad6-b707-2218a0ff0051" aria-label="Expand &quot;What industries can benefit from Jina AI's solutions?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What industries can benefit from Jina AI's solutions?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="23e0102f-5803-4ad6-b707-2218a0ff0051" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Our services are versatile and adaptable, making them suitable for a wide range of industries, including e-commerce, legal tech, digital marketing, gaming, healthcare, finance, and many more.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="9adb3978-b5c8-4bb1-a675-29aff48a83c2" aria-label="Expand &quot;How do we start a project with Jina AI?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How do we start a project with Jina AI?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="9adb3978-b5c8-4bb1-a675-29aff48a83c2" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">You can get in touch with our sales team through the contact form on this page. We would love to discuss your project requirements and how our solutions can help your business.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f460bb91-2ef1-4b36-9b75-94f15f6d7987" aria-label="Expand &quot;What support do you provide after implementing a solution?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What support do you provide after implementing a solution?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f460bb91-2ef1-4b36-9b75-94f15f6d7987" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">We provide continuous support to ensure the smooth operation of our solutions. This includes troubleshooting, regular updates, and improvements based on your feedback and needs.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f4e08eee-47e3-4419-9688-fe827a3f728f" aria-label="Expand &quot;What is the typical duration for a project?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the typical duration for a project?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f4e08eee-47e3-4419-9688-fe827a3f728f" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Project duration varies depending on the complexity and scope of the project. After understanding your requirements, we can provide a more accurate estimate.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="8df53dc0-fee6-4d47-8a2b-c56df67af4be" aria-label="Expand &quot;How does Jina AI protect my data?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How does Jina AI protect my data?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="8df53dc0-fee6-4d47-8a2b-c56df67af4be" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Data security is our top priority. We adhere to strict data protection policies and regulations to ensure your data is secure and confidential.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="77bbe0d6-fb22-48bd-9ce4-407da1a7093b" aria-label="Expand &quot;What is the pricing structure for your services?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the pricing structure for your services?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="77bbe0d6-fb22-48bd-9ce4-407da1a7093b" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Pricing depends on the project's complexity and requirements. We offer both project-based and retainer pricing models. Please contact our sales team for more information.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="4ba6843d-248e-4cd0-b614-7a860857c413" aria-label="Expand &quot;What are the licensing terms for your solutions?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What are the licensing terms for your solutions?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="4ba6843d-248e-4cd0-b614-7a860857c413" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">We provide different licensing options based on the nature of the project and the client's needs. Detailed terms can be discussed with our sales team.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="7e1a4abb-0b0d-4ed8-a0f5-02a77fff4d5e" aria-label="Expand &quot;What is your service area?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is your service area?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="7e1a4abb-0b0d-4ed8-a0f5-02a77fff4d5e" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">We provide services globally, with our headquarters based in Berlin, Europe, and additional offices in Beijing and Shenzhen.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="ae511aea-98db-43cb-a1a0-edea648f6aa8" aria-label="Expand &quot;Do you offer onsite support?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Do you offer onsite support?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="ae511aea-98db-43cb-a1a0-edea648f6aa8" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Yes, we offer onsite support, especially for clients located near our offices in Berlin, Beijing, and Shenzhen. For other locations, we strive to provide the best possible remote support and can arrange for onsite support if necessary.</div></div></div></div></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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q-field--with-bottom" for="f_a8781c50-7755-491e-a71b-78a9fec38a2b"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" aria-label="Company size" id="f_a8781c50-7755-491e-a71b-78a9fec38a2b" type="text"><div class="q-field__label no-pointer-events absolute ellipsis">Company size</div></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></div><div data-v-69ac199c="" class="col-12 q-pa-sm"><label data-v-69ac199c="" class="q-field row no-wrap items-start q-field--filled q-input q-field--square q-field--labeled q-field--dark q-field--with-bottom" for="f_a5333ab0-c050-42c7-8dae-cc0cf90c094c"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" aria-label="Company website" placeholder="URL for your company's homepage or LinkedIn profile" id="f_a5333ab0-c050-42c7-8dae-cc0cf90c094c" type="text"><div class="q-field__label no-pointer-events absolute ellipsis">Company website</div></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></div><div data-v-69ac199c="" class="col-6 q-pa-sm"><label data-v-69ac199c="" class="q-field row no-wrap items-start q-field--filled q-input q-field--square q-field--labeled q-field--dark q-field--with-bottom" for="f_d7edf21f-583d-4e3a-93e7-fadb7fd08cd8"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" aria-label="Department" id="f_d7edf21f-583d-4e3a-93e7-fadb7fd08cd8" type="text"><div class="q-field__label no-pointer-events absolute ellipsis">Department</div></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></div><div data-v-69ac199c="" class="col-6 q-pa-sm"><label data-v-69ac199c="" class="q-field row no-wrap items-start q-field--filled q-input q-field--square q-field--labeled q-field--dark q-field--with-bottom" for="f_97fecfc9-1965-4e51-abe9-21c2163faa6d"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" aria-label="Job role" id="f_97fecfc9-1965-4e51-abe9-21c2163faa6d" type="text"><div class="q-field__label no-pointer-events absolute ellipsis">Job role</div></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></div><div data-v-69ac199c="" class="col-12 q-pa-sm"><label data-v-69ac199c="" class="q-field row no-wrap items-start q-field--filled q-select q-field--auto-height q-select--with-input q-select--with-chips q-select--multiple q-field--square q-field--labeled q-field--dark" for="f_8107c0a0-4345-4dd8-87d0-2ff7a24221d7"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><div class="q-field__native row items-center"><input class="q-field__input q-placeholder col" type="search" tabindex="0" role="combobox" aria-label="Which products are you interested in?" aria-readonly="false" aria-autocomplete="list" aria-expanded="false" aria-controls="f_8107c0a0-4345-4dd8-87d0-2ff7a24221d7_lb" id="f_8107c0a0-4345-4dd8-87d0-2ff7a24221d7"></div><div class="q-field__label no-pointer-events absolute ellipsis">Which products are you interested in?</div></div><div class="q-field__append q-field__marginal row no-wrap items-center q-anchor--skip"><i class="q-icon fas fa-caret-down q-select__dropdown-icon" aria-hidden="true" role="presentation"> </i></div></div></div></label></div></div><div data-v-69ac199c="" class="q-pl-sm"><label data-v-69ac199c="" class="q-field row no-wrap items-start q-field--filled q-textarea q-field--square q-field--labeled q-field--dark full-width q-mt-md" for="f_fd2b3089-cc8c-48cf-b484-742f014b074b"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><textarea class="q-field__native q-placeholder" tabindex="0" rows="6" aria-label="Tell us more about your project" id="f_fd2b3089-cc8c-48cf-b484-742f014b074b"></textarea><div class="q-field__label no-pointer-events absolute ellipsis">Tell us more about your project</div></div></div></div></label></div><div data-v-69ac199c="" class="q-card__actions justify-start q-card__actions--horiz row"><div data-v-69ac199c="" class="row justify-start items-start q-my-lg text-grey-6"><div data-v-69ac199c="" class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy text-primary" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div data-v-69ac199c="" class="q-pl-sm">By submitting, you confirm that you agree to the processing of your personal data by Jina AI as described in the <a data-v-69ac199c="" href="/legal#privacy-policy" class="text-grey-6">Privacy Statement</a></div></div></div></div><button data-v-69ac199c="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square disabled q-btn--square full-width" tabindex="-1" type="submit" disabled="" aria-disabled="true" style="font-size: 20px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">send</i><span class="block">Submit</span></span></button></div></form></div></div></div></div><div data-v-69ac199c="" class="col-6"><div data-v-69ac199c="" class="row q-py-xl justify-center q-pr-xl"><div data-v-69ac199c="" class="col-10 col-xl-10"><div data-v-69ac199c=""><div data-v-69ac199c="" class="text-h6 text-grey-5 text-weight-medium">Trusted by</div><div data-v-69ac199c="" class="row justify-start items-center q-mt-lg"><div data-v-69ac199c="" class="col-12 col-lg-6"><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-myntor.e924e0a2.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-uizard.7a824218.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-LOreal.3bf2271c.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div 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style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-Microsoft.78059602.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-Canva.c2c6e466.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-Travelperk.f4d54894.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition 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style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-salesforce.fff476c7.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-Farfetch.c76d1699.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-stability_ai.277f9015.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-Zalando.ffc742a3.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-Holidu.145e3007.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-Talabat.a036088b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" 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style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-Sopra_Steria.7d836082.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-zoho.c81341cd.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-69ac199c="" class="q-img q-img--menu q-ma-md col-3 col-md-2" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo-Infineon.f54a7bcc.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div></div><div data-v-69ac199c="" class="row q-py-xl justify-center bg-dark"><div data-v-69ac199c="" class="col-10 q-py-xl q-my-xl"><div data-v-69ac199c="" class="text-h2 text-center q-py-xl">Impact Snapshots</div><div data-v-69ac199c="" class="q-scrollarea q-scrollarea--dark full-width" style="height: 300px;"><div class="q-scrollarea__container scroll relative-position fit hide-scrollbar"><div class="q-scrollarea__content absolute"><div data-v-69ac199c="" class="q-list q-list--dark row justify-start"><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Enable high-accuracy search within 3D mesh data using point cloud information.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Design a content-based search engine for short animation films.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Enhance e-commerce conversion rates by fine-tuning embedding models.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Execute prompt tuning to boost efficiency for a business consulting company.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Pioneer game scene understanding and automatic annotation for a leading gaming enterprise.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Implement real-time input expansion for a chatbot company, enhancing user experience.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Revolutionize legal tech by enabling efficient search within lengthy legal documents.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Support a high-throughput generative art service for large-scale operations.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Carry out process mining and modeling using advanced language models.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Leverage computer vision to improve digital accessibility of government websites.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Fine-tune LLM for a consulting firm to optimize finance data analysis.</div></div></div><div data-v-69ac199c="" class="q-item q-item-type row no-wrap q-item--dark col-12" role="listitem"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Advance marketing strategies by fine-tuning text-to-image models for style transferring.</div></div></div></div></div></div><div class="q-scrollarea__bar q-scrollarea__bar--v absolute-right" aria-hidden="true"></div><div class="q-scrollarea__bar q-scrollarea__bar--h absolute-bottom q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--v absolute-right" aria-hidden="true" style="top: 0px; height: 98px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="left: 0px; width: 667px;"></div></div></div></div></div></div><div data-v-69ac199c="" class="row q-px-lg q-mt-xl q-pb-md non-selectable justify-center"><div data-v-69ac199c="" class="text-h2">FAQ</div></div><div data-v-69ac199c="" class="q-pa-xl row items-start q-gutter-xl justify-center"><div data-v-69ac199c="" class="q-list q-list--dark col-11 col-md-8"><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f045c133-7b84-4f84-bb34-8d6779cf4311" aria-label="Expand &quot;What does Jina AI specialize in?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What does Jina AI specialize in?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f045c133-7b84-4f84-bb34-8d6779cf4311" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Jina AI specializes in multimodal AI technologies, including embedding-tuning, embedding-serving, prompt-tuning, and prompt-serving. We leverage advanced tools like Kubernetes and serverless architectures to create robust, scalable, and production-ready solutions.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="122bf78c-9387-4e30-82c7-10abcffdf402" aria-label="Expand &quot;What types of AI does Jina AI work with?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What types of AI does Jina AI work with?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="122bf78c-9387-4e30-82c7-10abcffdf402" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Our expertise spans a broad spectrum, encompassing large language models, text, image, video, audio understanding, neural search, and generative art.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="6d00a74c-9a69-416c-9e78-02a87becd10a" aria-label="Expand &quot;Are your solutions scalable and production-ready?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Are your solutions scalable and production-ready?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="6d00a74c-9a69-416c-9e78-02a87becd10a" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Yes, our solutions are designed to be scalable and ready for production. We build our solutions using cloud-native technologies that allow for efficient scaling and reliable performance in production environments.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f0520e0c-a56a-4cff-9d99-0c385cec7988" aria-label="Expand &quot;What industries can benefit from Jina AI's solutions?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What industries can benefit from Jina AI's solutions?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f0520e0c-a56a-4cff-9d99-0c385cec7988" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Our services are versatile and adaptable, making them suitable for a wide range of industries, including e-commerce, legal tech, digital marketing, gaming, healthcare, finance, and many more.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="3c7b8553-4119-48ec-8899-d3c144237aec" aria-label="Expand &quot;How do we start a project with Jina AI?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How do we start a project with Jina AI?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="3c7b8553-4119-48ec-8899-d3c144237aec" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">You can get in touch with our sales team through the contact form on this page. We would love to discuss your project requirements and how our solutions can help your business.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="962e4cc4-1dcf-490c-9642-9df9d39fb9d2" aria-label="Expand &quot;What support do you provide after implementing a solution?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What support do you provide after implementing a solution?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="962e4cc4-1dcf-490c-9642-9df9d39fb9d2" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">We provide continuous support to ensure the smooth operation of our solutions. This includes troubleshooting, regular updates, and improvements based on your feedback and needs.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="c6f5a401-1456-4887-a472-e23692e0b7f7" aria-label="Expand &quot;What is the typical duration for a project?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the typical duration for a project?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="c6f5a401-1456-4887-a472-e23692e0b7f7" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Project duration varies depending on the complexity and scope of the project. After understanding your requirements, we can provide a more accurate estimate.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="968b999a-8f4c-4a86-8d50-2edb41636552" aria-label="Expand &quot;How does Jina AI protect my data?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How does Jina AI protect my data?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="968b999a-8f4c-4a86-8d50-2edb41636552" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Data security is our top priority. We adhere to strict data protection policies and regulations to ensure your data is secure and confidential.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="57bb027e-8ab2-49bb-8c46-75c3bb103196" aria-label="Expand &quot;What is the pricing structure for your services?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the pricing structure for your services?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="57bb027e-8ab2-49bb-8c46-75c3bb103196" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Pricing depends on the project's complexity and requirements. We offer both project-based and retainer pricing models. Please contact our sales team for more information.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="d4e9371a-22cc-4c2e-81d4-8f28ef2b9fb7" aria-label="Expand &quot;What are the licensing terms for your solutions?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What are the licensing terms for your solutions?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="d4e9371a-22cc-4c2e-81d4-8f28ef2b9fb7" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">We provide different licensing options based on the nature of the project and the client's needs. Detailed terms can be discussed with our sales team.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="e5f1ef5d-d97d-44bb-91ae-b10bba3c4c4a" aria-label="Expand &quot;What is your service area?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is your service area?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="e5f1ef5d-d97d-44bb-91ae-b10bba3c4c4a" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">We provide services globally, with our headquarters based in Berlin, Europe, and additional offices in Beijing and Shenzhen.</div></div></div></div></div><div data-v-69ac199c="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="06123561-ce30-455c-96b9-91d4f644ae6b" aria-label="Expand &quot;Do you offer onsite support?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Do you offer onsite support?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="06123561-ce30-455c-96b9-91d4f644ae6b" style="display: none;"><div data-v-69ac199c="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-69ac199c="" class="q-card__section q-card__section--vert">Yes, we offer onsite support, especially for clients located near our offices in Berlin, Beijing, and Shenzhen. For other locations, we strive to provide the best possible remote support and can arrange for onsite support if necessary.</div></div></div></div></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. All rights reserved.</div></div></div></div><footer class="q-footer q-layout__section--marginal fixed-bottom lock-blur bg-transparent print-hide"><div class="row"><div class="q-btn-group row no-wrap q-btn-group--flat inline col-12 col-md-6 justify-center"><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://discord.jina.ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-discord" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://github.com/jina-ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-github" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://huggingface.co/jinaai" target="_blank" style="font-size: 10px; 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@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Embedding API</title><meta charset="utf-8"><meta name="title" content="Embedding API"><meta name="description" content="Top-performing, 8192-token context length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/embeddings"><meta property="og:title" content="Embedding API"><meta property="og:description" content="Top-performing, 8192-token context length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial"><meta property="og:image" content="https://jina.ai/banner-embedding-api.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/embeddings"><meta property="twitter:title" content="Embedding API"><meta property="twitter:description" content="Top-performing, 8192-token context length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial"><meta property="twitter:image" content="https://jina.ai/banner-embedding-api.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Embedding API</title><meta charset="utf-8"><meta name="title" content="Embedding API"><meta name="description" content="Top-performing, 8192-token context length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/embeddings"><meta property="og:title" content="Embedding API"><meta property="og:description" content="Top-performing, 8192-token context length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial"><meta property="og:image" content="https://jina.ai/banner-embedding-api.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/embeddings"><meta property="twitter:title" content="Embedding API"><meta property="twitter:description" content="Top-performing, 8192-token context length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial"><meta property="twitter:image" content="https://jina.ai/banner-embedding-api.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/EmbeddingPage.9df14c35.js"><link rel="stylesheet" href="/assets/EmbeddingPage.2cf4eeef.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QCarousel.7c089181.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/use-cache.b0833c75.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/use-fullscreen.324b1ba3.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/useMetaTags.f561479d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/LabeledPanel.e1df998a.js"><link rel="stylesheet" href="/assets/LabeledPanel.562f7eef.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTabs.f5653f56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTable.ea86ce71.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QForm.c9044a42.js"><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
       uc.reloadOnOptIn('BJz7qNsdj-7'); // reload page on YouTube opt-in</script><style prerender-ignore>.uc-embedding-container {
       min-height: 100% !important;
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@@ -11,7 +11,7 @@
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jerboa</div><div class="q-item__label q-item__label--caption text-caption">An experimental finetuner for open-source LLMs</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="3902253e-2113-46e0-baf4-cf75d6aef1a4" aria-label="Expand &quot;Company&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><span class="q-icon" aria-hidden="true" role="presentation"><img src="/J.svg"></span></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Company</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="3902253e-2113-46e0-baf4-cf75d6aef1a4" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/about-us"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">About us</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/contact-sales"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Contact sales</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/open-day"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Open day</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/internship"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Intern program</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://jobs.lever.co/jina-ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Join us</div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">open_in_new</i></div></div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div></div></div></div><div class="q-scrollarea__bar q-scrollarea__bar--v absolute-right q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__bar q-scrollarea__bar--h absolute-bottom q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--v absolute-right q-scrollarea__thumb--invisible" aria-hidden="true" style="top: 0px; height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><div data-v-56f00a36="" class="row items-center embedding-banner q-pa-xl"><div data-v-56f00a36="" class="" style="max-width: 600px;"><h2 data-v-56f00a36="" class="text-weight-bold q-mt-xl q-py-xl text-h2">Embeddings</h2><div data-v-56f00a36="" class="text-body2 text-grey-5">The only open-source embedding model that supports 8192-token context length, putting it on par with OpenAI's proprietary Ada 22 model, in both capabilities and performance on the Massive Text Embedding Benchmark (MTEB).</div></div><div data-v-56f00a36="" class="col-12 row"><div data-v-56f00a36="" class="q-item q-item-type row no-wrap q-item--dark col-12 col-sm-6 col-md-3" role="listitem"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow q-ma-sm bg-transparent lock-blur q-pa-md"><div data-v-56f00a36="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-56f00a36="" class="q-item__section column q-item__section--main justify-center"><div data-v-56f00a36="" class="q-item__label text-h5 q-mb-xl">8192 tokens</div><div data-v-56f00a36="" class="q-item__label q-item__label--caption text-caption">World's first open-source embedding model with support for a groundbreaking 8192-token context length. Imagine embedding an entire chapter in a single step!</div></div></div></div></div><div data-v-56f00a36="" class="q-item q-item-type row no-wrap q-item--dark col-12 col-sm-6 col-md-3" role="listitem"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow q-ma-sm bg-transparent lock-blur q-pa-md"><div data-v-56f00a36="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-56f00a36="" class="q-item__section column q-item__section--main justify-center"><div data-v-56f00a36="" class="q-item__label text-h5 q-mb-xl">Drop-in OpenAI Alternative</div><div data-v-56f00a36="" class="q-item__label q-item__label--caption text-caption">Achieve top-tier performance and full compatibility with OpenAI. Our model ensures smooth integration with your current workflow, offering a hassle-free transition.</div></div></div></div></div><div data-v-56f00a36="" class="q-item q-item-type row no-wrap q-item--dark col-12 col-sm-6 col-md-3" role="listitem"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow q-ma-sm bg-transparent lock-blur q-pa-md"><div data-v-56f00a36="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-56f00a36="" class="q-item__section column q-item__section--main justify-center"><div data-v-56f00a36="" class="q-item__label text-h5 q-mb-xl">80% cheaper</div><div data-v-56f00a36="" class="q-item__label q-item__label--caption text-caption">Begin with complimentary tokens and benefit from a streamlined purchase process. Experience the same powerful embedding capabilities at a fifth of the cost of OpenAI.</div></div></div></div></div></div></div><div data-v-56f00a36="" class="q-pa-xl"><div data-v-56f00a36="" class="row q-mt-xl q-py-xl justify-center"><div data-v-56f00a36="" class="q-mb-lg q-pb-md"><div data-v-56f00a36="" class="text-h2 text-white q-mb-lg text-center justify-center">Embedding API</div></div></div><div data-v-56f00a36="" class="q-my-xl text-center text-grey-5 text-h6 text-weight-light">Try our world-class embedding models to improve your search and RAG systems. Start with a free trial!</div><div data-v-56f00a36="" class="row justify-center"><div data-v-56f00a36="" class="col-12 col-md-9"><div class="full-width"><label class="q-field row no-wrap items-start q-field--standout q-input q-field--labeled q-field--dark q-field--with-bottom q-field--readonly full-width" for="f_ab3ebab8-1853-48ab-8c20-be0c37b85ae8" aria-readonly="true"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__prepend q-field__marginal row no-wrap items-center"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">refresh</i></span></button></div><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder ellipsis" tabindex="0" aria-label="API key" id="f_ab3ebab8-1853-48ab-8c20-be0c37b85ae8" readonly="" type="text" style="font-family: monospace;"><div class="q-field__label no-pointer-events absolute ellipsis">API key</div></div><div class="q-field__append q-field__marginal row no-wrap items-center"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text- q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">content_copy</i></span></button></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"><div>Each new key has some free tokens for you to try out. You can top up your key at any time. Make sure to store your API key at a safe place!</div></div></div></div></label></div><div class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow full-width q-mt-xl"><div class="q-tabs row no-wrap items-center q-tabs--not-scrollable q-tabs--horizontal q-tabs__arrows--inside q-tabs--mobile-without-arrows" role="tablist"><div class="q-tabs__content scroll--mobile row no-wrap items-center self-stretch hide-scrollbar relative-position q-tabs__content--align-left"><div class="q-tab relative-position self-stretch flex flex-center text-center q-tab--active text-primary q-focusable q-hoverable cursor-pointer" tabindex="0" role="tab" aria-selected="true"><div class="q-focus-helper" tabindex="-1"></div><div class="q-tab__content self-stretch flex-center relative-position q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon notranslate material-icons q-tab__icon" aria-hidden="true" role="presentation">code</i><div class="q-tab__label">code</div></div><div class="q-tab__indicator absolute-bottom text-primary"></div></div><div class="q-tab relative-position self-stretch flex flex-center text-center q-tab--inactive q-focusable q-hoverable cursor-pointer" tabindex="-1" role="tab" aria-selected="false"><div class="q-focus-helper" tabindex="-1"></div><div class="q-tab__content self-stretch flex-center relative-position q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon notranslate material-icons q-tab__icon" aria-hidden="true" role="presentation">shopping_cart</i><div class="q-tab__label">Top up</div></div><div class="q-tab__indicator absolute-bottom text-primary"></div></div><div class="q-space"></div><a class="q-btn q-btn-item non-selectable no-outline q-btn--standard q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch" tabindex="0" href="/embeddings#faq" style="font-size: 14px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row no-wrap text-no-wrap"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">help_outline</i><span class="block">faq</span></span></a></div><i class="q-icon fas fa-chevron-left q-tabs__arrow q-tabs__arrow--left absolute q-tab__icon" aria-hidden="true" role="presentation"> </i><i class="q-icon fas fa-chevron-right q-tabs__arrow q-tabs__arrow--right absolute q-tab__icon q-tabs__arrow--faded" aria-hidden="true" role="presentation"> </i></div><hr class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div class="q-tab-panels q-panel-parent q-tab-panels--dark q-dark"><div class="q-panel scroll" role="tabpanel" style="--q-transition-duration:300ms;"><div class="q-tab-panel" role="tabpanel"><div class="row q-mb-md q-pa-none"><div class="row q-gutter-sm"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons cursor-pointer" aria-hidden="true" role="presentation">help_outline</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label q-item__label--overline text-overline row items-center">Available tokens</div><div class="q-item__label">0</div></div></div><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">sync</i></span></button></div><div class="q-space"></div><div class="row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch q-btn--square q-btn-dropdown q-btn-dropdown--simple" tabindex="0" type="button" aria-expanded="false" aria-haspopup="true" aria-controls="fb109176-3b5f-4c37-a771-392f4fb8326c" aria-label="Expand"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row no-wrap text-no-wrap"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">view_in_ar</i><div class="full-width ellipsis q-pl-md"></div><i class="q-icon fas fa-caret-down q-btn-dropdown__arrow q-btn-dropdown__arrow-container" aria-hidden="true" role="presentation"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch q-btn--square q-btn-dropdown q-btn-dropdown--simple" tabindex="0" type="button" aria-expanded="false" aria-haspopup="true" aria-controls="b0b5f0c4-f7f1-4a2e-869a-ea3ab27e8190" aria-label="Expand"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row no-wrap text-no-wrap"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">data_object</i><div class="full-width ellipsis q-pl-md">curl</div><i class="q-icon fas fa-caret-down q-btn-dropdown__arrow q-btn-dropdown__arrow-container" aria-hidden="true" role="presentation"> </i></span></button></div></div><hr class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div class="q-py-lg q-px-md" style="position: relative;"><div class="q-markdown"><pre class="q-markdown--code q-markdown--code__inner language-bash"><code><span class="token function">curl</span> https://api.jina.ai/v1/embeddings <span class="token punctuation">\</span>
+    gtag('config', 'G-9T52NXDS9T');</script></head><body class="desktop no-touch body--dark"><div id="q-app" data-v-app class="hidden"><div class="q-layout q-layout--standard" tabindex="-1" style="min-height: 600px;"><header class="q-header q-layout__section--marginal fixed-top text-white lock-blur bg-transparent print-hide"><div class="q-toolbar row no-wrap items-center q-px-none" role="toolbar"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch" tabindex="0" type="button" style="padding: 24px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">reorder</i></span></button><hr class="q-separator q-separator--vertical q-separator--dark" aria-orientation="vertical"><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch" tabindex="0" href="/" style="font-size: 32px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="q-icon" aria-hidden="true" role="img"><img src="/Jina - Dark.svg"></span></span></a><div class="q-space"></div><label class="q-field row no-wrap items-start q-field--borderless q-select q-field--auto-height q-select--without-input q-select--without-chips q-select--single q-field--float q-field--dense q-field--dark" for="f_9ee2304d-0086-49bd-8503-53584b64cc83"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__prepend q-field__marginal row no-wrap items-center"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">language</i></div><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><div class="q-field__native row items-center"><span>English</span><input class="q-select__focus-target" id="f_9ee2304d-0086-49bd-8503-53584b64cc83" readonly="" tabindex="0" role="combobox" aria-readonly="false" aria-autocomplete="none" aria-expanded="false" aria-controls="f_9ee2304d-0086-49bd-8503-53584b64cc83_lb"></div></div><div class="q-field__append q-field__marginal row no-wrap items-center q-anchor--skip"><i class="q-icon fas fa-caret-down q-select__dropdown-icon" aria-hidden="true" role="presentation"> </i></div></div></div></label></div></header><div class="q-drawer-container"><div class="q-drawer__opener fixed-left" aria-hidden="true"></div><div class="fullscreen q-drawer__backdrop hidden" aria-hidden="true" style="background-color: rgba(0, 0, 0, 0);"></div><aside class="q-drawer q-drawer--left q-drawer--bordered q-drawer--dark q-dark q-layout--prevent-focus fixed q-drawer--on-top q-drawer--mobile q-drawer--top-padding" style="width: 300px; transform: translateX(-300px);"><div class="q-drawer__content fit scroll"><div class="q-scrollarea q-scrollarea--dark fit"><div class="q-scrollarea__container scroll relative-position fit hide-scrollbar"><div class="q-scrollarea__content absolute"><div class="q-list q-list--dark q-list--padding"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/news"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">notifications</i></div></div></div><div class="q-item__section column q-item__section--main justify-center">News</div></a><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="9e4698d6-e03e-4682-889d-71f4db548c53" aria-label="Expand &quot;For Enterprises&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Enterprises</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="9e4698d6-e03e-4682-889d-71f4db548c53" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/embeddings"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Embeddings</div><div class="q-item__label q-item__label--caption text-caption">Our world-class embeddings for your search and RAG systems</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="9e32b55b-1fd9-4bae-bfd7-ea4cc7c83495" aria-label="Expand &quot;For Power Users&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Power Users</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="9e32b55b-1fd9-4bae-bfd7-ea4cc7c83495" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://promptperfect.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://promptperfect.jina.ai/PromptPerfect-light.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">PromptPerfect</div><div class="q-item__label q-item__label--caption text-caption">Premier tool for prompt engineering</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://scenex.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://scenex.jina.ai/SceneX - Light.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">SceneXplain</div><div class="q-item__label q-item__label--caption text-caption">Leading AI solution for image captions and video summaries</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://bestbanner.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://bestbanner.jina.ai/bestbanner-light.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">BestBanner</div><div class="q-item__label q-item__label--caption text-caption">Blog to banner, without the prompts!</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://chat.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://chat.jina.ai/JinaChat - Light.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="fae5928c-110c-481c-b67c-b664404d5818" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="fae5928c-110c-481c-b67c-b664404d5818" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jerboa</div><div class="q-item__label q-item__label--caption text-caption">An experimental finetuner for open-source LLMs</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f515e7ae-bd0f-413a-81c2-a6396f36cbed" aria-label="Expand &quot;Company&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><span class="q-icon" aria-hidden="true" role="presentation"><img src="/J.svg"></span></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Company</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f515e7ae-bd0f-413a-81c2-a6396f36cbed" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/about-us"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">About us</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/contact-sales"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Contact sales</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/open-day"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Open day</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/internship"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Intern program</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://jobs.lever.co/jina-ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Join us</div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">open_in_new</i></div></div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div></div></div></div><div class="q-scrollarea__bar q-scrollarea__bar--v absolute-right q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__bar q-scrollarea__bar--h absolute-bottom q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--v absolute-right q-scrollarea__thumb--invisible" aria-hidden="true" style="top: 0px; height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><div data-v-ee5d8eb8="" class="row items-center embedding-banner q-pa-xl"><div data-v-ee5d8eb8="" class="" style="max-width: 600px;"><h2 data-v-ee5d8eb8="" class="text-weight-bold q-mt-xl q-py-xl text-h2">Embeddings</h2><div data-v-ee5d8eb8="" class="text-body2 text-grey-5">The only open-source embedding model that supports 8192-token context length, putting it on par with OpenAI's proprietary Ada 22 model, in both capabilities and performance on the Massive Text Embedding Benchmark (MTEB).</div></div><div data-v-ee5d8eb8="" class="col-12 row"><div data-v-ee5d8eb8="" class="q-item q-item-type row no-wrap q-item--dark col-12 col-sm-6 col-md-3" role="listitem"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow q-ma-sm bg-transparent lock-blur q-pa-md"><div data-v-ee5d8eb8="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-ee5d8eb8="" class="q-item__section column q-item__section--main justify-center"><div data-v-ee5d8eb8="" class="q-item__label text-h5 q-mb-xl">8192 tokens</div><div data-v-ee5d8eb8="" class="q-item__label q-item__label--caption text-caption">World's first open-source embedding model with support for a groundbreaking 8192-token context length. Imagine embedding an entire chapter in a single step!</div></div></div></div></div><div data-v-ee5d8eb8="" class="q-item q-item-type row no-wrap q-item--dark col-12 col-sm-6 col-md-3" role="listitem"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow q-ma-sm bg-transparent lock-blur q-pa-md"><div data-v-ee5d8eb8="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-ee5d8eb8="" class="q-item__section column q-item__section--main justify-center"><div data-v-ee5d8eb8="" class="q-item__label text-h5 q-mb-xl">Drop-in OpenAI Alternative</div><div data-v-ee5d8eb8="" class="q-item__label q-item__label--caption text-caption">Achieve top-tier performance and full compatibility with OpenAI. Our model ensures smooth integration with your current workflow, offering a hassle-free transition.</div></div></div></div></div><div data-v-ee5d8eb8="" class="q-item q-item-type row no-wrap q-item--dark col-12 col-sm-6 col-md-3" role="listitem"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow q-ma-sm bg-transparent lock-blur q-pa-md"><div data-v-ee5d8eb8="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-ee5d8eb8="" class="q-item__section column q-item__section--main justify-center"><div data-v-ee5d8eb8="" class="q-item__label text-h5 q-mb-xl">80% cheaper</div><div data-v-ee5d8eb8="" class="q-item__label q-item__label--caption text-caption">Begin with complimentary tokens and benefit from a streamlined purchase process. Experience the same powerful embedding capabilities at a fifth of the cost of OpenAI.</div></div></div></div></div></div></div><div data-v-ee5d8eb8="" class="q-pa-xl"><div data-v-ee5d8eb8="" class="row q-mt-xl q-py-xl justify-center"><div data-v-ee5d8eb8="" class="q-mb-lg q-pb-md"><div data-v-ee5d8eb8="" class="text-h2 text-white q-mb-lg text-center justify-center">Embedding API</div></div></div><div data-v-ee5d8eb8="" class="q-my-xl text-center text-grey-5 text-h6 text-weight-light">Try our world-class embedding models to improve your search and RAG systems. Start with a free trial!</div><div data-v-ee5d8eb8="" class="row justify-center"><div data-v-ee5d8eb8="" class="col-12 col-md-9"><div class="full-width"><label class="q-field row no-wrap items-start q-field--standout q-input q-field--labeled q-field--dark q-field--with-bottom q-field--readonly full-width" for="f_cf0d37a1-d0b4-47a8-b012-2be4fb9cc16f" aria-readonly="true"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__prepend q-field__marginal row no-wrap items-center"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">refresh</i></span></button></div><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder ellipsis" tabindex="0" aria-label="API key" id="f_cf0d37a1-d0b4-47a8-b012-2be4fb9cc16f" readonly="" type="text" style="font-family: monospace;"><div class="q-field__label no-pointer-events absolute ellipsis">API key</div></div><div class="q-field__append q-field__marginal row no-wrap items-center"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text- q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">content_copy</i></span></button></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"><div>Each new key has some free tokens for you to try out. You can top up your key at any time. Make sure to store your API key at a safe place!</div></div></div></div></label></div><div class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow full-width q-mt-xl"><div class="q-tabs row no-wrap items-center q-tabs--not-scrollable q-tabs--horizontal q-tabs__arrows--inside q-tabs--mobile-without-arrows" role="tablist"><div class="q-tabs__content scroll--mobile row no-wrap items-center self-stretch hide-scrollbar relative-position q-tabs__content--align-left"><div class="q-tab relative-position self-stretch flex flex-center text-center q-tab--active text-primary q-focusable q-hoverable cursor-pointer" tabindex="0" role="tab" aria-selected="true"><div class="q-focus-helper" tabindex="-1"></div><div class="q-tab__content self-stretch flex-center relative-position q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon notranslate material-icons q-tab__icon" aria-hidden="true" role="presentation">code</i><div class="q-tab__label">code</div></div><div class="q-tab__indicator absolute-bottom text-primary"></div></div><div class="q-tab relative-position self-stretch flex flex-center text-center q-tab--inactive q-focusable q-hoverable cursor-pointer" tabindex="-1" role="tab" aria-selected="false"><div class="q-focus-helper" tabindex="-1"></div><div class="q-tab__content self-stretch flex-center relative-position q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon notranslate material-icons q-tab__icon" aria-hidden="true" role="presentation">shopping_cart</i><div class="q-tab__label">Top up</div></div><div class="q-tab__indicator absolute-bottom text-primary"></div></div><div class="q-space"></div><a class="q-btn q-btn-item non-selectable no-outline q-btn--standard q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch" tabindex="0" href="/embeddings#faq" style="font-size: 14px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row no-wrap text-no-wrap"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">help_outline</i><span class="block">faq</span></span></a></div><i class="q-icon fas fa-chevron-left q-tabs__arrow q-tabs__arrow--left absolute q-tab__icon" aria-hidden="true" role="presentation"> </i><i class="q-icon fas fa-chevron-right q-tabs__arrow q-tabs__arrow--right absolute q-tab__icon q-tabs__arrow--faded" aria-hidden="true" role="presentation"> </i></div><hr class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div class="q-tab-panels q-panel-parent q-tab-panels--dark q-dark"><div class="q-panel scroll" role="tabpanel" style="--q-transition-duration:300ms;"><div class="q-tab-panel" role="tabpanel"><div class="row q-mb-md q-pa-none"><div class="row q-gutter-sm"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons cursor-pointer" aria-hidden="true" role="presentation">help_outline</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label q-item__label--overline text-overline row items-center">Available tokens</div><div class="q-item__label">0</div></div></div><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">sync</i></span></button></div><div class="q-space"></div><div class="row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch q-btn--square q-btn-dropdown q-btn-dropdown--simple" tabindex="0" type="button" aria-expanded="false" aria-haspopup="true" aria-controls="9b0272fe-c7b1-4401-a736-a0645e388ad1" aria-label="Expand"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row no-wrap text-no-wrap"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">view_in_ar</i><div class="full-width ellipsis q-pl-md"></div><i class="q-icon fas fa-caret-down q-btn-dropdown__arrow q-btn-dropdown__arrow-container" aria-hidden="true" role="presentation"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch q-btn--square q-btn-dropdown q-btn-dropdown--simple" tabindex="0" type="button" aria-expanded="false" aria-haspopup="true" aria-controls="705d2235-e5b5-4570-93c4-a63588de355b" aria-label="Expand"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row no-wrap text-no-wrap"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">data_object</i><div class="full-width ellipsis q-pl-md">curl</div><i class="q-icon fas fa-caret-down q-btn-dropdown__arrow q-btn-dropdown__arrow-container" aria-hidden="true" role="presentation"> </i></span></button></div></div><hr class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div class="q-py-lg q-px-md" style="position: relative;"><div class="q-markdown"><pre class="q-markdown--code q-markdown--code__inner language-bash"><code><span class="token function">curl</span> https://api.jina.ai/v1/embeddings <span class="token punctuation">\</span>
   <span class="token parameter variable">-H</span> <span class="token string">"Content-Type: application/json"</span> <span class="token punctuation">\</span>
   <span class="token parameter variable">-H</span> <span class="token string">"Authorization: Bearer <span class="token variable">$JINA_API_KEY</span>"</span> <span class="token punctuation">\</span>
   <span class="token parameter variable">-d</span> <span class="token string">'{
@@ -20,4 +20,4 @@
   }'</span>
 </code></pre>
 
-</div><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-amber q-btn--actionable q-focusable q-hoverable q-btn--dense q-markdown__copy" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="q-icon" aria-hidden="true" role="img"><svg viewBox="0 0 24 24"><path d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg></span></span></button></div></div></div></div></div></div></div></div><div data-v-56f00a36="" class="q-mt-xl q-pa-xl bg-dark text-center"><div data-v-56f00a36="" class="row q-mt-xl q-py-xl justify-center"><div data-v-56f00a36="" class="q-mb-lg q-pb-md"><div data-v-56f00a36="" class="text-h2 text-white q-mb-lg justify-center">On-premises deployment</div></div></div><div data-v-56f00a36="" class="row justify-center q-px-md"><div data-v-56f00a36="" class="col-12 col-md-6 text-grey-5">Deploy Jina Embeddings models in AWS Sagemaker, and soon in Microsoft Azure and Google Cloud Services, or contact our sales team to get customized Kubernetes deployments for your Virtual Private Cloud and on-premises servers.</div></div><div data-v-56f00a36="" class="row justify-center"><div data-v-56f00a36="" class="q-btn-group row no-wrap q-btn-group--outline q-btn-group--square inline q-my-xl"><a data-v-56f00a36="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="https://aws.amazon.com/marketplace/seller-profile?id=seller-stch2ludm6vgy" target="_blank" style="font-size: 24px; padding: 32px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-aws" aria-hidden="true" role="img"> </i></span></a><button data-v-56f00a36="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square disabled q-btn--no-uppercase q-btn--square" tabindex="-1" type="button" disabled="" aria-disabled="true" style="font-size: 24px; padding: 32px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-microsoft" aria-hidden="true" role="img"> </i></span></button><button data-v-56f00a36="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square disabled q-btn--no-uppercase q-btn--square" tabindex="-1" type="button" disabled="" aria-disabled="true" style="font-size: 24px; padding: 32px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-google" aria-hidden="true" role="img"> </i></span></button><a data-v-56f00a36="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="/contact-sales" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">handshake</i><span class="block">Contact sales</span></span></a></div></div></div><div data-v-56f00a36="" class="q-py-xl bg-dark row justify-center"><div data-v-56f00a36="" class="row col-10"><div class="col-12 col-md-5 column justify-start items-center"><a class="row items-center justify-start text-h2 text-white" href="#developers" style="text-decoration: none !important;">Integrations</a><div class="row text-grey-5 q-py-lg"><div class="col-12 col-md-8">Seamlessly and easily integrate the Jina Embeddings API with any of these databases, frameworks and applications below. Our tutorials will show you how.</div></div><div class="row text-grey-5 q-py-lg relative-position"><div class="col-12 col-md-8"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">LLM Orchestration</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">RAG</div></div></div></div><div class="q-img q-img--menu absolute" role="img" style="width: 100%; top: 100%; left: -40%; z-index: -1;"><div style="padding-bottom: 98.4356%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/pattern-developers.4f94c0e3.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div class="col-12 col-md-7 row justify-center"><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-MongoDB.982c1a31.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">MongoDB</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-MongoDB.982c1a31.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">MongoDB</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Weaviate.7149e9ab.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Weaviate</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Weaviate.7149e9ab.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Weaviate</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Qdrant.934fd07b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Qdrant</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Qdrant.934fd07b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Qdrant</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="data:image/png;base64,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" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Pinecone</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="data:image/png;base64,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" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Pinecone</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Chroma.2b9ab43a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Chroma</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Chroma.2b9ab43a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Chroma</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Langchain.f2ee033d.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Langchain</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">LLM Orchestration</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Langchain.f2ee033d.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Langchain</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-LlamaIndex.480689aa.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">LlamaIndex</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">LLM Orchestration</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">RAG</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-LlamaIndex.480689aa.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">LlamaIndex</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Dify.8dc6e6d4.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Dify</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">LLM Orchestration</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">RAG</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Dify.8dc6e6d4.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Dify</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-deepset.d499330a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">Haystack</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">RAG</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-deepset.d499330a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Haystack</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-SuperDuperDB.94465a4c.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-body">SuperDuperDB</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-SuperDuperDB.94465a4c.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">SuperDuperDB</div></div></div></div></div></div><div data-v-56f00a36="" class="q-my-xl" id="learning"><div data-v-56f00a36="" class="row q-mt-xl q-py-xl text-center justify-center text-h2">Learning about Embeddings</div><div data-v-56f00a36="" class="row justify-center q-px-md"><div data-v-56f00a36="" class="text-grey-5 text-center col-12 col-md-6">Where to start with embeddings? We've got you covered. Learn about embeddings from the ground up with our comprehensive guide.</div></div><div data-v-56f00a36="" class="row justify-center items-center q-pa-xl"><div data-v-56f00a36="" class="q-carousel q-panel-parent q-carousel--with-padding q-carousel--dark q-dark q-carousel--navigation-bottom bg-transparent" style="height: auto;"><div class="q-carousel__slides-container"><div class="q-panel scroll" role="tabpanel" style="--q-transition-duration:300ms;"><div data-v-56f00a36="" class="q-carousel__slide column"><div data-v-56f00a36="" class="row fit justify-center items-center no-wrap"><div data-v-56f00a36="" class="col-12 col-sm-6 col-md-4 col-xl-3 self-stretch q-pa-sm"><div data-v-4867f981="" data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow cursor-pointer q-hoverable full-height" style="overflow: hidden; text-decoration: none !important;"><span data-v-4867f981="" class="q-focus-helper"></span><div data-v-4867f981="" class="q-card__section q-card__section--vert q-pa-none"><div data-v-4867f981="" class="q-img q-img--menu" role="img" style="height: 200px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="200px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--18--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert" style="height: 250px;"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center text-h6 text-weight-light"><div data-v-4867f981="" class="q-item__label" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Embeddings in Depth</div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This second article in our series on embedding technology is much more concrete. It explains where embeddings come from and how they are used.</div></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-4867f981="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label">Scott Martens</div><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption">November 15, 2023 • 17 minutes read</div></div></div></div></div></div><div data-v-56f00a36="" class="col-12 col-sm-6 col-md-4 col-xl-3 self-stretch q-pa-sm"><div data-v-4867f981="" data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow cursor-pointer q-hoverable full-height" style="overflow: hidden; text-decoration: none !important;"><span data-v-4867f981="" class="q-focus-helper"></span><div data-v-4867f981="" class="q-card__section q-card__section--vert q-pa-none"><div data-v-4867f981="" class="q-img q-img--menu" role="img" style="height: 200px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="200px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--19-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert" style="height: 250px;"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center text-h6 text-weight-light"><div data-v-4867f981="" class="q-item__label" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">How Embeddings Drive AI: A Comprehensive Presentation</div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Embeddings are a core concept and technology in AI, present in some form across the spectrum of AI applications. Properly understanding and mastering this technology positions you to leverage AI models to add the most value to your business.</div></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-4867f981="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label">Scott Martens</div><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption">October 19, 2023 • 7 minutes read</div></div></div></div></div></div></div></div></div></div><div class="q-carousel__control q-carousel__navigation no-wrap absolute flex q-carousel__navigation--buttons q-carousel__navigation--bottom"><div class="q-carousel__navigation-inner flex flex-center no-wrap"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable q-btn--dense q-carousel__navigation-icon q-carousel__navigation-icon--active" tabindex="0" type="button" style="font-size: 10px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-circle" aria-hidden="true" role="img"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable q-btn--dense q-carousel__navigation-icon q-carousel__navigation-icon--inactive" tabindex="0" type="button" style="font-size: 10px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-circle" aria-hidden="true" role="img"> </i></span></button></div></div></div></div></div><div data-v-56f00a36="" class="q-my-xl"><div data-v-56f00a36="" class="row q-mt-xl q-py-xl text-center justify-center text-h2">Our Publications</div><div data-v-56f00a36="" class="row justify-center q-px-md"><div data-v-56f00a36="" class="text-grey-5 text-center col-12 col-md-6">To understand how our large language models were trained from scratch for embedding tasks, check out our latest research and publications. Meet our team at the EMNLP, ACL, SIGIR, NeurIPS, and ICML conferences.</div></div><div data-v-56f00a36="" class="row q-my-xl justify-center"><div data-v-56f00a36="" class="col-11 col-md-7 col-lg-8"><div class="q-card q-card--dark q-dark q-card--flat no-shadow q-hoverable cursor-pointer q-mb-md"><span class="q-focus-helper"></span><div class="q-linear-progress text-primary research-card__progress" role="progressbar" aria-valuemin="0" aria-valuemax="1" aria-valuenow="100" style="font-size: 4px; --q-linear-progress-speed:2100ms;"><div class="q-linear-progress__track absolute-full q-linear-progress__track--with-transition q-linear-progress__track--dark" style="transform: scale3d(1, 1, 1);"></div><div class="q-linear-progress__model absolute-full q-linear-progress__model--with-transition q-linear-progress__model--determinate" style="transform: scale3d(100, 1, 1);"></div></div><div class="q-card__section q-card__section--horiz row no-wrap q-pa-none"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-pa-lg col-9" role="listitem" tabindex="0" href="https://arxiv.org/abs/2310.19923" target="_blank"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-mb-xl"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">2023.11</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><span class="q-icon q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"><img src="/arxiv_logo.svg"></span><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">arXiv</div></div></div></div><div class="q-space"></div><div class="q-item__label text-h6 q-mb-lg">Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Text embedding models have emerged as powerful tools for transforming sentences into fixed-sized feature vectors that encapsulate semantic information. While these models are essential for tasks like information retrieval, semantic clustering, and text re-ranking, most existing open-source models, especially those built on architectures like BERT, struggle to represent lengthy documents and often resort to truncation. One common approach to mitigate this challenge involves splitting documents into smaller paragraphs for embedding. However, this strategy results in a much larger set of vectors, consequently leading to increased memory consumption and computationally intensive vector searches with elevated latency.</div></div></a><div class="q-img q-img--menu research-card__img" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/paper_1.8ed04d7d.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow q-hoverable cursor-pointer q-mb-md"><span class="q-focus-helper"></span><div class="q-linear-progress text-primary research-card__progress" role="progressbar" aria-valuemin="0" aria-valuemax="1" aria-valuenow="100" style="font-size: 4px; --q-linear-progress-speed:2100ms;"><div class="q-linear-progress__track absolute-full q-linear-progress__track--with-transition q-linear-progress__track--dark" style="transform: scale3d(1, 1, 1);"></div><div class="q-linear-progress__model absolute-full q-linear-progress__model--with-transition q-linear-progress__model--determinate" style="transform: scale3d(100, 1, 1);"></div></div><div class="q-card__section q-card__section--horiz row no-wrap q-pa-none"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-pa-lg col-9" role="listitem" tabindex="0" href="https://arxiv.org/abs/2307.11224" target="_blank"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-mb-xl"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">2023.8</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">EMNLP 2023</div></div></div></div><div class="q-space"></div><div class="q-item__label text-h6 q-mb-lg">Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina Embeddings constitutes a set of high-performance sentence embedding models adept at translating textual inputs into numerical representations, capturing the semantics of the text. These models excel in applications like dense retrieval and semantic textual similarity. This paper details the development of Jina Embeddings, starting with the creation of high-quality pairwise and triplet datasets. It underlines the crucial role of data cleaning in dataset preparation, offers in-depth insights into the model training process, and concludes with a comprehensive performance evaluation using the Massive Text Embedding Benchmark (MTEB).</div></div></a><div class="q-img q-img--menu research-card__img" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/paper_2.59e1399a.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div></div><div data-v-56f00a36="" class="bg-dark q-pt-xl" id="faq"><div data-v-56f00a36="" class="text-h2 text-center non-selectable q-my-xl">FAQ</div><form class="q-form row justify-center q-mb-xl"><label class="q-field row no-wrap items-start q-field--filled q-input q-field--square q-field--labeled q-field--dark q-field--with-bottom col-12 col-sm-10 col-md-8 col-lg-6" for="f_f4d2c558-4680-4c99-8037-52a008e023ff"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__prepend q-field__marginal row no-wrap items-center"><span class="q-icon" aria-hidden="true" role="presentation"><img src="/J.svg"></span></div><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" aria-label="Please describe your problem" placeholder="what distinguishes the small model from the base model?" id="f_f4d2c558-4680-4c99-8037-52a008e023ff" type="text"><div class="q-field__label no-pointer-events absolute ellipsis">Please describe your problem</div></div><div class="q-field__append q-field__marginal row no-wrap items-center"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" type="submit"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">send</i></span></button></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></form><div data-v-56f00a36="" class="row justify-center"><div data-v-56f00a36="" class="q-list q-list--dark col-11 col-md-6 q-py-xl"><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="d49a2f91-c519-4781-98b4-cd9755618cde" aria-label="Expand &quot;What distinguishes the Small model from the Base model?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What distinguishes the Small model from the Base model?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="d49a2f91-c519-4781-98b4-cd9755618cde" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">Both the Small and Base models are crafted utilizing the robust JinaBert architecture, differing primarily in their scale. The Small model comprises 33 million parameters, whereas the Base model comprises 137 million parameters. While the Base model delivers superior embedding performance, it incurs a minor trade-off in throughput (Queries per second), making the Small model a more agile option for certain use cases. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="beddcf39-4acf-47a6-b8e2-d8496ace3229" aria-label="Expand &quot;What is the anticipated Queries Per Second (QPS) for both the Small and Base models?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the anticipated Queries Per Second (QPS) for both the Small and Base models?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="beddcf39-4acf-47a6-b8e2-d8496ace3229" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">The QPS is contingent upon the length of the user-input sentences and the chosen model. For the Base model, the QPS can range from 4 to 100, while for the Small model, the range is between 10 to 300. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="7e6a6768-14e5-4155-8a51-f2ee74bbe910" aria-label="Expand &quot;Which languages are supported by your models?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Which languages are supported by your models?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="7e6a6768-14e5-4155-8a51-f2ee74bbe910" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">At present, our models exclusively support English. However, we are actively expanding our linguistic capabilities by training additional language-specific models. These forthcoming models are being designed to offer the same qualitative and quantitative advantages as the jina-embeddings-v2. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="b7036095-f18c-4d12-acda-e9fd1420f27b" aria-label="Expand &quot;What is the maximum number of characters I can input in a single sentence?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the maximum number of characters I can input in a single sentence?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="b7036095-f18c-4d12-acda-e9fd1420f27b" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">Our models are highly capable, allowing for an input length of 8192 tokens, which is significantly longer than what most other models offer. A token can be as short as one character or as long as one word (e.g., 'a' or 'apple'). The number of characters you can input into a sentence depends on the length and complexity of the words used. This extended input length of jina-embedddings-v2 models enables more comprehensive text analysis and higher accuracy in understanding the context, especially in scenarios dealing with extensive textual data. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="8aea25a5-c240-4c8f-8914-b574f8897256" aria-label="Expand &quot;What is the maximum number of sentences I can include in a single request?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the maximum number of sentences I can include in a single request?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="8aea25a5-c240-4c8f-8914-b574f8897256" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">A single API call can accommodate up to 2048 sentences or texts, allowing for extensive text analysis in one go. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="d9052da9-ccdf-465c-8ab3-37b5b4dac023" aria-label="Expand &quot;On what basis is the Base model characterized as state-of-the-art?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">On what basis is the Base model characterized as state-of-the-art?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="d9052da9-ccdf-465c-8ab3-37b5b4dac023" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">Our assertion stems from rigorous assessments conducted under the open-source evaluation framework, Massive Text Embedding Benchmark (MTEB). Our Base model has achieved an average rank of 17th on this leaderboard, with particularly impressive performance in core tasks like classification, summarization, and text-similarity. Notably, it stands out as the sole open-source model that supports an extensive 8192 token input context length, a sign of state-of-the-art performance. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f1fd9a47-d689-4fc7-9f18-a1f5f5890407" aria-label="Expand &quot;How do Jina Embeddings models compare to OpenAI's text-embedding-ada002 model?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How do Jina Embeddings models compare to OpenAI's text-embedding-ada002 model?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f1fd9a47-d689-4fc7-9f18-a1f5f5890407" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">According to the MTEB Leaderboard, our Base model holds its ground against OpenAI’s text-embedding-ada-002, showcasing comparable performance on average (ranking 17th versus 15th). Moreover, our Base model surpasses OpenAI’s offering in several tasks including classification, pair-classification, re-ranking, and summarization. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="726139e1-d277-4583-867e-df4feae3e7ca" aria-label="Expand &quot;I am currently utilizing OpenAI's text-embedding-ada-002. How seamless is the transition to your solution?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">I am currently utilizing OpenAI's text-embedding-ada-002. How seamless is the transition to your solution?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="726139e1-d277-4583-867e-df4feae3e7ca" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">Transitioning is made effortless as our API endpoint, https://api.jina.ai/v1/embeddings, aligns perfectly with the input and output JSON schemas of OpenAI’s endpoint for the text-embeddings-ada-002 model. This compatibility allows users to integrate our model as a direct drop-in replacement for text-embeddings-ada-002 when utilizing OpenAI’s endpoint. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="125de8d2-1f65-4798-a16b-1818503d96f4" aria-label="Expand &quot;Is the billing based on the number of sentences or requests?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is the billing based on the number of sentences or requests?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="125de8d2-1f65-4798-a16b-1818503d96f4" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">Our billing model is based on the total number of tokens processed. Users have the flexibility to distribute these tokens across as many sentences as they desire, providing a cost-effective and adaptable solution for varying text analysis needs. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="86b21842-e489-4b3c-9d6e-1f63f746c04b" aria-label="Expand &quot;Is there a free trial available for new users?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is there a free trial available for new users?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="86b21842-e489-4b3c-9d6e-1f63f746c04b" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">Yes, we welcome new users by offering a complimentary trial for embedding up to 10,000 tokens using any of our models. An auto-generated API key facilitates this trial. Upon exhaustion of the free token limit, users can effortlessly purchase top-ups for their existing API keys via the designated 'Top-Up' tab. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="8e389cf5-ca66-4e6e-807a-ebbd64350539" aria-label="Expand &quot;Do API keys have an expiration date?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Do API keys have an expiration date?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="8e389cf5-ca66-4e6e-807a-ebbd64350539" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">No, our API keys do not have an expiration date. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="98fa7cfc-f792-4272-8298-243f83a9938b" aria-label="Expand &quot;Is user input data utilized for training your models?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is user input data utilized for training your models?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="98fa7cfc-f792-4272-8298-243f83a9938b" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">No, we uphold a strict privacy policy and do not utilize user input data for training our models. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="18e553c5-40bb-4502-bf24-064830be70ef" aria-label="Expand &quot;Are tokens charged for failed requests?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Are tokens charged for failed requests?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="18e553c5-40bb-4502-bf24-064830be70ef" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">No, tokens are not charged in the event of failed requests. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="fcd7b336-7983-46e6-a2d1-8153e2a1750e" aria-label="Expand &quot;What payment methods are accepted?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What payment methods are accepted?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="fcd7b336-7983-46e6-a2d1-8153e2a1750e" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">We have partnered with Stripe to facilitate a smooth payment process. Through this platform, we accept various payment methods including credit cards, Google Pay, and PayPal for your convenience. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="30b9e8a1-aed4-4bbf-90b7-3ea7489006c8" aria-label="Expand &quot;Is invoicing available for token purchases?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is invoicing available for token purchases?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="30b9e8a1-aed4-4bbf-90b7-3ea7489006c8" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">Yes, upon purchasing tokens, an invoice will be sent to the email address associated with your Stripe account. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="6d694f50-d290-4a6e-a4ab-ddf09bc0b360" aria-label="Expand &quot;What should I do if I forget my API key?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What should I do if I forget my API key?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="6d694f50-d290-4a6e-a4ab-ddf09bc0b360" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">For free quota usage, you can easily generate a new API key on https://jina.ai/embeddings. If your key has been topped-up, please reach out to support AT jina.ai using your registered email for assistance. </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="9ce211e4-42c6-4b70-8487-92133a4ec9dd" aria-label="Expand &quot;Do you provide models for embedding images or audio?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Do you provide models for embedding images or audio?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="9ce211e4-42c6-4b70-8487-92133a4ec9dd" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">We are actively working on multimodal models that will cater to text, images, and audio embedding. Stay tuned for these updates! </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="bd2611a9-d517-49f5-8a81-e0b2fa1250c3" aria-label="Expand &quot;Is there an option to fine-tune Jina Embedding models using private or company data?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is there an option to fine-tune Jina Embedding models using private or company data?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="bd2611a9-d517-49f5-8a81-e0b2fa1250c3" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">While we currently do not offer fine-tuning services, we are gearing up to introduce this feature soon. Keep an eye out for this feature! </div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="4788bea5-e8c9-448e-b0ef-209f18907ef0" aria-label="Expand &quot;Can your endpoints be hosted privately on AWS, Azure, or GCP marketplaces?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Can your endpoints be hosted privately on AWS, Azure, or GCP marketplaces?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="4788bea5-e8c9-448e-b0ef-209f18907ef0" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">AWS SageMaker is available now. Soon, jina-embeddings-v2 model packages will be accessible through all major cloud service providers' platforms. <a data-v-56f00a36="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle text-primary q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://aws.amazon.com/marketplace/seller-profile?id=seller-stch2ludm6vgy" target="_blank" style="font-size: 8px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">AWS SageMaker</span><i class="q-icon on-right notranslate material-icons" aria-hidden="true" role="img">launch</i></span></a></div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="4e6a5fbb-6d15-4220-85df-0ea05a05028a" aria-label="Expand &quot;How were the jina-embeddings-v2 models trained?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How were the jina-embeddings-v2 models trained?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="4e6a5fbb-6d15-4220-85df-0ea05a05028a" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">For an in-depth understanding of our training methodology, data, and evaluations, we invite you to explore our technical report available on arXiv. <a data-v-56f00a36="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle text-primary q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://arxiv.org/abs/2310.19923" target="_blank" style="font-size: 8px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">launch</i></span></a></div></div></div></div></div><div data-v-56f00a36="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="afe13ff3-cd61-4e64-bb78-0d7a34902966" aria-label="Expand &quot;How many API requests can I make every second?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How many API requests can I make every second?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="afe13ff3-cd61-4e64-bb78-0d7a34902966" style="display: none;"><div data-v-56f00a36="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-56f00a36="" class="q-card__section q-card__section--vert">Each user can make up to 100 requests per second, allowing to input 204,800 input sentences per second. </div></div></div></div></div></div></div></div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+</div><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-amber q-btn--actionable q-focusable q-hoverable q-btn--dense q-markdown__copy" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="q-icon" aria-hidden="true" role="img"><svg viewBox="0 0 24 24"><path d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg></span></span></button></div></div></div></div></div></div></div></div><div data-v-ee5d8eb8="" class="q-mt-xl q-pa-xl bg-dark text-center"><div data-v-ee5d8eb8="" class="row q-mt-xl q-py-xl justify-center"><div data-v-ee5d8eb8="" class="q-mb-lg q-pb-md"><div data-v-ee5d8eb8="" class="text-h2 text-white q-mb-lg justify-center">On-premises deployment</div></div></div><div data-v-ee5d8eb8="" class="row justify-center q-px-md"><div data-v-ee5d8eb8="" class="col-12 col-md-6 text-grey-5">Deploy Jina Embeddings models in AWS Sagemaker, and soon in Microsoft Azure and Google Cloud Services, or contact our sales team to get customized Kubernetes deployments for your Virtual Private Cloud and on-premises servers.</div></div><div data-v-ee5d8eb8="" class="row justify-center"><div data-v-ee5d8eb8="" class="q-btn-group row no-wrap q-btn-group--outline q-btn-group--square inline q-my-xl"><a data-v-ee5d8eb8="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="https://aws.amazon.com/marketplace/seller-profile?id=seller-stch2ludm6vgy" target="_blank" style="font-size: 24px; padding: 32px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-aws" aria-hidden="true" role="img"> </i></span></a><button data-v-ee5d8eb8="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square disabled q-btn--no-uppercase q-btn--square" tabindex="-1" type="button" disabled="" aria-disabled="true" style="font-size: 24px; padding: 32px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-microsoft" aria-hidden="true" role="img"> </i></span></button><button data-v-ee5d8eb8="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square disabled q-btn--no-uppercase q-btn--square" tabindex="-1" type="button" disabled="" aria-disabled="true" style="font-size: 24px; padding: 32px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-google" aria-hidden="true" role="img"> </i></span></button><a data-v-ee5d8eb8="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="/contact-sales" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">handshake</i><span class="block">Contact sales</span></span></a></div></div></div><div data-v-ee5d8eb8="" class="q-py-xl bg-dark row justify-center"><div data-v-ee5d8eb8="" class="row col-10"><div class="col-12 col-md-5 column justify-start items-center"><a class="row items-center justify-start text-h2 text-white" href="#developers" style="text-decoration: none !important;">Integrations</a><div class="row text-grey-5 q-py-lg"><div class="col-12 col-md-8">Seamlessly and easily integrate the Jina Embeddings API with any of these databases, frameworks and applications below. Our tutorials will show you how.</div></div><div class="row text-grey-5 q-py-lg relative-position"><div class="col-12 col-md-8"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">LLM Orchestration</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">RAG</div></div></div></div><div class="q-img q-img--menu absolute" role="img" style="width: 100%; top: 100%; left: -40%; z-index: -1;"><div style="padding-bottom: 98.4356%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/pattern-developers.4f94c0e3.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div class="col-12 col-md-7 row justify-center"><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-MongoDB.982c1a31.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">MongoDB</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-MongoDB.982c1a31.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">MongoDB</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Weaviate.7149e9ab.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Weaviate</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Weaviate.7149e9ab.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Weaviate</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Qdrant.934fd07b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Qdrant</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Qdrant.934fd07b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Qdrant</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="data:image/png;base64,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" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Pinecone</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAGAAAABgCAYAAADimHc4AAAACXBIWXMAABYlAAAWJQFJUiTwAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAA98SURBVHgB7Z0L1FRVGYa3imR4R/GKSGpq3jV1kZKhmeUlY5XL0kS7sNIszcqsNMysLNQs0nRZarZSs9C8mxoVlhdULBU1WqKgqZAR4gVQUN6+h++wGM6/z5kzM+fMjD//u9a7fpjZc84++/Zd9z4h9KGjWCn0UkgaYH/eb9zJ+JJxwkorrTQ19KF6WONvZRxrnGpcZJxrvMM4KPShGljjrmxcy/hZ47+MC7Q8FhuvNa4X+lAurFHXNB5ivC4Z8Vl43fjjZHnqQxmwxtzF+Avjv1UM/zOODn1oHtaA/YxbG88yTjO+qcYwz7iHceXQh8ZgjbaR8dPGf6g1PG7c3dhrNcHSYY31YePvjf9V63jDeINxo9CH+rCG2tc4S/nLDQL4GeMrke8WRz5baBxvXCP0IR/WSG83PqVsvGi8xjgy4/tnc377Da4f+pAPa6Qvqqd+D/5sHGUcmNMB31S23Hgh+f0qoQ/ZsAbaxHhTTcM9bfyqcTMlGo39/XqkgVmS3ms8MPlNGixPU4z7hRUVcmNqnRqi7QxVSkjKDa57jWcrIkDts1sjDfxP4w6McOMnjM8rDmbIu0Ib0S9UDLmAG2bc1LhOcMcYn61fU4ypv6Fx1ZrP1k/KPWw8qebzCcZpOY61zSKfTTPOsd8gwK+3fw8xjo2UW2xcPfQmyLUMpj1CckHyd56KY5JxYMF7DTbOjFwDS3mtmnJrGK+q+Z4l6C7jrqE3wR7oy2odLAtDC97vIHkH1wJ9/9RI2SHy5QoBfHZtB7UTVS9BB4f2YvOw/DIGZhmfSRe05Qh74XT75xbGG+z/r4cOoOoO2Dy0F9uFnmv4i8E7oQes0Sfbn8mhg6isA2x0bRNciOYBoTcv4SLjmzXfIayfNT5tnB/q34+G3yDy1XPGJ0MByFXZc/in8argwvsV6yiFilDlDKADVqtTZoHxFuN5xiftQeeE5oFT7Q/G14yDjYMSzgzekUVA+HJU8rtjjTcZb7aOud/+zrD6vRHeKpBbra/Wl7FLjKQTQkmQu6oRsLsZP2Qc3sBvT1dPS5v6/c34E+OOxlVDt0MeHrxQxf30zxmPNvYPHYI8jvzXnDqiTeEMvF5uDA7sZH1zIbdkr4s8BCrizIwHxFod2YmHSgbM4fJoWVE8IHfi7WNcLXQTrELbyt0FafDZqYq7i8HDxh1Dm5F0wHbyCNuTKg5izBiZP5fbIN3REXLH17RIhX9mHGD8tnxKp4FFynpLuLGtkSruZ3yb3P/0KbkFzowouozi7j5C3RDmtEocpvgoH518z4NenYygNOgY/PpbqIPhQrt3f+MHjZfJw5cLVR+/M64dOgm5x/FLGRXcr6Ycy9RExWfCfONJ6gKNgwY1HmN8TPWB3FunketXMV1otCEZ302p+fcTxlOMd6bKYPQ8brzb9O5FoSDk6uc7jFuGksA17c++xk8aNynwE+q7OHQScg3oj5HR8XRGefJ6HkjKsCSh5hVOIUxG6MFaJvQXJdfA/9/UEib3lu6X8Rx5OCvptM5BHrWKRZ1uy/nN/vI8zkv5fcH7MOKHyQV7Wn1kWRuvJnJB7Tcj5O7rF9QYWDY/HjoNq8T6cqvxTuOcmgqel/MbNKOdVHD9lAfozzQ+oexURD4fEwpCHoE7Q55V0WiiF8CY3D90G6xSg+Quge1Ci0ga6Sj5bCkCDL8TVCcXVD5rnypwvZfl1nIsw2JyGc/YEqwCG6sCzUW+3GBxXqeeAZd6YJbQaf1zrk9W9ZU510AFfVDu30K23Bcpg9Ouc+nv8tF5iSLRpxavyww6K2nIZsBygptjz5x7YAnj34nJLlwnY+SOOFRsnHyxGXiFOmWEyS3XiUlFMMDQ4Zv26SQNQpbEaON/VA5o3AE591zVeIG8wxDibOpgQA1MlfuoevqzUAJOCe1G0lB7GiekKtSSY01uBTOi6lmf8xQ35LKAljUo574k65IfhAbFjOgXKcMylLbySY0/KrQT8uk4XL4exhoBx9ouoQnIHWP31WlMlqQfqfi+AICqyHIyIOO+yJq9lZGwK3dPjI1cl04bFtoFu9lqxmPlqles8fkMr+KI0ASShjhRPUcaqiXT/XLjNsYD1NPpxxLCcni34kA1/ryaMNLsNxsafxO5Jip3exJ85YGIryieowlYNlDVhqsFZ5rcGr2j5rosN+OTRu+flGGfQForotOOS+6f5Vp+SU2MWLmsmxS53tWhHZBrJN9Tfn4+5jtGVcsaQdLYNDBTHMG+cep7YgtpQ4wZsn/y/ZHKjj2wxO0WGoBcA4ppSqeFKiH3lW8gd7fOz3ggRijZZluFkiC3kOmELZVKH5fPxMsi9UBD2Topw1JJsu6cSDka8ojQAORyDxnxheTezAZk0IGhKsg1HXr+WmWDUfpDtXG3iTwN8ZZIXaakyuEaOT01cNDSUCdbNhrlRlx1kTC7+M7y/PssnwsCd5wa9IOXUC8s0imR+lwTKTsoGbHUlaXnkNAlKOI6Pd64d05ZBC0+c3R3fPyPBc9ofsL8+S+F6rBmiMcdeiRhWT2QWWOT34wz3h9KhF17YIs5TbkXn6XmgYOLjXA/MI4KJUIe9ozh8NAGyF0vZFLghEMtrkYNVevbQZdiZigRdr3vZNynIc2mifsi2FEMah2DCOIjQxMooir+Miyfs9ksHg/lYnbw5WZhzWekID4fqgUz7GLjyOAbTgBBJDIihoSyIdc2yKOPbfPks6LBiwtCBZAHZ94tz6zDeVdpbo48g+6ByPOhhmOrlLvbUq6G4k+PGV+vyTdOo2GgEk5Rtr/+6NBLIM+Ii+ER42ahbMh13ZjOzei/WO69ZKagGmKosBHu+/LcH46OIUl3ROglkBuBscQz1NyTQxWQByRiZj0+oY+EFQzy7LmYPwyBvEOoAoon3IIbtYJt909m/J2RtiC1Bn9Z+bJInisTc0bhazks9CIkz8om8CUJBUoFl+Sy8biMVQFXR/nxAXlA4jzFcbuqUMN61gEHHbEAolskYJ2jknV/udON67PE4F3FGCVd5abkfiglpFbuqmWh2Frgthlb1SzYXnEfDJVtKRZc4N4I+XPVM06M9lHauiv3/N6qfKCAsOM+K1mAmbFnKBvJ6Dgl46aEIUtXw+SjnlHHmhvLqCYIRAy5FG+sioVEiwDZWP6AlKeXp2Oxs+VLQmnLkDwq9j55JKxedgSGEMKv5Q3XclfD82odyMZqNES5AHoxIdO1tB0i8pgwGQrj1FgiFrODrIWWEmTlApiwKgrHAjUPlqlcD0ArFb3WSM4MbtibzR1bdCtoLqzC69qf44w4t7YNjdWR6Y4hNIM6heYxKakDSxp7j9lwzikqWyZ1Wr/gdUi1r24HvtwPU9oaJ88x4tCM19QaSCMsTTOSz8jV5Rbw4KSex8sDVa/n1INlc6/Q7ZDvy7pIjed95gF5tEWoAPKBRwdk7arESUls+qBQFbRsE8Phyd8Rcr143QYvxbVOVn3wsBPVGEg1LPWU3OS5ScvJyrZg3SdIwwmP1W3WkO9G/7V8mk1PyGa2E0ODkKexTM94IBxcLEukCo7JKDM543M8uKXZJvIlCAMrb6Y+Kldjqz1/Tr4f68ZIBc4IDUIeZcK2qB1VaB/43UdpWSLWbzMamdT1Pykem0CdZIa15KeXD7gsXxhAFmCLtOdwcGUbKyfm/AZhtlrGd3TohKQRcfWSSrJVqkwsPHqbPOsBNziGYCxwhM3SVKxYbnjuJY9tZ4FBgIVeuSumtmJsrovlyX8so/zSbUXEcteOfI9zizgCPhjykPpHysSSwvBNsS7jpzpS2Vl76PQNzwL5yGfzRVamNnXC9mivNzhppNi2npGpciwvCOmluxiZqseGBiFX/WIgDNmvphwG4tya7xcn9fxcaBLyVPtHU/dFNjEAq9N06lSK5NfY4XvDasqwNLCUTE+VYTQ2tJ9K8TQU5MTwVDlmw/nykUkj4T9CgLckiJP716qd98s1v85sS01uHsPQ5HtkxKWp0ViLn6oBFVG+gzGNGUoZXPI8VrKYkScIZgZKyxqJXH6xzrMUPSSf1Z07aVe+tzcNBCgq5THyoERWxgSfLzmUo+C9aNSYxvUXRXbGy+UJQp3kqdLOm5Bvm2JfxB6h05Dr12ng/cM2yDPPmRGok0MbuNe6xnsi1/qVCp4pGrlmvzrfI7sqf9VJ2esXB+dxrkLWqOO02/ON15vzrpEEKtS72CkknIb4amgQSefzsp/LrR5ZB/oRTPmMlaHO5JJOsrJ1Dw9sFK10QEztigk6PIIczndvcE/lY40cwpGARuAM0vcYOdAJ+2B740N2rYVFLyI3kg4wfs24sxHL9mS7xoJUOdb2Q4MPpkVJ/ZndV9jfC0n2DZ2GPCG1CFDV2CRR6ibmZJ0vnN8v3+QxTssrBfx7dKQsO+dvjzwLQr2z5wEtheKJWmlgpSKsO/5yBGVnU2Mlpy1uXBux/WXnhpLRyj6uIiOBB/uAkTcWEehGsHXqSC/OAH0w+JJYC84YRSVeIsyT+rG8xdwKt4RugeJJSXkgc+Fb8njrtp2YFXJ/UWxfMU7A0+TBfwy5qyNl5oZugjwgMVeNg4fFqYZbt6mN3C3UeUAyCGK+fNJLeFEQ638s7/Oa0E2wCq1nRE3DV1/kQLs0cBMfGtqMpIFjJ2FhHJLpfYTiBmTD/qu2QR5SxAnGaYd/l3skF9XpALZ4duQdXvIc/6wTsWKjnwzvSmZr6cdCWkXJGtg9uL6Ow42gdMxavcj06ePrXIuMBDZdE9vFZiED4x7jI43o/xnX5rUo3w097RkO3UsrCpcYx9g9Z4W3CuT+fzIICGYgL1Bba3NsDqvze5x5LBWza5aE+cloLLQzXTmCXq6VjVd9MJNxeb/1X3El1zAOlW/qyGscthzVO6eT16PU8+c8WFOeY8YQ/kTx0HIwJIly1VMkcCruHlYUyPNvyGaodw4QHbRDnWtNV+uo9CiybnydKx7IfYK/2ioP7EysemSyO5TdnbNDRejGDsCjuk2Bcljim2Z9aaMWC7fVdBQ8rZOrfIVJN3YA2s0LBcrhocxzRZN90aqWx9uXJoQK0dljduPgHTCcNTG4TjlcwlNzvkdl5NUonA/Bc+LbYUYwc3hrH53D2k6iLQORs4jWSP3+zMrOgEjQjR2Az+VKI2G/DTLKoKvfFdwmiMIajtlBBveSkGbwZ10lIf9e+tnSNqBz6AhmDp3PG5SeCSsitCz/MmatEu5kP0KveBN2175PXZ7ohCubA7HfGVw4zzBODB7SnBp6Abr+hfZJR6CasjzwHq+XW3VD9KEPfehDH5bg/0KiBLCW1REBAAAAAElFTkSuQmCC" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Pinecone</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Chroma.2b9ab43a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Chroma</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Chroma.2b9ab43a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Chroma</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Langchain.f2ee033d.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Langchain</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">LLM Orchestration</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Langchain.f2ee033d.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Langchain</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-LlamaIndex.480689aa.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">LlamaIndex</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">LLM Orchestration</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">RAG</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-LlamaIndex.480689aa.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">LlamaIndex</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Dify.8dc6e6d4.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Dify</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">LLM Orchestration</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">RAG</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-Dify.8dc6e6d4.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Dify</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-deepset.d499330a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">Haystack</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">RAG</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-deepset.d499330a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Haystack</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-SuperDuperDB.94465a4c.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-body">SuperDuperDB</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-SuperDuperDB.94465a4c.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">SuperDuperDB</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="data:image/png;base64,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" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="text-h6">Epsilla</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Store</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="data:image/png;base64,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" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Epsilla</div></div></div></div></div></div><div data-v-ee5d8eb8="" class="q-my-xl" id="learning"><div data-v-ee5d8eb8="" class="row q-mt-xl q-py-xl text-center justify-center text-h2">Learning about Embeddings</div><div data-v-ee5d8eb8="" class="row justify-center q-px-md"><div data-v-ee5d8eb8="" class="text-grey-5 text-center col-12 col-md-6">Where to start with embeddings? We've got you covered. Learn about embeddings from the ground up with our comprehensive guide.</div></div><div data-v-ee5d8eb8="" class="row justify-center items-center q-pa-xl"><div data-v-ee5d8eb8="" class="q-carousel q-panel-parent q-carousel--with-padding q-carousel--dark q-dark q-carousel--navigation-bottom bg-transparent" style="height: auto;"><div class="q-carousel__slides-container"><div class="q-panel scroll" role="tabpanel" style="--q-transition-duration:300ms;"><div data-v-ee5d8eb8="" class="q-carousel__slide column"><div data-v-ee5d8eb8="" class="row fit justify-center items-center no-wrap"><div data-v-ee5d8eb8="" class="col-12 col-sm-6 col-md-4 col-xl-3 self-stretch q-pa-sm"><div data-v-4867f981="" data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow cursor-pointer q-hoverable full-height" style="overflow: hidden; text-decoration: none !important;"><span data-v-4867f981="" class="q-focus-helper"></span><div data-v-4867f981="" class="q-card__section q-card__section--vert q-pa-none"><div data-v-4867f981="" class="q-img q-img--menu" role="img" style="height: 200px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="200px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--18--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert" style="height: 250px;"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center text-h6 text-weight-light"><div data-v-4867f981="" class="q-item__label" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Embeddings in Depth</div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This second article in our series on embedding technology is much more concrete. It explains where embeddings come from and how they are used.</div></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-4867f981="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label">Scott Martens</div><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption">November 15, 2023 • 17 minutes read</div></div></div></div></div></div><div data-v-ee5d8eb8="" class="col-12 col-sm-6 col-md-4 col-xl-3 self-stretch q-pa-sm"><div data-v-4867f981="" data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow cursor-pointer q-hoverable full-height" style="overflow: hidden; text-decoration: none !important;"><span data-v-4867f981="" class="q-focus-helper"></span><div data-v-4867f981="" class="q-card__section q-card__section--vert q-pa-none"><div data-v-4867f981="" class="q-img q-img--menu" role="img" style="height: 200px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="200px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--19-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert" style="height: 250px;"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center text-h6 text-weight-light"><div data-v-4867f981="" class="q-item__label" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">How Embeddings Drive AI: A Comprehensive Presentation</div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Embeddings are a core concept and technology in AI, present in some form across the spectrum of AI applications. Properly understanding and mastering this technology positions you to leverage AI models to add the most value to your business.</div></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-4867f981="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label">Scott Martens</div><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption">October 19, 2023 • 7 minutes read</div></div></div></div></div></div></div></div></div></div><div class="q-carousel__control q-carousel__navigation no-wrap absolute flex q-carousel__navigation--buttons q-carousel__navigation--bottom"><div class="q-carousel__navigation-inner flex flex-center no-wrap"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable q-btn--dense q-carousel__navigation-icon q-carousel__navigation-icon--active" tabindex="0" type="button" style="font-size: 10px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-circle" aria-hidden="true" role="img"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable q-btn--dense q-carousel__navigation-icon q-carousel__navigation-icon--inactive" tabindex="0" type="button" style="font-size: 10px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-circle" aria-hidden="true" role="img"> </i></span></button></div></div></div></div></div><div data-v-ee5d8eb8="" class="q-my-xl"><div data-v-ee5d8eb8="" class="row q-mt-xl q-py-xl text-center justify-center text-h2">Our Publications</div><div data-v-ee5d8eb8="" class="row justify-center q-px-md"><div data-v-ee5d8eb8="" class="text-grey-5 text-center col-12 col-md-6">To understand how our large language models were trained from scratch for embedding tasks, check out our latest research and publications. Meet our team at the EMNLP, ACL, SIGIR, NeurIPS, and ICML conferences.</div></div><div data-v-ee5d8eb8="" class="row q-my-xl justify-center"><div data-v-ee5d8eb8="" class="col-11 col-md-7 col-lg-8"><div class="q-card q-card--dark q-dark q-card--flat no-shadow q-hoverable cursor-pointer q-mb-md"><span class="q-focus-helper"></span><div class="q-linear-progress text-primary research-card__progress" role="progressbar" aria-valuemin="0" aria-valuemax="1" aria-valuenow="100" style="font-size: 4px; --q-linear-progress-speed:2100ms;"><div class="q-linear-progress__track absolute-full q-linear-progress__track--with-transition q-linear-progress__track--dark" style="transform: scale3d(1, 1, 1);"></div><div class="q-linear-progress__model absolute-full q-linear-progress__model--with-transition q-linear-progress__model--determinate" style="transform: scale3d(100, 1, 1);"></div></div><div class="q-card__section q-card__section--horiz row no-wrap q-pa-none"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-pa-lg col-9" role="listitem" tabindex="0" href="https://arxiv.org/abs/2310.19923" target="_blank"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-mb-xl"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">2023.11</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><span class="q-icon q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"><img src="/arxiv_logo.svg"></span><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">arXiv</div></div></div></div><div class="q-space"></div><div class="q-item__label text-h6 q-mb-lg">Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Text embedding models have emerged as powerful tools for transforming sentences into fixed-sized feature vectors that encapsulate semantic information. While these models are essential for tasks like information retrieval, semantic clustering, and text re-ranking, most existing open-source models, especially those built on architectures like BERT, struggle to represent lengthy documents and often resort to truncation. One common approach to mitigate this challenge involves splitting documents into smaller paragraphs for embedding. However, this strategy results in a much larger set of vectors, consequently leading to increased memory consumption and computationally intensive vector searches with elevated latency.</div></div></a><div class="q-img q-img--menu research-card__img" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/paper_1.8ed04d7d.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow q-hoverable cursor-pointer q-mb-md"><span class="q-focus-helper"></span><div class="q-linear-progress text-primary research-card__progress" role="progressbar" aria-valuemin="0" aria-valuemax="1" aria-valuenow="100" style="font-size: 4px; --q-linear-progress-speed:2100ms;"><div class="q-linear-progress__track absolute-full q-linear-progress__track--with-transition q-linear-progress__track--dark" style="transform: scale3d(1, 1, 1);"></div><div class="q-linear-progress__model absolute-full q-linear-progress__model--with-transition q-linear-progress__model--determinate" style="transform: scale3d(100, 1, 1);"></div></div><div class="q-card__section q-card__section--horiz row no-wrap q-pa-none"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-pa-lg col-9" role="listitem" tabindex="0" href="https://arxiv.org/abs/2307.11224" target="_blank"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-mb-xl"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">2023.8</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">EMNLP 2023</div></div></div></div><div class="q-space"></div><div class="q-item__label text-h6 q-mb-lg">Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina Embeddings constitutes a set of high-performance sentence embedding models adept at translating textual inputs into numerical representations, capturing the semantics of the text. These models excel in applications like dense retrieval and semantic textual similarity. This paper details the development of Jina Embeddings, starting with the creation of high-quality pairwise and triplet datasets. It underlines the crucial role of data cleaning in dataset preparation, offers in-depth insights into the model training process, and concludes with a comprehensive performance evaluation using the Massive Text Embedding Benchmark (MTEB).</div></div></a><div class="q-img q-img--menu research-card__img" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/paper_2.59e1399a.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div></div><div data-v-ee5d8eb8="" class="bg-dark q-pt-xl" id="faq"><div data-v-ee5d8eb8="" class="text-h2 text-center non-selectable q-my-xl">FAQ</div><form class="q-form row justify-center q-mb-xl"><label class="q-field row no-wrap items-start q-field--filled q-input q-field--square q-field--labeled q-field--dark q-field--with-bottom col-12 col-sm-10 col-md-8 col-lg-6" for="f_bebfe018-b170-4f1a-ba17-758c42015c8f"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__prepend q-field__marginal row no-wrap items-center"><span class="q-icon" aria-hidden="true" role="presentation"><img src="/J.svg"></span></div><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" aria-label="Please describe your problem" placeholder="what distinguishes the small model from the base model?" id="f_bebfe018-b170-4f1a-ba17-758c42015c8f" type="text"><div class="q-field__label no-pointer-events absolute ellipsis">Please describe your problem</div></div><div class="q-field__append q-field__marginal row no-wrap items-center"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" type="submit"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">send</i></span></button></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></form><div data-v-ee5d8eb8="" class="row justify-center"><div data-v-ee5d8eb8="" class="q-list q-list--dark col-11 col-md-6 q-py-xl"><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="02dae6bf-d89b-469c-8a29-36e6f0d31943" aria-label="Expand &quot;What distinguishes the Small model from the Base model?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What distinguishes the Small model from the Base model?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="02dae6bf-d89b-469c-8a29-36e6f0d31943" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">Both the Small and Base models are crafted utilizing the robust JinaBert architecture, differing primarily in their scale. The Small model comprises 33 million parameters, whereas the Base model comprises 137 million parameters. While the Base model delivers superior embedding performance, it incurs a minor trade-off in throughput (Queries per second), making the Small model a more agile option for certain use cases. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="11c1d5b8-d5c2-4704-bf38-5ece2f292d0c" aria-label="Expand &quot;What is the anticipated Queries Per Second (QPS) for both the Small and Base models?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the anticipated Queries Per Second (QPS) for both the Small and Base models?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="11c1d5b8-d5c2-4704-bf38-5ece2f292d0c" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">The QPS is contingent upon the length of the user-input sentences and the chosen model. For the Base model, the QPS can range from 4 to 100, while for the Small model, the range is between 10 to 300. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="92826f7c-e6ff-407a-b078-af3990b7f2f1" aria-label="Expand &quot;Which languages are supported by your models?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Which languages are supported by your models?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="92826f7c-e6ff-407a-b078-af3990b7f2f1" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">At present, our models exclusively support English. However, we are actively expanding our linguistic capabilities by training additional language-specific models. These forthcoming models are being designed to offer the same qualitative and quantitative advantages as the jina-embeddings-v2. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="56b7a1a3-4510-40d8-8799-5634b8fbd57d" aria-label="Expand &quot;What is the maximum number of characters I can input in a single sentence?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the maximum number of characters I can input in a single sentence?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="56b7a1a3-4510-40d8-8799-5634b8fbd57d" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">Our models are highly capable, allowing for an input length of 8192 tokens, which is significantly longer than what most other models offer. A token can be as short as one character or as long as one word (e.g., 'a' or 'apple'). The number of characters you can input into a sentence depends on the length and complexity of the words used. This extended input length of jina-embedddings-v2 models enables more comprehensive text analysis and higher accuracy in understanding the context, especially in scenarios dealing with extensive textual data. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="b3533b82-65ad-470d-a2a8-24b69bf8a800" aria-label="Expand &quot;What is the maximum number of sentences I can include in a single request?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the maximum number of sentences I can include in a single request?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="b3533b82-65ad-470d-a2a8-24b69bf8a800" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">A single API call can accommodate up to 2048 sentences or texts, allowing for extensive text analysis in one go. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="2e1d5b46-9c95-4b02-b35c-1a518507ba91" aria-label="Expand &quot;On what basis is the Base model characterized as state-of-the-art?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">On what basis is the Base model characterized as state-of-the-art?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="2e1d5b46-9c95-4b02-b35c-1a518507ba91" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">Our assertion stems from rigorous assessments conducted under the open-source evaluation framework, Massive Text Embedding Benchmark (MTEB). Our Base model has achieved an average rank of 17th on this leaderboard, with particularly impressive performance in core tasks like classification, summarization, and text-similarity. Notably, it stands out as the sole open-source model that supports an extensive 8192 token input context length, a sign of state-of-the-art performance. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="6cf4d9e4-eb1d-45f4-842a-8da08c51f57d" aria-label="Expand &quot;How do Jina Embeddings models compare to OpenAI's text-embedding-ada002 model?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How do Jina Embeddings models compare to OpenAI's text-embedding-ada002 model?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="6cf4d9e4-eb1d-45f4-842a-8da08c51f57d" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">According to the MTEB Leaderboard, our Base model holds its ground against OpenAI’s text-embedding-ada-002, showcasing comparable performance on average (ranking 17th versus 15th). Moreover, our Base model surpasses OpenAI’s offering in several tasks including classification, pair-classification, re-ranking, and summarization. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="79d8d0ed-521e-4180-b5b3-95b70a1eb6b0" aria-label="Expand &quot;I am currently utilizing OpenAI's text-embedding-ada-002. How seamless is the transition to your solution?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">I am currently utilizing OpenAI's text-embedding-ada-002. How seamless is the transition to your solution?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="79d8d0ed-521e-4180-b5b3-95b70a1eb6b0" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">Transitioning is made effortless as our API endpoint, https://api.jina.ai/v1/embeddings, aligns perfectly with the input and output JSON schemas of OpenAI’s endpoint for the text-embeddings-ada-002 model. This compatibility allows users to integrate our model as a direct drop-in replacement for text-embeddings-ada-002 when utilizing OpenAI’s endpoint. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="14fb6f75-5c02-492a-ba80-2b566f8e4ef5" aria-label="Expand &quot;Is the billing based on the number of sentences or requests?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is the billing based on the number of sentences or requests?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="14fb6f75-5c02-492a-ba80-2b566f8e4ef5" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">Our billing model is based on the total number of tokens processed. Users have the flexibility to distribute these tokens across as many sentences as they desire, providing a cost-effective and adaptable solution for varying text analysis needs. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="ec209392-af26-4299-8aca-5d9ce823bc91" aria-label="Expand &quot;Is there a free trial available for new users?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is there a free trial available for new users?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="ec209392-af26-4299-8aca-5d9ce823bc91" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">Yes, we welcome new users by offering a complimentary trial for embedding up to 10,000 tokens using any of our models. An auto-generated API key facilitates this trial. Upon exhaustion of the free token limit, users can effortlessly purchase top-ups for their existing API keys via the designated 'Top-Up' tab. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="efd575b1-f35f-4df1-9078-15a00839d1e5" aria-label="Expand &quot;Do API keys have an expiration date?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Do API keys have an expiration date?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="efd575b1-f35f-4df1-9078-15a00839d1e5" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">No, our API keys do not have an expiration date. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="a3f2dc24-a865-44cf-9efe-219f5efda5f0" aria-label="Expand &quot;Is user input data utilized for training your models?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is user input data utilized for training your models?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="a3f2dc24-a865-44cf-9efe-219f5efda5f0" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">No, we uphold a strict privacy policy and do not utilize user input data for training our models. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="b55e25eb-4fba-4c1f-8aa8-8bf47c38e68d" aria-label="Expand &quot;Are tokens charged for failed requests?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Are tokens charged for failed requests?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="b55e25eb-4fba-4c1f-8aa8-8bf47c38e68d" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">No, tokens are not charged in the event of failed requests. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="c8068ac1-fe12-494d-9ebf-fe30ab7878a8" aria-label="Expand &quot;What payment methods are accepted?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What payment methods are accepted?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="c8068ac1-fe12-494d-9ebf-fe30ab7878a8" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">We have partnered with Stripe to facilitate a smooth payment process. Through this platform, we accept various payment methods including credit cards, Google Pay, and PayPal for your convenience. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="628fd2e4-d9d1-4a33-b322-e2f756a1acc4" aria-label="Expand &quot;Is invoicing available for token purchases?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is invoicing available for token purchases?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="628fd2e4-d9d1-4a33-b322-e2f756a1acc4" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">Yes, upon purchasing tokens, an invoice will be sent to the email address associated with your Stripe account. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="1b2b2cf1-38a6-4d53-96b1-e2cd1b7744e8" aria-label="Expand &quot;What should I do if I forget my API key?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What should I do if I forget my API key?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="1b2b2cf1-38a6-4d53-96b1-e2cd1b7744e8" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">For free quota usage, you can easily generate a new API key on https://jina.ai/embeddings. If your key has been topped-up, please reach out to support AT jina.ai using your registered email for assistance. </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="3dc6533a-28aa-4e47-a5a0-aad2ea3a4295" aria-label="Expand &quot;Do you provide models for embedding images or audio?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Do you provide models for embedding images or audio?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="3dc6533a-28aa-4e47-a5a0-aad2ea3a4295" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">We are actively working on multimodal models that will cater to text, images, and audio embedding. Stay tuned for these updates! </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="7ef2780c-ec68-4d25-870f-f3464f28f193" aria-label="Expand &quot;Is there an option to fine-tune Jina Embedding models using private or company data?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is there an option to fine-tune Jina Embedding models using private or company data?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="7ef2780c-ec68-4d25-870f-f3464f28f193" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">While we currently do not offer fine-tuning services, we are gearing up to introduce this feature soon. Keep an eye out for this feature! </div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="00e4fb98-43ea-4fba-829b-7c5651f34876" aria-label="Expand &quot;Can your endpoints be hosted privately on AWS, Azure, or GCP marketplaces?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Can your endpoints be hosted privately on AWS, Azure, or GCP marketplaces?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="00e4fb98-43ea-4fba-829b-7c5651f34876" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">AWS SageMaker is available now. Soon, jina-embeddings-v2 model packages will be accessible through all major cloud service providers' platforms. <a data-v-ee5d8eb8="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle text-primary q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://aws.amazon.com/marketplace/seller-profile?id=seller-stch2ludm6vgy" target="_blank" style="font-size: 8px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">AWS SageMaker</span><i class="q-icon on-right notranslate material-icons" aria-hidden="true" role="img">launch</i></span></a></div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="84427e3b-2a99-4330-bade-5f11b8217749" aria-label="Expand &quot;How were the jina-embeddings-v2 models trained?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How were the jina-embeddings-v2 models trained?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="84427e3b-2a99-4330-bade-5f11b8217749" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">For an in-depth understanding of our training methodology, data, and evaluations, we invite you to explore our technical report available on arXiv. <a data-v-ee5d8eb8="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle text-primary q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://arxiv.org/abs/2310.19923" target="_blank" style="font-size: 8px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">launch</i></span></a></div></div></div></div></div><div data-v-ee5d8eb8="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="197cbedc-b5fc-45bc-bab7-0d9b4b0358fd" aria-label="Expand &quot;How many API requests can I make every second?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How many API requests can I make every second?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="197cbedc-b5fc-45bc-bab7-0d9b4b0358fd" style="display: none;"><div data-v-ee5d8eb8="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-ee5d8eb8="" class="q-card__section q-card__section--vert">Each user can make up to 100 requests per second, allowing to input 204,800 input sentences per second. </div></div></div></div></div></div></div></div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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 &#x1F195; Features
 Add Epsilla connector (#1835)
 We have integra&#x2026;</div><div class="kg-bookmark-metadata"><img class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt="DocArray 0.40.0 Update"><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img src="https://opengraph.githubassets.com/668ee783e022a27964faa8e5f0a854cc1dea3f036e49bb10f4413288f5b2066f/docarray/docarray/releases/tag/v0.40.0" alt="DocArray 0.40.0 Update"></div></a></figure><h2 id="%F0%9F%86%95-features">&#x1F195; Features</h2><h3 id="add-epsilla-connector-1835">Add Epsilla connector (<a href="https://github.com/docarray/docarray/pull/1835?ref=jina-ai-gmbh.ghost.io">#1835</a>)</h3><p>We have integrated&#xA0;<a href="https://epsilla.com/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Epsilla</a>&#xA0;into DocArray.</p><p>Here&apos;s a simple example of how to use it:</p><pre><code class="language-Python">import numpy as np
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina AI - Your Portal to Multimodal AI</title><meta charset="utf-8"><meta name="title" content="Jina AI - Your Portal to Multimodal AI"><meta name="description" content="Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. We aim to democratize access to the limitless potential of AI-generated creativity and innovation, empowering individuals and businesses alike."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/"><meta property="og:title" content="Jina AI - Your Portal to Multimodal AI"><meta property="og:description" content="Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. We aim to democratize access to the limitless potential of AI-generated creativity and innovation, empowering individuals and businesses alike."><meta property="og:image" content="https://jina.ai/banner.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/"><meta property="twitter:title" content="Jina AI - Your Portal to Multimodal AI"><meta property="twitter:description" content="Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. We aim to democratize access to the limitless potential of AI-generated creativity and innovation, empowering individuals and businesses alike."><meta property="twitter:image" content="https://jina.ai/banner.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jerboa</div><div class="q-item__label q-item__label--caption text-caption">An experimental finetuner for open-source LLMs</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark 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You can top up your key at any time. Make sure to store your API key at a safe place!</div></div></div></div></label></div><div class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow full-width q-mt-xl"><div class="q-tabs row no-wrap items-center q-tabs--not-scrollable q-tabs--horizontal q-tabs__arrows--inside q-tabs--mobile-without-arrows" role="tablist"><div class="q-tabs__content scroll--mobile row no-wrap items-center self-stretch hide-scrollbar relative-position q-tabs__content--align-left"><div class="q-tab relative-position self-stretch flex flex-center text-center q-tab--active text-primary q-focusable q-hoverable cursor-pointer" tabindex="0" role="tab" aria-selected="true"><div class="q-focus-helper" tabindex="-1"></div><div class="q-tab__content self-stretch flex-center relative-position q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon notranslate material-icons q-tab__icon" aria-hidden="true" role="presentation">code</i><div class="q-tab__label">code</div></div><div class="q-tab__indicator absolute-bottom text-primary"></div></div><div class="q-tab relative-position self-stretch flex flex-center text-center q-tab--inactive q-focusable q-hoverable cursor-pointer" tabindex="-1" role="tab" aria-selected="false"><div class="q-focus-helper" tabindex="-1"></div><div class="q-tab__content self-stretch flex-center relative-position q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon notranslate material-icons q-tab__icon" aria-hidden="true" role="presentation">shopping_cart</i><div class="q-tab__label">Top up</div></div><div class="q-tab__indicator absolute-bottom text-primary"></div></div><div class="q-space"></div><a class="q-btn q-btn-item non-selectable no-outline q-btn--standard q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch" tabindex="0" href="/embeddings#faq" style="font-size: 14px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row no-wrap text-no-wrap"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">help_outline</i><span class="block">faq</span></span></a></div><i class="q-icon fas fa-chevron-left q-tabs__arrow q-tabs__arrow--left absolute q-tab__icon" aria-hidden="true" role="presentation"> </i><i class="q-icon fas fa-chevron-right q-tabs__arrow q-tabs__arrow--right absolute q-tab__icon q-tabs__arrow--faded" aria-hidden="true" role="presentation"> </i></div><hr class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div class="q-tab-panels q-panel-parent q-tab-panels--dark q-dark"><div class="q-panel scroll" role="tabpanel" style="--q-transition-duration:300ms;"><div class="q-tab-panel" role="tabpanel"><div class="row q-mb-md q-pa-none"><div class="row q-gutter-sm"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons cursor-pointer" aria-hidden="true" role="presentation">help_outline</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label q-item__label--overline text-overline row items-center">Available tokens</div><div class="q-item__label">0</div></div></div><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">sync</i></span></button></div><div class="q-space"></div><div class="row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch q-btn--square q-btn-dropdown q-btn-dropdown--simple" tabindex="0" type="button" aria-expanded="false" aria-haspopup="true" aria-controls="7b6ce243-2db3-4dca-ad01-456b1c41a1f9" aria-label="Expand"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row no-wrap text-no-wrap"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">view_in_ar</i><div class="full-width ellipsis q-pl-md"></div><i class="q-icon fas fa-caret-down q-btn-dropdown__arrow q-btn-dropdown__arrow-container" aria-hidden="true" role="presentation"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch q-btn--square q-btn-dropdown q-btn-dropdown--simple" tabindex="0" type="button" aria-expanded="false" aria-haspopup="true" aria-controls="d06e7309-bb02-4583-8d18-2404e337da33" aria-label="Expand"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row no-wrap text-no-wrap"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">data_object</i><div class="full-width ellipsis q-pl-md">curl</div><i class="q-icon fas fa-caret-down q-btn-dropdown__arrow q-btn-dropdown__arrow-container" aria-hidden="true" role="presentation"> </i></span></button></div></div><hr class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div class="q-py-lg q-px-md" style="position: relative;"><div class="q-markdown"><pre class="q-markdown--code q-markdown--code__inner language-bash"><code><span class="token function">curl</span> https://api.jina.ai/v1/embeddings <span class="token punctuation">\</span>
+    gtag('config', 'G-9T52NXDS9T');</script></head><body class="desktop no-touch body--dark"><div id="q-app" data-v-app class="hidden"><div class="q-layout q-layout--standard" tabindex="-1" style="min-height: 600px;"><header class="q-header q-layout__section--marginal fixed-top text-white lock-blur bg-transparent print-hide"><div class="q-toolbar row no-wrap items-center q-px-none" role="toolbar"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch" tabindex="0" type="button" style="padding: 24px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">reorder</i></span></button><hr class="q-separator q-separator--vertical q-separator--dark" aria-orientation="vertical"><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch" tabindex="0" href="/" style="font-size: 32px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="q-icon" aria-hidden="true" role="img"><img src="/Jina - Dark.svg"></span></span></a><div class="q-space"></div><label class="q-field row no-wrap items-start q-field--borderless q-select q-field--auto-height q-select--without-input q-select--without-chips q-select--single q-field--float q-field--dense q-field--dark" for="f_6941b231-6a72-40e1-b834-9c238f37deb6"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__prepend q-field__marginal row no-wrap items-center"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">language</i></div><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><div class="q-field__native row items-center"><span>English</span><input class="q-select__focus-target" id="f_6941b231-6a72-40e1-b834-9c238f37deb6" readonly="" tabindex="0" role="combobox" aria-readonly="false" aria-autocomplete="none" aria-expanded="false" aria-controls="f_6941b231-6a72-40e1-b834-9c238f37deb6_lb"></div></div><div class="q-field__append q-field__marginal row no-wrap items-center q-anchor--skip"><i class="q-icon fas fa-caret-down q-select__dropdown-icon" aria-hidden="true" role="presentation"> </i></div></div></div></label></div></header><div class="q-drawer-container"><div class="q-drawer__opener fixed-left" aria-hidden="true"></div><div class="fullscreen q-drawer__backdrop hidden" aria-hidden="true" style="background-color: rgba(0, 0, 0, 0);"></div><aside class="q-drawer q-drawer--left q-drawer--bordered q-drawer--dark q-dark q-layout--prevent-focus fixed q-drawer--on-top q-drawer--mobile q-drawer--top-padding" style="width: 300px; transform: translateX(-300px);"><div class="q-drawer__content fit scroll"><div class="q-scrollarea q-scrollarea--dark fit"><div class="q-scrollarea__container scroll relative-position fit hide-scrollbar"><div class="q-scrollarea__content absolute"><div class="q-list q-list--dark q-list--padding"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/news"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">notifications</i></div></div></div><div class="q-item__section column q-item__section--main justify-center">News</div></a><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f0261c4d-707c-44d3-9e74-a9ea6f018d9d" aria-label="Expand &quot;For Enterprises&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Enterprises</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f0261c4d-707c-44d3-9e74-a9ea6f018d9d" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/embeddings"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Embeddings</div><div class="q-item__label q-item__label--caption text-caption">Our world-class embeddings for your search and RAG systems</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="b2e0828b-7924-48c1-b125-f4fed69c8b50" aria-label="Expand &quot;For Power Users&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Power Users</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="b2e0828b-7924-48c1-b125-f4fed69c8b50" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://promptperfect.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://promptperfect.jina.ai/PromptPerfect-light.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">PromptPerfect</div><div class="q-item__label q-item__label--caption text-caption">Premier tool for prompt engineering</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://scenex.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://scenex.jina.ai/SceneX - Light.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">SceneXplain</div><div class="q-item__label q-item__label--caption text-caption">Leading AI solution for image captions and video summaries</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://bestbanner.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://bestbanner.jina.ai/bestbanner-light.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">BestBanner</div><div class="q-item__label q-item__label--caption text-caption">Blog to banner, without the prompts!</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://chat.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://chat.jina.ai/JinaChat - Light.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="a4816a2c-9ac2-4d23-b2d2-e915d8c9eb9b" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="a4816a2c-9ac2-4d23-b2d2-e915d8c9eb9b" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; 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style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="q-py-xl q-my-xl row justify-center" id="find-your-portals"><div data-v-3a0b7298="" class="col-11"><div data-v-3a0b7298="" class="column justify-center items-center"><a data-v-3a0b7298="" class="text-h3 q-mb-xl text-center text-white" href="#find-your-portals" style="text-decoration: none !important;">Find Your Portal</a></div><form class="q-form row justify-center q-mb-xl"><label class="q-field row no-wrap items-start q-field--filled q-input q-field--square q-field--labeled q-field--dark q-field--with-bottom col-12 col-sm-10 col-md-8 col-lg-6" for="f_9352320c-d31b-4e73-af0b-21887004ceb6"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__prepend q-field__marginal row no-wrap items-center"><span class="q-icon" aria-hidden="true" role="presentation"><img src="/J.svg"></span></div><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" aria-label="Please describe your problem" placeholder="How to enable high-accuracy search within 3d mesh data using point cloud information?" id="f_9352320c-d31b-4e73-af0b-21887004ceb6" type="text"><div class="q-field__label no-pointer-events absolute ellipsis">Please describe your problem</div></div><div class="q-field__append q-field__marginal row no-wrap items-center"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" type="submit"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" 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text-weight-light"><div data-v-3a0b7298="" class="q-item__section column q-item__section--main justify-center q-my-lg"><div data-v-3a0b7298="" class="q-item__label">For Enterprises</div><div data-v-3a0b7298="" class="q-item__label q-item__label--caption text-caption">Discover scalable multimodal AI strategies tailored to meet business needs.</div></div></div></div></a><a data-v-3a0b7298="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable col-12 col-sm-6 col-md-3 q-pa-none" role="listitem" tabindex="0" href="#power-users"><div class="q-focus-helper" tabindex="-1"></div><div data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow full-width bg-transparent q-pa-none"><div data-v-3a0b7298="" class="q-parallax q-pa-none" style="height: 300px;"><div class="q-parallax__media absolute-full"><img src="prosumer-card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-3a0b7298="" class="q-card__section q-card__section--vert text-h6 text-weight-light"><div data-v-3a0b7298="" class="q-item__section column q-item__section--main justify-center q-my-lg"><div data-v-3a0b7298="" class="q-item__label">For Power Users</div><div data-v-3a0b7298="" class="q-item__label q-item__label--caption text-caption">Utilize our streamlined multimodal tools to enhance your productivity.</div></div></div></div></a><a data-v-3a0b7298="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable col-12 col-sm-6 col-md-3 q-pa-none" role="listitem" tabindex="0" href="#developers"><div class="q-focus-helper" tabindex="-1"></div><div data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow full-width bg-transparent q-pa-none"><div data-v-3a0b7298="" class="q-parallax q-pa-none" style="height: 300px;"><div class="q-parallax__media absolute-full"><img src="developer-card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-3a0b7298="" class="q-card__section q-card__section--vert text-h6 text-weight-light"><div data-v-3a0b7298="" class="q-item__section column q-item__section--main justify-center q-my-lg"><div data-v-3a0b7298="" class="q-item__label">For Developers</div><div data-v-3a0b7298="" class="q-item__label q-item__label--caption text-caption">Experience a comprehensive open-source multimodal AI stack designed for developers.</div></div></div></div></a></div></div></div><div data-v-3a0b7298="" class="q-py-xl row justify-center relative-position" id="enterprises" style="background: linear-gradient(to bottom, var(--q-dark), var(--q-dark-page));"><div data-v-3a0b7298="" class="q-img q-img--menu absolute-bottom" role="img" style="width: 100%; max-height: 440px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img 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justify-center q-my-xl text-grey-5">Try our world-class embedding models to improve your search and RAG systems. Start with a free trial!</div><div data-v-3a0b7298="" class="row q-my-xl q-py-xl justify-between"><div data-v-3a0b7298="" class="col-12 col-md-5 col-lg-4"><div data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-transparent full-height q-mb-xl q-pb-md"><div data-v-3a0b7298="" class="text-h3 text-white q-mb-lg">Embeddings</div><div data-v-3a0b7298="" class="text-grey-5 q-mb-xl"><div data-v-3a0b7298="" class="q-list q-list--dark"><div data-v-3a0b7298="" class="q-item q-item-type row no-wrap q-item--dark text-grey-5 q-pa-none" role="listitem">The only open-source embedding model that supports 8192-token context length, putting it on par with OpenAI's proprietary Ada 22 model, in both capabilities and performance on the Massive Text Embedding Benchmark (MTEB).</div><a data-v-3a0b7298="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable text-grey-5 q-pa-none q-my-xl" role="listitem" tabindex="0" href="/embeddings"><div class="q-focus-helper" tabindex="-1"></div><div data-v-3a0b7298="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i data-v-3a0b7298="" class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">cloud</i></div><div data-v-3a0b7298="" class="q-item__section column q-item__section--main justify-center">Try our hosted solution, a drop-in replacement for OpenAI's embedding API.</div><div data-v-3a0b7298="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i data-v-3a0b7298="" class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">chevron_right</i></div></a><div data-v-3a0b7298="" class="q-item q-item-type row no-wrap q-item--dark text-grey-5 q-pa-none" role="listitem"><div data-v-3a0b7298="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i data-v-3a0b7298="" class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">dns</i></div><div data-v-3a0b7298="" class="q-item__section column q-item__section--main justify-center"><div data-v-3a0b7298="" class="q-item__label q-item__label--overline text-overline">On-premises deployment</div><div data-v-3a0b7298="" class="q-item__label">Available on the marketplaces of your enterprise cloud</div></div><div data-v-3a0b7298="" class="q-item__section column q-item__section--side justify-center"><div data-v-3a0b7298="" class="q-btn-group row no-wrap q-btn-group--outline q-btn-group--square inline"><a data-v-3a0b7298="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="https://aws.amazon.com/marketplace/seller-profile?id=seller-stch2ludm6vgy" target="_blank" style="padding: 16px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-aws" aria-hidden="true" role="img"> </i><div data-v-3a0b7298="" class="q-badge flex inline items-center no-wrap q-badge--single-line q-badge--floating q-badge--rounded" role="status"></div></span></a><button data-v-3a0b7298="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square disabled q-btn--no-uppercase q-btn--square" tabindex="-1" type="button" disabled="" aria-disabled="true" style="padding: 16px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-microsoft" aria-hidden="true" role="img"> </i></span></button><button data-v-3a0b7298="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square disabled q-btn--no-uppercase q-btn--square" tabindex="-1" type="button" disabled="" aria-disabled="true" style="padding: 16px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-google" aria-hidden="true" role="img"> </i></span></button></div></div></div></div></div><div data-v-3a0b7298="" class="q-space"></div><div data-v-3a0b7298="" class="q-card__actions justify-start q-card__actions--horiz row q-mt-xl"></div></div></div><div data-v-3a0b7298="" class="col-12 col-md-7"><div class="full-width"><label class="q-field row no-wrap items-start q-field--standout q-input q-field--labeled q-field--dark q-field--with-bottom q-field--readonly full-width" for="f_6d948143-537b-4bca-806a-bb4dd9469a52" aria-readonly="true"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__prepend q-field__marginal row no-wrap items-center"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">refresh</i></span></button></div><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder ellipsis" tabindex="0" aria-label="API key" id="f_6d948143-537b-4bca-806a-bb4dd9469a52" readonly="" type="text" style="font-family: monospace;"><div class="q-field__label no-pointer-events absolute ellipsis">API key</div></div><div class="q-field__append q-field__marginal row no-wrap items-center"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text- q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">content_copy</i></span></button></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"><div>Each new key has some free tokens for you to try out. You can top up your key at any time. Make sure to store your API key at a safe place!</div></div></div></div></label></div><div class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow full-width q-mt-xl"><div class="q-tabs row no-wrap items-center q-tabs--not-scrollable q-tabs--horizontal q-tabs__arrows--inside q-tabs--mobile-without-arrows" role="tablist"><div class="q-tabs__content scroll--mobile row no-wrap items-center self-stretch hide-scrollbar relative-position q-tabs__content--align-left"><div class="q-tab relative-position self-stretch flex flex-center text-center q-tab--active text-primary q-focusable q-hoverable cursor-pointer" tabindex="0" role="tab" aria-selected="true"><div class="q-focus-helper" tabindex="-1"></div><div class="q-tab__content self-stretch flex-center relative-position q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon notranslate material-icons q-tab__icon" aria-hidden="true" role="presentation">code</i><div class="q-tab__label">code</div></div><div class="q-tab__indicator absolute-bottom text-primary"></div></div><div class="q-tab relative-position self-stretch flex flex-center text-center q-tab--inactive q-focusable q-hoverable cursor-pointer" tabindex="-1" role="tab" aria-selected="false"><div class="q-focus-helper" tabindex="-1"></div><div class="q-tab__content self-stretch flex-center relative-position q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon notranslate material-icons q-tab__icon" aria-hidden="true" role="presentation">shopping_cart</i><div class="q-tab__label">Top up</div></div><div class="q-tab__indicator absolute-bottom text-primary"></div></div><div class="q-space"></div><a class="q-btn q-btn-item non-selectable no-outline q-btn--standard q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch" tabindex="0" href="/embeddings#faq" style="font-size: 14px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row no-wrap text-no-wrap"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">help_outline</i><span class="block">faq</span></span></a></div><i class="q-icon fas fa-chevron-left q-tabs__arrow q-tabs__arrow--left absolute q-tab__icon" aria-hidden="true" role="presentation"> </i><i class="q-icon fas fa-chevron-right q-tabs__arrow q-tabs__arrow--right absolute q-tab__icon q-tabs__arrow--faded" aria-hidden="true" role="presentation"> </i></div><hr class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div class="q-tab-panels q-panel-parent q-tab-panels--dark q-dark"><div class="q-panel scroll" role="tabpanel" style="--q-transition-duration:300ms;"><div class="q-tab-panel" role="tabpanel"><div class="row q-mb-md q-pa-none"><div class="row q-gutter-sm"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons cursor-pointer" aria-hidden="true" role="presentation">help_outline</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label q-item__label--overline text-overline row items-center">Available tokens</div><div class="q-item__label">0</div></div></div><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">sync</i></span></button></div><div class="q-space"></div><div class="row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch q-btn--square q-btn-dropdown q-btn-dropdown--simple" tabindex="0" type="button" aria-expanded="false" aria-haspopup="true" aria-controls="5f6baf78-9475-4c7c-a301-84117f13f2f6" aria-label="Expand"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row no-wrap text-no-wrap"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">view_in_ar</i><div class="full-width ellipsis q-pl-md"></div><i class="q-icon fas fa-caret-down q-btn-dropdown__arrow q-btn-dropdown__arrow-container" aria-hidden="true" role="presentation"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch q-btn--square q-btn-dropdown q-btn-dropdown--simple" tabindex="0" type="button" aria-expanded="false" aria-haspopup="true" aria-controls="a4d79dfd-aee3-460c-b5ab-ea848b95c670" aria-label="Expand"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row no-wrap text-no-wrap"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">data_object</i><div class="full-width ellipsis q-pl-md">curl</div><i class="q-icon fas fa-caret-down q-btn-dropdown__arrow q-btn-dropdown__arrow-container" aria-hidden="true" role="presentation"> </i></span></button></div></div><hr class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div class="q-py-lg q-px-md" style="position: relative;"><div class="q-markdown"><pre class="q-markdown--code q-markdown--code__inner language-bash"><code><span class="token function">curl</span> https://api.jina.ai/v1/embeddings <span class="token punctuation">\</span>
   <span class="token parameter variable">-H</span> <span class="token string">"Content-Type: application/json"</span> <span class="token punctuation">\</span>
   <span class="token parameter variable">-H</span> <span class="token string">"Authorization: Bearer <span class="token variable">$JINA_API_KEY</span>"</span> <span class="token punctuation">\</span>
   <span class="token parameter variable">-d</span> <span class="token string">'{
@@ -20,4 +20,4 @@
   }'</span>
 </code></pre>
 
-</div><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-amber q-btn--actionable q-focusable q-hoverable q-btn--dense q-markdown__copy" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="q-icon" aria-hidden="true" role="img"><svg viewBox="0 0 24 24"><path d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg></span></span></button></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="row q-mt-xl q-pt-xl justify-between"><div data-v-3a0b7298="" class="col-12 col-md-5 col-lg-4"><div data-v-3a0b7298="" class="q-mb-lg q-pb-md"><div data-v-3a0b7298="" class="row text-h3 text-white q-mb-lg">Our Publications</div><div data-v-3a0b7298="" class="text-grey-5">To understand how our large language models were trained from scratch for embedding tasks, check out our latest research and publications. Meet our team at the EMNLP, ACL, SIGIR, NeurIPS, and ICML conferences.</div></div></div><div data-v-3a0b7298="" class="col-12 col-md-7"><div class="q-card q-card--dark q-dark q-card--flat no-shadow q-hoverable cursor-pointer q-mb-md"><span class="q-focus-helper"></span><div class="q-linear-progress text-primary research-card__progress" role="progressbar" aria-valuemin="0" aria-valuemax="1" aria-valuenow="100" style="font-size: 4px; --q-linear-progress-speed:2100ms;"><div class="q-linear-progress__track absolute-full q-linear-progress__track--with-transition q-linear-progress__track--dark" style="transform: scale3d(1, 1, 1);"></div><div class="q-linear-progress__model absolute-full q-linear-progress__model--with-transition q-linear-progress__model--determinate" style="transform: scale3d(100, 1, 1);"></div></div><div class="q-card__section q-card__section--horiz row no-wrap q-pa-none"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-pa-lg col-9" role="listitem" tabindex="0" href="https://arxiv.org/abs/2310.19923" target="_blank"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-mb-xl"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">2023.11</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><span class="q-icon q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"><img src="/arxiv_logo.svg"></span><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">arXiv</div></div></div></div><div class="q-space"></div><div class="q-item__label text-h6 q-mb-lg">Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Text embedding models have emerged as powerful tools for transforming sentences into fixed-sized feature vectors that encapsulate semantic information. While these models are essential for tasks like information retrieval, semantic clustering, and text re-ranking, most existing open-source models, especially those built on architectures like BERT, struggle to represent lengthy documents and often resort to truncation. One common approach to mitigate this challenge involves splitting documents into smaller paragraphs for embedding. However, this strategy results in a much larger set of vectors, consequently leading to increased memory consumption and computationally intensive vector searches with elevated latency.</div></div></a><div class="q-img q-img--menu research-card__img" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/paper_1.8ed04d7d.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow q-hoverable cursor-pointer q-mb-md"><span class="q-focus-helper"></span><div class="q-linear-progress text-primary research-card__progress" role="progressbar" aria-valuemin="0" aria-valuemax="1" aria-valuenow="100" style="font-size: 4px; --q-linear-progress-speed:2100ms;"><div class="q-linear-progress__track absolute-full q-linear-progress__track--with-transition q-linear-progress__track--dark" style="transform: scale3d(1, 1, 1);"></div><div class="q-linear-progress__model absolute-full q-linear-progress__model--with-transition q-linear-progress__model--determinate" style="transform: scale3d(100, 1, 1);"></div></div><div class="q-card__section q-card__section--horiz row no-wrap q-pa-none"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-pa-lg col-9" role="listitem" tabindex="0" href="https://arxiv.org/abs/2307.11224" target="_blank"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-mb-xl"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">2023.8</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">EMNLP 2023</div></div></div></div><div class="q-space"></div><div class="q-item__label text-h6 q-mb-lg">Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina Embeddings constitutes a set of high-performance sentence embedding models adept at translating textual inputs into numerical representations, capturing the semantics of the text. These models excel in applications like dense retrieval and semantic textual similarity. This paper details the development of Jina Embeddings, starting with the creation of high-quality pairwise and triplet datasets. It underlines the crucial role of data cleaning in dataset preparation, offers in-depth insights into the model training process, and concludes with a comprehensive performance evaluation using the Massive Text Embedding Benchmark (MTEB).</div></div></a><div class="q-img q-img--menu research-card__img" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/paper_2.59e1399a.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="q-py-xl q-my-xl row justify-center relative-position" id="power-users"><div data-v-3a0b7298="" class="q-img q-img--menu absolute-bottom-right" role="img" style="width: 80%; z-index: -1;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/pattern-sdk.fcc07f38.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-3a0b7298="" class="col-11"><a data-v-3a0b7298="" class="row justify-center q-gutter-x-sm text-h2 text-white q-my-xl q-py-xl" href="#power-users" style="text-decoration: none !important;"><div data-v-3a0b7298="">For</div><div data-v-3a0b7298="" style="background: linear-gradient(to right, rgba(107, 73, 255, 0.8), rgb(255, 115, 147)) text; -webkit-text-fill-color: transparent;">Power Users</div></a><div data-v-3a0b7298="" class="row justify-center q-my-xl text-grey-5">Experience powerful, user-friendly multimodal AI apps. No coding, no fuss, just results.</div><div data-v-3a0b7298="" class="column justify-center items-center"><div data-v-3a0b7298="" class="row fit justify-center items-center q-mt-lg"><div data-v-3a0b7298="" class="col-12 q-px-sm q-py-md" style="height: auto;"><div data-v-9abd4bf8="" data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-pa-lg text-white fit overflow-hidden cursor-pointer my-card q-hoverable rounded-borders"><span data-v-9abd4bf8="" class="q-focus-helper"></span><div data-v-9abd4bf8="" class="row fit"><div data-v-9abd4bf8="" class="q-card__section q-card__section--vert column col-12 col-lg-5 no-wrap"><div data-v-9abd4bf8="" class="row items-center"><div data-v-9abd4bf8="" class="q-img q-img--menu q-mr-sm" role="img" aria-label="" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://promptperfect.jina.ai/PromptPerfect-light.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu" role="img" aria-label="" style="width: 150px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/PromptPerfect.0db3b440.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-9abd4bf8="" class="row full-width text-weight-light text-h5 q-mt-lg"><div data-v-9abd4bf8="" class="col-12 col-sm-10">Premier tool for prompt engineering</div></div><div data-v-9abd4bf8="" class="q-card__section q-card__section--vert col q-pa-none q-pt-md"><div data-v-9abd4bf8="" class="q-splitter no-wrap q-splitter--vertical row q-splitter--workable q-splitter--dark fit"><div class="q-splitter__panel q-splitter__before full-height" style="width: 40%;"><div data-v-9abd4bf8="" class="q-card__section q-card__section--vert bg-grey-12 full-height rounded-borders q-pa-sm"><div data-v-9abd4bf8="" class="q-item q-item-type row no-wrap q-item--dark text-grey-10 text-body2 q-pa-none" role="listitem"><div data-v-9abd4bf8="" class="q-item__section column q-item__section--main justify-center"><div data-v-9abd4bf8="" class="q-item__label q-item__label--caption text-caption text-grey-8">Original prompt</div><div data-v-9abd4bf8="" class="q-item__label q-py-md" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 10;">Your role is to be my brainstorming partner.</div></div></div></div></div><div class="q-splitter__separator"><div class="q-splitter__separator-area absolute-full"><div data-v-9abd4bf8="" class="q-avatar bg-info text-white q-chip--colored" style="font-size: 2em;"><div class="q-avatar__content row flex-center overflow-hidden"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">sync_alt</i></div></div></div></div><div class="q-splitter__panel q-splitter__after col"><div data-v-9abd4bf8="" class="q-card__section q-card__section--vert bg-promptperfect full-height rounded-borders q-pa-sm"><div data-v-9abd4bf8="" class="q-item q-item-type row no-wrap q-item--dark text-white text-body2 q-pa-none" role="listitem"><div data-v-9abd4bf8="" class="q-item__section column q-item__section--main justify-center"><div data-v-9abd4bf8="" class="q-item__label q-item__label--caption text-caption text-grey-5">Optimized prompt</div><div data-v-9abd4bf8="" class="q-item__label q-py-md" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 9;">Your task is to be my brainstorming partner and provide creative ideas and suggestions for a given topic or problem. Your response should include original, unique, and relevant ideas that could help solve the problem or further explore the topic in an interesting way. Please note that your response should also take into account any specific requirements or constraints of the task.</div></div></div></div></div></div></div></div><div data-v-9abd4bf8="" class="q-card__section q-card__section--vert col-12 col-lg-7"><div data-v-9abd4bf8="" class="q-item q-item-type row no-wrap q-item--dark column rounded-borders text-white bg-grey-10 fit" role="listitem"><div data-v-9abd4bf8="" class="row text-grey-5 text-subtitle2 text-weight-light text-uppercase q-my-md">Text models</div><div data-v-9abd4bf8="" class="row justify-start items-center"><div data-v-9abd4bf8="" class="col-12"><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-chatgpt.619298f9.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-gpt3.fa7b97cd.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-gpt4.0ec3c1ca.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-stablelm.22649423.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-claude.d3214a05.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-claude2.885442a5.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-ernie.3b3b81f1.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-command.c22268f0.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-llama7b.32ec0462.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-llama13b.3dc34538.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-llama70b.e7552cbe.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-jinachat.dff4afb3.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-9abd4bf8="" class="row text-grey-5 text-subtitle2 text-weight-light text-uppercase q-my-md">Image models</div><div data-v-9abd4bf8="" class="row justify-start items-center"><div data-v-9abd4bf8="" class="col-12"><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-dalle2.1822fdac.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-sdxl.e5323437.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-midjourney.35d3c163.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-sd.938f1c41.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-kandinsky.ee36f5b8.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-dreamshaper.1029a401.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-absolutereality.1ca5c477.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-anything.f641ae91.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-deliberate.a8228b3c.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-sdxl-emoji.e020ab86.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-lexica.f98ffeed.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="col-12 q-px-sm q-py-md" style="height: auto;"><div data-v-0847e7dc="" data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-pa-lg bg-dark text-white fit overflow-hidden cursor-pointer my-card q-hoverable rounded-borders"><span data-v-0847e7dc="" class="q-focus-helper"></span><div data-v-0847e7dc="" class="full-height absolute-right card-bg"></div><div data-v-0847e7dc="" class="row fit"><div data-v-0847e7dc="" class="q-card__section q-card__section--vert column column col-12 col-lg-5 justify-start items-start"><div data-v-0847e7dc="" class="row items-center"><div data-v-0847e7dc="" class="q-img q-img--menu q-mr-sm" role="img" aria-label="" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://scenex.jina.ai/SceneX - Light.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-0847e7dc="" class="q-img q-img--menu" role="img" aria-label="" style="width: 150px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/SceneXplain.d7bc8012.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-0847e7dc="" class="row full-width text-weight-light text-h5 q-mt-lg">Leading AI solution for image captions and video summaries</div><div data-v-0847e7dc="" class="q-card__section q-card__section--vert row col justify-start items-start q-mt-lg"><div data-v-0847e7dc="" class="q-img q-img--menu col-5 relative-position rounded-borders" role="img" style="z-index: 10;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="scenex-example.gif" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-0847e7dc="" class="q-card q-card--dark q-dark q-card--flat no-shadow col-7 bg-pink-12 text-white q-pa-md relative-position" style="margin-left: -10px; margin-top: 35px;"><i data-v-0847e7dc="" class="q-icon text-pink-12 fa-solid fa-arrow-turn-down absolute" aria-hidden="true" role="presentation" style="left: 17px; top: -23px;"></i><div data-v-0847e7dc="" class="ellipsis-5-lines">This video appears to be a nature footage featuring a charming white bunny and a butterfly in a grassy field. The bunny is seen interacting with the butterfly in different ways, showcasing their unique relationship. The natural surroundings provide a picturesque backdrop, enhancing the beauty of this simple yet captivating scene.</div></div></div></div><div data-v-0847e7dc="" class="q-card__section q-card__section--vert col-12 col-lg-7"><div data-v-0847e7dc="" class="q-item q-item-type row no-wrap q-item--dark column rounded-borders text-white fit" role="listitem"><div data-v-0847e7dc="" class="q-list q-list--dark"><div data-v-0847e7dc="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-my-sm" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-0847e7dc="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-image2text.ebccb1d3.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--main justify-center"><div data-v-0847e7dc="" class="q-item__label text-pink-6">Caption Image</div><div data-v-0847e7dc="" class="q-item__label q-item__label--caption text-caption ellipsis">Generate a textual description of the image.</div></div></div><div data-v-0847e7dc="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-my-sm" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-0847e7dc="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-image2json.35b549f2.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--main justify-center"><div data-v-0847e7dc="" class="q-item__label text-pink-6">Extract JSON from Image</div><div data-v-0847e7dc="" class="q-item__label q-item__label--caption text-caption ellipsis">Generate a structured JSON format from the image using a predefined schema. This allows for specific data extraction from the image.</div></div></div><div data-v-0847e7dc="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-my-sm" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-0847e7dc="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-VQA.f0555b28.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--main justify-center"><div data-v-0847e7dc="" class="q-item__label text-pink-6">Visual Q&amp;A</div><div data-v-0847e7dc="" class="q-item__label q-item__label--caption text-caption ellipsis">Answer a query based on the image's content.</div></div></div><div data-v-0847e7dc="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-my-sm" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-0847e7dc="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-video2text.52fa889f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--main justify-center"><div data-v-0847e7dc="" class="q-item__label text-pink-6">Summarize Video</div><div data-v-0847e7dc="" class="q-item__label q-item__label--caption text-caption ellipsis">Generate a concise summary of the video, highlighting key events.</div></div></div><div data-v-0847e7dc="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-my-sm" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-0847e7dc="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-image2text+voice.12170321.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--main justify-center"><div data-v-0847e7dc="" class="q-item__label text-pink-6">Generate Story</div><div data-v-0847e7dc="" class="q-item__label q-item__label--caption text-caption ellipsis">Craft a story inspired by the image, often featuring dialogues or monologues of its characters.</div></div></div></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="row fit justify-center items-center q-mt-lg"><div data-v-3a0b7298="" class="col-12 col-md-4 q-px-sm q-py-md" style="height: 480px;"><div data-v-39dbf15b="" data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-pa-lg text-white fit overflow-hidden cursor-pointer my-card q-hoverable rounded-borders"><div data-v-39dbf15b="" class="full-height absolute-right card-bg"></div><span data-v-39dbf15b="" class="q-focus-helper"></span><div data-v-39dbf15b="" class="q-card__section q-card__section--vert column justify-start items-start"><div data-v-39dbf15b="" class="row items-center"><div data-v-39dbf15b="" class="q-img q-img--menu q-mr-sm" role="img" aria-label="" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://chat.jina.ai/JinaChat - Light.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-39dbf15b="" class="q-img q-img--menu" role="img" aria-label="" style="width: 100px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jinachat-long.a75b4791.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-39dbf15b="" class="row full-width text-weight-light text-h5 q-mt-lg"><div data-v-39dbf15b="" class="col-11">More modality, longer memory, less cost</div></div></div><div data-v-39dbf15b="" class="q-card__section q-card__section--vert row justify-center items-center full-width q-mt-sm"><div data-v-39dbf15b="" class="col-5 column justify-center bg-white rounded-borders shadow-1 q-pa-md relative-position" style="width: 95%; box-shadow: rgba(0, 0, 0, 0.05) 0px 2px 16px 4px; z-index: 7;"><div data-v-39dbf15b="" class="q-message q-message-sent"><div class="q-message-container row items-end no-wrap reverse"><div class=""><div class="q-message-text q-message-text--sent text-grey-3"><div class="q-message-text-content q-message-text-content--sent"><div>Who are you?</div></div></div></div></div></div><div data-v-39dbf15b="" class="q-img q-img--menu absolute-left" role="img" aria-label="" style="width: 36px; transform: translateX(-50%);"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" width="36px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jinachat-pen.5dbd5a16.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-39dbf15b="" class="q-img q-img--menu absolute-top" role="img" aria-label="" style="width: 56px; left: 50%; transform: translate(-50%, -50%);"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" width="56px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jinachat-hand.8ff791f4.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-39dbf15b="" class="q-img q-img--menu absolute-top-right" role="img" aria-label="" style="width: 36px; transform: translate(50%, -50%);"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" width="36px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jinachat-think.df40ad8c.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-39dbf15b="" class="col-5 column justify-center bg-white rounded-borders shadow-1 q-pa-md full-width relative-position" style="margin-top: -10px; box-shadow: rgba(0, 0, 0, 0.05) 0px 2px 16px 4px; z-index: 8;"><div data-v-39dbf15b="" class="q-message q-message-received center-chat-message"><div class="q-message-container row items-end no-wrap"><img class="q-message-avatar q-message-avatar--received" src="https://chat.jina.ai/JinaChat - Light.svg" aria-hidden="true"><div class=""><div class="q-message-text q-message-text--received text-blue-7"><div class="q-message-text-content q-message-text-content--received text-white"><div>I'm a LLM chat service made by Jina AI</div></div></div></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="col-12 col-md-4 q-px-sm q-py-md" style="height: 480px;"><div data-v-12da09fe="" data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-pa-lg text-white fit overflow-hidden cursor-pointer bg-black q-hoverable my-card rounded-borders"><div data-v-12da09fe="" class="full-height absolute-right card-bg"></div><span data-v-12da09fe="" class="q-focus-helper"></span><div data-v-12da09fe="" class="q-card__section q-card__section--vert column justify-start items-start fit"><div data-v-12da09fe="" class="row items-center"><div data-v-12da09fe="" class="q-img q-img--menu q-mr-sm" role="img" aria-label="" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://bestbanner.jina.ai/bestbanner-light.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-12da09fe="" class="q-img q-img--menu" role="img" aria-label="" style="width: 120px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/BestBanner.85dfb1db.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-12da09fe="" class="row full-width text-weight-light text-h5 q-mt-lg">Blog to banner, without the prompts!</div><div data-v-12da09fe="" class="q-card__section q-card__section--horiz row no-wrap col items-center q-mt-xl"><div data-v-12da09fe="" class="q-card q-card--dark q-dark col-5"><div data-v-12da09fe="" class="q-card__section q-card__section--vert q-pa-none"><div data-v-12da09fe="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-12da09fe="" class="q-item__section column q-item__section--main justify-center"><div data-v-12da09fe="" class="q-item__label q-item__label--overline text-overline">Alice's Adventures in Wonderland - Chapter 1</div><div data-v-12da09fe="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Alice was beginning to get very tired of sitting by her sister on the bank, and of having nothing to do: once or twice she had peeped into the book her sister was reading, but it had no pictures or conversations in it, “and what is the use of a book,” thought Alice “without pictures or conversations?” So she was considering in her own mind (as well as she could, for the hot day made her feel very sleepy and stupid), whether the pleasure of making a daisy-chain would be worth the trouble of getting up and picking the daisies, when suddenly a White Rabbit with pink eyes ran close by her.</div></div></div></div></div><div data-v-12da09fe="" class="q-card__section q-card__section--vert col q-pa-none"><div data-v-12da09fe="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="bestbanner_example.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="col-12 col-md-4 q-px-sm q-py-md" style="height: 480px;"><div data-v-d1cf110c="" data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-pa-lg text-white fit cursor-pointer my-card q-hoverable rounded-borders"><span data-v-d1cf110c="" class="q-focus-helper"></span><div data-v-d1cf110c="" class="q-card__section q-card__section--vert column justify-start items-start fit"><div data-v-d1cf110c="" class="row items-center"><div data-v-d1cf110c="" class="q-img q-img--menu q-mr-sm" role="img" aria-label="" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-d1cf110c="" class="q-img q-img--menu" role="img" aria-label="" style="width: 90px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/Rationale.389fb532.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-d1cf110c="" class="row full-width text-weight-light text-white text-h5 q-my-lg">See two sides of the coin, make rational decisions</div><div data-v-d1cf110c="" class="column col justify-start items-start full-width no-wrap"><span data-v-d1cf110c="" class="text-h7">Decision</span><div data-v-d1cf110c="" class="q-card q-card--bordered q-card--flat no-shadow full-width q-pa-md q-mt-sm bg-transparent"><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-grey-4" style="--q-skeleton-speed:1500ms; width: 100%;"></div><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-grey-4 col col-8" style="--q-skeleton-speed:1500ms; width: 70%;"></div></div><div data-v-d1cf110c="" class="row q-mt-md full-width"><div data-v-d1cf110c="" class="row justify-start items-center full-width"><div data-v-d1cf110c="" class="row col items-center q-pr-sm"><button data-v-d1cf110c="" class="q-btn q-btn-item non-selectable no-outline q-btn--unelevated q-btn--round bg-teal-4 text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">thumb_up</i></span></button><div data-v-d1cf110c="" class="col q-pl-sm"><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-teal-4" style="--q-skeleton-speed:1500ms; width: 30%;"></div><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-teal-4" style="--q-skeleton-speed:1500ms; width: 100%;"></div><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-teal-4" style="--q-skeleton-speed:1500ms; width: 100%;"></div></div></div><div data-v-d1cf110c="" class="row col items-center q-pr-sm"><button data-v-d1cf110c="" class="q-btn q-btn-item non-selectable no-outline q-btn--unelevated q-btn--round bg-red-4 text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">thumb_down</i></span></button><div data-v-d1cf110c="" class="col q-pl-sm"><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-red-4" style="--q-skeleton-speed:1500ms; width: 30%;"></div><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-red-4" style="--q-skeleton-speed:1500ms; width: 100%;"></div><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-red-4" style="--q-skeleton-speed:1500ms; width: 100%;"></div></div></div></div></div></div></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="q-py-xl q-my-xl row justify-center bg-dark" id="developers"><div data-v-3a0b7298="" class="col-11 relative-position" style="z-index: 1;"><a data-v-3a0b7298="" class="row justify-center q-gutter-x-sm text-h2 text-white q-my-xl q-py-xl" href="#developers" style="text-decoration: none !important;"><div data-v-3a0b7298="">For</div><div data-v-3a0b7298="" style="background: linear-gradient(to right, rgb(64, 101, 235), rgb(98, 255, 73)) text; -webkit-text-fill-color: transparent;">Developers</div></a><div data-v-3a0b7298="" class="row justify-center items-center q-my-xl text-grey-5">Unleash the full power of multimodal AI with cutting-edge cloud-native technologies and open-source infrastructure.</div><div data-v-3a0b7298="" class="row q-my-xl justify-center"><a data-v-3a0b7298="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square col-12 col-md-10 col-lg-8" tabindex="0" href="jina-ai-multimodal-stack-20230720.pdf" target="_blank" style="padding: 32px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><div data-v-3a0b7298="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/mm-stack.10034a23.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></span></a></div><div data-v-3a0b7298="" class="row q-my-xl q-py-xl"><div class="col-12 col-md-5 column justify-start items-center"><a class="row items-center justify-start text-h2 text-white" href="#developers" style="text-decoration: none !important;">Multimodal Stack</a><div class="row text-grey-5 q-py-lg"><div class="col-12 col-md-8">The developer-friendly, cloud-native, and production-ready stack for building multimodal AI applications.</div></div><div class="row text-grey-5 q-py-lg relative-position"><div class="col-12 col-md-8"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Data Structure</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><i class="q-icon fab fa-linux q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Linux Foundation</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Core</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">science</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Incubating</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Orchestration</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Cloud Native</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Kubernetes</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">school</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Graduated</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Tuning</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Mid Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Small Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Prompt Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">egg</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Sandbox</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Database</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">archive</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Archived</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Prompt Tuning</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Large Size Model</div></div></div></div><div class="q-img q-img--menu absolute" role="img" style="width: 100%; top: 100%; left: -40%; z-index: -1;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/pattern-developers.4f94c0e3.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div class="col-12 col-md-7 row justify-center"><div class="q-pa-xs col-12" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">Jina</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">19.5K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Orchestration</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Cloud Native</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Kubernetes</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Core</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">school</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Graduated</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Jina</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Build multimodal AI applications on the cloud</div></div></div><div class="q-pa-xs col-12" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">DocArray</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">2.6K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Data Structure</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-linux q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Linux Foundation</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Core</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">science</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Incubating</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">DocArray</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">The data structure for multimodal data</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-body">LangChain-Serve</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1.5K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Small Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Prompt Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">egg</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Sandbox</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">LangChain-Serve</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Langchain apps on production with Jina &amp; FastAPI</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">VectorDB</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">409 Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Database</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">egg</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Sandbox</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">VectorDB</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">A Python vector database you just need - no more, no less</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">RunGPT</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">121 Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Large Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">egg</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Sandbox</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">RunGPT</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">An open-source cloud-native of large multimodal models serving framework</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">Finetuner</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1.4K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Tuning</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">science</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Incubating</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Finetuner</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Fine-tune embeddings on domain specific data for better search quality</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-body">DALL-E Flow</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">2.8K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Mid Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">archive</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Archived</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">DALL-E Flow</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">A human-in-the-Loop workflow for creating HD images from text</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">DiscoArt</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">3.8K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Mid Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">archive</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Archived</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">DiscoArt</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Create compelling Disco Diffusion artworks in one line of code</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-body">CLIP-as-service</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">12K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Mid Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">science</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Incubating</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">CLIP-as-service</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Embed images and sentences into fixed-length vectors with CLIP</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">JCloud</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">292 Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Cloud Native</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Kubernetes</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">science</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Incubating</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">JCloud</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-body">Executor Hub</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">archive</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Archived</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Executor Hub</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Share and discover building blocks for multimodal AI applications</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">ThinkGPT</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1.4K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Prompt Tuning</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Prompt Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">archive</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Archived</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">ThinkGPT</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Agent techniques to augment your LLM and push it beyond its limits</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">DevGPT</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1.5K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Prompt Tuning</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">archive</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Archived</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">DevGPT</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Your virtual development team</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">Jerboa</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">30 Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Large Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">egg</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Sandbox</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Jerboa</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">An experimental finetuner for open-source LLMs</div></div></div></div></div><div data-v-3a0b7298="" class="row q-my-xl q-py-xl justify-between"><div data-v-3a0b7298="" class="col-12 col-md-5 column justify-start items-center"><div data-v-3a0b7298="" class="row items-center justify-start text-h2"><div data-v-3a0b7298="" class="q-pr-sm">Multimodal</div><div data-v-3a0b7298="" style="background: linear-gradient(to right, rgba(107, 73, 255, 0.8), rgb(255, 115, 147)) text; -webkit-text-fill-color: transparent;">Starter Kit</div></div><div data-v-3a0b7298="" class="row text-grey-5 q-py-lg"><div data-v-3a0b7298="" class="col-12 col-md-8">Want to build high-level AIGC applications using PromptPerfect, SceneXplain, BestBanner, JinaChat, Rationale APIs? We've got you covered! Try our easy-to-use SDK and get started in minutes.</div></div><div data-v-3a0b7298="" class="column q-gutter-y-md q-my-xl"><div data-v-3a0b7298="" class="q-btn-group row no-wrap q-btn-group--outline q-btn-group--square inline"><a data-v-3a0b7298="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="https://github.com/jina-ai/jinaai-py" target="_blank" style="padding: 16px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left fa-brands fa-python" aria-hidden="true" role="img"> </i><span class="block">Build with Python</span></span></a><hr data-v-3a0b7298="" class="q-separator q-separator--vertical q-separator--dark" aria-orientation="vertical"><a data-v-3a0b7298="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="https://github.com/jina-ai/jinaai-js" target="_blank" style="padding: 16px; 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text-decoration: none !important;"><span data-v-4867f981="" class="q-focus-helper"></span><div data-v-4867f981="" class="q-card__section q-card__section--vert q-pa-none"><div data-v-4867f981="" class="q-img q-img--menu" role="img" style="height: 200px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="200px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert" style="height: 250px;"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center text-h6 text-weight-light"><div data-v-4867f981="" class="q-item__label" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-4867f981="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label">Engineering Group</div><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div></div></div><div data-v-3a0b7298="" class="col-12 col-sm-6 col-md-4 col-xl-3 self-stretch q-pa-sm"><div data-v-4867f981="" data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow cursor-pointer q-hoverable full-height" style="overflow: hidden; text-decoration: none !important;"><span data-v-4867f981="" class="q-focus-helper"></span><div data-v-4867f981="" class="q-card__section q-card__section--vert q-pa-none"><div data-v-4867f981="" class="q-img q-img--menu" role="img" style="height: 200px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="200px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert" style="height: 250px;"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center text-h6 text-weight-light"><div data-v-4867f981="" class="q-item__label" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-4867f981="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label">Scott Martens</div><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div></div></div></div></div></div></div><div class="q-carousel__control q-carousel__navigation no-wrap absolute flex q-carousel__navigation--buttons q-carousel__navigation--bottom"><div class="q-carousel__navigation-inner flex flex-center no-wrap"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable q-btn--dense q-carousel__navigation-icon q-carousel__navigation-icon--active" tabindex="0" type="button" style="font-size: 10px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-circle" aria-hidden="true" role="img"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable q-btn--dense q-carousel__navigation-icon q-carousel__navigation-icon--inactive" tabindex="0" type="button" style="font-size: 10px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-circle" aria-hidden="true" role="img"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable q-btn--dense q-carousel__navigation-icon q-carousel__navigation-icon--inactive" tabindex="0" type="button" style="font-size: 10px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-circle" aria-hidden="true" role="img"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable q-btn--dense q-carousel__navigation-icon q-carousel__navigation-icon--inactive" tabindex="0" type="button" style="font-size: 10px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-circle" aria-hidden="true" role="img"> </i></span></button></div></div></div><a data-v-3a0b7298="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="/news" style="font-size: 20px; 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+</div><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-amber q-btn--actionable q-focusable q-hoverable q-btn--dense q-markdown__copy" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="q-icon" aria-hidden="true" role="img"><svg viewBox="0 0 24 24"><path d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg></span></span></button></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="row q-mt-xl q-pt-xl justify-between"><div data-v-3a0b7298="" class="col-12 col-md-5 col-lg-4"><div data-v-3a0b7298="" class="q-mb-lg q-pb-md"><div data-v-3a0b7298="" class="row text-h3 text-white q-mb-lg">Our Publications</div><div data-v-3a0b7298="" class="text-grey-5">To understand how our large language models were trained from scratch for embedding tasks, check out our latest research and publications. Meet our team at the EMNLP, ACL, SIGIR, NeurIPS, and ICML conferences.</div></div></div><div data-v-3a0b7298="" class="col-12 col-md-7"><div class="q-card q-card--dark q-dark q-card--flat no-shadow q-hoverable cursor-pointer q-mb-md"><span class="q-focus-helper"></span><div class="q-linear-progress text-primary research-card__progress" role="progressbar" aria-valuemin="0" aria-valuemax="1" aria-valuenow="100" style="font-size: 4px; --q-linear-progress-speed:2100ms;"><div class="q-linear-progress__track absolute-full q-linear-progress__track--with-transition q-linear-progress__track--dark" style="transform: scale3d(1, 1, 1);"></div><div class="q-linear-progress__model absolute-full q-linear-progress__model--with-transition q-linear-progress__model--determinate" style="transform: scale3d(100, 1, 1);"></div></div><div class="q-card__section q-card__section--horiz row no-wrap q-pa-none"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-pa-lg col-9" role="listitem" tabindex="0" href="https://arxiv.org/abs/2310.19923" target="_blank"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-mb-xl"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">2023.11</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><span class="q-icon q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"><img src="/arxiv_logo.svg"></span><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">arXiv</div></div></div></div><div class="q-space"></div><div class="q-item__label text-h6 q-mb-lg">Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Text embedding models have emerged as powerful tools for transforming sentences into fixed-sized feature vectors that encapsulate semantic information. While these models are essential for tasks like information retrieval, semantic clustering, and text re-ranking, most existing open-source models, especially those built on architectures like BERT, struggle to represent lengthy documents and often resort to truncation. One common approach to mitigate this challenge involves splitting documents into smaller paragraphs for embedding. However, this strategy results in a much larger set of vectors, consequently leading to increased memory consumption and computationally intensive vector searches with elevated latency.</div></div></a><div class="q-img q-img--menu research-card__img" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/paper_1.8ed04d7d.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow q-hoverable cursor-pointer q-mb-md"><span class="q-focus-helper"></span><div class="q-linear-progress text-primary research-card__progress" role="progressbar" aria-valuemin="0" aria-valuemax="1" aria-valuenow="100" style="font-size: 4px; --q-linear-progress-speed:2100ms;"><div class="q-linear-progress__track absolute-full q-linear-progress__track--with-transition q-linear-progress__track--dark" style="transform: scale3d(1, 1, 1);"></div><div class="q-linear-progress__model absolute-full q-linear-progress__model--with-transition q-linear-progress__model--determinate" style="transform: scale3d(100, 1, 1);"></div></div><div class="q-card__section q-card__section--horiz row no-wrap q-pa-none"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-pa-lg col-9" role="listitem" tabindex="0" href="https://arxiv.org/abs/2307.11224" target="_blank"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-mb-xl"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">2023.8</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">EMNLP 2023</div></div></div></div><div class="q-space"></div><div class="q-item__label text-h6 q-mb-lg">Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina Embeddings constitutes a set of high-performance sentence embedding models adept at translating textual inputs into numerical representations, capturing the semantics of the text. These models excel in applications like dense retrieval and semantic textual similarity. This paper details the development of Jina Embeddings, starting with the creation of high-quality pairwise and triplet datasets. It underlines the crucial role of data cleaning in dataset preparation, offers in-depth insights into the model training process, and concludes with a comprehensive performance evaluation using the Massive Text Embedding Benchmark (MTEB).</div></div></a><div class="q-img q-img--menu research-card__img" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/paper_2.59e1399a.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="q-py-xl q-my-xl row justify-center relative-position" id="power-users"><div data-v-3a0b7298="" class="q-img q-img--menu absolute-bottom-right" role="img" style="width: 80%; z-index: -1;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/pattern-sdk.fcc07f38.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-3a0b7298="" class="col-11"><a data-v-3a0b7298="" class="row justify-center q-gutter-x-sm text-h2 text-white q-my-xl q-py-xl" href="#power-users" style="text-decoration: none !important;"><div data-v-3a0b7298="">For</div><div data-v-3a0b7298="" style="background: linear-gradient(to right, rgba(107, 73, 255, 0.8), rgb(255, 115, 147)) text; -webkit-text-fill-color: transparent;">Power Users</div></a><div data-v-3a0b7298="" class="row justify-center q-my-xl text-grey-5">Experience powerful, user-friendly multimodal AI apps. No coding, no fuss, just results.</div><div data-v-3a0b7298="" class="column justify-center items-center"><div data-v-3a0b7298="" class="row fit justify-center items-center q-mt-lg"><div data-v-3a0b7298="" class="col-12 q-px-sm q-py-md" style="height: auto;"><div data-v-9abd4bf8="" data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-pa-lg text-white fit overflow-hidden cursor-pointer my-card q-hoverable rounded-borders"><span data-v-9abd4bf8="" class="q-focus-helper"></span><div data-v-9abd4bf8="" class="row fit"><div data-v-9abd4bf8="" class="q-card__section q-card__section--vert column col-12 col-lg-5 no-wrap"><div data-v-9abd4bf8="" class="row items-center"><div data-v-9abd4bf8="" class="q-img q-img--menu q-mr-sm" role="img" aria-label="" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://promptperfect.jina.ai/PromptPerfect-light.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu" role="img" aria-label="" style="width: 150px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/PromptPerfect.0db3b440.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-9abd4bf8="" class="row full-width text-weight-light text-h5 q-mt-lg"><div data-v-9abd4bf8="" class="col-12 col-sm-10">Premier tool for prompt engineering</div></div><div data-v-9abd4bf8="" class="q-card__section q-card__section--vert col q-pa-none q-pt-md"><div data-v-9abd4bf8="" class="q-splitter no-wrap q-splitter--vertical row q-splitter--workable q-splitter--dark fit"><div class="q-splitter__panel q-splitter__before full-height" style="width: 40%;"><div data-v-9abd4bf8="" class="q-card__section q-card__section--vert bg-grey-12 full-height rounded-borders q-pa-sm"><div data-v-9abd4bf8="" class="q-item q-item-type row no-wrap q-item--dark text-grey-10 text-body2 q-pa-none" role="listitem"><div data-v-9abd4bf8="" class="q-item__section column q-item__section--main justify-center"><div data-v-9abd4bf8="" class="q-item__label q-item__label--caption text-caption text-grey-8">Original prompt</div><div data-v-9abd4bf8="" class="q-item__label q-py-md" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 10;">Your role is to be my brainstorming partner.</div></div></div></div></div><div class="q-splitter__separator"><div class="q-splitter__separator-area absolute-full"><div data-v-9abd4bf8="" class="q-avatar bg-info text-white q-chip--colored" style="font-size: 2em;"><div class="q-avatar__content row flex-center overflow-hidden"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">sync_alt</i></div></div></div></div><div class="q-splitter__panel q-splitter__after col"><div data-v-9abd4bf8="" class="q-card__section q-card__section--vert bg-promptperfect full-height rounded-borders q-pa-sm"><div data-v-9abd4bf8="" class="q-item q-item-type row no-wrap q-item--dark text-white text-body2 q-pa-none" role="listitem"><div data-v-9abd4bf8="" class="q-item__section column q-item__section--main justify-center"><div data-v-9abd4bf8="" class="q-item__label q-item__label--caption text-caption text-grey-5">Optimized prompt</div><div data-v-9abd4bf8="" class="q-item__label q-py-md" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 9;">Your task is to be my brainstorming partner and provide creative ideas and suggestions for a given topic or problem. Your response should include original, unique, and relevant ideas that could help solve the problem or further explore the topic in an interesting way. Please note that your response should also take into account any specific requirements or constraints of the task.</div></div></div></div></div></div></div></div><div data-v-9abd4bf8="" class="q-card__section q-card__section--vert col-12 col-lg-7"><div data-v-9abd4bf8="" class="q-item q-item-type row no-wrap q-item--dark column rounded-borders text-white bg-grey-10 fit" role="listitem"><div data-v-9abd4bf8="" class="row text-grey-5 text-subtitle2 text-weight-light text-uppercase q-my-md">Text models</div><div data-v-9abd4bf8="" class="row justify-start items-center"><div data-v-9abd4bf8="" class="col-12"><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-chatgpt.619298f9.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-gpt3.fa7b97cd.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-gpt4.0ec3c1ca.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-stablelm.22649423.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-claude.d3214a05.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-claude2.885442a5.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-ernie.3b3b81f1.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-command.c22268f0.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-llama7b.32ec0462.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-llama13b.3dc34538.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-llama70b.e7552cbe.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-jinachat.dff4afb3.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-9abd4bf8="" class="row text-grey-5 text-subtitle2 text-weight-light text-uppercase q-my-md">Image models</div><div data-v-9abd4bf8="" class="row justify-start items-center"><div data-v-9abd4bf8="" class="col-12"><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-dalle2.1822fdac.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-sdxl.e5323437.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-midjourney.35d3c163.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-sd.938f1c41.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-kandinsky.ee36f5b8.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-dreamshaper.1029a401.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-absolutereality.1ca5c477.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-anything.f641ae91.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-deliberate.a8228b3c.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-sdxl-emoji.e020ab86.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-9abd4bf8="" class="q-img q-img--menu q-ma-sm col-3 col-md-2" role="img" style="width: 115px; height: 24px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/model-lexica.f98ffeed.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="col-12 q-px-sm q-py-md" style="height: auto;"><div data-v-0847e7dc="" data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-pa-lg bg-dark text-white fit overflow-hidden cursor-pointer my-card q-hoverable rounded-borders"><span data-v-0847e7dc="" class="q-focus-helper"></span><div data-v-0847e7dc="" class="full-height absolute-right card-bg"></div><div data-v-0847e7dc="" class="row fit"><div data-v-0847e7dc="" class="q-card__section q-card__section--vert column column col-12 col-lg-5 justify-start items-start"><div data-v-0847e7dc="" class="row items-center"><div data-v-0847e7dc="" class="q-img q-img--menu q-mr-sm" role="img" aria-label="" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://scenex.jina.ai/SceneX - Light.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-0847e7dc="" class="q-img q-img--menu" role="img" aria-label="" style="width: 150px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/SceneXplain.d7bc8012.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-0847e7dc="" class="row full-width text-weight-light text-h5 q-mt-lg">Leading AI solution for image captions and video summaries</div><div data-v-0847e7dc="" class="q-card__section q-card__section--vert row col justify-start items-start q-mt-lg"><div data-v-0847e7dc="" class="q-img q-img--menu col-5 relative-position rounded-borders" role="img" style="z-index: 10;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="scenex-example.gif" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-0847e7dc="" class="q-card q-card--dark q-dark q-card--flat no-shadow col-7 bg-pink-12 text-white q-pa-md relative-position" style="margin-left: -10px; margin-top: 35px;"><i data-v-0847e7dc="" class="q-icon text-pink-12 fa-solid fa-arrow-turn-down absolute" aria-hidden="true" role="presentation" style="left: 17px; top: -23px;"></i><div data-v-0847e7dc="" class="ellipsis-5-lines">This video appears to be a nature footage featuring a charming white bunny and a butterfly in a grassy field. The bunny is seen interacting with the butterfly in different ways, showcasing their unique relationship. The natural surroundings provide a picturesque backdrop, enhancing the beauty of this simple yet captivating scene.</div></div></div></div><div data-v-0847e7dc="" class="q-card__section q-card__section--vert col-12 col-lg-7"><div data-v-0847e7dc="" class="q-item q-item-type row no-wrap q-item--dark column rounded-borders text-white fit" role="listitem"><div data-v-0847e7dc="" class="q-list q-list--dark"><div data-v-0847e7dc="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-my-sm" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-0847e7dc="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-image2text.ebccb1d3.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--main justify-center"><div data-v-0847e7dc="" class="q-item__label text-pink-6">Caption Image</div><div data-v-0847e7dc="" class="q-item__label q-item__label--caption text-caption ellipsis">Generate a textual description of the image.</div></div></div><div data-v-0847e7dc="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-my-sm" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-0847e7dc="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-image2json.35b549f2.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--main justify-center"><div data-v-0847e7dc="" class="q-item__label text-pink-6">Extract JSON from Image</div><div data-v-0847e7dc="" class="q-item__label q-item__label--caption text-caption ellipsis">Generate a structured JSON format from the image using a predefined schema. This allows for specific data extraction from the image.</div></div></div><div data-v-0847e7dc="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-my-sm" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-0847e7dc="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-VQA.f0555b28.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--main justify-center"><div data-v-0847e7dc="" class="q-item__label text-pink-6">Visual Q&amp;A</div><div data-v-0847e7dc="" class="q-item__label q-item__label--caption text-caption ellipsis">Answer a query based on the image's content.</div></div></div><div data-v-0847e7dc="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-my-sm" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-0847e7dc="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-video2text.52fa889f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--main justify-center"><div data-v-0847e7dc="" class="q-item__label text-pink-6">Summarize Video</div><div data-v-0847e7dc="" class="q-item__label q-item__label--caption text-caption ellipsis">Generate a concise summary of the video, highlighting key events.</div></div></div><div data-v-0847e7dc="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable q-my-sm" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-0847e7dc="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/icon-image2text+voice.12170321.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-0847e7dc="" class="q-item__section column q-item__section--main justify-center"><div data-v-0847e7dc="" class="q-item__label text-pink-6">Generate Story</div><div data-v-0847e7dc="" class="q-item__label q-item__label--caption text-caption ellipsis">Craft a story inspired by the image, often featuring dialogues or monologues of its characters.</div></div></div></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="row fit justify-center items-center q-mt-lg"><div data-v-3a0b7298="" class="col-12 col-md-4 q-px-sm q-py-md" style="height: 480px;"><div data-v-39dbf15b="" data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-pa-lg text-white fit overflow-hidden cursor-pointer my-card q-hoverable rounded-borders"><div data-v-39dbf15b="" class="full-height absolute-right card-bg"></div><span data-v-39dbf15b="" class="q-focus-helper"></span><div data-v-39dbf15b="" class="q-card__section q-card__section--vert column justify-start items-start"><div data-v-39dbf15b="" class="row items-center"><div data-v-39dbf15b="" class="q-img q-img--menu q-mr-sm" role="img" aria-label="" style="width: 40px; height: 40px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://chat.jina.ai/JinaChat - Light.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-39dbf15b="" class="q-img q-img--menu" role="img" aria-label="" style="width: 100px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jinachat-long.a75b4791.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-39dbf15b="" class="row full-width text-weight-light text-h5 q-mt-lg"><div data-v-39dbf15b="" class="col-11">More modality, longer memory, less cost</div></div></div><div data-v-39dbf15b="" class="q-card__section q-card__section--vert row justify-center items-center full-width q-mt-sm"><div data-v-39dbf15b="" class="col-5 column justify-center bg-white rounded-borders shadow-1 q-pa-md relative-position" style="width: 95%; box-shadow: rgba(0, 0, 0, 0.05) 0px 2px 16px 4px; z-index: 7;"><div data-v-39dbf15b="" class="q-message q-message-sent"><div class="q-message-container row items-end no-wrap reverse"><div class=""><div class="q-message-text q-message-text--sent text-grey-3"><div class="q-message-text-content q-message-text-content--sent"><div>Who are you?</div></div></div></div></div></div><div data-v-39dbf15b="" class="q-img q-img--menu absolute-left" role="img" aria-label="" style="width: 36px; transform: translateX(-50%);"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" width="36px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jinachat-pen.5dbd5a16.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-39dbf15b="" class="q-img q-img--menu absolute-top" role="img" aria-label="" style="width: 56px; left: 50%; transform: translate(-50%, -50%);"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" width="56px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jinachat-hand.8ff791f4.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-39dbf15b="" class="q-img q-img--menu absolute-top-right" role="img" aria-label="" style="width: 36px; transform: translate(50%, -50%);"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" width="36px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jinachat-think.df40ad8c.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-39dbf15b="" class="col-5 column justify-center bg-white rounded-borders shadow-1 q-pa-md full-width relative-position" style="margin-top: -10px; box-shadow: rgba(0, 0, 0, 0.05) 0px 2px 16px 4px; z-index: 8;"><div data-v-39dbf15b="" class="q-message q-message-received center-chat-message"><div class="q-message-container row items-end no-wrap"><img class="q-message-avatar q-message-avatar--received" src="https://chat.jina.ai/JinaChat - Light.svg" aria-hidden="true"><div class=""><div class="q-message-text q-message-text--received text-blue-7"><div class="q-message-text-content q-message-text-content--received text-white"><div>I'm a LLM chat service made by Jina AI</div></div></div></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="col-12 col-md-4 q-px-sm q-py-md" style="height: 480px;"><div data-v-12da09fe="" data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-pa-lg text-white fit overflow-hidden cursor-pointer bg-black q-hoverable my-card rounded-borders"><div data-v-12da09fe="" class="full-height absolute-right card-bg"></div><span data-v-12da09fe="" class="q-focus-helper"></span><div data-v-12da09fe="" class="q-card__section q-card__section--vert column justify-start items-start fit"><div data-v-12da09fe="" class="row items-center"><div data-v-12da09fe="" class="q-img q-img--menu q-mr-sm" role="img" aria-label="" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://bestbanner.jina.ai/bestbanner-light.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-12da09fe="" class="q-img q-img--menu" role="img" aria-label="" style="width: 120px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/BestBanner.85dfb1db.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-12da09fe="" class="row full-width text-weight-light text-h5 q-mt-lg">Blog to banner, without the prompts!</div><div data-v-12da09fe="" class="q-card__section q-card__section--horiz row no-wrap col items-center q-mt-xl"><div data-v-12da09fe="" class="q-card q-card--dark q-dark col-5"><div data-v-12da09fe="" class="q-card__section q-card__section--vert q-pa-none"><div data-v-12da09fe="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-12da09fe="" class="q-item__section column q-item__section--main justify-center"><div data-v-12da09fe="" class="q-item__label q-item__label--overline text-overline">Alice's Adventures in Wonderland - Chapter 1</div><div data-v-12da09fe="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Alice was beginning to get very tired of sitting by her sister on the bank, and of having nothing to do: once or twice she had peeped into the book her sister was reading, but it had no pictures or conversations in it, “and what is the use of a book,” thought Alice “without pictures or conversations?” So she was considering in her own mind (as well as she could, for the hot day made her feel very sleepy and stupid), whether the pleasure of making a daisy-chain would be worth the trouble of getting up and picking the daisies, when suddenly a White Rabbit with pink eyes ran close by her.</div></div></div></div></div><div data-v-12da09fe="" class="q-card__section q-card__section--vert col q-pa-none"><div data-v-12da09fe="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="bestbanner_example.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="col-12 col-md-4 q-px-sm q-py-md" style="height: 480px;"><div data-v-d1cf110c="" data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-pa-lg text-white fit cursor-pointer my-card q-hoverable rounded-borders"><span data-v-d1cf110c="" class="q-focus-helper"></span><div data-v-d1cf110c="" class="q-card__section q-card__section--vert column justify-start items-start fit"><div data-v-d1cf110c="" class="row items-center"><div data-v-d1cf110c="" class="q-img q-img--menu q-mr-sm" role="img" aria-label="" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-d1cf110c="" class="q-img q-img--menu" role="img" aria-label="" style="width: 90px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/Rationale.389fb532.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-d1cf110c="" class="row full-width text-weight-light text-white text-h5 q-my-lg">See two sides of the coin, make rational decisions</div><div data-v-d1cf110c="" class="column col justify-start items-start full-width no-wrap"><span data-v-d1cf110c="" class="text-h7">Decision</span><div data-v-d1cf110c="" class="q-card q-card--bordered q-card--flat no-shadow full-width q-pa-md q-mt-sm bg-transparent"><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-grey-4" style="--q-skeleton-speed:1500ms; width: 100%;"></div><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-grey-4 col col-8" style="--q-skeleton-speed:1500ms; width: 70%;"></div></div><div data-v-d1cf110c="" class="row q-mt-md full-width"><div data-v-d1cf110c="" class="row justify-start items-center full-width"><div data-v-d1cf110c="" class="row col items-center q-pr-sm"><button data-v-d1cf110c="" class="q-btn q-btn-item non-selectable no-outline q-btn--unelevated q-btn--round bg-teal-4 text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">thumb_up</i></span></button><div data-v-d1cf110c="" class="col q-pl-sm"><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-teal-4" style="--q-skeleton-speed:1500ms; width: 30%;"></div><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-teal-4" style="--q-skeleton-speed:1500ms; width: 100%;"></div><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-teal-4" style="--q-skeleton-speed:1500ms; width: 100%;"></div></div></div><div data-v-d1cf110c="" class="row col items-center q-pr-sm"><button data-v-d1cf110c="" class="q-btn q-btn-item non-selectable no-outline q-btn--unelevated q-btn--round bg-red-4 text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">thumb_down</i></span></button><div data-v-d1cf110c="" class="col q-pl-sm"><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-red-4" style="--q-skeleton-speed:1500ms; width: 30%;"></div><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-red-4" style="--q-skeleton-speed:1500ms; width: 100%;"></div><div data-v-d1cf110c="" class="q-skeleton q-skeleton--dark q-skeleton--type-text bg-red-4" style="--q-skeleton-speed:1500ms; width: 100%;"></div></div></div></div></div></div></div></div></div></div></div></div></div><div data-v-3a0b7298="" class="q-py-xl q-my-xl row justify-center bg-dark" id="developers"><div data-v-3a0b7298="" class="col-11 relative-position" style="z-index: 1;"><a data-v-3a0b7298="" class="row justify-center q-gutter-x-sm text-h2 text-white q-my-xl q-py-xl" href="#developers" style="text-decoration: none !important;"><div data-v-3a0b7298="">For</div><div data-v-3a0b7298="" style="background: linear-gradient(to right, rgb(64, 101, 235), rgb(98, 255, 73)) text; -webkit-text-fill-color: transparent;">Developers</div></a><div data-v-3a0b7298="" class="row justify-center items-center q-my-xl text-grey-5">Unleash the full power of multimodal AI with cutting-edge cloud-native technologies and open-source infrastructure.</div><div data-v-3a0b7298="" class="row q-my-xl justify-center"><a data-v-3a0b7298="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square col-12 col-md-10 col-lg-8" tabindex="0" href="jina-ai-multimodal-stack-20230720.pdf" target="_blank" style="padding: 32px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><div data-v-3a0b7298="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/mm-stack.10034a23.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></span></a></div><div data-v-3a0b7298="" class="row q-my-xl q-py-xl"><div class="col-12 col-md-5 column justify-start items-center"><a class="row items-center justify-start text-h2 text-white" href="#developers" style="text-decoration: none !important;">Multimodal Stack</a><div class="row text-grey-5 q-py-lg"><div class="col-12 col-md-8">The developer-friendly, cloud-native, and production-ready stack for building multimodal AI applications.</div></div><div class="row text-grey-5 q-py-lg relative-position"><div class="col-12 col-md-8"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Data Structure</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><i class="q-icon fab fa-linux q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Linux Foundation</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Core</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">science</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Incubating</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Orchestration</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Cloud Native</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Kubernetes</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">school</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Graduated</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Tuning</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Mid Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Small Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Prompt Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">egg</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Sandbox</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Database</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">archive</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Archived</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Prompt Tuning</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--clickable cursor-pointer non-selectable q-hoverable q-chip--square q-chip--dark q-dark no-border-radius non-selectable cursor-pointer" tabindex="0" style="font-size: 14px;"><div class="q-focus-helper"></div><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Large Size Model</div></div></div></div><div class="q-img q-img--menu absolute" role="img" style="width: 100%; top: 100%; left: -40%; z-index: -1;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/pattern-developers.4f94c0e3.svg" style="object-fit: fill; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div class="col-12 col-md-7 row justify-center"><div class="q-pa-xs col-12" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">Jina</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">19.5K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Orchestration</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Cloud Native</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Kubernetes</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Core</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">school</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Graduated</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Jina</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Build multimodal AI applications on the cloud</div></div></div><div class="q-pa-xs col-12" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">DocArray</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">2.6K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Data Structure</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-linux q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Linux Foundation</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Core</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">science</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Incubating</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">DocArray</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">The data structure for multimodal data</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-body">LangChain-Serve</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1.5K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Small Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Prompt Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">egg</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Sandbox</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">LangChain-Serve</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Langchain apps on production with Jina &amp; FastAPI</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">VectorDB</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">409 Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Vector Database</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">egg</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Sandbox</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">VectorDB</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">A Python vector database you just need - no more, no less</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">RunGPT</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">122 Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Large Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">egg</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Sandbox</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">RunGPT</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">An open-source cloud-native of large multimodal models serving framework</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">Finetuner</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1.4K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Tuning</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">science</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Incubating</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Finetuner</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Fine-tune embeddings on domain specific data for better search quality</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-body">DALL-E Flow</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">2.8K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Mid Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">archive</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Archived</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">DALL-E Flow</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">A human-in-the-Loop workflow for creating HD images from text</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">DiscoArt</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">3.8K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Mid Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">archive</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Archived</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">DiscoArt</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Create compelling Disco Diffusion artworks in one line of code</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-body">CLIP-as-service</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">12K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Mid Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">science</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Incubating</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">CLIP-as-service</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Embed images and sentences into fixed-length vectors with CLIP</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">JCloud</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">292 Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Cloud Native</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Kubernetes</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">science</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Incubating</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">JCloud</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgba(107, 73, 255, 0.8), rgb(255, 115, 147), rgb(242, 191, 132)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-body">Executor Hub</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Embedding Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">archive</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Archived</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Executor Hub</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Share and discover building blocks for multimodal AI applications</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">ThinkGPT</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1.4K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Prompt Tuning</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Prompt Serving</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">archive</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Archived</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">ThinkGPT</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Agent techniques to augment your LLM and push it beyond its limits</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">DevGPT</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1.5K Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Prompt Tuning</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">archive</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Archived</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">DevGPT</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">Your virtual development team</div></div></div><div class="q-pa-xs col-6" style="max-height: 260px;"><div class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow q-px-sm q-py-lg text-white full-height relative-position cursor-pointer bg-dark-page overflow-hidden non-selectable"><div class="absolute-full" style="background-image: linear-gradient(-135deg, rgb(52, 164, 179), rgb(117, 83, 254), rgb(244, 170, 82), rgb(255, 196, 122)); z-index: 10; display: none;"><div class="q-card__section q-card__section--vert row items-center q-gutter-sm text-no-wrap no-wrap"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div class="text-h6">Jerboa</div></div><div class="q-card__section q-card__section--vert text-white"><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon fab fa-github q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation"> </i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">30 Stars</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Large Size Model</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">egg</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Sandbox</div></div></div><div class="q-chip row inline no-wrap items-center text-grey-3 q-chip--colored q-chip--outline q-chip--square q-chip--dark q-dark no-border-radius" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Model Serving</div></div></div></div><div class="q-card__actions justify-end q-card__actions--horiz row"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round text-white q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">arrow_right_alt</i></span></button></div></div><div class="q-card__section q-card__section--vert row justify-center"><div class="q-img q-img--menu" role="img" style="width: 40px; height: 40px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="40px" width="40px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-card__section q-card__section--vert row justify-center text-no-wrap text-h6 text-weight-light q-pa-none">Jerboa</div><div class="q-card__section q-card__section--vert text-caption q-px-xs text-center">An experimental finetuner for open-source LLMs</div></div></div></div></div><div data-v-3a0b7298="" class="row q-my-xl q-py-xl justify-between"><div data-v-3a0b7298="" class="col-12 col-md-5 column justify-start items-center"><div data-v-3a0b7298="" class="row items-center justify-start text-h2"><div data-v-3a0b7298="" class="q-pr-sm">Multimodal</div><div data-v-3a0b7298="" style="background: linear-gradient(to right, rgba(107, 73, 255, 0.8), rgb(255, 115, 147)) text; -webkit-text-fill-color: transparent;">Starter Kit</div></div><div data-v-3a0b7298="" class="row text-grey-5 q-py-lg"><div data-v-3a0b7298="" class="col-12 col-md-8">Want to build high-level AIGC applications using PromptPerfect, SceneXplain, BestBanner, JinaChat, Rationale APIs? We've got you covered! Try our easy-to-use SDK and get started in minutes.</div></div><div data-v-3a0b7298="" class="column q-gutter-y-md q-my-xl"><div data-v-3a0b7298="" class="q-btn-group row no-wrap q-btn-group--outline q-btn-group--square inline"><a data-v-3a0b7298="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="https://github.com/jina-ai/jinaai-py" target="_blank" style="padding: 16px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left fa-brands fa-python" aria-hidden="true" role="img"> </i><span class="block">Build with Python</span></span></a><hr data-v-3a0b7298="" class="q-separator q-separator--vertical q-separator--dark" aria-orientation="vertical"><a data-v-3a0b7298="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="https://github.com/jina-ai/jinaai-js" target="_blank" style="padding: 16px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left fa-brands fa-js" aria-hidden="true" role="img"> </i><span class="block">Build with JavaScript</span></span></a></div></div></div><div data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow col-12 col-md-7"><div class="q-tabs row no-wrap items-center q-tabs--not-scrollable q-tabs--horizontal q-tabs__arrows--inside q-tabs--mobile-without-arrows q-tabs--dense bg-grey-10" role="tablist" icon="code"><div class="q-tabs__content scroll--mobile row no-wrap items-center self-stretch hide-scrollbar relative-position q-tabs__content--align-justify"><div class="q-tab relative-position self-stretch flex flex-center text-center q-tab--active q-focusable q-hoverable cursor-pointer" tabindex="0" role="tab" aria-selected="true"><div class="q-focus-helper" tabindex="-1"></div><div class="q-tab__content self-stretch flex-center relative-position q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon notranslate material-icons q-tab__icon" aria-hidden="true" role="presentation">summarize</i><div class="q-tab__label">Example</div></div><div class="q-tab__indicator absolute-bottom text-white"></div></div><div class="q-tab relative-position self-stretch flex flex-center text-center q-tab--inactive q-focusable q-hoverable cursor-pointer" tabindex="-1" role="tab" aria-selected="false"><div class="q-focus-helper" tabindex="-1"></div><div class="q-tab__content self-stretch flex-center relative-position q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon fab fa-python q-tab__icon" aria-hidden="true" role="presentation"> </i><div class="q-tab__label">python</div></div><div class="q-tab__indicator absolute-bottom text-white"></div></div><div class="q-tab relative-position self-stretch flex flex-center text-center q-tab--inactive q-focusable q-hoverable cursor-pointer" tabindex="-1" role="tab" aria-selected="false"><div class="q-focus-helper" tabindex="-1"></div><div class="q-tab__content self-stretch flex-center relative-position q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon fab fa-js-square q-tab__icon" aria-hidden="true" role="presentation"> </i><div class="q-tab__label">javascript</div></div><div class="q-tab__indicator absolute-bottom text-white"></div></div></div><i class="q-icon fas fa-chevron-left q-tabs__arrow q-tabs__arrow--left absolute q-tab__icon" aria-hidden="true" role="presentation"> </i><i class="q-icon fas fa-chevron-right q-tabs__arrow q-tabs__arrow--right absolute q-tab__icon q-tabs__arrow--faded" aria-hidden="true" role="presentation"> </i></div><div class="q-tab-panels q-panel-parent q-tab-panels--dark q-dark q-mb-md bg-dark"><div class="q-panel scroll" role="tabpanel" style="--q-transition-duration:300ms;"><div class="q-tab-panel" role="tabpanel"><div class="q-img q-img--menu" role="img" style="max-height: 550px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/SDK-example.dd1a7fa4.svg" style="object-fit: contain; 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text-decoration: none !important;"><span data-v-4867f981="" class="q-focus-helper"></span><div data-v-4867f981="" class="q-card__section q-card__section--vert q-pa-none"><div data-v-4867f981="" class="q-img q-img--menu" role="img" style="height: 200px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="200px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert" style="height: 250px;"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center text-h6 text-weight-light"><div data-v-4867f981="" class="q-item__label" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-4867f981="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label">Engineering Group</div><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div></div></div><div data-v-3a0b7298="" class="col-12 col-sm-6 col-md-4 col-xl-3 self-stretch q-pa-sm"><div data-v-4867f981="" data-v-3a0b7298="" class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow cursor-pointer q-hoverable full-height" style="overflow: hidden; text-decoration: none !important;"><span data-v-4867f981="" class="q-focus-helper"></span><div data-v-4867f981="" class="q-card__section q-card__section--vert q-pa-none"><div data-v-4867f981="" class="q-img q-img--menu" role="img" style="height: 200px;"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" height="200px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert" style="height: 250px;"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center text-h6 text-weight-light"><div data-v-4867f981="" class="q-item__label" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div></div></div><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div></div><div data-v-4867f981="" class="q-card__section q-card__section--vert"><div data-v-4867f981="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-4867f981="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-4867f981="" class="q-item__section column q-item__section--main justify-center"><div data-v-4867f981="" class="q-item__label">Scott Martens</div><div data-v-4867f981="" class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div></div></div></div></div></div></div><div class="q-carousel__control q-carousel__navigation no-wrap absolute flex q-carousel__navigation--buttons q-carousel__navigation--bottom"><div class="q-carousel__navigation-inner flex flex-center no-wrap"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable q-btn--dense q-carousel__navigation-icon q-carousel__navigation-icon--active" tabindex="0" type="button" style="font-size: 10px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-circle" aria-hidden="true" role="img"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable q-btn--dense q-carousel__navigation-icon q-carousel__navigation-icon--inactive" tabindex="0" type="button" style="font-size: 10px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-circle" aria-hidden="true" role="img"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable q-btn--dense q-carousel__navigation-icon q-carousel__navigation-icon--inactive" tabindex="0" type="button" style="font-size: 10px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-circle" aria-hidden="true" role="img"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--round q-btn--actionable q-focusable q-hoverable q-btn--dense q-carousel__navigation-icon q-carousel__navigation-icon--inactive" tabindex="0" type="button" style="font-size: 10px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-circle" aria-hidden="true" role="img"> </i></span></button></div></div></div><a data-v-3a0b7298="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase q-btn--square" tabindex="0" href="/news" style="font-size: 20px; 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padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-meetup" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="mailto:support@jina.ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">email</i></span></a></div><div class="row col-12 col-md-6 items-center text-caption justify-center"><div class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--stretch inline" no-caps=""><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch text-caption" tabindex="0" href="/legal/#privacy-policy" style="padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">Privacy Policy</span></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch text-caption" tabindex="0" href="/legal/#terms-and-conditions" style="padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">Terms and Conditions</span></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch text-caption" tabindex="0" href="javascript:UC_UI.showSecondLayer();" style="padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">Privacy Settings</span></span></a></div></div></div></footer></div></div><div id="q-notify" data-v-app=""><div class="q-notifications"><div class="q-notifications__list q-notifications__list--top fixed column no-wrap items-start"></div><div class="q-notifications__list q-notifications__list--top fixed column no-wrap items-end"></div><div class="q-notifications__list q-notifications__list--bottom fixed column no-wrap items-start"></div><div class="q-notifications__list q-notifications__list--bottom fixed column no-wrap items-end"></div><div class="q-notifications__list q-notifications__list--top fixed column no-wrap items-center"></div><div class="q-notifications__list q-notifications__list--bottom fixed column no-wrap items-center"></div><div class="q-notifications__list q-notifications__list--center fixed column no-wrap items-start justify-center"></div><div class="q-notifications__list q-notifications__list--center fixed column no-wrap items-end justify-center"></div><div class="q-notifications__list q-notifications__list--center fixed column no-wrap flex-center"></div></div></div></body></html>
\ No newline at end of file
diff --git a/internship/index.html b/internship/index.html
index dda3fd3cef6..ac278f1467d 100644
--- a/internship/index.html
+++ b/internship/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Intern Program</title><meta charset="utf-8"><meta name="title" content="Intern Program"><meta name="description" content="Worldwide call for students: Intern in research, engineering, marketing, sales and more to pioneer multimodal AI together."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/internship"><meta property="og:title" content="Intern Program"><meta property="og:description" content="Worldwide call for students: Intern in research, engineering, marketing, sales and more to pioneer multimodal AI together."><meta property="og:image" content="https://jina.ai/banner-internship.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/internship"><meta property="twitter:title" content="Intern Program"><meta property="twitter:description" content="Worldwide call for students: Intern in research, engineering, marketing, sales and more to pioneer multimodal AI together."><meta property="twitter:image" content="https://jina.ai/banner-internship.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Intern Program</title><meta charset="utf-8"><meta name="title" content="Intern Program"><meta name="description" content="Worldwide call for students: Intern in research, engineering, marketing, sales and more to pioneer multimodal AI together."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/internship"><meta property="og:title" content="Intern Program"><meta property="og:description" content="Worldwide call for students: Intern in research, engineering, marketing, sales and more to pioneer multimodal AI together."><meta property="og:image" content="https://jina.ai/banner-internship.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/internship"><meta property="twitter:title" content="Intern Program"><meta property="twitter:description" content="Worldwide call for students: Intern in research, engineering, marketing, sales and more to pioneer multimodal AI together."><meta property="twitter:image" content="https://jina.ai/banner-internship.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
   <link rel="stylesheet" href="/assets/index.9fe6336f.css">
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/InternshipPage.3127fdca.js"><link rel="stylesheet" href="/assets/InternshipPage.98115a6d.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QParallax.bd31f995.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/useMetaTags.f561479d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jerboa</div><div class="q-item__label q-item__label--caption text-caption">An experimental finetuner for open-source LLMs</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="8566cbae-8963-474d-838e-3cbdf91ef1d9" aria-label="Expand &quot;Company&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><span class="q-icon" aria-hidden="true" role="presentation"><img src="/J.svg"></span></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Company</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="8566cbae-8963-474d-838e-3cbdf91ef1d9" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/about-us"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">About us</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/contact-sales"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Contact sales</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/open-day"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Open day</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/internship"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Intern program</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://jobs.lever.co/jina-ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Join us</div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">open_in_new</i></div></div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div></div></div></div><div class="q-scrollarea__bar q-scrollarea__bar--v absolute-right q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__bar q-scrollarea__bar--h absolute-bottom q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--v absolute-right q-scrollarea__thumb--invisible" aria-hidden="true" style="top: 0px; height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-06c9a5ac="" class="q-page" style="min-height: 449px;"><div data-v-06c9a5ac="" class="row q-py-xl justify-center items-center q-px-lg internship-background"><div data-v-06c9a5ac="" class="col-12 col-md-10 q-py-xl q-ma-xl q-ml-sm q-pl-sm"><div data-v-06c9a5ac="" class="q-my-xl text-weight-bold text-h2">Intern Program</div><div data-v-06c9a5ac="" class="q-pt-lg q-mb-xl text-subtitle1" style="width: 100%;">Worldwide call for students: Intern in research, engineering, marketing, sales and more to pioneer multimodal AI together.</div></div></div><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow row justify-center bg-dark-page q-py-xl"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert col-12 col-md-9"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center text-h2 q-pb-lg text-center">Explore stories from our interns</div></div><div data-v-06c9a5ac="" class="row q-mt-lg justify-center"><div data-v-06c9a5ac="" class="col-12 col-sm-6 col-md-4"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm"><div data-v-06c9a5ac="" class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 56.25%;"></div></div><div class="q-responsive__content absolute-full fit"><iframe data-v-06c9a5ac="" src="https://www.youtube.com/embed/pfG_d0gqdMk" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h5 handwritten1">Jonathan Geuter</div><div data-v-06c9a5ac="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Fine-tuned LLM models for better embeddings</div></div><div data-v-06c9a5ac="" class="q-item__section column q-item__section--side q-item__section--top justify-start q-item__section--avatar"><div data-v-06c9a5ac="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software Engineer Intern</div></div></div></div></div></div></div></div><div data-v-06c9a5ac="" class="col-12 col-sm-6 col-md-4"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm"><div data-v-06c9a5ac="" class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 56.25%;"></div></div><div class="q-responsive__content absolute-full fit"><iframe data-v-06c9a5ac="" src="https://www.youtube.com/embed/_4-MGLJmtmM" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h5 handwritten2">Sebastian Weisshaar</div><div data-v-06c9a5ac="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Explored the potential of Retrieval Augmented Generation</div></div><div data-v-06c9a5ac="" class="q-item__section column q-item__section--side q-item__section--top justify-start q-item__section--avatar"><div data-v-06c9a5ac="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software Engineer Intern</div></div></div></div></div></div></div></div><div data-v-06c9a5ac="" class="col-12 col-sm-6 col-md-4"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm"><div data-v-06c9a5ac="" class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 56.25%;"></div></div><div class="q-responsive__content absolute-full fit"><iframe data-v-06c9a5ac="" src="https://www.youtube.com/embed/Eg4p7XewMN4" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h5 handwritten3">Louis Milliken</div><div data-v-06c9a5ac="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Published a paper on the topic of sentence embeddings</div></div><div data-v-06c9a5ac="" class="q-item__section column q-item__section--side q-item__section--top justify-start q-item__section--avatar"><div data-v-06c9a5ac="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software Engineer Intern</div></div></div></div></div></div></div></div><div data-v-06c9a5ac="" class="col-12 col-sm-6 col-md-4"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm"><div data-v-06c9a5ac="" class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 56.25%;"></div></div><div class="q-responsive__content absolute-full fit"><iframe data-v-06c9a5ac="" src="https://www.youtube.com/embed/NloMmcC4QmY" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h5 handwritten1">Yuxi Lu</div><div data-v-06c9a5ac="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Injecting continuous youthful vitality into the team</div></div><div data-v-06c9a5ac="" class="q-item__section column q-item__section--side q-item__section--top justify-start q-item__section--avatar"><div data-v-06c9a5ac="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Recruiting and Administrative Intern</div></div></div></div></div></div></div></div><div data-v-06c9a5ac="" class="col-12 col-sm-6 col-md-4"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm"><div data-v-06c9a5ac="" class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 56.25%;"></div></div><div class="q-responsive__content absolute-full fit"><iframe data-v-06c9a5ac="" src="https://www.youtube.com/embed/sLEu_mLl0zE" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h5 handwritten2">Kaipeng Huang</div><div data-v-06c9a5ac="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Benchmarked quantization techniques to compress LLM</div></div><div data-v-06c9a5ac="" class="q-item__section column q-item__section--side q-item__section--top justify-start q-item__section--avatar"><div data-v-06c9a5ac="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software Engineer Intern</div></div></div></div></div></div></div></div><div data-v-06c9a5ac="" class="col-12 col-sm-6 col-md-4"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm"><div data-v-06c9a5ac="" class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 56.25%;"></div></div><div class="q-responsive__content absolute-full fit"><iframe data-v-06c9a5ac="" src="https://www.youtube.com/embed/PtJw0e7h4s8" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h5 handwritten3">Wenjie Hua</div><div data-v-06c9a5ac="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Creating and promoting compelling campaign for PromptPerfect</div></div><div data-v-06c9a5ac="" class="q-item__section column q-item__section--side q-item__section--top justify-start q-item__section--avatar"><div data-v-06c9a5ac="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Developer Relations Intern</div></div></div></div></div></div></div></div></div></div></div><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow row justify-center q-py-xl col-12 col-xl-10"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert text-h2 text-center q-my-xl">Our thriving alumni network</div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert row justify-center items-center q-py-xl q-my-xl"><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 37.7358%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_Carnegie_Mellon_University.10e68cbb.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_University_of_California_Berkeley.e1004510.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_Tsinghua.0b553bea.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_Harvard_University.ab67e0d6.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_ETH_Zurich.34438a4e.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/Logo_Technical_University_of_Munich.1f951f0f.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_KAIST.4c3e242e.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 20%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_armsterdam.bc69cf2b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 55.9524%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/Logo_der_Technischen_Universität_Berlin.8ee79d74.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 39.2157%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/TU_Delft_Logo.0f5ee4b8.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_BUPT.6bb5fca7.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_CNU.2b043e48.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_Xiamen_University.c0ee1c9e.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow row items-center bg-dark-page justify-center q-py-xl"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert col-12 col-md-4"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark justify-center text-h2 q-pb-lg" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center">Kickstart your adventure with Jina AI</div></div><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark text-subtitle1 q-mt-sm" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center">Embark on a transformative journey with Jina AI. Our comprehensive internship program invites all passionate minds who aspire to shape the future of artificial intelligence. Join us to get real-world experience, work on challenging projects, and collaborate with some of the brightest minds in the AI industry.</div></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert col-12 col-md-6 row"><div data-v-06c9a5ac="" class="col-12 col-md-6"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm q-hoverable"><span data-v-06c9a5ac="" class="q-focus-helper"></span><div data-v-06c9a5ac="" class="q-parallax" style="height: 300px;"><div class="q-parallax__media absolute-full"><img src="/developer-card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h6 q-mb-sm">Winter / 2023</div></div></div><div data-v-06c9a5ac="" class="q-card__actions justify-start q-card__actions--horiz row"><a data-v-06c9a5ac="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable apply-btn full-width" tabindex="0" href="https://jobs.lever.co/jina-ai/8a9b0075-0fd6-40ab-9c67-1b55dd431c82" target="_blank"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">open_in_new</i><span class="block">Apply now</span></span></a></div></div></div><div data-v-06c9a5ac="" class="col-12 col-md-6"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm q-hoverable"><span data-v-06c9a5ac="" class="q-focus-helper"></span><div data-v-06c9a5ac="" class="q-parallax" style="height: 300px;"><div class="q-parallax__media absolute-full"><img src="/prosumer-card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h6 q-mb-sm">Spring / 2024</div></div></div><div data-v-06c9a5ac="" class="q-card__actions justify-start q-card__actions--horiz row"><a data-v-06c9a5ac="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable apply-btn full-width" tabindex="0" href="https://jobs.lever.co/jina-ai/c3335e56-dfb0-40d7-871d-f1a87ccb0e8d" target="_blank"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">open_in_new</i><span class="block">Apply now</span></span></a></div></div></div><div data-v-06c9a5ac="" class="col-12 col-md-6"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm q-hoverable"><span data-v-06c9a5ac="" class="q-focus-helper"></span><div data-v-06c9a5ac="" class="q-parallax" style="height: 300px;"><div class="q-parallax__media absolute-full"><img src="/summer-card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h6 q-mb-sm">Summer / 2024</div></div></div><div data-v-06c9a5ac="" class="q-card__actions justify-start q-card__actions--horiz row"><a data-v-06c9a5ac="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable apply-btn full-width" tabindex="0" href="https://jobs.lever.co/jina-ai/f79464ed-0537-413c-81fe-6710bf83d569" target="_blank"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">open_in_new</i><span class="block">Apply now</span></span></a></div></div></div><div data-v-06c9a5ac="" class="col-12 col-md-6"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm q-hoverable"><span data-v-06c9a5ac="" class="q-focus-helper"></span><div data-v-06c9a5ac="" class="q-parallax" style="height: 300px;"><div class="q-parallax__media absolute-full"><img src="/enterprise-card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h6 q-mb-sm">Autumn / 2024</div></div></div><div data-v-06c9a5ac="" class="q-card__actions justify-start q-card__actions--horiz row"><a data-v-06c9a5ac="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable apply-btn full-width" tabindex="0" href="https://jobs.lever.co/jina-ai/d17e522f-4095-4e22-91a0-523938132664" target="_blank"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">open_in_new</i><span class="block">Apply now</span></span></a></div></div></div></div></div><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow row justify-center q-py-xl"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert text-h2 text-center q-my-xl col-12">FAQ</div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert col-12 col-sm-9 col-md-6"><div data-v-06c9a5ac="" class="q-list q-list--dark"><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="9c9a5d37-863f-472d-b8c1-0d1396a526f5" aria-label="Expand &quot;Who can apply for the Jina AI internship program?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Who can apply for the Jina AI internship program?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="9c9a5d37-863f-472d-b8c1-0d1396a526f5" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Undergraduate, Masters, and Ph.D. students from all over the world, with interest in fields such as research, engineering, marketing, and sales, are encouraged to apply. We also welcome non-technical internships in marketing, sales, executive assistance, and more. We are seeking passionate individuals ready to pioneer multimodal AI with us.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="35417cbd-2c33-4af6-8de4-60ba16f130cd" aria-label="Expand &quot;Where will the internship take place?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Where will the internship take place?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="35417cbd-2c33-4af6-8de4-60ba16f130cd" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Internships must be carried out onsite at one of our offices, which are located in Berlin, Beijing, and Shenzhen.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="e3eebcef-cc81-4d8d-9baa-bd6a2d027c4f" aria-label="Expand &quot;Does Jina AI assist with visa processes?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Does Jina AI assist with visa processes?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="e3eebcef-cc81-4d8d-9baa-bd6a2d027c4f" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Yes, Jina AI offers reasonable assistance in the visa process for successful applicants.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="50dd48e4-4a50-41dd-af54-76b81b47687f" aria-label="Expand &quot;Does Jina AI provide any allowances or benefits for interns?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Does Jina AI provide any allowances or benefits for interns?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="50dd48e4-4a50-41dd-af54-76b81b47687f" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Yes, Jina AI provides a reasonable amount of living cost coverage for interns during the internship period.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="c096634e-0116-4a99-a90d-b28571d94dea" aria-label="Expand &quot;Can I work on my Master's thesis during the internship at Jina AI?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Can I work on my Master's thesis during the internship at Jina AI?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="c096634e-0116-4a99-a90d-b28571d94dea" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Yes, it is possible to work on your Master's thesis during your internship at Jina AI, typically applicable to students at German universities. However, you must have prior communication and agreement from your university's supervisor. Note that we do not help students find advisors.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="bc57dee7-c948-4d59-a3ec-4a2c85da0b78" aria-label="Expand &quot;What does the application process involve?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What does the application process involve?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="bc57dee7-c948-4d59-a3ec-4a2c85da0b78" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">The application process includes submitting your application form, a resume, a cover letter expressing your interest and motivation, and any relevant professional links such as GitHub or LinkedIn. We evaluate candidates based on their performance during the interview and their performance in their university.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="50ea25be-3961-463e-95e5-94750c3cd954" aria-label="Expand &quot;Does Jina AI provide any letter of recommendation post-internship?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Does Jina AI provide any letter of recommendation post-internship?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="50ea25be-3961-463e-95e5-94750c3cd954" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Yes, successful interns may receive a letter of recommendation at the end of their internship, signed by our CEO.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f58922e0-952f-46c3-9b83-3630b5602768" aria-label="Expand &quot;What is the duration of the internship?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the duration of the internship?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f58922e0-952f-46c3-9b83-3630b5602768" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">The duration of the internship varies based on the role and project. However, it typically ranges from three to six months.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="b1c06406-57f9-4334-8e4f-1afdcb288b13" aria-label="Expand &quot;Can I apply if I don't have prior experience in AI?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Can I apply if I don't have prior experience in AI?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="b1c06406-57f9-4334-8e4f-1afdcb288b13" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Yes, we welcome applications from all academic backgrounds. We value your passion and commitment to learn as much as prior experience.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="9319ae6b-f68c-47af-9518-d368a59006ad" aria-label="Expand &quot;Is this a paid internship?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is this a paid internship?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="9319ae6b-f68c-47af-9518-d368a59006ad" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Yes, our internship program offers competitive remuneration.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="0fe0edf8-d48e-4884-a978-c6322b133bed" aria-label="Expand &quot;What opportunities will I have as a Jina AI intern?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What opportunities will I have as a Jina AI intern?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="0fe0edf8-d48e-4884-a978-c6322b133bed" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">As a Jina AI intern, you'll get hands-on experience working on challenging projects, learn from industry experts, be part of a vibrant community, and have the opportunity to make real contributions to our pioneering work in multimodal AI.</div></div></div></div></div></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jerboa</div><div class="q-item__label q-item__label--caption text-caption">An experimental finetuner for open-source LLMs</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="044cc6e5-bc3d-4268-b718-24578cc83634" aria-label="Expand &quot;Company&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><span class="q-icon" aria-hidden="true" role="presentation"><img src="/J.svg"></span></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Company</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="044cc6e5-bc3d-4268-b718-24578cc83634" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/about-us"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">About us</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/contact-sales"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Contact sales</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/open-day"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Open day</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/internship"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Intern program</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://jobs.lever.co/jina-ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Join us</div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">open_in_new</i></div></div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div></div></div></div><div class="q-scrollarea__bar q-scrollarea__bar--v absolute-right q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__bar q-scrollarea__bar--h absolute-bottom q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--v absolute-right q-scrollarea__thumb--invisible" aria-hidden="true" style="top: 0px; height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-06c9a5ac="" class="q-page" style="min-height: 449px;"><div data-v-06c9a5ac="" class="row q-py-xl justify-center items-center q-px-lg internship-background"><div data-v-06c9a5ac="" class="col-12 col-md-10 q-py-xl q-ma-xl q-ml-sm q-pl-sm"><div data-v-06c9a5ac="" class="q-my-xl text-weight-bold text-h2">Intern Program</div><div data-v-06c9a5ac="" class="q-pt-lg q-mb-xl text-subtitle1" style="width: 100%;">Worldwide call for students: Intern in research, engineering, marketing, sales and more to pioneer multimodal AI together.</div></div></div><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow row justify-center bg-dark-page q-py-xl"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert col-12 col-md-9"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center text-h2 q-pb-lg text-center">Explore stories from our interns</div></div><div data-v-06c9a5ac="" class="row q-mt-lg justify-center"><div data-v-06c9a5ac="" class="col-12 col-sm-6 col-md-4"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm"><div data-v-06c9a5ac="" class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 56.25%;"></div></div><div class="q-responsive__content absolute-full fit"><iframe data-v-06c9a5ac="" src="https://www.youtube.com/embed/pfG_d0gqdMk" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h5 handwritten1">Jonathan Geuter</div><div data-v-06c9a5ac="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Fine-tuned LLM models for better embeddings</div></div><div data-v-06c9a5ac="" class="q-item__section column q-item__section--side q-item__section--top justify-start q-item__section--avatar"><div data-v-06c9a5ac="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software Engineer Intern</div></div></div></div></div></div></div></div><div data-v-06c9a5ac="" class="col-12 col-sm-6 col-md-4"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm"><div data-v-06c9a5ac="" class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 56.25%;"></div></div><div class="q-responsive__content absolute-full fit"><iframe data-v-06c9a5ac="" src="https://www.youtube.com/embed/_4-MGLJmtmM" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h5 handwritten2">Sebastian Weisshaar</div><div data-v-06c9a5ac="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Explored the potential of Retrieval Augmented Generation</div></div><div data-v-06c9a5ac="" class="q-item__section column q-item__section--side q-item__section--top justify-start q-item__section--avatar"><div data-v-06c9a5ac="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software Engineer Intern</div></div></div></div></div></div></div></div><div data-v-06c9a5ac="" class="col-12 col-sm-6 col-md-4"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm"><div data-v-06c9a5ac="" class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 56.25%;"></div></div><div class="q-responsive__content absolute-full fit"><iframe data-v-06c9a5ac="" src="https://www.youtube.com/embed/Eg4p7XewMN4" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h5 handwritten3">Louis Milliken</div><div data-v-06c9a5ac="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Published a paper on the topic of sentence embeddings</div></div><div data-v-06c9a5ac="" class="q-item__section column q-item__section--side q-item__section--top justify-start q-item__section--avatar"><div data-v-06c9a5ac="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software Engineer Intern</div></div></div></div></div></div></div></div><div data-v-06c9a5ac="" class="col-12 col-sm-6 col-md-4"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm"><div data-v-06c9a5ac="" class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 56.25%;"></div></div><div class="q-responsive__content absolute-full fit"><iframe data-v-06c9a5ac="" src="https://www.youtube.com/embed/NloMmcC4QmY" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h5 handwritten1">Yuxi Lu</div><div data-v-06c9a5ac="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Injecting continuous youthful vitality into the team</div></div><div data-v-06c9a5ac="" class="q-item__section column q-item__section--side q-item__section--top justify-start q-item__section--avatar"><div data-v-06c9a5ac="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Recruiting and Administrative Intern</div></div></div></div></div></div></div></div><div data-v-06c9a5ac="" class="col-12 col-sm-6 col-md-4"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm"><div data-v-06c9a5ac="" class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 56.25%;"></div></div><div class="q-responsive__content absolute-full fit"><iframe data-v-06c9a5ac="" src="https://www.youtube.com/embed/sLEu_mLl0zE" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h5 handwritten2">Kaipeng Huang</div><div data-v-06c9a5ac="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Benchmarked quantization techniques to compress LLM</div></div><div data-v-06c9a5ac="" class="q-item__section column q-item__section--side q-item__section--top justify-start q-item__section--avatar"><div data-v-06c9a5ac="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software Engineer Intern</div></div></div></div></div></div></div></div><div data-v-06c9a5ac="" class="col-12 col-sm-6 col-md-4"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm"><div data-v-06c9a5ac="" class="q-responsive"><div class="q-responsive__filler overflow-hidden"><div style="padding-bottom: 56.25%;"></div></div><div class="q-responsive__content absolute-full fit"><iframe data-v-06c9a5ac="" src="https://www.youtube.com/embed/PtJw0e7h4s8" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h5 handwritten3">Wenjie Hua</div><div data-v-06c9a5ac="" class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Creating and promoting compelling campaign for PromptPerfect</div></div><div data-v-06c9a5ac="" class="q-item__section column q-item__section--side q-item__section--top justify-start q-item__section--avatar"><div data-v-06c9a5ac="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Developer Relations Intern</div></div></div></div></div></div></div></div></div></div></div><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow row justify-center q-py-xl col-12 col-xl-10"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert text-h2 text-center q-my-xl">Our thriving alumni network</div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert row justify-center items-center q-py-xl q-my-xl"><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 37.7358%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_Carnegie_Mellon_University.10e68cbb.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_University_of_California_Berkeley.e1004510.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_Tsinghua.0b553bea.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_Harvard_University.ab67e0d6.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_ETH_Zurich.34438a4e.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/Logo_Technical_University_of_Munich.1f951f0f.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_KAIST.4c3e242e.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 20%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_armsterdam.bc69cf2b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 55.9524%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/Logo_der_Technischen_Universität_Berlin.8ee79d74.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 39.2157%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/TU_Delft_Logo.0f5ee4b8.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_BUPT.6bb5fca7.png" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_CNU.2b043e48.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div data-v-06c9a5ac="" class="q-img q-img--menu q-ma-lg col-2 col-md-3" role="img" style="width: 120px; height: 40px;"><div style="padding-bottom: 33.3333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/logo_Xiamen_University.c0ee1c9e.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow row items-center bg-dark-page justify-center q-py-xl"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert col-12 col-md-4"><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark justify-center text-h2 q-pb-lg" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center">Kickstart your adventure with Jina AI</div></div><div data-v-06c9a5ac="" class="q-item q-item-type row no-wrap q-item--dark text-subtitle1 q-mt-sm" role="listitem"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center">Embark on a transformative journey with Jina AI. Our comprehensive internship program invites all passionate minds who aspire to shape the future of artificial intelligence. Join us to get real-world experience, work on challenging projects, and collaborate with some of the brightest minds in the AI industry.</div></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert col-12 col-md-6 row"><div data-v-06c9a5ac="" class="col-12 col-md-6"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm q-hoverable"><span data-v-06c9a5ac="" class="q-focus-helper"></span><div data-v-06c9a5ac="" class="q-parallax" style="height: 300px;"><div class="q-parallax__media absolute-full"><img src="/developer-card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h6 q-mb-sm">Winter / 2023</div></div></div><div data-v-06c9a5ac="" class="q-card__actions justify-start q-card__actions--horiz row"><a data-v-06c9a5ac="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable apply-btn full-width" tabindex="0" href="https://jobs.lever.co/jina-ai/8a9b0075-0fd6-40ab-9c67-1b55dd431c82" target="_blank"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">open_in_new</i><span class="block">Apply now</span></span></a></div></div></div><div data-v-06c9a5ac="" class="col-12 col-md-6"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm q-hoverable"><span data-v-06c9a5ac="" class="q-focus-helper"></span><div data-v-06c9a5ac="" class="q-parallax" style="height: 300px;"><div class="q-parallax__media absolute-full"><img src="/prosumer-card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h6 q-mb-sm">Spring / 2024</div></div></div><div data-v-06c9a5ac="" class="q-card__actions justify-start q-card__actions--horiz row"><a data-v-06c9a5ac="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable apply-btn full-width" tabindex="0" href="https://jobs.lever.co/jina-ai/c3335e56-dfb0-40d7-871d-f1a87ccb0e8d" target="_blank"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">open_in_new</i><span class="block">Apply now</span></span></a></div></div></div><div data-v-06c9a5ac="" class="col-12 col-md-6"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm q-hoverable"><span data-v-06c9a5ac="" class="q-focus-helper"></span><div data-v-06c9a5ac="" class="q-parallax" style="height: 300px;"><div class="q-parallax__media absolute-full"><img src="/summer-card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h6 q-mb-sm">Summer / 2024</div></div></div><div data-v-06c9a5ac="" class="q-card__actions justify-start q-card__actions--horiz row"><a data-v-06c9a5ac="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable apply-btn full-width" tabindex="0" href="https://jobs.lever.co/jina-ai/f79464ed-0537-413c-81fe-6710bf83d569" target="_blank"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">open_in_new</i><span class="block">Apply now</span></span></a></div></div></div><div data-v-06c9a5ac="" class="col-12 col-md-6"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow q-ma-sm q-hoverable"><span data-v-06c9a5ac="" class="q-focus-helper"></span><div data-v-06c9a5ac="" class="q-parallax" style="height: 300px;"><div class="q-parallax__media absolute-full"><img src="/enterprise-card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert"><div data-v-06c9a5ac="" class="q-item__section column q-item__section--main justify-center"><div data-v-06c9a5ac="" class="q-item__label text-h6 q-mb-sm">Autumn / 2024</div></div></div><div data-v-06c9a5ac="" class="q-card__actions justify-start q-card__actions--horiz row"><a data-v-06c9a5ac="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable apply-btn full-width" tabindex="0" href="https://jobs.lever.co/jina-ai/d17e522f-4095-4e22-91a0-523938132664" target="_blank"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">open_in_new</i><span class="block">Apply now</span></span></a></div></div></div></div></div><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--square no-border-radius q-card--flat no-shadow row justify-center q-py-xl"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert text-h2 text-center q-my-xl col-12">FAQ</div><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert col-12 col-sm-9 col-md-6"><div data-v-06c9a5ac="" class="q-list q-list--dark"><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="48279cba-5d0f-4b2e-bd45-a43ca4dfd8ea" aria-label="Expand &quot;Who can apply for the Jina AI internship program?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Who can apply for the Jina AI internship program?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="48279cba-5d0f-4b2e-bd45-a43ca4dfd8ea" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Undergraduate, Masters, and Ph.D. students from all over the world, with interest in fields such as research, engineering, marketing, and sales, are encouraged to apply. We also welcome non-technical internships in marketing, sales, executive assistance, and more. We are seeking passionate individuals ready to pioneer multimodal AI with us.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="42fc5ded-9ee6-4c83-a981-851458fbe1cd" aria-label="Expand &quot;Where will the internship take place?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Where will the internship take place?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="42fc5ded-9ee6-4c83-a981-851458fbe1cd" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Internships must be carried out onsite at one of our offices, which are located in Berlin, Beijing, and Shenzhen.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="5c4cb47f-8266-446b-ad33-1e588dba068b" aria-label="Expand &quot;Does Jina AI assist with visa processes?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Does Jina AI assist with visa processes?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="5c4cb47f-8266-446b-ad33-1e588dba068b" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Yes, Jina AI offers reasonable assistance in the visa process for successful applicants.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="c2efc563-7f38-4713-a667-14b974ed76bd" aria-label="Expand &quot;Does Jina AI provide any allowances or benefits for interns?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Does Jina AI provide any allowances or benefits for interns?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="c2efc563-7f38-4713-a667-14b974ed76bd" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Yes, Jina AI provides a reasonable amount of living cost coverage for interns during the internship period.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="d3bee064-d9a7-4258-afb4-2e62c4c37813" aria-label="Expand &quot;Can I work on my Master's thesis during the internship at Jina AI?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Can I work on my Master's thesis during the internship at Jina AI?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="d3bee064-d9a7-4258-afb4-2e62c4c37813" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Yes, it is possible to work on your Master's thesis during your internship at Jina AI, typically applicable to students at German universities. However, you must have prior communication and agreement from your university's supervisor. Note that we do not help students find advisors.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="38fc117f-2626-40c2-9e00-107e4c93223e" aria-label="Expand &quot;What does the application process involve?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What does the application process involve?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="38fc117f-2626-40c2-9e00-107e4c93223e" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">The application process includes submitting your application form, a resume, a cover letter expressing your interest and motivation, and any relevant professional links such as GitHub or LinkedIn. We evaluate candidates based on their performance during the interview and their performance in their university.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="4e33be93-e525-4746-91b2-1ada358ac8a9" aria-label="Expand &quot;Does Jina AI provide any letter of recommendation post-internship?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Does Jina AI provide any letter of recommendation post-internship?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="4e33be93-e525-4746-91b2-1ada358ac8a9" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Yes, successful interns may receive a letter of recommendation at the end of their internship, signed by our CEO.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="4422c04d-807d-4ab4-83ef-9657aa2ea029" aria-label="Expand &quot;What is the duration of the internship?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the duration of the internship?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="4422c04d-807d-4ab4-83ef-9657aa2ea029" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">The duration of the internship varies based on the role and project. However, it typically ranges from three to six months.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="a87f1b75-915a-46e0-83bc-c88ceaa2ad8a" aria-label="Expand &quot;Can I apply if I don't have prior experience in AI?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Can I apply if I don't have prior experience in AI?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="a87f1b75-915a-46e0-83bc-c88ceaa2ad8a" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Yes, we welcome applications from all academic backgrounds. We value your passion and commitment to learn as much as prior experience.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="3759daaa-0deb-41bb-884c-1e7ae43212a3" aria-label="Expand &quot;Is this a paid internship?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is this a paid internship?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="3759daaa-0deb-41bb-884c-1e7ae43212a3" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">Yes, our internship program offers competitive remuneration.</div></div></div></div></div><div data-v-06c9a5ac="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="5598d827-878c-4910-89c6-94279fcda279" aria-label="Expand &quot;What opportunities will I have as a Jina AI intern?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What opportunities will I have as a Jina AI intern?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="5598d827-878c-4910-89c6-94279fcda279" style="display: none;"><div data-v-06c9a5ac="" class="q-card q-card--dark q-dark q-card--flat no-shadow bg-dark-page"><div data-v-06c9a5ac="" class="q-card__section q-card__section--vert">As a Jina AI intern, you'll get hands-on experience working on challenging projects, learn from industry experts, be part of a vibrant community, and have the opportunity to make real contributions to our pioneering work in multimodal AI.</div></div></div></div></div></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. All rights reserved.</div></div></div></div><footer class="q-footer q-layout__section--marginal fixed-bottom lock-blur bg-transparent print-hide"><div class="row"><div class="q-btn-group row no-wrap q-btn-group--flat inline col-12 col-md-6 justify-center"><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://discord.jina.ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-discord" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://github.com/jina-ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-github" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://huggingface.co/jinaai" target="_blank" style="font-size: 10px; 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diff --git a/it/index.html b/it/index.html
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+++ b/it/index.html
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   <link rel="stylesheet" href="/assets/index.9fe6336f.css">
 </head><body><div id=q-app></div></body></html>
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diff --git a/ja/index.html b/ja/index.html
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+++ b/ja/index.html
@@ -9,6 +9,6 @@
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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>A Guide for Super-Resolution- Ordinary to Extraordinary with Inference</title><meta charset="utf-8"><meta name="title" content="A Guide for Super-Resolution- Ordinary to Extraordinary with Inference"><meta name="description" content="Dive into the realm of generative AI as we unravel, compare, and implement super-resolution models for image upscaling on Jina AI Cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/a-guide-for-super-resolution-ordinary-to-extraordinary-with-inference"><meta property="og:title" content="A Guide for Super-Resolution- Ordinary to Extraordinary with Inference"><meta property="og:description" content="Dive into the realm of generative AI as we unravel, compare, and implement super-resolution models for image upscaling on Jina AI Cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Blog-images--10-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/a-guide-for-super-resolution-ordinary-to-extraordinary-with-inference"><meta property="twitter:title" content="A Guide for Super-Resolution- Ordinary to Extraordinary with Inference"><meta property="twitter:description" content="Dive into the realm of generative AI as we unravel, compare, and implement super-resolution models for image upscaling on Jina AI Cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Blog-images--10-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>A Guide for Super-Resolution- Ordinary to Extraordinary with Inference</title><meta charset="utf-8"><meta name="title" content="A Guide for Super-Resolution- Ordinary to Extraordinary with Inference"><meta name="description" content="Dive into the realm of generative AI as we unravel, compare, and implement super-resolution models for image upscaling on Jina AI Cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/a-guide-for-super-resolution-ordinary-to-extraordinary-with-inference"><meta property="og:title" content="A Guide for Super-Resolution- Ordinary to Extraordinary with Inference"><meta property="og:description" content="Dive into the realm of generative AI as we unravel, compare, and implement super-resolution models for image upscaling on Jina AI Cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Blog-images--10-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/a-guide-for-super-resolution-ordinary-to-extraordinary-with-inference"><meta property="twitter:title" content="A Guide for Super-Resolution- Ordinary to Extraordinary with Inference"><meta property="twitter:description" content="Dive into the realm of generative AI as we unravel, compare, and implement super-resolution models for image upscaling on Jina AI Cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Blog-images--10-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">A Guide for Super-Resolution- Ordinary to Extraordinary with Inference</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Dive into the realm of generative AI as we unravel, compare, and implement super-resolution models for image upscaling on Jina AI Cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 105px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/--.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 121.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/profile-option-2.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 75px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 112.212%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/-----.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jie Fu, Alex C-G, Saahil Ognawala, Zihao Jing</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 03, 2023 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="introduction">Introduction</h2><p>In the fast-paced field of generative AI, the need for high-quality images is more critical than ever. This article explores the complex yet fascinating topic of image upscaling, a specific machine learning task designed to increase the size of small images without losing their original resolution. We begin by defining the super-resolution task in machine learning, followed by a discussion on the typical models used for this task. For this discussion, we will take an academic approach to literature review in the field of super-resolution - something that the long-term readers of Jina AI’s blog posts may find unusual but, hopefully, still valuable. We then compare these models to give you a clearer understanding of their strengths and weaknesses. Following this, we guide you through the practical application of these models on Jina AI Cloud.</p><p>Lastly, we detail how these upscaling models can prove beneficial for generative AI application developers, particularly in tandem with other generative AI models, such as Stable Diffusion, for the purpose of image enhancement, restoration or data augmentation.</p><p>Our goal is to provide you with a comprehensive understanding of the image upscaling process and its potential applications.</p><h2 id="1-what-is-the-super-resolution-task">1 What is the Super-resolution Task?</h2><p>The super-resolution task is an exciting computer vision task whose goal is to restore a low-resolution image (blurry, pixelated) to a high-resolution image, making it sharper and more detailed. This task plays an important role in our daily lives, for example, by converting old, low-resolution photos into sharper, high-definition versions, or by providing sharper picture quality in video calls.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh6.googleusercontent.com/Hl5aIqZ8pHpwlcbgxu2mLz6iSnAvgpZS6DOVcdyzU8Kg3ifBTniYwwCU5KaPtjj08U2GQ7yO1t9bvCDlibd3Icnd2tgyKIZB68rdOUW9X6ikoUsz8Ic1VT9hHrYqRbI75dBxo0Ihn6BRMCoURYXO2iQ" class="kg-image" alt="" width="526" height="249"></figure><p>The super-resolution models are intelligent algorithms developed to achieve this goal. They infer missing details in low-resolution images and generate high-resolution images by learning in-depth about the details and features of the image, as well as pattern and contextual information. The magic of these models is that they can recover without an actual high-resolution image, relying only on existing low-resolution images as input.</p><p>With the rapid development of artificial intelligence and deep learning, super-resolution technology has made tremendous progress. It has brought us amazing image enhancement capabilities that not only improve image quality but also drive innovation in many application areas. Super-resolution tasks and super-scoring models undoubtedly add color to our digital world and bring us a more wonderful visual experience.</p><p>In this article, we will introduce our readers to some of the most common machine learning model architectures and techniques for super-resolution, that are currently state-of-the-art. At the end of the article, we will also show how you can access some of these models and turn your own low-resolution images into sharper and more detailed versions of themselves.</p><h2 id="2-commonly-used-models-and-principles">2 Commonly Used Models and Principles</h2><p>This section focuses on understanding the state-of-the-art models used for super-resolution. We divide these models into two main categories for ease of understanding: <em>slow but effective models</em>, and <em>fast but potentially less effective models</em>. In the first subsection, we will delve into <em>four</em> models that, while taking a bit longer to produce results, ensure high-quality upscaled image output. Conversely, the second subsection will introduce you to <em>three</em> models that are known for their speed, even though they might sometimes compromise on effectiveness. This balanced perspective aims to equip you with the knowledge to decide which model best aligns with your specific requirements and constraints.<br>In the next section of the article, we will objectively evaluate all the discussed models, considering their speed and accuracy. </p><h3 id="21-slow-but-effective-models">2.1 Slow but Effective Models</h3><h4 id="211-swinir">2.1.1 <a href="https://github.com/JingyunLiang/SwinIR?ref=jina-ai-gmbh.ghost.io">SwinIR</a></h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/8k3VtWv3itKe47QTAJ5PkQZcba-Ml5bLSlMSc-QYWYF0-c0ogKzpUs8Z4BVeIWGN7K_ypGoi5caJ5Lil9hDFdcwcNAyVtPcOExEw8tgJMdQ-7c8Q9rX32m3cWAQwy0KsxKWclG8pNWAEMTsvMMK4n-U" class="kg-image" alt="" width="624" height="224"></figure><p>A strong baseline model, SwinIR for image restoration is based on the Swin Transformer. SwinIR consists of three parts: shallow feature extraction, deep feature extraction and high-quality image reconstruction. In particular, the deep feature extraction module is composed of several residual Swin Transformer blocks (RSTB), each of which has several Swin Transformer layers together with a residual connection. The author conducts experiments on image super-resolution (including classical, lightweight and real-world image super-resolution). Significant super-resolution effects were obtained.</p><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">ℹ️</div><div class="kg-callout-text"><strong>Clarification - Setting parameters:</strong> There are some specific parameters in some of these models. This section will describe some of them like tile and tile pad.</div></div><p>The tile parameter is in the SwinIr and Real-ESRGAN model. As images result in the out of GPU memory issue, this tile option will first crop input images into tiles, and then process each of them. Finally, they will be merged into one image.</p><p>Therefore, you could use it when you have limited GPU memory, but don’t even dream of speeding up inference with this operation.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh6.googleusercontent.com/ycp4Mz27TT19l5MK1sPsa7cYtwOy6f45mP5mcardfxzzwZpVSPZKDSgu58MaEwt--hjS-PFqC3EaW9XrXjDJmABc21XYdUhZ7-VNtGcobJjwlhSabVIhUK-AQdkAe6r98CoOwjMrOs2YPguMXgfH-2Y" class="kg-image" alt="" width="163" height="145"></figure><p><code>tile_overlap</code> is the same as <code>tile_pad</code> – it characterizes the degree of overlap between the two parts that are segmented. A higher <code>tile_pad</code> value means more parts of the input image are segmented, resulting in a “smoother” result.</p><h4 id="212-real-esrgan">2.1.2 <a href="https://github.com/xinntao/Real-ESRGAN?ref=jina-ai-gmbh.ghost.io">Real-ESRGAN</a></h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh6.googleusercontent.com/SCDn5FCUJqEI8cGA4yZCzXg8itK4cpLH9UHJ5g2UvULv0nuYcoUA1k9X7gxfFNIpbJk06l8lp9uhTtyTcA13sNaOM8F4bgc3OIjQXLCw45xVRRPagvbp_u5dGnkEYdD_iUluTMk8aqbK8fohidnoZr0" class="kg-image" alt="" width="624" height="167"></figure><p>Real-ESRGAN generator is the same generator (SR network) as ESRGAN, which is a deep network with several residual-in-residual dense blocks (RRDB). It also extends the original ×4 ESRGAN architecture to perform super-resolution with a scale factor of ×2. As ESRGAN is a heavy network, it first employs the pixel-unshuffle (an inverse operation of <a href="https://arxiv.org/abs/1609.05158v2?ref=jina-ai-gmbh.ghost.io">pixel-shuffle</a>, which is an operation used in super-resolution models to implement efficient sub-pixel convolutions. &nbsp;Specifically it rearranges elements in a tensor of shape [∗,C×r**2,H,W] to a tensor of shape [∗,C,r×H,r×W]) to reduce the spatial size and enlarge the channel size before feeding inputs into the main ESRGAN architecture. Thus, most calculation is performed in a smaller resolution space, which can reduce the GPU memory and computational resources consumption.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh4.googleusercontent.com/eEgo2JBKeD0AQLGpyIFnGlvrqnom4uhVP9yHBX9jS-gB611XHb43YcewqELdp3JXjM3vrUtjOL_n5_VzB_ASqveCcSMSWlfxlEaBIyJ5jTpe9gvBcXnaQFXQKKujgIIdCoMbnPRpyTb1CWo3rM1eLXQ" class="kg-image" alt="" width="327" height="184"></figure><h4 id="213-swin2sr">2.1.3 <a href="https://github.com/mv-lab/swin2sr?ref=jina-ai-gmbh.ghost.io">Swin2sr</a></h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh6.googleusercontent.com/x-AlJpxD3yBEiNISeHn8dwLKNlwcJGwVe4f0CPlSGXb93T31bC6y3AmwJ8Y_S0V0hp43f84MbYVzxFDLczN3jXlK-cY5LQEhqq-VUdIZUeAIDvIe6OafB_iVoXyUcL9PxNXLjjmhK98XUryre7gaCQs" class="kg-image" alt="" width="624" height="288"></figure><p>In swin2sr works, the authors explore the novel Swin Transformer V2, to improve SwinIR for image super-resolution, and in particular, the compressed input scenario. Using this method we can tackle the major issues in training transformer vision models, such as training instability, resolution gaps between pre-training and fine-tuning, and hunger on data. Experimental results demonstrate that the method, Swin2SR, can improve the training convergence and performance of SwinIR, and is a top-five solution at the "<a href="https://arxiv.org/abs/2208.11184?ref=jina-ai-gmbh.ghost.io">AIM 2022 Challenge on Super-Resolution of Compressed Image and Video</a>".</p><h4 id="214-stable-diffusion-upscaler">2.1.4 <a href="https://huggingface.co/stabilityai/stable-diffusion-x4-upscaler/tree/main?ref=jina-ai-gmbh.ghost.io">Stable Diffusion Upscaler</a></h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/jPHfafvMe_ZppFCTmMRkz69p-etQwqVtIlb9DpATYDTNReHX9CJcboYt0vkKFDLXJEnRdw5WL-vRkHjvz0S-gZ2yCH2SDPAXziCbuGaSKvC_b9JE1QoMOT7VwsMgI1pf3ChYZ9V919TjVT8gPwfBN4I" class="kg-image" alt="" width="624" height="297"></figure><p>Stable Diffusion Upscaler (SDU) is a super-resolution model based on the diffusion process. It converts a low-resolution image into a high-resolution image by introducing random noise and diffusion processes. The model includes an encoder, a diffusion layer and a decoder. The encoder maps the low-resolution image to the feature space, the diffusion layer improves the image quality by random noise and iteratively updating the feature map, and the decoder maps the feature map back to the high-resolution image space. SDU utilizes a nonlinear diffusion process and the introduction of random noise to be able to handle a diversity of details and textures, generating a more realistic and detailed high-resolution image. The implementation of specific models may vary, and the above description provides a general overview.</p><p>However, although this model has a better inference effect, at the same time the resource consumption is huge, under the same conditions, its inference time and memory occupation is several times that of other models. Due to its economic limitations, we do not introduce this model for the time being.</p><h3 id="22-fast-but-ineffective-models">2.2 Fast but Ineffective Models</h3><h4 id="221-bicubic">2.2.1 <a href="https://github.com/aselsan-research-imaging-team/bicubic-plusplus?ref=jina-ai-gmbh.ghost.io">bicubic</a></h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh6.googleusercontent.com/-EHyCR013dPSUqqkjXxxndbhj1tVie4aNrxPf3LNzDOfy_EbG-UpqRghi0rr4cWDrAikfnfWY_3IhNai_wRfJRxQshRI-AN-JkGqdKOJ3VCvgCK9LdJGhUQ9959MpiGEJfA9Z0_eZYjny1dAOYKTKws" class="kg-image" alt="" width="624" height="208"></figure><p>The authors propose a real-time and lightweight single-image super-resolution (SR) network named Bicubic++. Bicubic++ learns quick reversible downgraded and lower resolution features of the image to decrease the number of computations. They also apply an end-to-end global structured pruning of convolutional layers without using metrics like magnitude and gradient norms and focus on optimizing the pruned network's PSNR on the validation set. Furthermore, they also applied bias removal to the convolutional layers to enhance the inference speed.</p><h4 id="222-dipnet">2.2.2 <a href="https://github.com/xiumu00/DIPNet?ref=jina-ai-gmbh.ghost.io">DIPNet</a></h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/xRpwmdd76ij1SqlVQbh2lIPyJrWBOAnHSEN285LpLFK6ITLF3phqUKbknG5i0v0Bo441oII31OCbv17I1zvhyuhUaLmgx5LIMtzFD8It9XNamE_xb6FLGdr3OHwhdaWzVJLfAC0ASCzD0P0QtbfxK4I" class="kg-image" alt="" width="624" height="288"></figure><p>Specifically, they leverage enhanced high-resolution output as additional supervision to improve the learning ability of lightweight student networks. Upon convergence of the student network, we further simplify our network structure to a more lightweight level using reparameterization techniques and iterative network pruning. Meanwhile, they adopt an effective lightweight network training strategy that combines multi-anchor distillation and progressive learning, enabling the lightweight network to achieve outstanding performance. Ultimately, our proposed method achieves the fastest inference time among all participants in the <a href="https://openaccess.thecvf.com/content/CVPR2023W/NTIRE/papers/Li_NTIRE_2023_Challenge_on_Efficient_Super-Resolution_Methods_and_Results_CVPRW_2023_paper.pdf?ref=jina-ai-gmbh.ghost.io">NTIRE 2023</a> efficient super-resolution challenge while maintaining competitive super-resolution performance. The results show that the approach achieves comparable performance in representative dataset DIV2K, both qualitatively and quantitatively, with faster inference and fewer network parameters.</p><h4 id="223-lapsrn">2.2.3 LapSRN</h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/qOPOPgsesykp5wmzX7HB6KJUxP7IX45YyolKZGcJHWsKQDEIiNhWtmhHBHbJmfOkTzXyuJsHEqtkPKkW_koHpgJXl1-Qu7TEQ13uk_EhagXmzRyN3lnFhIxwPZ_yTUDtb7jxCWQpC82Y5W43Q5965cQ" class="kg-image" alt="" width="476" height="344"></figure><p>In this paper, the authors propose the Laplacian Pyramid Super-Resolution Network (LapSRN) to progressively reconstruct the sub-band residuals of high-resolution images. At each pyramid level, the model takes coarse-resolution feature maps as input, predicts the high-frequency residuals, and uses transposed convolutions for upsampling to the finer level. The method does not require bicubic interpolation as the pre-processing step and thus dramatically reduces the computational complexity. They train the proposed LapSRN with deep supervision using a robust Charbonnier loss function and achieve high-quality reconstruction. Furthermore, the network generates multi-scale predictions in one feed-forward pass through the progressive reconstruction, thereby facilitating resource-aware applications. Extensive quantitative and qualitative evaluations of benchmark datasets show that the proposed algorithm performs favorably against the state-of-the-art methods in terms of speed and accuracy.</p><h2 id="3-comparing-and-contrasting-models">3 Comparing and Contrasting Models</h2><p>We designed a series of evaluation procedures for evaluating the performance of each model. In this section, we present this evaluation in terms of the output of the models, inference time, GPU memory usage and other metrics, all evaluated independently and uniformly. </p><p>In all, considering the cost and performance, we may recommend that users use <em>Real-ESRGAN</em> if they are looking for high-quality upscaled images, with a reasonably low memory footprint. However, if users want to process a lot of images in a limited amount of time, at the cost of potentially lower-quality image outputs, then they should pick <em>DIPNet</em>. </p><p>The following graphs show the output comparison of the models. For tags under the images (e.g. Sheriff_5.966_2746), the first part of it is the filename of the image. The second and third parts are the inference time(s) and memory cost (MB), which will give you a clearer understanding of the inference process.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh3.googleusercontent.com/S2V_UC9oiT6X2VxHQsJ3ka0XxSe12YjxYhEzhnfnskK0a55dYkUMnvdqgFIB3b3uFEcm6-vhXNJpVahiny7eybETrT_Jat9vmAMjvVXKBA73_Tf1UG5o_ImbMC73Sw8YeTXUp8pGJtFJwo3t245r81Y" class="kg-image" alt="" width="624" height="721"></figure><p>Then there is the resource consummation examination of each model.</p><p><em>Dots per ms</em> means how large of an image can be processed per millisecond, and <em>Dots per MB</em> means how big of an image can be handled per MB GPU memory.</p><p>This may help you understand the costs of each model.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh4.googleusercontent.com/Hb3lhbPfmGyPMhuMBz30oFt5j1T4q2cJ97JTZBGuyjAIEj6bPMkMyiE2Z2A1Uc7Hm9szq61juPZ25aHfpG-CUfww6Iss3GvxI6pSAXdZPRRC2p0rF78GzgcDPBq_AUukteFoU5sUznaKOPcyYphGs6w" class="kg-image" alt="" width="624" height="385"></figure><p><em>DPS</em> (documents per second) represents the number of documents the model handled per second. In the examination below, the last column lists the maximum size of an image that the model can process using no more than 16G GPU memory (we assume that an image with a size greater than 1024*1024 does not need upscaling).</p><table style="border:none;border-collapse:collapse;"><colgroup><col width="180"><col width="146"><col width="150"><col width="143"></colgroup><tbody><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Model</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">dps</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Memory (GB)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Max image size</span></p></td></tr><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">swin2ir-compressed(x4)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">0.172</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">15.796</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">800*800</span></p></td></tr><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">swin2ir-real(x4)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">0.14</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">15.804</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">890*890</span></p></td></tr><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">swinir(x4)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">0.156</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">15.071</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">850*850</span></p></td></tr><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Real-ESRGAN(x4)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">0.267</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">14.899</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">990*990</span></p></td></tr><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">bicubic++(x3)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">10.592</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">0</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">1024*1024</span></p></td></tr><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">DIPNet(x4)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">357.143</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">1.88</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">1024*1024</span></p></td></tr></tbody></table><p>The result shows that bicubic and DIPNet have a great score on these two aspects, and the other 5 models have almost the same memory utilization. However, the performance of bicubic and DIPNet may not be satisfactory. Amongst all evaluated models, Real-ESRGAN has the best inference speed and moderate performance. SwinIR and Swin2ir-real seem to have almost the same performance and inference speed, which is equally matched with Real-ESRGAN (without face enhancement).</p><h2 id="4-using-super-resolution-models-in-inference-client">4 Using Super-resolution Models in Inference Client</h2><p>Let’s use Jina AI’s Inference to enjoy the visual feast of ordinary to extraordinary.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.readme.io/docs/client-initialization?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Connecting to Inference with a Python Client</div><div class="kg-bookmark-description">InstallationInference Client is available on PyPI and can be installed using pip:Shellpip install inference-client Client InitializationTo get started with the Inference Client, you’ll need to import the Client class from the inference_client package:Pythonfrom inference_client import Client We prov…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://files.readme.io/d8cf8d5-favicon.ico" alt=""><span class="kg-bookmark-author">Jina AI Cloud Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://files.readme.io/4890f37-Company_logo_dark.svg" alt=""></div></a></figure><p><a href="https://jina.readme.io/docs/client-initialization?ref=jina-ai-gmbh.ghost.io">Jina Inference Client</a> is a Python library that allows you to interact with the Jina AI Inference. It provides a simple and intuitive API to perform various tasks such as image captioning, encoding, ranking, visual question answering (VQA), and image upscaling. Here’s a simple example of how to use super-resolution models with Inference client.</p><p>First, you need to install Inference Client using pip:</p><pre><code class="hljs language-undefined">pip install inference-client</code></pre><p>Supposing that you have a Jina Flow serving an upscaling model running at <em>grpc://localhost:51001</em>, you need to initialize the inference client using the following code:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> inference_client <span class="hljs-keyword">import</span> Client
-<span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> DocumentArray, Document
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="559913cb-fe88-4095-8e72-2e2b26aad7f3" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="559913cb-fe88-4095-8e72-2e2b26aad7f3" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Dive into the realm of generative AI as we unravel, compare, and implement super-resolution models for image upscaling on Jina AI Cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 121.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/profile-option-2.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 75px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/-----.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jie Fu, Alex C-G, Saahil Ognawala, Zihao Jing</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 03, 2023 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="introduction">Introduction</h2><p>In the fast-paced field of generative AI, the need for high-quality images is more critical than ever. This article explores the complex yet fascinating topic of image upscaling, a specific machine learning task designed to increase the size of small images without losing their original resolution. We begin by defining the super-resolution task in machine learning, followed by a discussion on the typical models used for this task. For this discussion, we will take an academic approach to literature review in the field of super-resolution - something that the long-term readers of Jina AI’s blog posts may find unusual but, hopefully, still valuable. We then compare these models to give you a clearer understanding of their strengths and weaknesses. Following this, we guide you through the practical application of these models on Jina AI Cloud.</p><p>Lastly, we detail how these upscaling models can prove beneficial for generative AI application developers, particularly in tandem with other generative AI models, such as Stable Diffusion, for the purpose of image enhancement, restoration or data augmentation.</p><p>Our goal is to provide you with a comprehensive understanding of the image upscaling process and its potential applications.</p><h2 id="1-what-is-the-super-resolution-task">1 What is the Super-resolution Task?</h2><p>The super-resolution task is an exciting computer vision task whose goal is to restore a low-resolution image (blurry, pixelated) to a high-resolution image, making it sharper and more detailed. This task plays an important role in our daily lives, for example, by converting old, low-resolution photos into sharper, high-definition versions, or by providing sharper picture quality in video calls.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh6.googleusercontent.com/Hl5aIqZ8pHpwlcbgxu2mLz6iSnAvgpZS6DOVcdyzU8Kg3ifBTniYwwCU5KaPtjj08U2GQ7yO1t9bvCDlibd3Icnd2tgyKIZB68rdOUW9X6ikoUsz8Ic1VT9hHrYqRbI75dBxo0Ihn6BRMCoURYXO2iQ" class="kg-image" alt="" width="526" height="249"></figure><p>The super-resolution models are intelligent algorithms developed to achieve this goal. They infer missing details in low-resolution images and generate high-resolution images by learning in-depth about the details and features of the image, as well as pattern and contextual information. The magic of these models is that they can recover without an actual high-resolution image, relying only on existing low-resolution images as input.</p><p>With the rapid development of artificial intelligence and deep learning, super-resolution technology has made tremendous progress. It has brought us amazing image enhancement capabilities that not only improve image quality but also drive innovation in many application areas. Super-resolution tasks and super-scoring models undoubtedly add color to our digital world and bring us a more wonderful visual experience.</p><p>In this article, we will introduce our readers to some of the most common machine learning model architectures and techniques for super-resolution, that are currently state-of-the-art. At the end of the article, we will also show how you can access some of these models and turn your own low-resolution images into sharper and more detailed versions of themselves.</p><h2 id="2-commonly-used-models-and-principles">2 Commonly Used Models and Principles</h2><p>This section focuses on understanding the state-of-the-art models used for super-resolution. We divide these models into two main categories for ease of understanding: <em>slow but effective models</em>, and <em>fast but potentially less effective models</em>. In the first subsection, we will delve into <em>four</em> models that, while taking a bit longer to produce results, ensure high-quality upscaled image output. Conversely, the second subsection will introduce you to <em>three</em> models that are known for their speed, even though they might sometimes compromise on effectiveness. This balanced perspective aims to equip you with the knowledge to decide which model best aligns with your specific requirements and constraints.<br>In the next section of the article, we will objectively evaluate all the discussed models, considering their speed and accuracy. </p><h3 id="21-slow-but-effective-models">2.1 Slow but Effective Models</h3><h4 id="211-swinir">2.1.1 <a href="https://github.com/JingyunLiang/SwinIR?ref=jina-ai-gmbh.ghost.io">SwinIR</a></h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/8k3VtWv3itKe47QTAJ5PkQZcba-Ml5bLSlMSc-QYWYF0-c0ogKzpUs8Z4BVeIWGN7K_ypGoi5caJ5Lil9hDFdcwcNAyVtPcOExEw8tgJMdQ-7c8Q9rX32m3cWAQwy0KsxKWclG8pNWAEMTsvMMK4n-U" class="kg-image" alt="" width="624" height="224"></figure><p>A strong baseline model, SwinIR for image restoration is based on the Swin Transformer. SwinIR consists of three parts: shallow feature extraction, deep feature extraction and high-quality image reconstruction. In particular, the deep feature extraction module is composed of several residual Swin Transformer blocks (RSTB), each of which has several Swin Transformer layers together with a residual connection. The author conducts experiments on image super-resolution (including classical, lightweight and real-world image super-resolution). Significant super-resolution effects were obtained.</p><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">ℹ️</div><div class="kg-callout-text"><strong>Clarification - Setting parameters:</strong> There are some specific parameters in some of these models. This section will describe some of them like tile and tile pad.</div></div><p>The tile parameter is in the SwinIr and Real-ESRGAN model. As images result in the out of GPU memory issue, this tile option will first crop input images into tiles, and then process each of them. Finally, they will be merged into one image.</p><p>Therefore, you could use it when you have limited GPU memory, but don’t even dream of speeding up inference with this operation.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh6.googleusercontent.com/ycp4Mz27TT19l5MK1sPsa7cYtwOy6f45mP5mcardfxzzwZpVSPZKDSgu58MaEwt--hjS-PFqC3EaW9XrXjDJmABc21XYdUhZ7-VNtGcobJjwlhSabVIhUK-AQdkAe6r98CoOwjMrOs2YPguMXgfH-2Y" class="kg-image" alt="" width="163" height="145"></figure><p><code>tile_overlap</code> is the same as <code>tile_pad</code> – it characterizes the degree of overlap between the two parts that are segmented. A higher <code>tile_pad</code> value means more parts of the input image are segmented, resulting in a “smoother” result.</p><h4 id="212-real-esrgan">2.1.2 <a href="https://github.com/xinntao/Real-ESRGAN?ref=jina-ai-gmbh.ghost.io">Real-ESRGAN</a></h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh6.googleusercontent.com/SCDn5FCUJqEI8cGA4yZCzXg8itK4cpLH9UHJ5g2UvULv0nuYcoUA1k9X7gxfFNIpbJk06l8lp9uhTtyTcA13sNaOM8F4bgc3OIjQXLCw45xVRRPagvbp_u5dGnkEYdD_iUluTMk8aqbK8fohidnoZr0" class="kg-image" alt="" width="624" height="167"></figure><p>Real-ESRGAN generator is the same generator (SR network) as ESRGAN, which is a deep network with several residual-in-residual dense blocks (RRDB). It also extends the original ×4 ESRGAN architecture to perform super-resolution with a scale factor of ×2. As ESRGAN is a heavy network, it first employs the pixel-unshuffle (an inverse operation of <a href="https://arxiv.org/abs/1609.05158v2?ref=jina-ai-gmbh.ghost.io">pixel-shuffle</a>, which is an operation used in super-resolution models to implement efficient sub-pixel convolutions. &nbsp;Specifically it rearranges elements in a tensor of shape [∗,C×r**2,H,W] to a tensor of shape [∗,C,r×H,r×W]) to reduce the spatial size and enlarge the channel size before feeding inputs into the main ESRGAN architecture. Thus, most calculation is performed in a smaller resolution space, which can reduce the GPU memory and computational resources consumption.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh4.googleusercontent.com/eEgo2JBKeD0AQLGpyIFnGlvrqnom4uhVP9yHBX9jS-gB611XHb43YcewqELdp3JXjM3vrUtjOL_n5_VzB_ASqveCcSMSWlfxlEaBIyJ5jTpe9gvBcXnaQFXQKKujgIIdCoMbnPRpyTb1CWo3rM1eLXQ" class="kg-image" alt="" width="327" height="184"></figure><h4 id="213-swin2sr">2.1.3 <a href="https://github.com/mv-lab/swin2sr?ref=jina-ai-gmbh.ghost.io">Swin2sr</a></h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh6.googleusercontent.com/x-AlJpxD3yBEiNISeHn8dwLKNlwcJGwVe4f0CPlSGXb93T31bC6y3AmwJ8Y_S0V0hp43f84MbYVzxFDLczN3jXlK-cY5LQEhqq-VUdIZUeAIDvIe6OafB_iVoXyUcL9PxNXLjjmhK98XUryre7gaCQs" class="kg-image" alt="" width="624" height="288"></figure><p>In swin2sr works, the authors explore the novel Swin Transformer V2, to improve SwinIR for image super-resolution, and in particular, the compressed input scenario. Using this method we can tackle the major issues in training transformer vision models, such as training instability, resolution gaps between pre-training and fine-tuning, and hunger on data. Experimental results demonstrate that the method, Swin2SR, can improve the training convergence and performance of SwinIR, and is a top-five solution at the "<a href="https://arxiv.org/abs/2208.11184?ref=jina-ai-gmbh.ghost.io">AIM 2022 Challenge on Super-Resolution of Compressed Image and Video</a>".</p><h4 id="214-stable-diffusion-upscaler">2.1.4 <a href="https://huggingface.co/stabilityai/stable-diffusion-x4-upscaler/tree/main?ref=jina-ai-gmbh.ghost.io">Stable Diffusion Upscaler</a></h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/jPHfafvMe_ZppFCTmMRkz69p-etQwqVtIlb9DpATYDTNReHX9CJcboYt0vkKFDLXJEnRdw5WL-vRkHjvz0S-gZ2yCH2SDPAXziCbuGaSKvC_b9JE1QoMOT7VwsMgI1pf3ChYZ9V919TjVT8gPwfBN4I" class="kg-image" alt="" width="624" height="297"></figure><p>Stable Diffusion Upscaler (SDU) is a super-resolution model based on the diffusion process. It converts a low-resolution image into a high-resolution image by introducing random noise and diffusion processes. The model includes an encoder, a diffusion layer and a decoder. The encoder maps the low-resolution image to the feature space, the diffusion layer improves the image quality by random noise and iteratively updating the feature map, and the decoder maps the feature map back to the high-resolution image space. SDU utilizes a nonlinear diffusion process and the introduction of random noise to be able to handle a diversity of details and textures, generating a more realistic and detailed high-resolution image. The implementation of specific models may vary, and the above description provides a general overview.</p><p>However, although this model has a better inference effect, at the same time the resource consumption is huge, under the same conditions, its inference time and memory occupation is several times that of other models. Due to its economic limitations, we do not introduce this model for the time being.</p><h3 id="22-fast-but-ineffective-models">2.2 Fast but Ineffective Models</h3><h4 id="221-bicubic">2.2.1 <a href="https://github.com/aselsan-research-imaging-team/bicubic-plusplus?ref=jina-ai-gmbh.ghost.io">bicubic</a></h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh6.googleusercontent.com/-EHyCR013dPSUqqkjXxxndbhj1tVie4aNrxPf3LNzDOfy_EbG-UpqRghi0rr4cWDrAikfnfWY_3IhNai_wRfJRxQshRI-AN-JkGqdKOJ3VCvgCK9LdJGhUQ9959MpiGEJfA9Z0_eZYjny1dAOYKTKws" class="kg-image" alt="" width="624" height="208"></figure><p>The authors propose a real-time and lightweight single-image super-resolution (SR) network named Bicubic++. Bicubic++ learns quick reversible downgraded and lower resolution features of the image to decrease the number of computations. They also apply an end-to-end global structured pruning of convolutional layers without using metrics like magnitude and gradient norms and focus on optimizing the pruned network's PSNR on the validation set. Furthermore, they also applied bias removal to the convolutional layers to enhance the inference speed.</p><h4 id="222-dipnet">2.2.2 <a href="https://github.com/xiumu00/DIPNet?ref=jina-ai-gmbh.ghost.io">DIPNet</a></h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/xRpwmdd76ij1SqlVQbh2lIPyJrWBOAnHSEN285LpLFK6ITLF3phqUKbknG5i0v0Bo441oII31OCbv17I1zvhyuhUaLmgx5LIMtzFD8It9XNamE_xb6FLGdr3OHwhdaWzVJLfAC0ASCzD0P0QtbfxK4I" class="kg-image" alt="" width="624" height="288"></figure><p>Specifically, they leverage enhanced high-resolution output as additional supervision to improve the learning ability of lightweight student networks. Upon convergence of the student network, we further simplify our network structure to a more lightweight level using reparameterization techniques and iterative network pruning. Meanwhile, they adopt an effective lightweight network training strategy that combines multi-anchor distillation and progressive learning, enabling the lightweight network to achieve outstanding performance. Ultimately, our proposed method achieves the fastest inference time among all participants in the <a href="https://openaccess.thecvf.com/content/CVPR2023W/NTIRE/papers/Li_NTIRE_2023_Challenge_on_Efficient_Super-Resolution_Methods_and_Results_CVPRW_2023_paper.pdf?ref=jina-ai-gmbh.ghost.io">NTIRE 2023</a> efficient super-resolution challenge while maintaining competitive super-resolution performance. The results show that the approach achieves comparable performance in representative dataset DIV2K, both qualitatively and quantitatively, with faster inference and fewer network parameters.</p><h4 id="223-lapsrn">2.2.3 LapSRN</h4><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/qOPOPgsesykp5wmzX7HB6KJUxP7IX45YyolKZGcJHWsKQDEIiNhWtmhHBHbJmfOkTzXyuJsHEqtkPKkW_koHpgJXl1-Qu7TEQ13uk_EhagXmzRyN3lnFhIxwPZ_yTUDtb7jxCWQpC82Y5W43Q5965cQ" class="kg-image" alt="" width="476" height="344"></figure><p>In this paper, the authors propose the Laplacian Pyramid Super-Resolution Network (LapSRN) to progressively reconstruct the sub-band residuals of high-resolution images. At each pyramid level, the model takes coarse-resolution feature maps as input, predicts the high-frequency residuals, and uses transposed convolutions for upsampling to the finer level. The method does not require bicubic interpolation as the pre-processing step and thus dramatically reduces the computational complexity. They train the proposed LapSRN with deep supervision using a robust Charbonnier loss function and achieve high-quality reconstruction. Furthermore, the network generates multi-scale predictions in one feed-forward pass through the progressive reconstruction, thereby facilitating resource-aware applications. Extensive quantitative and qualitative evaluations of benchmark datasets show that the proposed algorithm performs favorably against the state-of-the-art methods in terms of speed and accuracy.</p><h2 id="3-comparing-and-contrasting-models">3 Comparing and Contrasting Models</h2><p>We designed a series of evaluation procedures for evaluating the performance of each model. In this section, we present this evaluation in terms of the output of the models, inference time, GPU memory usage and other metrics, all evaluated independently and uniformly. </p><p>In all, considering the cost and performance, we may recommend that users use <em>Real-ESRGAN</em> if they are looking for high-quality upscaled images, with a reasonably low memory footprint. However, if users want to process a lot of images in a limited amount of time, at the cost of potentially lower-quality image outputs, then they should pick <em>DIPNet</em>. </p><p>The following graphs show the output comparison of the models. For tags under the images (e.g. Sheriff_5.966_2746), the first part of it is the filename of the image. The second and third parts are the inference time(s) and memory cost (MB), which will give you a clearer understanding of the inference process.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh3.googleusercontent.com/S2V_UC9oiT6X2VxHQsJ3ka0XxSe12YjxYhEzhnfnskK0a55dYkUMnvdqgFIB3b3uFEcm6-vhXNJpVahiny7eybETrT_Jat9vmAMjvVXKBA73_Tf1UG5o_ImbMC73Sw8YeTXUp8pGJtFJwo3t245r81Y" class="kg-image" alt="" width="624" height="721"></figure><p>Then there is the resource consummation examination of each model.</p><p><em>Dots per ms</em> means how large of an image can be processed per millisecond, and <em>Dots per MB</em> means how big of an image can be handled per MB GPU memory.</p><p>This may help you understand the costs of each model.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh4.googleusercontent.com/Hb3lhbPfmGyPMhuMBz30oFt5j1T4q2cJ97JTZBGuyjAIEj6bPMkMyiE2Z2A1Uc7Hm9szq61juPZ25aHfpG-CUfww6Iss3GvxI6pSAXdZPRRC2p0rF78GzgcDPBq_AUukteFoU5sUznaKOPcyYphGs6w" class="kg-image" alt="" width="624" height="385"></figure><p><em>DPS</em> (documents per second) represents the number of documents the model handled per second. In the examination below, the last column lists the maximum size of an image that the model can process using no more than 16G GPU memory (we assume that an image with a size greater than 1024*1024 does not need upscaling).</p><table style="border:none;border-collapse:collapse;"><colgroup><col width="180"><col width="146"><col width="150"><col width="143"></colgroup><tbody><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Model</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">dps</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Memory (GB)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Max image size</span></p></td></tr><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">swin2ir-compressed(x4)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">0.172</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">15.796</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">800*800</span></p></td></tr><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">swin2ir-real(x4)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">0.14</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">15.804</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">890*890</span></p></td></tr><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">swinir(x4)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">0.156</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">15.071</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">850*850</span></p></td></tr><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Real-ESRGAN(x4)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">0.267</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">14.899</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">990*990</span></p></td></tr><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">bicubic++(x3)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">10.592</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">0</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">1024*1024</span></p></td></tr><tr style="height:16.5pt"><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">DIPNet(x4)</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">357.143</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">1.88</span></p></td><td style="border-left:solid #cccccc 0.75pt;border-right:solid #cccccc 0.75pt;border-bottom:solid #cccccc 0.75pt;border-top:solid #cccccc 0.75pt;vertical-align:bottom;background-color:#b6d7a8;padding:2pt 2pt 2pt 2pt;overflow:hidden;overflow-wrap:break-word;"><p dir="ltr" style="line-height:1.38;text-align: center;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">1024*1024</span></p></td></tr></tbody></table><p>The result shows that bicubic and DIPNet have a great score on these two aspects, and the other 5 models have almost the same memory utilization. However, the performance of bicubic and DIPNet may not be satisfactory. Amongst all evaluated models, Real-ESRGAN has the best inference speed and moderate performance. SwinIR and Swin2ir-real seem to have almost the same performance and inference speed, which is equally matched with Real-ESRGAN (without face enhancement).</p><h2 id="4-using-super-resolution-models-in-inference-client">4 Using Super-resolution Models in Inference Client</h2><p>Let’s use Jina AI’s Inference to enjoy the visual feast of ordinary to extraordinary.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.readme.io/docs/client-initialization?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Connecting to Inference with a Python Client</div><div class="kg-bookmark-description">InstallationInference Client is available on PyPI and can be installed using pip:Shellpip install inference-client Client InitializationTo get started with the Inference Client, you’ll need to import the Client class from the inference_client package:Pythonfrom inference_client import Client We prov…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://files.readme.io/d8cf8d5-favicon.ico" alt=""><span class="kg-bookmark-author">Jina AI Cloud Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://files.readme.io/4890f37-Company_logo_dark.svg" alt=""></div></a></figure><p><a href="https://jina.readme.io/docs/client-initialization?ref=jina-ai-gmbh.ghost.io">Jina Inference Client</a> is a Python library that allows you to interact with the Jina AI Inference. It provides a simple and intuitive API to perform various tasks such as image captioning, encoding, ranking, visual question answering (VQA), and image upscaling. Here’s a simple example of how to use super-resolution models with Inference client.</p><p>First, you need to install Inference Client using pip:</p><pre><code>pip install inference-client</code></pre><p>Supposing that you have a Jina Flow serving an upscaling model running at <em>grpc://localhost:51001</em>, you need to initialize the inference client using the following code:</p><pre><code class="language-python">from inference_client import Client
+from jina import DocumentArray, Document
 
 client = Client()
-model = client.get_model(<span class="hljs-string">'grpc://localhost:51001'</span>)</code></pre><p>Secondly, images can be loaded from a URI on the internet or from your local filesystem:</p><pre><code class="language-python hljs">doc = [Document(uri=image, tags={<span class="hljs-string">"image_format"</span>: <span class="hljs-string">"png"</span>})]</code></pre><p><code>image_format</code> is the output format of the image. If not set, the original image format will be used.</p><p>Now you can call the client to perform the upscaling:</p><pre><code class="language-python hljs">result = model.upscale(image=doc, output_path=<span class="hljs-string">'upscaled_image.png'</span>)</code></pre><p>You can also specify the output size or ratio for the output image. However, it cannot be larger than the original image size * <code>upscale_ratio</code>. For example, the following code specifies the output image’s width as 600 pixels. Note that for parameter setting we follow the <a href="https://ffmpeg.org/ffmpeg-formats.html?ref=jina-ai-gmbh.ghost.io">FFMPEG style</a>.</p><pre><code class="language-python hljs">result = model.upscale(image=image, scale=<span class="hljs-string">'600:-1'</span>, output_path=<span class="hljs-string">'upscaled_image.png'</span>)</code></pre><p>We also support a <a href="https://jina.readme.io/docs/connecting-to-inference-with-a-javascript-client?ref=jina-ai-gmbh.ghost.io">JavaScript client</a> and plain HTTP requests <a href="https://jina.readme.io/docs/image-upscaling?ref=jina-ai-gmbh.ghost.io#plain-http-requests-via-curl">through cURL</a>.</p><h2 id="5-working-with-aigc">5 Working with AIGC</h2><p>Integrating super-resolution (SR) models into the AIGC (Artificial Intelligence in Graphics and Creative) field, particularly in collaboration with <a href="https://stability.ai/stablediffusion?ref=jina-ai-gmbh.ghost.io">Stable Diffusion</a>, can enhance the quality and creativity of image generation and manipulation. Here's how super-resolution models can be integrated and co-work with Stable Diffusion:</p><ol><li>Image Enhancement and Upscaling: These models can be used to enhance low-resolution images and upscale them to higher resolutions with improved details and clarity. The high-resolution images obtained from super-resolution can then be used as inputs for stable diffusion algorithms, enabling more precise and realistic image manipulations.</li><li>Style Transfer and Artistic Rendering: By combining super-resolution with stable diffusion, artists and designers can upscale low-resolution artwork and then apply style transfer techniques to achieve unique and creative visual effects. The high-resolution images produced by super-resolution can capture more intricate details, enabling stable diffusion to better preserve and transfer artistic styles.</li><li>Video Super-Resolution: Integrating these models with stable diffusion can be especially beneficial for video processing. Super-resolution can be applied to each frame of a low-resolution video, followed by stable diffusion-based techniques to generate high-resolution, smooth, and stable video sequences.</li><li>Generative Models and Data Augmentation: These models can be used as a pre-processing step to upscale low-resolution training images in generative models like GANs (Generative Adversarial Networks) or VAEs (Variational Autoencoders). This integration can improve the quality and diversity of generated images.</li><li>Image Restoration and Manipulation: By combining these models with stable diffusion, it becomes possible to restore and manipulate images with higher fidelity and finer details. For tasks like image inpainting or denoising, super-resolution can be employed to generate high-resolution versions of damaged images, followed by stable diffusion to reconstruct and fill in missing regions.</li><li>Real-Time Applications: The combination of super-resolution and stable diffusion can lead to real-time image and video processing applications. For example, super-resolution can upscale low-resolution input frames in real-time, followed by stable diffusion for stylistic rendering or other creative effects, providing interactive and visually appealing experiences.</li></ol><p>Overall, integrating super-resolution models with stable diffusion opens up a wide range of possibilities for enhancing image quality, boosting creative capabilities, and advancing the AIGC field. This collaborative approach empowers artists, designers, and developers to create more realistic, vibrant, and captivating visual content across various domains and applications. </p><p>Now, Jina AI’s users have the opportunity to try out the super-resolution task using our best-in-class model-as-a-service offering, <a href="https://cloud.jina.ai/user/inference?ref=jina-ai-gmbh.ghost.io">Inference</a>, on Jina AI Cloud.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/user/inference?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">The most advanced MLOps platform for multimodal AI, neural search and creative AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a></figure><p> You can also get in touch with us with your questions on our <a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io">Discord channel</a>.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Join Jina AI Discord</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fa-guide-for-super-resolution-ordinary-to-extraordinary-with-inference%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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+model = client.get_model('grpc://localhost:51001')</code></pre><p>Secondly, images can be loaded from a URI on the internet or from your local filesystem:</p><pre><code class="language-python">doc = [Document(uri=image, tags={"image_format": "png"})]</code></pre><p><code>image_format</code> is the output format of the image. If not set, the original image format will be used.</p><p>Now you can call the client to perform the upscaling:</p><pre><code class="language-python">result = model.upscale(image=doc, output_path='upscaled_image.png')</code></pre><p>You can also specify the output size or ratio for the output image. However, it cannot be larger than the original image size * <code>upscale_ratio</code>. For example, the following code specifies the output image’s width as 600 pixels. Note that for parameter setting we follow the <a href="https://ffmpeg.org/ffmpeg-formats.html?ref=jina-ai-gmbh.ghost.io">FFMPEG style</a>.</p><pre><code class="language-python">result = model.upscale(image=image, scale='600:-1', output_path='upscaled_image.png')</code></pre><p>We also support a <a href="https://jina.readme.io/docs/connecting-to-inference-with-a-javascript-client?ref=jina-ai-gmbh.ghost.io">JavaScript client</a> and plain HTTP requests <a href="https://jina.readme.io/docs/image-upscaling?ref=jina-ai-gmbh.ghost.io#plain-http-requests-via-curl">through cURL</a>.</p><h2 id="5-working-with-aigc">5 Working with AIGC</h2><p>Integrating super-resolution (SR) models into the AIGC (Artificial Intelligence in Graphics and Creative) field, particularly in collaboration with <a href="https://stability.ai/stablediffusion?ref=jina-ai-gmbh.ghost.io">Stable Diffusion</a>, can enhance the quality and creativity of image generation and manipulation. Here's how super-resolution models can be integrated and co-work with Stable Diffusion:</p><ol><li>Image Enhancement and Upscaling: These models can be used to enhance low-resolution images and upscale them to higher resolutions with improved details and clarity. The high-resolution images obtained from super-resolution can then be used as inputs for stable diffusion algorithms, enabling more precise and realistic image manipulations.</li><li>Style Transfer and Artistic Rendering: By combining super-resolution with stable diffusion, artists and designers can upscale low-resolution artwork and then apply style transfer techniques to achieve unique and creative visual effects. The high-resolution images produced by super-resolution can capture more intricate details, enabling stable diffusion to better preserve and transfer artistic styles.</li><li>Video Super-Resolution: Integrating these models with stable diffusion can be especially beneficial for video processing. Super-resolution can be applied to each frame of a low-resolution video, followed by stable diffusion-based techniques to generate high-resolution, smooth, and stable video sequences.</li><li>Generative Models and Data Augmentation: These models can be used as a pre-processing step to upscale low-resolution training images in generative models like GANs (Generative Adversarial Networks) or VAEs (Variational Autoencoders). This integration can improve the quality and diversity of generated images.</li><li>Image Restoration and Manipulation: By combining these models with stable diffusion, it becomes possible to restore and manipulate images with higher fidelity and finer details. For tasks like image inpainting or denoising, super-resolution can be employed to generate high-resolution versions of damaged images, followed by stable diffusion to reconstruct and fill in missing regions.</li><li>Real-Time Applications: The combination of super-resolution and stable diffusion can lead to real-time image and video processing applications. For example, super-resolution can upscale low-resolution input frames in real-time, followed by stable diffusion for stylistic rendering or other creative effects, providing interactive and visually appealing experiences.</li></ol><p>Overall, integrating super-resolution models with stable diffusion opens up a wide range of possibilities for enhancing image quality, boosting creative capabilities, and advancing the AIGC field. This collaborative approach empowers artists, designers, and developers to create more realistic, vibrant, and captivating visual content across various domains and applications. </p><p>Now, Jina AI’s users have the opportunity to try out the super-resolution task using our best-in-class model-as-a-service offering, <a href="https://cloud.jina.ai/user/inference?ref=jina-ai-gmbh.ghost.io">Inference</a>, on Jina AI Cloud.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/user/inference?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">The most advanced MLOps platform for multimodal AI, neural search and creative AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a></figure><p> You can also get in touch with us with your questions on our <a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io">Discord channel</a>.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Join Jina AI Discord</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fa-guide-for-super-resolution-ordinary-to-extraordinary-with-inference%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</title><meta charset="utf-8"><meta name="title" content="A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain"><meta name="description" content="See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain"><meta property="og:title" content="A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain"><meta property="og:description" content="See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain"><meta property="twitter:title" content="A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain"><meta property="twitter:description" content="See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</title><meta charset="utf-8"><meta name="title" content="A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain"><meta name="description" content="See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain"><meta property="og:title" content="A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain"><meta property="og:description" content="See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain"><meta property="twitter:title" content="A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain"><meta property="twitter:description" content="See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.385%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Lisa Li, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 21, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>We recently wrote about SceneXplain's new <a href="https://www.notion.so/A-Magic-Carpet-Ride-Building-Vivid-Product-Stories-with-SceneXplain-7a07a53a3ffa48b083d9abe9c3c1c3af?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">JSON Schema Store</a>, which lets you use predefined JSON schemas to extract information from images in a structured format. In this post, we're going to see how that's used by our partner, <a href="http://www.akia.cn/eindex.asp?ref=jina-ai-gmbh.ghost.io">AKIA Carpet &amp; Rugs</a>, for building up an AI-powered product stories generation bot to empower sales.</p><p>In our prior examples, we've primarily used either cURL or Python to access <a href="https://www.notion.so/A-Magic-Carpet-Ride-Building-Vivid-Product-Stories-with-SceneXplain-7a07a53a3ffa48b083d9abe9c3c1c3af?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">SceneXplain's API</a>. But in this post, we're switching things up a bit by using JavaScript.</p><h2 id="about-akia-carpet-rugs">About AKIA Carpet &amp; Rugs</h2><p>In July 2008, Gary Chen founded AKIA Carpet &amp; Rugs, which is now marking its 15th year of operation. The team, initially inspired by traditional Asian craftsmanship, has been dedicated to developing contemporary aesthetic styles. AKIA has grown into a brand known for its unique fusion of modern art with traditional design and weaving techniques.</p><p>As a carpet manufacturer, AKIA specializes in a range of products including mid-to-high-end decorative carpets, tapestries, and carpets for specific projects. The company integrates design, research, production, and sales, both domestically and internationally. Known for innovative design and high-quality products, AKIA has earned a solid reputation in China's high-end carpet market.</p><h2 id="crafting-a-winning-product-story-with-scenexplain"><strong>Crafting a Winning Product Story with SceneXplain</strong></h2><p>AKIA Carpet &amp; Rugs primarily caters to the mid-to-high-end market, focusing on the aesthetic appeal of their products. Their clientele often looks for carpets that not only complement their home design but also express their unique taste. Recognizing this, AKIA collaborates with skilled designers to create a diverse range of styles, resulting in an extensive collection of carpet designs and images. The challenge lies in effectively communicating the artistic value of these designs to discerning customers, a crucial factor in attracting clients.</p><p>Previously, crafting compelling narratives for a large array of product images, akin to artworks, was a daunting task. This required copywriters who were not only skilled in writing but also knowledgeable in design and art. Additionally, the need to swiftly identify the perfect product image from an extensive collection to meet specific customer preferences was a significant challenge. Traditional image labeling methods, focusing on basic attributes like color, shape, and material, proved insufficient for customers who often describe their needs in more abstract terms.</p><p>SceneXplain offers a dual solution to these challenges. Its approach is based on narration rather than mere description, aiming to weave engaging stories around images. This aligns with SceneXplain's core philosophy: storytelling brings images to life. By providing stories that resonate with the artistic nature of AKIA's products, SceneXplain addresses their need for an intuitive, aesthetically aligned way of presenting their carpets.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot-2023-12-19-at-6.47.11-PM.png" class="kg-image" alt="" width="2000" height="1183" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Screenshot-2023-12-19-at-6.47.11-PM.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/Screenshot-2023-12-19-at-6.47.11-PM.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/Screenshot-2023-12-19-at-6.47.11-PM.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/12/Screenshot-2023-12-19-at-6.47.11-PM.png 2400w" sizes="(min-width: 720px) 720px"></figure><blockquote>"Embrace Yourself" is a piece of art in the form of a carpet, exuding minimalist charm and contemporary simplicity. This piece features the elegant, abstract depiction of a round, white figure at its center—an embodiment of purity and serenity. With meticulously crafted black outlines that grace the soothing white background, this carpet tells a subtle but impactful visual story. Each line is placed with thoughtful precision, evoking emotions and depth without cluttering the visual space. The characteristic round head of the figure in the design adds a touch of futuristic whimsy, creating a space for imagination to soar. The light gray tones and stark white spaces between the lines further enhance the abstract quality, offering a calm and peaceful atmosphere to any room. Whether adorning a modern living area or a chic office space, "Embrace Yourself" promises to be more than just a carpet—it is a promise of self-discovery and a celebration of space and form. Its simplicity and abstraction are not just visually appealing but are crafted to engage the observer in an almost meditative contemplation.</blockquote><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot-2023-12-19-at-7.18.18-PM.png" class="kg-image" alt="" width="2000" height="1189" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Screenshot-2023-12-19-at-7.18.18-PM.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/Screenshot-2023-12-19-at-7.18.18-PM.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/Screenshot-2023-12-19-at-7.18.18-PM.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/12/Screenshot-2023-12-19-at-7.18.18-PM.png 2400w" sizes="(min-width: 720px) 720px"></figure><blockquote>"Dancer" is an evocative piece of home decor where color and geometry resonate to a rhythm of their own. Adorning a rich navy blue background, this carpet features a dynamic composition of blue and orange lines and squares that glide across the fabric, suggesting movement and energy, much like a dancer in the spotlight. The striking orange lines dance diagonally, connecting a series of crisp white squares, which are themselves accented with black detailing, reminiscent of precise footwork on a dance stage. Unequivocally modern, "Dancer" employs the contrast of deep blues with vibrant oranges and whites to create an abstract visual narrative that is open to interpretation, yet commands attention. Each element on "Dancer" is painstakingly arranged to bring a sense of balance and fluidity, paralleling a choreographed performance that tells a story with every twist and turn. The pattern encourages the eye to leap and land much like a viewer watching an enthralling solo dance performance, making "Dancer" not just a carpet, but a conversation piece that captivates and inspires.</blockquote><h2 id="product-story-generation-a-holistic-solution">Product story generation: A holistic solution</h2><p>In AKIA’s use case, their product manager wants to automatically create stories for all their products. The stories should use some high-quality examples as a guide, which contain aesthetic explanations. Their specific needs are:</p><ul><li>Textual descriptions of their products</li><li>Stories for each product that follow the examples they provide</li><li>Batch processing of images triggered by the chat channel</li></ul><p>Based on these requirements, visual question answering (VQA) is the best fit, because:</p><ul><li>Visual question answering outputs textual descriptions.</li><li>In the question, you can also provide a prompt in a specific format on demand.</li><li>You can inject your own examples into the prompt to guide the model’s output.</li><li>Once you have the prompt’s basic structure, you can convert it to a template with variables that can be automatically populated each time you use it.</li></ul><p>SceneXplain’s API provides a wide range of options for configuring your request, including image captioning, alt-text generation, visual question answering, JSON output, and more.</p><p>Several fields are required to execute a VQA task via the API:</p><ul><li>API endpoint: <code>https://api.scenex.jina.ai/v1/describe</code></li><li>API key: <code>'x-api-key': token ${YOUR_API_KEY}</code>. You can generate and manage your API key on our <a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io">API page</a>.</li><li>Request payload, which is your task configuration, providing the image you want to process, setting <code>question_answer</code> in the <code>features</code> property, and setting your prompt in the <code>question</code> property.</li></ul><p>Here’s a code snippet for such an API call in JavaScript:</p><pre><code class="language-jsx hljs language-javascript"><span class="hljs-keyword">const</span> body = {
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.385%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Lisa Li, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 21, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>We recently wrote about SceneXplain's new <a href="https://www.notion.so/A-Magic-Carpet-Ride-Building-Vivid-Product-Stories-with-SceneXplain-7a07a53a3ffa48b083d9abe9c3c1c3af?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">JSON Schema Store</a>, which lets you use predefined JSON schemas to extract information from images in a structured format. In this post, we're going to see how that's used by our partner, <a href="http://www.akia.cn/eindex.asp?ref=jina-ai-gmbh.ghost.io">AKIA Carpet &amp; Rugs</a>, for building up an AI-powered product stories generation bot to empower sales.</p><p>In our prior examples, we've primarily used either cURL or Python to access <a href="https://www.notion.so/A-Magic-Carpet-Ride-Building-Vivid-Product-Stories-with-SceneXplain-7a07a53a3ffa48b083d9abe9c3c1c3af?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">SceneXplain's API</a>. But in this post, we're switching things up a bit by using JavaScript.</p><h2 id="about-akia-carpet-rugs">About AKIA Carpet &amp; Rugs</h2><p>In July 2008, Gary Chen founded AKIA Carpet &amp; Rugs, which is now marking its 15th year of operation. The team, initially inspired by traditional Asian craftsmanship, has been dedicated to developing contemporary aesthetic styles. AKIA has grown into a brand known for its unique fusion of modern art with traditional design and weaving techniques.</p><p>As a carpet manufacturer, AKIA specializes in a range of products including mid-to-high-end decorative carpets, tapestries, and carpets for specific projects. The company integrates design, research, production, and sales, both domestically and internationally. Known for innovative design and high-quality products, AKIA has earned a solid reputation in China's high-end carpet market.</p><h2 id="crafting-a-winning-product-story-with-scenexplain"><strong>Crafting a Winning Product Story with SceneXplain</strong></h2><p>AKIA Carpet &amp; Rugs primarily caters to the mid-to-high-end market, focusing on the aesthetic appeal of their products. Their clientele often looks for carpets that not only complement their home design but also express their unique taste. Recognizing this, AKIA collaborates with skilled designers to create a diverse range of styles, resulting in an extensive collection of carpet designs and images. The challenge lies in effectively communicating the artistic value of these designs to discerning customers, a crucial factor in attracting clients.</p><p>Previously, crafting compelling narratives for a large array of product images, akin to artworks, was a daunting task. This required copywriters who were not only skilled in writing but also knowledgeable in design and art. Additionally, the need to swiftly identify the perfect product image from an extensive collection to meet specific customer preferences was a significant challenge. Traditional image labeling methods, focusing on basic attributes like color, shape, and material, proved insufficient for customers who often describe their needs in more abstract terms.</p><p>SceneXplain offers a dual solution to these challenges. Its approach is based on narration rather than mere description, aiming to weave engaging stories around images. This aligns with SceneXplain's core philosophy: storytelling brings images to life. By providing stories that resonate with the artistic nature of AKIA's products, SceneXplain addresses their need for an intuitive, aesthetically aligned way of presenting their carpets.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot-2023-12-19-at-6.47.11-PM.png" class="kg-image" alt="" width="2000" height="1183" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Screenshot-2023-12-19-at-6.47.11-PM.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/Screenshot-2023-12-19-at-6.47.11-PM.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/Screenshot-2023-12-19-at-6.47.11-PM.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/12/Screenshot-2023-12-19-at-6.47.11-PM.png 2400w" sizes="(min-width: 720px) 720px"></figure><blockquote>"Embrace Yourself" is a piece of art in the form of a carpet, exuding minimalist charm and contemporary simplicity. This piece features the elegant, abstract depiction of a round, white figure at its center—an embodiment of purity and serenity. With meticulously crafted black outlines that grace the soothing white background, this carpet tells a subtle but impactful visual story. Each line is placed with thoughtful precision, evoking emotions and depth without cluttering the visual space. The characteristic round head of the figure in the design adds a touch of futuristic whimsy, creating a space for imagination to soar. The light gray tones and stark white spaces between the lines further enhance the abstract quality, offering a calm and peaceful atmosphere to any room. Whether adorning a modern living area or a chic office space, "Embrace Yourself" promises to be more than just a carpet—it is a promise of self-discovery and a celebration of space and form. Its simplicity and abstraction are not just visually appealing but are crafted to engage the observer in an almost meditative contemplation.</blockquote><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot-2023-12-19-at-7.18.18-PM.png" class="kg-image" alt="" width="2000" height="1189" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Screenshot-2023-12-19-at-7.18.18-PM.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/Screenshot-2023-12-19-at-7.18.18-PM.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/Screenshot-2023-12-19-at-7.18.18-PM.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/12/Screenshot-2023-12-19-at-7.18.18-PM.png 2400w" sizes="(min-width: 720px) 720px"></figure><blockquote>"Dancer" is an evocative piece of home decor where color and geometry resonate to a rhythm of their own. Adorning a rich navy blue background, this carpet features a dynamic composition of blue and orange lines and squares that glide across the fabric, suggesting movement and energy, much like a dancer in the spotlight. The striking orange lines dance diagonally, connecting a series of crisp white squares, which are themselves accented with black detailing, reminiscent of precise footwork on a dance stage. Unequivocally modern, "Dancer" employs the contrast of deep blues with vibrant oranges and whites to create an abstract visual narrative that is open to interpretation, yet commands attention. Each element on "Dancer" is painstakingly arranged to bring a sense of balance and fluidity, paralleling a choreographed performance that tells a story with every twist and turn. The pattern encourages the eye to leap and land much like a viewer watching an enthralling solo dance performance, making "Dancer" not just a carpet, but a conversation piece that captivates and inspires.</blockquote><h2 id="product-story-generation-a-holistic-solution">Product story generation: A holistic solution</h2><p>In AKIA’s use case, their product manager wants to automatically create stories for all their products. The stories should use some high-quality examples as a guide, which contain aesthetic explanations. Their specific needs are:</p><ul><li>Textual descriptions of their products</li><li>Stories for each product that follow the examples they provide</li><li>Batch processing of images triggered by the chat channel</li></ul><p>Based on these requirements, visual question answering (VQA) is the best fit, because:</p><ul><li>Visual question answering outputs textual descriptions.</li><li>In the question, you can also provide a prompt in a specific format on demand.</li><li>You can inject your own examples into the prompt to guide the model’s output.</li><li>Once you have the prompt’s basic structure, you can convert it to a template with variables that can be automatically populated each time you use it.</li></ul><p>SceneXplain’s API provides a wide range of options for configuring your request, including image captioning, alt-text generation, visual question answering, JSON output, and more.</p><p>Several fields are required to execute a VQA task via the API:</p><ul><li>API endpoint: <code>https://api.scenex.jina.ai/v1/describe</code></li><li>API key: <code>'x-api-key': token ${YOUR_API_KEY}</code>. You can generate and manage your API key on our <a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io">API page</a>.</li><li>Request payload, which is your task configuration, providing the image you want to process, setting <code>question_answer</code> in the <code>features</code> property, and setting your prompt in the <code>question</code> property.</li></ul><p>Here’s a code snippet for such an API call in JavaScript:</p><pre><code class="language-jsx">const body = {
+  "data": [
     {
-			<span class="hljs-string">"image"</span>: <span class="hljs-string">"The image you want to process, it can be a base64 string or a URL"</span>,
-      <span class="hljs-string">"features"</span>: [
-        <span class="hljs-string">"question_answer"</span>
+			"image": "The image you want to process, it can be a base64 string or a URL",
+      "features": [
+        "question_answer"
       ],
-      <span class="hljs-string">"algorithm"</span>: <span class="hljs-string">"jelly"</span>,
-      <span class="hljs-string">"languages"</span>: [
-        <span class="hljs-string">"en"</span>
+      "algorithm": "jelly",
+      "languages": [
+        "en"
       ],
-		<span class="hljs-string">"question"</span>: <span class="hljs-string">"your prompt"</span>
+		"question": "your prompt"
     }
   ]
 };
 
-<span class="hljs-keyword">const</span> <span class="hljs-variable constant_">YOUR_API_KEY</span> = <span class="hljs-string">'your_generated_API_key_here'</span>;
+const YOUR_API_KEY = 'your_generated_API_key_here';
 
-<span class="hljs-title function_">fetch</span>(<span class="hljs-string">'https://api.scenex.jina.ai/v1/describe'</span>, {
-  <span class="hljs-attr">headers</span>: {
-    <span class="hljs-string">'x-api-key'</span>: <span class="hljs-string">`token <span class="hljs-subst">${YOUR_API_KEY}</span>`</span>,
-    <span class="hljs-string">'content-type'</span>: <span class="hljs-string">'application/json'</span>
+fetch('https://api.scenex.jina.ai/v1/describe', {
+  headers: {
+    'x-api-key': `token ${YOUR_API_KEY}`,
+    'content-type': 'application/json'
   },
-  <span class="hljs-attr">body</span>: <span class="hljs-title class_">JSON</span>.<span class="hljs-title function_">stringify</span>(body),
-  <span class="hljs-attr">method</span>: <span class="hljs-string">'POST'</span>
+  body: JSON.stringify(body),
+  method: 'POST'
 })
-.<span class="hljs-title function_">then</span>(<span class="hljs-keyword">async</span> (resp) =&gt; {
-  <span class="hljs-keyword">if</span> (resp.<span class="hljs-property">ok</span>) {
-    <span class="hljs-keyword">const</span> data = <span class="hljs-keyword">await</span> resp.<span class="hljs-title function_">json</span>();
-    <span class="hljs-variable language_">console</span>.<span class="hljs-title function_">log</span>(data);
+.then(async (resp) =&gt; {
+  if (resp.ok) {
+    const data = await resp.json();
+    console.log(data);
   }
 });
-</code></pre><p>The payload’s <code>data</code> property is an array that can have several configurations, meaning you can batch-process your images via the API.</p><h2 id="connecting-akia-to-scenexplain%E2%80%99s-api-via-bot">Connecting AKIA to SceneXplain’s API via bot</h2><p>AKIA uses <a href="https://www.larksuite.com/en_eu?ref=jina-ai-gmbh.ghost.io">Lark</a> for their internal messaging, which is a Chinese application similar to Slack, Microsoft Teams, and Discord. An employee of AKIA can simply send a message to their SceneXplain chatbot that includes an image and a topic.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/21700476455_.pic.jpg" class="kg-image" alt="" width="1821" height="1140" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/21700476455_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/21700476455_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/21700476455_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/21700476455_.pic.jpg 1821w" sizes="(min-width: 720px) 720px"></figure><p>The chatbot sends back a detailed description of the carpet. Here’s how it would look in English:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/SceneX-carpet--3-.png" class="kg-image" alt="" width="847" height="291" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/SceneX-carpet--3-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/SceneX-carpet--3-.png 847w" sizes="(min-width: 720px) 720px"></figure><p>Behind the scenes, there’s a middleware service that connects Lark to the SceneXplain API:</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/workflow.png" class="kg-image" alt="" width="1000" height="221" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/workflow.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/workflow.png 1000w"></figure><p>It shuttles the data between the two services and performs several key tasks:</p><ul><li>Message validation</li><li>API payload generation</li><li>API calling</li><li>Message formatting</li></ul><p>The process is:</p><ol><li>Receive image and topic in message from Lark chatbot</li><li>Check message format is valid. If not, return an error.</li><li>Base64-encode the image and wrap both it and the topic into a payload, using the topic as the question in visual question answering (VQA)</li><li>Send the payload to the API</li><li>API generates a description and sends that back</li><li>Format the message to fit Lark’s API</li><li>Send the message back to the Lark chatbot</li></ol><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">We’re not going to go into the workings of the Lark API here. We want to keep this post as service-agnostic as possible, so it’s relevant to whatever service you want to integrate with SceneXplain.</div></div><p>We’re just going to focus on the middleware (“Your service” in the diagram above). All you need is a few lines of code to reformulate the request, pass it on, and then do the same for the response.</p><pre><code class="language-jsx hljs language-javascript"><span class="hljs-comment">// Function to call SceneXplain `/describe` API</span>
-<span class="hljs-keyword">const</span> <span class="hljs-title function_">describe</span> = <span class="hljs-keyword">async</span> (<span class="hljs-params">image: string, name: string, topic: string</span>) =&gt; {
-  <span class="hljs-comment">// prepare payload</span>
-  <span class="hljs-keyword">const</span> newBody = {
-    <span class="hljs-attr">data</span>: [
+</code></pre><p>The payload’s <code>data</code> property is an array that can have several configurations, meaning you can batch-process your images via the API.</p><h2 id="connecting-akia-to-scenexplain%E2%80%99s-api-via-bot">Connecting AKIA to SceneXplain’s API via bot</h2><p>AKIA uses <a href="https://www.larksuite.com/en_eu?ref=jina-ai-gmbh.ghost.io">Lark</a> for their internal messaging, which is a Chinese application similar to Slack, Microsoft Teams, and Discord. An employee of AKIA can simply send a message to their SceneXplain chatbot that includes an image and a topic.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/21700476455_.pic.jpg" class="kg-image" alt="" width="1821" height="1140" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/21700476455_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/21700476455_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/21700476455_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/21700476455_.pic.jpg 1821w" sizes="(min-width: 720px) 720px"></figure><p>The chatbot sends back a detailed description of the carpet. Here’s how it would look in English:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/SceneX-carpet--3-.png" class="kg-image" alt="" width="847" height="291" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/SceneX-carpet--3-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/SceneX-carpet--3-.png 847w" sizes="(min-width: 720px) 720px"></figure><p>Behind the scenes, there’s a middleware service that connects Lark to the SceneXplain API:</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/workflow.png" class="kg-image" alt="" width="1000" height="221" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/workflow.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/workflow.png 1000w"></figure><p>It shuttles the data between the two services and performs several key tasks:</p><ul><li>Message validation</li><li>API payload generation</li><li>API calling</li><li>Message formatting</li></ul><p>The process is:</p><ol><li>Receive image and topic in message from Lark chatbot</li><li>Check message format is valid. If not, return an error.</li><li>Base64-encode the image and wrap both it and the topic into a payload, using the topic as the question in visual question answering (VQA)</li><li>Send the payload to the API</li><li>API generates a description and sends that back</li><li>Format the message to fit Lark’s API</li><li>Send the message back to the Lark chatbot</li></ol><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">We’re not going to go into the workings of the Lark API here. We want to keep this post as service-agnostic as possible, so it’s relevant to whatever service you want to integrate with SceneXplain.</div></div><p>We’re just going to focus on the middleware (“Your service” in the diagram above). All you need is a few lines of code to reformulate the request, pass it on, and then do the same for the response.</p><pre><code class="language-jsx">// Function to call SceneXplain `/describe` API
+const describe = async (image: string, name: string, topic: string) =&gt; {
+  // prepare payload
+  const newBody = {
+    data: [
       {
-        <span class="hljs-attr">image</span>: image,
-        <span class="hljs-attr">features</span>: [
-          <span class="hljs-string">"question_answer"</span>
+        image: image,
+        features: [
+          "question_answer"
         ],
-        <span class="hljs-attr">languages</span>: [<span class="hljs-string">'zh-CN'</span>],
-        <span class="hljs-attr">algorithm</span>: <span class="hljs-string">'Jelly'</span>,
-        <span class="hljs-attr">question</span>: <span class="hljs-string">`your prompt, incorporating <span class="hljs-subst">${name}</span> and <span class="hljs-subst">${topic}</span>, plus optional example for desired output format for in-context learning`</span>
+        languages: ['zh-CN'],
+        algorithm: 'Jelly',
+        question: `your prompt, incorporating ${name} and ${topic}, plus optional example for desired output format for in-context learning`
       }
     ]
   }
 
-  <span class="hljs-comment">// call SceneXplain API</span>
-  <span class="hljs-keyword">try</span> {
-    <span class="hljs-keyword">const</span> resp = <span class="hljs-keyword">await</span> <span class="hljs-title function_">fetch</span>(<span class="hljs-string">'https://api.scenex.jina.ai/v1/describe'</span>, {
-      <span class="hljs-attr">headers</span>: {
-        <span class="hljs-string">'x-api-key'</span>: <span class="hljs-string">`token <span class="hljs-subst">${process.env.scenexKey}</span>`</span>,
-        <span class="hljs-string">'content-type'</span>: <span class="hljs-string">'application/json'</span>
+  // call SceneXplain API
+  try {
+    const resp = await fetch('https://api.scenex.jina.ai/v1/describe', {
+      headers: {
+        'x-api-key': `token ${process.env.scenexKey}`,
+        'content-type': 'application/json'
       },
-      <span class="hljs-attr">body</span>: <span class="hljs-title class_">JSON</span>.<span class="hljs-title function_">stringify</span>(newBody),
-      <span class="hljs-attr">method</span>: <span class="hljs-string">'POST'</span>,
+      body: JSON.stringify(newBody),
+      method: 'POST',
     });
-    <span class="hljs-keyword">if</span> (!resp.<span class="hljs-property">ok</span>) {
-      <span class="hljs-keyword">const</span> error = <span class="hljs-keyword">await</span> resp.<span class="hljs-title function_">text</span>();
-      <span class="hljs-keyword">throw</span> error;
+    if (!resp.ok) {
+      const error = await resp.text();
+      throw error;
     }
-    <span class="hljs-keyword">const</span> data = <span class="hljs-keyword">await</span> resp.<span class="hljs-title function_">json</span>() <span class="hljs-keyword">as</span> any;
-    <span class="hljs-variable language_">console</span>.<span class="hljs-title function_">log</span>(<span class="hljs-string">`describe result: <span class="hljs-subst">${<span class="hljs-built_in">JSON</span>.stringify(data, <span class="hljs-literal">null</span>, <span class="hljs-number">2</span>)}</span>`</span>);
-    <span class="hljs-keyword">if</span> (data.<span class="hljs-property">code</span> !== <span class="hljs-number">200</span>) <span class="hljs-keyword">throw</span> data;
-    <span class="hljs-keyword">const</span> result = data.<span class="hljs-property">result</span>[<span class="hljs-number">0</span>];
+    const data = await resp.json() as any;
+    console.log(`describe result: ${JSON.stringify(data, null, 2)}`);
+    if (data.code !== 200) throw data;
+    const result = data.result[0];
 
-    <span class="hljs-comment">// get result in the required language</span>
-    <span class="hljs-keyword">return</span> result.<span class="hljs-property">i18n</span>[<span class="hljs-string">'zh-CN'</span>];
-  } <span class="hljs-keyword">catch</span> (e) {
-    <span class="hljs-variable language_">console</span>.<span class="hljs-title function_">log</span>(<span class="hljs-string">`describe error: <span class="hljs-subst">${<span class="hljs-built_in">JSON</span>.stringify(e, <span class="hljs-literal">null</span>, <span class="hljs-number">2</span>)}</span>`</span>);
-    <span class="hljs-keyword">return</span> <span class="hljs-string">''</span>;
+    // get result in the required language
+    return result.i18n['zh-CN'];
+  } catch (e) {
+    console.log(`describe error: ${JSON.stringify(e, null, 2)}`);
+    return '';
   }
 }
-</code></pre><p>As you can see from the <code>question</code> field in the example payload above, you can include some example output to help the algorithm in generating the kind of description you desire. And, of course, you don’t <em>have</em> to use JavaScript to build your middleware service - any programming language with an HTTP library can access <a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io">SceneXplain’s API</a>.</p><h2 id="wrapping-up">Wrapping up</h2><p>Do you want to follow in AKIA’s footsteps and use SceneXplain to build vivid product stories from your images and videos? Head over to <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">https://scenex.jina.ai</a> to get started. Or for business use cases, fill in our <a href="https://jina.ai/contact-sales/?ref=jina-ai-gmbh.ghost.io">sales form</a> and we’ll be happy to roll out the red carpet.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fa-magic-carpet-ride-building-vivid-product-stories-with-scenexplain%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Incorporate users' time, date and location into your prompts. Plus contents of other websites, and outputs of other prompts themselves!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 07, 2023 • 8 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Blog-images--13-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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\ No newline at end of file
+</code></pre><p>As you can see from the <code>question</code> field in the example payload above, you can include some example output to help the algorithm in generating the kind of description you desire. And, of course, you don’t <em>have</em> to use JavaScript to build your middleware service - any programming language with an HTTP library can access <a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io">SceneXplain’s API</a>.</p><h2 id="wrapping-up">Wrapping up</h2><p>Do you want to follow in AKIA’s footsteps and use SceneXplain to build vivid product stories from your images and videos? Head over to <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">https://scenex.jina.ai</a> to get started. Or for business use cases, fill in our <a href="https://jina.ai/contact-sales/?ref=jina-ai-gmbh.ghost.io">sales form</a> and we’ll be happy to roll out the red carpet.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fa-magic-carpet-ride-building-vivid-product-stories-with-scenexplain%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="51b0fec8-a517-4015-bf3c-cbcf24a5411c" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="51b0fec8-a517-4015-bf3c-cbcf24a5411c" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Michael Günther</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 16, 2023 • 17 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The sun blazed down on the glistening sidewalks of Sentosa, a symphony of laughter and chatter filling the air. Tourists, decked in their holiday best, meandered through the vibrantmaze of Universal Studios, their faces alight with the joy of a day out in this fantasy land. The click of cameras capturing moments against the backdrop of thrilling rides and colorful parades was omnipresent. Nearby, the enticing aromas of international cuisines wafted through the air, luring guests to indulge in a culinary adventure.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/2911702641285_.pic.jpg" class="kg-image" alt="" width="1440" height="1080" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/2911702641285_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/2911702641285_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/2911702641285_.pic.jpg 1440w" sizes="(min-width: 720px) 720px"></figure><p>In stark contrast, just a stone's throw away, nestled in the heart of this revelry, was the Resorts World Convention Centre. Here, the atmosphere was charged with a different kind of excitement. The halls buzzed not with the sound of holiday-making, but with the fervor of intellectual discourse. Young researchers and seasoned academics, their conference badges swaying gently with each step, engaged in animated discussions about the latest in NLP.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/image-3.png" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/image-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/image-3.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/12/image-3.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>As I walked into this place, the difference was clear. On one side, there was the loud and happy noise of a holiday resort, full of life and excitement. On the other side, there was a serious and busy atmosphere where people talked about NLP , LLMs, ChatGPT, prompting, and Google's new Gemini model. It was like a movie scene – where learning and fun came together in a surprising way.</p><p>In this blog, I'll share some observations of EMNLP 2023 and some of the most interesting papers and posters we discovered at the conference.</p><h2 id="emnlp-2022-to-2023-shifts">EMNLP: 2022 to 2023 Shifts</h2><p>Attending EMNLP 2022 in Abu Dhabi and now looking back at EMNLP 2023, I've observed significant shifts in research focus and conference dynamics. These changes, driven by the swift advancements in AI, paint a vivid picture of our adaptive and forward-looking community. Below, I share a comparison of the two conferences, highlighting how our priorities and discussions have transformed in just a year.</p>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Michael Günther</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 16, 2023 • 17 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The sun blazed down on the glistening sidewalks of Sentosa, a symphony of laughter and chatter filling the air. Tourists, decked in their holiday best, meandered through the vibrantmaze of Universal Studios, their faces alight with the joy of a day out in this fantasy land. The click of cameras capturing moments against the backdrop of thrilling rides and colorful parades was omnipresent. Nearby, the enticing aromas of international cuisines wafted through the air, luring guests to indulge in a culinary adventure.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/2911702641285_.pic.jpg" class="kg-image" alt="" width="1440" height="1080" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/2911702641285_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/2911702641285_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/2911702641285_.pic.jpg 1440w" sizes="(min-width: 720px) 720px"></figure><p>In stark contrast, just a stone's throw away, nestled in the heart of this revelry, was the Resorts World Convention Centre. Here, the atmosphere was charged with a different kind of excitement. The halls buzzed not with the sound of holiday-making, but with the fervor of intellectual discourse. Young researchers and seasoned academics, their conference badges swaying gently with each step, engaged in animated discussions about the latest in NLP.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/image-3.png" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/image-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/image-3.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/12/image-3.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>As I walked into this place, the difference was clear. On one side, there was the loud and happy noise of a holiday resort, full of life and excitement. On the other side, there was a serious and busy atmosphere where people talked about NLP , LLMs, ChatGPT, prompting, and Google's new Gemini model. It was like a movie scene – where learning and fun came together in a surprising way.</p><p>In this blog, I'll share some observations of EMNLP 2023 and some of the most interesting papers and posters we discovered at the conference.</p><h2 id="emnlp-2022-to-2023-shifts">EMNLP: 2022 to 2023 Shifts</h2><p>Attending EMNLP 2022 in Abu Dhabi and now looking back at EMNLP 2023, I've observed significant shifts in research focus and conference dynamics. These changes, driven by the swift advancements in AI, paint a vivid picture of our adaptive and forward-looking community. Below, I share a comparison of the two conferences, highlighting how our priorities and discussions have transformed in just a year.</p>
 
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-        </figure><h3 id="lightning-talks-and-panel-discussion">Lightning Talks and Panel Discussion</h3><p>The BoF session featured lightning talks by renowned researchers like Huiqiang, Hassan, Hwiyeol, Mattia, and Yang Chen. Each speaker brought a unique perspective to the table, sharing their latest findings in embedding research within NLP. The talks sparked an energizing dialogue that transitioned into a thought-provoking panel discussion.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.33386 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3041702708673_.pic.jpg" width="1702" height="1276" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3041702708673_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3041702708673_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3041702708673_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/3041702708673_.pic.jpg 1702w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33386 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3031702708669_.pic.jpg" width="1702" height="1276" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3031702708669_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3031702708669_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3031702708669_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/3031702708669_.pic.jpg 1702w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33386 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3061702708681_.pic.jpg" width="1702" height="1276" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3061702708681_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3061702708681_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3061702708681_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/3061702708681_.pic.jpg 1702w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.33386 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3051702708676_.pic-1.jpg" width="1702" height="1276" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3051702708676_.pic-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3051702708676_.pic-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3051702708676_.pic-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/3051702708676_.pic-1.jpg 1702w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33386 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3081702708695_.pic.jpg" width="1702" height="1276" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3081702708695_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3081702708695_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3081702708695_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/3081702708695_.pic.jpg 1702w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>The panel, graced by Sebastian Ruder, Nicola Cancedda, Chia Ying Lee, Michael Günther, and Han Xiao, delved deep into the intricacies of embedding technologies. They covered a breadth of topics, from the evolution of embeddings to their future in a world increasingly dominated by Generative AI and Large Language Models (LLMs).</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3011702708364_.pic.jpg" class="kg-image" alt="" width="720" height="541" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3011702708364_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/3011702708364_.pic.jpg 720w" sizes="(min-width: 720px) 720px"></figure><h3 id="key-takeaways-from-the-panel">Key Takeaways from the Panel</h3><ol><li><strong>Diverse Perspectives on Embeddings:</strong><br>The panelists introduced themselves and their work with various embeddings, discussing the common threads and divergences they've observed. They emphasized the nuanced differences in how embeddings behave depending on their design and application contexts.</li><li><strong>The Relevance of Embeddings Amidst Generative AI:</strong><br>With 2023's spotlight on LLMs, the panelists reflected on the enduring importance of embeddings. They highlighted that despite the LLM trend, embeddings retain a crucial role in understanding and processing language at a more granular level.</li><li><strong>Context Length in Embeddings vs. LLMs:</strong><br>A curious observation was the disparity in context length expansion between LLMs and embedding models. The panelists shed light on the technical and practical constraints that currently limit the context window in embedding models.</li><li><strong>Search and Generation:</strong><br>Addressing the assertion that 'search is an overfitted generation, and generation is an underfitted search,' the panelists shared mixed views, sparking a lively debate on the interplay between search functions and generative capabilities.</li><li><strong>Future of RAG and Agent Models:</strong><br>Looking towards EMNLP 2024, the conversation turned to the prospective challenges and developments in Retrieval Augmented Generation (RAG) and agent models. The panelists hinted at their vision for the future integration of embeddings within these applications, recognizing the pivotal role they will continue to play.</li></ol><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.750751 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3101702709471_.pic_hd-1.jpg" width="2000" height="2664" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3101702709471_.pic_hd-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3101702709471_.pic_hd-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3101702709471_.pic_hd-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/12/3101702709471_.pic_hd-1.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.750751 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3091702709471_.pic_hd.jpg" width="2000" height="2664" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3091702709471_.pic_hd.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3091702709471_.pic_hd.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3091702709471_.pic_hd.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/12/3091702709471_.pic_hd.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h2 id="summary">Summary</h2><p>Wrapping up EMNLP 2023, I'm buzzing with ideas and energized by the community's shared passion for pushing the boundaries of NLP. Our Embeddings BoF session was a hit – the engagement and insights made it a highlight for me.</p><p>Looking to get hands-on with the future of embeddings? We are hiring! We're all about diving deep into long-context, multilingual, and multimodal embeddings. So, if you're up for the challenge, check out the open roles here and maybe I'll see you at our Berlin, Shenzhen, or Beijing office.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/internship/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Intern Program</div><div class="kg-bookmark-description">Worldwide call for students: Intern in research, engineering, marketing, sales and more to pioneer multimodal AI together.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/banner-internship.png" alt=""></div></a></figure><p>Can't wait to see what we'll cook up by EMNLP 2024 in Miami. Until then, keep innovating, keep questioning, and let's keep the conversations going!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fa-tale-of-two-worlds-emnlp-2023-at-sentosa%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-ap-virtual-ticket-giveaway-for-pycon-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina AI Virtual Ticket Giveaway for PyCon 2023 Online</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina AI's giving away PyCon US Online passes. Deadline April 10.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/avatar.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jocelyn Matthews</div><div class="q-item__label q-item__label--caption text-caption">April 03, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/virtual-ticket-promo.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+        </figure><h3 id="lightning-talks-and-panel-discussion">Lightning Talks and Panel Discussion</h3><p>The BoF session featured lightning talks by renowned researchers like Huiqiang, Hassan, Hwiyeol, Mattia, and Yang Chen. Each speaker brought a unique perspective to the table, sharing their latest findings in embedding research within NLP. The talks sparked an energizing dialogue that transitioned into a thought-provoking panel discussion.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.33386 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3041702708673_.pic.jpg" width="1702" height="1276" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3041702708673_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3041702708673_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3041702708673_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/3041702708673_.pic.jpg 1702w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33386 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3031702708669_.pic.jpg" width="1702" height="1276" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3031702708669_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3031702708669_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3031702708669_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/3031702708669_.pic.jpg 1702w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33386 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3061702708681_.pic.jpg" width="1702" height="1276" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3061702708681_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3061702708681_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3061702708681_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/3061702708681_.pic.jpg 1702w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.33386 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3051702708676_.pic-1.jpg" width="1702" height="1276" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3051702708676_.pic-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3051702708676_.pic-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3051702708676_.pic-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/3051702708676_.pic-1.jpg 1702w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33386 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3081702708695_.pic.jpg" width="1702" height="1276" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3081702708695_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3081702708695_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3081702708695_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/3081702708695_.pic.jpg 1702w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>The panel, graced by Sebastian Ruder, Nicola Cancedda, Chia Ying Lee, Michael Günther, and Han Xiao, delved deep into the intricacies of embedding technologies. They covered a breadth of topics, from the evolution of embeddings to their future in a world increasingly dominated by Generative AI and Large Language Models (LLMs).</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3011702708364_.pic.jpg" class="kg-image" alt="" width="720" height="541" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3011702708364_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/3011702708364_.pic.jpg 720w" sizes="(min-width: 720px) 720px"></figure><h3 id="key-takeaways-from-the-panel">Key Takeaways from the Panel</h3><ol><li><strong>Diverse Perspectives on Embeddings:</strong><br>The panelists introduced themselves and their work with various embeddings, discussing the common threads and divergences they've observed. They emphasized the nuanced differences in how embeddings behave depending on their design and application contexts.</li><li><strong>The Relevance of Embeddings Amidst Generative AI:</strong><br>With 2023's spotlight on LLMs, the panelists reflected on the enduring importance of embeddings. They highlighted that despite the LLM trend, embeddings retain a crucial role in understanding and processing language at a more granular level.</li><li><strong>Context Length in Embeddings vs. LLMs:</strong><br>A curious observation was the disparity in context length expansion between LLMs and embedding models. The panelists shed light on the technical and practical constraints that currently limit the context window in embedding models.</li><li><strong>Search and Generation:</strong><br>Addressing the assertion that 'search is an overfitted generation, and generation is an underfitted search,' the panelists shared mixed views, sparking a lively debate on the interplay between search functions and generative capabilities.</li><li><strong>Future of RAG and Agent Models:</strong><br>Looking towards EMNLP 2024, the conversation turned to the prospective challenges and developments in Retrieval Augmented Generation (RAG) and agent models. The panelists hinted at their vision for the future integration of embeddings within these applications, recognizing the pivotal role they will continue to play.</li></ol><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.750751 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3101702709471_.pic_hd-1.jpg" width="2000" height="2664" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3101702709471_.pic_hd-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3101702709471_.pic_hd-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3101702709471_.pic_hd-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/12/3101702709471_.pic_hd-1.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.750751 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/3091702709471_.pic_hd.jpg" width="2000" height="2664" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/3091702709471_.pic_hd.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/3091702709471_.pic_hd.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/3091702709471_.pic_hd.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/12/3091702709471_.pic_hd.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h2 id="summary">Summary</h2><p>Wrapping up EMNLP 2023, I'm buzzing with ideas and energized by the community's shared passion for pushing the boundaries of NLP. Our Embeddings BoF session was a hit – the engagement and insights made it a highlight for me.</p><p>Looking to get hands-on with the future of embeddings? We are hiring! We're all about diving deep into long-context, multilingual, and multimodal embeddings. So, if you're up for the challenge, check out the open roles here and maybe I'll see you at our Berlin, Shenzhen, or Beijing office.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/internship/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Intern Program</div><div class="kg-bookmark-description">Worldwide call for students: Intern in research, engineering, marketing, sales and more to pioneer multimodal AI together.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/banner-internship.png" alt=""></div></a></figure><p>Can't wait to see what we'll cook up by EMNLP 2024 in Miami. Until then, keep innovating, keep questioning, and let's keep the conversations going!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fa-tale-of-two-worlds-emnlp-2023-at-sentosa%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-ap-virtual-ticket-giveaway-for-pycon-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina AI Virtual Ticket Giveaway for PyCon 2023 Online</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina AI's giving away PyCon US Online passes. Deadline April 10.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/avatar.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jocelyn Matthews</div><div class="q-item__label q-item__label--caption text-caption">April 03, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/virtual-ticket-promo.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>AgentChain: Chain together models to perform complex tasks</title><meta charset="utf-8"><meta name="title" content="AgentChain: Chain together models to perform complex tasks"><meta name="description" content="AgentChain uses LLMs for planning and orchestrating multiple Agents or Large Models for accomplishing sophisticated tasks. AgentChain is fully multimodal: it accepts text, image, audio, tabular data"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/agentchain-chain-together-models-to-perform-complex-tasks"><meta property="og:title" content="AgentChain: Chain together models to perform complex tasks"><meta property="og:description" content="AgentChain uses LLMs for planning and orchestrating multiple Agents or Large Models for accomplishing sophisticated tasks. AgentChain is fully multimodal: it accepts text, image, audio, tabular data"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Agentchain-banner.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/agentchain-chain-together-models-to-perform-complex-tasks"><meta property="twitter:title" content="AgentChain: Chain together models to perform complex tasks"><meta property="twitter:description" content="AgentChain uses LLMs for planning and orchestrating multiple Agents or Large Models for accomplishing sophisticated tasks. AgentChain is fully multimodal: it accepts text, image, audio, tabular data"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Agentchain-banner.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">AgentChain: Chain together models to perform complex tasks</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">AgentChain uses LLMs for planning and orchestrating multiple Agents or Large Models for accomplishing sophisticated tasks. AgentChain is fully multimodal: it accepts text, image, audio, tabular data</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/1604136227948.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alaeddine Abdessalem, Aziz Belaweid</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 15, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/03/Demo1--sound-.mp4" poster="https://img.spacergif.org/v1/1280x720/0a/spacer.png" width="1280" height="720" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/03/media-thumbnail-ember143.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p><a href="https://github.com/jina-ai/agentchain?ref=jina-ai-gmbh.ghost.io">AgentChain</a> uses Large Language Models (LLMs) for planning and orchestrating multiple Agents or Large Models (LMs) for accomplishing sophisticated tasks. AgentChain is fully multimodal: it accepts text, image, audio, tabular data as input and output.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/agentchain?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/agentchain: Use Large Language Models (LLMs) for reasoning, and orchestrate multiple large models for accomplishing sophisticated tasks</div><div class="kg-bookmark-description">Use Large Language Models (LLMs) for reasoning, and orchestrate multiple large models for accomplishing sophisticated tasks - GitHub - jina-ai/agentchain: Use Large Language Models (LLMs) for reaso…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/613456719/62506f53-c7fd-4dfe-9ff6-303eef282c92" alt=""></div></a></figure><ul><li>🧠 <strong>LLMs as the brain:</strong> AgentChain leverages state-of-the-art Large Language Models to provide users with the ability to plan and make decisions based on natural language inputs. This feature makes AgentChain a versatile tool for a wide range of applications, such as task execution given natural language instructions, data understanding, and data generation.</li><li>🌟 <strong>Fully Multimodal IO:</strong> AgentChain is fully multimodal, accepting input and output from various modalities, such as text, image, audio, or video (coming soon). This feature makes AgentChain a versatile tool for a wide range of applications, such as computer vision, speech recognition, and transitioning from one modality to another.</li><li>🤝 <strong>Orchestrate Versatile Agents:</strong> AgentChain can orchestrate multiple agents to perform complex tasks. Using composability and hierarchical structuring of tools AgentChain can choose inelligently which tools to use and when for a certain task. This feature makes AgentChain a powerful tool for projects that require complex combination of tools.</li><li>🔧 <strong>Customizable for Ad-hoc Needs:</strong> AgentChain can be customized to fit specific project requirements, making it a versatile tool for a wide range of applications. Specific requirements can be met by enhancing capabilities with new agents (and distributed architecture coming soon).</li></ul><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/03/Demo2--sound-.mp4" poster="https://img.spacergif.org/v1/1280x720/0a/spacer.png" width="1280" height="720" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/03/media-thumbnail-ember164.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="agents-in-agentchain">Agents in AgentChain</h2><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/--2023-03-15-12.12.21.png" class="kg-image" alt="" width="2000" height="1102" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/--2023-03-15-12.12.21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/--2023-03-15-12.12.21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/03/--2023-03-15-12.12.21.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/03/--2023-03-15-12.12.21.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>AgentChain is a sophisticated system with the goal of solving general problems. It can orchestrate multiple agents to accomplish sub-problems. These agents are organized into different groups, each with their unique set of capabilities and functionalities. Here are some of the agent groups in AgentChain:</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/03/Demo3--sound-.mp4" poster="https://img.spacergif.org/v1/1280x720/0a/spacer.png" width="1280" height="720" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/03/media-thumbnail-ember181.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h3 id="searchagents">SearchAgents</h3><p>The <code>SearchAgents</code> group is responsible for gathering information from various sources, including search engines, online databases, and APIs. The agents in this group are highly skilled at retrieving up-to-date world knowledge and information. Some examples of agents in this group include the <code>Google Search API</code>, <code>Bing API</code>, <code>Wikipedia API</code>, and <code>Serp</code>.</p><h3 id="commsagents">CommsAgents</h3><p>The <code>CommsAgents</code> group is responsible for handling communication between different parties, such as sending emails, making phone calls, or messaging via various platforms. The agents in this group can integrate with a wide range of platforms. Some examples of agents in this group include <code>TwilioCaller</code>, <code>TwilioEmailWriter</code>, <code>TwilioMessenger</code> and <code>Slack</code>.</p><h3 id="toolsagents">ToolsAgents</h3><p>The <code>ToolsAgents</code> group is responsible for performing various computational tasks, such as performing calculations, running scripts, or executing commands. The agents in this group can work with a wide range of programming languages and tools. Some examples of agents in this group include <code>Math</code>, <code>Python REPL</code>, and <code>Terminal</code>.</p><h3 id="multimodalagents">MultiModalAgents</h3><p>The <code>MultiModalAgents</code> group is responsible for handling input and output from various modalities, such as text, image, audio, or video (coming soon). The agents in this group can process and understand different modalities. Some examples of agents in this group include <code>OpenAI Whisper</code>, <code>Blip2</code>, <code>Coqui</code>, and <code>StableDiffusion</code>.</p><h3 id="imageagents">ImageAgents</h3><p>The <code>ImageAgents</code> group is responsible for processing and manipulating images, such as enhancing image quality, object detection, or image recognition. The agents in this group can perform complex operations on them. Some examples of agents in this group include <code>Upscaler</code>, <code>ControlNet</code> and <code>YOLO</code>.</p><h3 id="dbagents">DBAgents</h3><p>The <code>DBAgents</code> group is responsible for adding and fetching data from your database, such as getting metrics or aggregations from your database. The agents in this group will interact with databases and enrich other agents with your database information. Some examples of agents in this group include <code>SQL</code>, <code>MongoDB</code>, <code>ElasticSearch</code>, <code>Qrant</code> and <code>Notion</code>.</p><h2 id="get-started">Get started</h2><ol><li>Clone the <a href="https://github.com/jina-ai/agentchain?ref=jina-ai-gmbh.ghost.io">AgentChain repo</a></li><li>Install requirements: <code>pip install -r requirements.txt</code></li><li>Download model checkpoints: <code>bash download.sh</code></li><li>Depending on the agents you need in-place, make sure to export environment variables:</li></ol><pre><code class="language-shell hljs">OPENAI_API_KEY={YOUR_OPENAI_API_KEY} # mandatory since the LLM is central in this application
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">AgentChain uses LLMs for planning and orchestrating multiple Agents or Large Models for accomplishing sophisticated tasks. AgentChain is fully multimodal: it accepts text, image, audio, tabular data</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/1604136227948.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alaeddine Abdessalem, Aziz Belaweid</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 15, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/03/Demo1--sound-.mp4" poster="https://img.spacergif.org/v1/1280x720/0a/spacer.png" width="1280" height="720" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/03/media-thumbnail-ember143.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p><a href="https://github.com/jina-ai/agentchain?ref=jina-ai-gmbh.ghost.io">AgentChain</a> uses Large Language Models (LLMs) for planning and orchestrating multiple Agents or Large Models (LMs) for accomplishing sophisticated tasks. AgentChain is fully multimodal: it accepts text, image, audio, tabular data as input and output.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/agentchain?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/agentchain: Use Large Language Models (LLMs) for reasoning, and orchestrate multiple large models for accomplishing sophisticated tasks</div><div class="kg-bookmark-description">Use Large Language Models (LLMs) for reasoning, and orchestrate multiple large models for accomplishing sophisticated tasks - GitHub - jina-ai/agentchain: Use Large Language Models (LLMs) for reaso…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/613456719/62506f53-c7fd-4dfe-9ff6-303eef282c92" alt=""></div></a></figure><ul><li>🧠 <strong>LLMs as the brain:</strong> AgentChain leverages state-of-the-art Large Language Models to provide users with the ability to plan and make decisions based on natural language inputs. This feature makes AgentChain a versatile tool for a wide range of applications, such as task execution given natural language instructions, data understanding, and data generation.</li><li>🌟 <strong>Fully Multimodal IO:</strong> AgentChain is fully multimodal, accepting input and output from various modalities, such as text, image, audio, or video (coming soon). This feature makes AgentChain a versatile tool for a wide range of applications, such as computer vision, speech recognition, and transitioning from one modality to another.</li><li>🤝 <strong>Orchestrate Versatile Agents:</strong> AgentChain can orchestrate multiple agents to perform complex tasks. Using composability and hierarchical structuring of tools AgentChain can choose inelligently which tools to use and when for a certain task. This feature makes AgentChain a powerful tool for projects that require complex combination of tools.</li><li>🔧 <strong>Customizable for Ad-hoc Needs:</strong> AgentChain can be customized to fit specific project requirements, making it a versatile tool for a wide range of applications. Specific requirements can be met by enhancing capabilities with new agents (and distributed architecture coming soon).</li></ul><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/03/Demo2--sound-.mp4" poster="https://img.spacergif.org/v1/1280x720/0a/spacer.png" width="1280" height="720" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/03/media-thumbnail-ember164.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="agents-in-agentchain">Agents in AgentChain</h2><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/--2023-03-15-12.12.21.png" class="kg-image" alt="" width="2000" height="1102" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/--2023-03-15-12.12.21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/--2023-03-15-12.12.21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/03/--2023-03-15-12.12.21.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/03/--2023-03-15-12.12.21.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>AgentChain is a sophisticated system with the goal of solving general problems. It can orchestrate multiple agents to accomplish sub-problems. These agents are organized into different groups, each with their unique set of capabilities and functionalities. Here are some of the agent groups in AgentChain:</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/03/Demo3--sound-.mp4" poster="https://img.spacergif.org/v1/1280x720/0a/spacer.png" width="1280" height="720" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/03/media-thumbnail-ember181.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h3 id="searchagents">SearchAgents</h3><p>The <code>SearchAgents</code> group is responsible for gathering information from various sources, including search engines, online databases, and APIs. The agents in this group are highly skilled at retrieving up-to-date world knowledge and information. Some examples of agents in this group include the <code>Google Search API</code>, <code>Bing API</code>, <code>Wikipedia API</code>, and <code>Serp</code>.</p><h3 id="commsagents">CommsAgents</h3><p>The <code>CommsAgents</code> group is responsible for handling communication between different parties, such as sending emails, making phone calls, or messaging via various platforms. The agents in this group can integrate with a wide range of platforms. Some examples of agents in this group include <code>TwilioCaller</code>, <code>TwilioEmailWriter</code>, <code>TwilioMessenger</code> and <code>Slack</code>.</p><h3 id="toolsagents">ToolsAgents</h3><p>The <code>ToolsAgents</code> group is responsible for performing various computational tasks, such as performing calculations, running scripts, or executing commands. The agents in this group can work with a wide range of programming languages and tools. Some examples of agents in this group include <code>Math</code>, <code>Python REPL</code>, and <code>Terminal</code>.</p><h3 id="multimodalagents">MultiModalAgents</h3><p>The <code>MultiModalAgents</code> group is responsible for handling input and output from various modalities, such as text, image, audio, or video (coming soon). The agents in this group can process and understand different modalities. Some examples of agents in this group include <code>OpenAI Whisper</code>, <code>Blip2</code>, <code>Coqui</code>, and <code>StableDiffusion</code>.</p><h3 id="imageagents">ImageAgents</h3><p>The <code>ImageAgents</code> group is responsible for processing and manipulating images, such as enhancing image quality, object detection, or image recognition. The agents in this group can perform complex operations on them. Some examples of agents in this group include <code>Upscaler</code>, <code>ControlNet</code> and <code>YOLO</code>.</p><h3 id="dbagents">DBAgents</h3><p>The <code>DBAgents</code> group is responsible for adding and fetching data from your database, such as getting metrics or aggregations from your database. The agents in this group will interact with databases and enrich other agents with your database information. Some examples of agents in this group include <code>SQL</code>, <code>MongoDB</code>, <code>ElasticSearch</code>, <code>Qrant</code> and <code>Notion</code>.</p><h2 id="get-started">Get started</h2><ol><li>Clone the <a href="https://github.com/jina-ai/agentchain?ref=jina-ai-gmbh.ghost.io">AgentChain repo</a></li><li>Install requirements: <code>pip install -r requirements.txt</code></li><li>Download model checkpoints: <code>bash download.sh</code></li><li>Depending on the agents you need in-place, make sure to export environment variables:</li></ol><pre><code class="language-shell">OPENAI_API_KEY={YOUR_OPENAI_API_KEY} # mandatory since the LLM is central in this application
 SERPAPI_API_KEY={YOUR_SERPAPI_API_KEY}  # make sure to include a serp API key in case you need the agent to be able to search the web
-<span class="hljs-meta prompt_">
-# </span><span class="language-bash">These environment variables are needed <span class="hljs-keyword">in</span> <span class="hljs-keyword">case</span> you want the agent to be able to make phone calls</span>
+
+# These environment variables are needed in case you want the agent to be able to make phone calls
 AWS_ACCESS_KEY_ID={YOUR_AWS_ACCESS_KEY_ID}
 AWS_SECRET_ACCESS_KEY={YOUR_AWS_SECRET_ACCESS_KEY}
 TWILIO_ACCOUNT_SID={YOUR_TWILIO_ACCOUNT_SID}
 TWILIO_AUTH_TOKEN={YOUR_TWILIO_AUTH_TOKEN}
-AWS_S3_BUCKET_NAME={YOUR_AWS_S3_BUCKET_NAME} # make sure to create an S3 bucket with public access</code></pre><ol><li>Install <code>ffmpeg</code> library (needed for whisper): <code>sudo apt update &amp;&amp; sudo apt install ffmpeg</code> (Ubuntu command)</li><li>Run the main script: <code>python main.py</code></li></ol><h2 id="visit-the-repo-now">Visit the repo now!</h2><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/agentchain?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/agentchain: Use Large Language Models (LLMs) for reasoning, and orchestrate multiple large models for accomplishing sophisticated tasks</div><div class="kg-bookmark-description">Use Large Language Models (LLMs) for reasoning, and orchestrate multiple large models for accomplishing sophisticated tasks - GitHub - jina-ai/agentchain: Use Large Language Models (LLMs) for reaso…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/613456719/62506f53-c7fd-4dfe-9ff6-303eef282c92" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fagentchain-chain-together-models-to-perform-complex-tasks%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+AWS_S3_BUCKET_NAME={YOUR_AWS_S3_BUCKET_NAME} # make sure to create an S3 bucket with public access</code></pre><ol><li>Install <code>ffmpeg</code> library (needed for whisper): <code>sudo apt update &amp;&amp; sudo apt install ffmpeg</code> (Ubuntu command)</li><li>Run the main script: <code>python main.py</code></li></ol><h2 id="visit-the-repo-now">Visit the repo now!</h2><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/agentchain?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/agentchain: Use Large Language Models (LLMs) for reasoning, and orchestrate multiple large models for accomplishing sophisticated tasks</div><div class="kg-bookmark-description">Use Large Language Models (LLMs) for reasoning, and orchestrate multiple large models for accomplishing sophisticated tasks - GitHub - jina-ai/agentchain: Use Large Language Models (LLMs) for reaso…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/613456719/62506f53-c7fd-4dfe-9ff6-303eef282c92" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fagentchain-chain-together-models-to-perform-complex-tasks%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>How Much Do We Get by Finetuning CLIP?</title><meta charset="utf-8"><meta name="title" content="How Much Do We Get by Finetuning CLIP?"><meta name="description" content="Jina AI Finetuner can bring performance improvements of up to 63% to pre-trained CLIP models. Here is how we did that."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/applying-jina-ai-finetuner-to-clip-less-data-smaller-models-higher-performance"><meta property="og:title" content="How Much Do We Get by Finetuning CLIP?"><meta property="og:description" content="Jina AI Finetuner can bring performance improvements of up to 63% to pre-trained CLIP models. Here is how we did that."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--12-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/applying-jina-ai-finetuner-to-clip-less-data-smaller-models-higher-performance"><meta property="twitter:title" content="How Much Do We Get by Finetuning CLIP?"><meta property="twitter:description" content="Jina AI Finetuner can bring performance improvements of up to 63% to pre-trained CLIP models. Here is how we did that."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--12-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How Much Do We Get by Finetuning CLIP?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI Finetuner can bring performance improvements of up to 63% to pre-trained CLIP models. Here is how we did that.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 93.2813%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/4B483B29-E306-402B-8635-64866C458406.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Bo Wang, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 27, 2022 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Large neural network models trained on enormous datasets have proven capable of amazing things that only a few years ago were considered very hard problems in artificial intelligence. For example, correctly labeling pictures of cats and kangaroos was considered a very hard problem until recently, but now we have good solutions using large neural networks.</p><p>However, these models are pre-trained with broad categories of data. Given some specific task, their performance is often disappointing.</p><p><strong>Jina AI Finetuner improves the performance of pre-trained models by adding new training data that better represents your specific use-cases.</strong><em> </em>Finetuner simplifies fine-tuning and makes it faster and more effective by streamlining the workflow and handling all the operational complexity and physical infrastructure in the Jina AI Cloud.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>We will apply Finetuner to OpenAI's CLIP model and use the recently released <a href="https://github.com/LAION-AI/CLIP_benchmark?ref=jina-ai-gmbh.ghost.io">CLIP Benchmark</a> suite from <a href="https://laion.ai/?ref=jina-ai-gmbh.ghost.io">LAION AI</a> to evaluate performance. We will show that <strong>Finetuner robustly improves performance for text-to-image search over the pre-trained models by up to 63%</strong>, when Finetuner is given data specific to some use-case.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/LAION-AI/CLIP_benchmark?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - LAION-AI/CLIP_benchmark: CLIP-like model evaluation</div><div class="kg-bookmark-description">CLIP-like model evaluation. Contribute to LAION-AI/CLIP_benchmark development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">LAION-AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/5de921ad1f4030088f441890691662aa6f74c03201d519e096dd052867c9da03/LAION-AI/CLIP_benchmark" alt=""></div></a></figure><h1 id="clip-for-image-search">CLIP for Image Search</h1><p><a href="https://openai.com/blog/clip/?ref=jina-ai-gmbh.ghost.io">CLIP</a> was introduced by OpenAI in 2021 as a neural network architecture for jointly training representations of images with representations of descriptive texts. It consists of two networks — an image encoder and a text encoder — and pre-trains them with pairs of images and texts from a dataset of 400 million images with captions drawn from publicly available sources on the Internet. The separate text encoder and image encoder are based on existing architectures for addressing the two media types separately. The main innovation of CLIP is to join the two encoders together at training time.</p><p>The results is a system in which, for example, the image encoder will translate a picture of a dog into a vector close to the vector that the text encoder produces for the word “dog”. This means we can search for pictures that match the text "dog" by looking for images that have nearby vector representations.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/dogs-and-cats-and-cosines-1.png" class="kg-image" alt="" width="1031" height="979" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/dogs-and-cats-and-cosines-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/dogs-and-cats-and-cosines-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/dogs-and-cats-and-cosines-1.png 1031w" sizes="(min-width: 720px) 720px"><figcaption>A highly schematized example of CLIP-produced vector embeddings. We would expect the vector embedding for the text “photo of a dog” to have much higher cosines with the vector embeddings for pictures of dogs than for pictures of cats.</figcaption></figure><p>Because of the very large and diverse image dataset used to train CLIP, it is a good performer in general purpose text-to-image search without any further training.</p><h1 id="fine-tuning-and-clip-benchmark">Fine-tuning and CLIP Benchmark</h1><p>We used three models for benchmarking, all available via <a href="https://github.com/mlfoundations/open_clip?ref=jina-ai-gmbh.ghost.io">OpenCLIP</a>:</p><table>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How Much Do We Get by Finetuning CLIP?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI Finetuner can bring performance improvements of up to 63% to pre-trained CLIP models. Here is how we did that.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 93.2813%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/4B483B29-E306-402B-8635-64866C458406.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Bo Wang, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 27, 2022 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Large neural network models trained on enormous datasets have proven capable of amazing things that only a few years ago were considered very hard problems in artificial intelligence. For example, correctly labeling pictures of cats and kangaroos was considered a very hard problem until recently, but now we have good solutions using large neural networks.</p><p>However, these models are pre-trained with broad categories of data. Given some specific task, their performance is often disappointing.</p><p><strong>Jina AI Finetuner improves the performance of pre-trained models by adding new training data that better represents your specific use-cases.</strong><em> </em>Finetuner simplifies fine-tuning and makes it faster and more effective by streamlining the workflow and handling all the operational complexity and physical infrastructure in the Jina AI Cloud.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>We will apply Finetuner to OpenAI's CLIP model and use the recently released <a href="https://github.com/LAION-AI/CLIP_benchmark?ref=jina-ai-gmbh.ghost.io">CLIP Benchmark</a> suite from <a href="https://laion.ai/?ref=jina-ai-gmbh.ghost.io">LAION AI</a> to evaluate performance. We will show that <strong>Finetuner robustly improves performance for text-to-image search over the pre-trained models by up to 63%</strong>, when Finetuner is given data specific to some use-case.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/LAION-AI/CLIP_benchmark?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - LAION-AI/CLIP_benchmark: CLIP-like model evaluation</div><div class="kg-bookmark-description">CLIP-like model evaluation. Contribute to LAION-AI/CLIP_benchmark development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">LAION-AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/5de921ad1f4030088f441890691662aa6f74c03201d519e096dd052867c9da03/LAION-AI/CLIP_benchmark" alt=""></div></a></figure><h1 id="clip-for-image-search">CLIP for Image Search</h1><p><a href="https://openai.com/blog/clip/?ref=jina-ai-gmbh.ghost.io">CLIP</a> was introduced by OpenAI in 2021 as a neural network architecture for jointly training representations of images with representations of descriptive texts. It consists of two networks — an image encoder and a text encoder — and pre-trains them with pairs of images and texts from a dataset of 400 million images with captions drawn from publicly available sources on the Internet. The separate text encoder and image encoder are based on existing architectures for addressing the two media types separately. The main innovation of CLIP is to join the two encoders together at training time.</p><p>The results is a system in which, for example, the image encoder will translate a picture of a dog into a vector close to the vector that the text encoder produces for the word “dog”. This means we can search for pictures that match the text "dog" by looking for images that have nearby vector representations.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/dogs-and-cats-and-cosines-1.png" class="kg-image" alt="" width="1031" height="979" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/dogs-and-cats-and-cosines-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/dogs-and-cats-and-cosines-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/dogs-and-cats-and-cosines-1.png 1031w" sizes="(min-width: 720px) 720px"><figcaption>A highly schematized example of CLIP-produced vector embeddings. We would expect the vector embedding for the text “photo of a dog” to have much higher cosines with the vector embeddings for pictures of dogs than for pictures of cats.</figcaption></figure><p>Because of the very large and diverse image dataset used to train CLIP, it is a good performer in general purpose text-to-image search without any further training.</p><h1 id="fine-tuning-and-clip-benchmark">Fine-tuning and CLIP Benchmark</h1><p>We used three models for benchmarking, all available via <a href="https://github.com/mlfoundations/open_clip?ref=jina-ai-gmbh.ghost.io">OpenCLIP</a>:</p><table>
 <thead>
 <tr>
 <th>model name</th>
@@ -163,4 +163,4 @@
 <td>10.4%</td>
 </tr>
 </tbody>
-</table><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-26.png" class="kg-image" alt="" width="640" height="480" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-26.png 640w"></figure><p><strong>For every model and dataset, there was improvement.</strong></p><p>Finetuner brought the most improvement with those datasets for which the pre-trained CLIP model had the poorest image recall. For the Flickr8k data, we see recall values in the range of 0.5 to 0.65 before fine-tuning, and values of 0.85 and up after fine-tuning, representing a very large 36% to 63% increase in recall.</p><p>For the Flickr30k data, we see much higher recall scores with only pre-training, and much less net improvement: Under 10% for all three models. When the pre-model is already doing very well, there is much less room for improvement. Although Finetuner does less to raise recall scores for this dataset, it still improves all models by a visible amount.</p><p>For the MS-COCO dataset, we see pre-training recall scores only slightly higher than for the Flickr8k dataset, but much less improvement: 7% to 17% depending on the model. MS-COCO, however, is a larger and much more diverse dataset and we should expect, given identical training hyper-parameters, that improvement would be smaller. This is still considerably more improvement than for the Flickr30k dataset.</p><p>Finetuner's impact on image recall scores is positive for every test condition used in CLIP Benchmark. <strong>This finding is robust over different models and datasets.</strong> Furthermore, the amount of improvement matches our intuitions about the effect fine-tuning should have. We see here that effect can be quite large. Going from recall levels of 0.55 to 0.87 is a dramatic increase in quality for a search system. </p><h1 id="summary">Summary </h1><p>We have shown that using Finetuner leads to performance gains, sometimes very large performance gains. </p><p>Fine-tuning is an established technique for improving the performance of large neural network models in specific use-cases. However, the practical complexity of performing fine-tuning can be daunting to IT professionals who do not routinely work with this kind of AI. Finetuner takes care of most of these problems for you via its simple interface.</p><p>Finetuner is not limited to CLIP, and can be used to tune other models including <a href="https://doi.org/10.1109/CVPR.2016.90?ref=jina-ai-gmbh.ghost.io">ResNet</a>, <a href="http://proceedings.mlr.press/v97/tan19a.html?ref=jina-ai-gmbh.ghost.io">EfficientNet</a> and language models like <a href="https://github.com/google-research/bert?ref=jina-ai-gmbh.ghost.io">BERT</a>. See the <a href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io#benchmark">Benchmarks section of the Finetuner README on GitHub</a> for some additional examples.</p><p>Please check out the Finetuner's documentation for more information.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Welcome to Finetuner!</div><div class="kg-bookmark-description">Fine-tuning is an effective way to improve the performance on neural search tasks. However, it is non-trivial for many deep learning engineers. Finetuner makes fine-tuning easier, faster and performant by streamlining the workflow and handling all complexity and infrastructure on the cloud. With ...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://finetuner.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">Finetuner Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://finetuner.jina.ai/_static/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fapplying-jina-ai-finetuner-to-clip-less-data-smaller-models-higher-performance%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+</table><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-26.png" class="kg-image" alt="" width="640" height="480" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-26.png 640w"></figure><p><strong>For every model and dataset, there was improvement.</strong></p><p>Finetuner brought the most improvement with those datasets for which the pre-trained CLIP model had the poorest image recall. For the Flickr8k data, we see recall values in the range of 0.5 to 0.65 before fine-tuning, and values of 0.85 and up after fine-tuning, representing a very large 36% to 63% increase in recall.</p><p>For the Flickr30k data, we see much higher recall scores with only pre-training, and much less net improvement: Under 10% for all three models. When the pre-model is already doing very well, there is much less room for improvement. Although Finetuner does less to raise recall scores for this dataset, it still improves all models by a visible amount.</p><p>For the MS-COCO dataset, we see pre-training recall scores only slightly higher than for the Flickr8k dataset, but much less improvement: 7% to 17% depending on the model. MS-COCO, however, is a larger and much more diverse dataset and we should expect, given identical training hyper-parameters, that improvement would be smaller. This is still considerably more improvement than for the Flickr30k dataset.</p><p>Finetuner's impact on image recall scores is positive for every test condition used in CLIP Benchmark. <strong>This finding is robust over different models and datasets.</strong> Furthermore, the amount of improvement matches our intuitions about the effect fine-tuning should have. We see here that effect can be quite large. Going from recall levels of 0.55 to 0.87 is a dramatic increase in quality for a search system. </p><h1 id="summary">Summary </h1><p>We have shown that using Finetuner leads to performance gains, sometimes very large performance gains. </p><p>Fine-tuning is an established technique for improving the performance of large neural network models in specific use-cases. However, the practical complexity of performing fine-tuning can be daunting to IT professionals who do not routinely work with this kind of AI. Finetuner takes care of most of these problems for you via its simple interface.</p><p>Finetuner is not limited to CLIP, and can be used to tune other models including <a href="https://doi.org/10.1109/CVPR.2016.90?ref=jina-ai-gmbh.ghost.io">ResNet</a>, <a href="http://proceedings.mlr.press/v97/tan19a.html?ref=jina-ai-gmbh.ghost.io">EfficientNet</a> and language models like <a href="https://github.com/google-research/bert?ref=jina-ai-gmbh.ghost.io">BERT</a>. See the <a href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io#benchmark">Benchmarks section of the Finetuner README on GitHub</a> for some additional examples.</p><p>Please check out the Finetuner's documentation for more information.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Welcome to Finetuner!</div><div class="kg-bookmark-description">Fine-tuning is an effective way to improve the performance on neural search tasks. However, it is non-trivial for many deep learning engineers. Finetuner makes fine-tuning easier, faster and performant by streamlining the workflow and handling all complexity and infrastructure on the cloud. With ...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://finetuner.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">Finetuner Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://finetuner.jina.ai/_static/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fapplying-jina-ai-finetuner-to-clip-less-data-smaller-models-higher-performance%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Are you ready for this Jelly? SceneXplain’s new algo kills hallucinations dead</title><meta charset="utf-8"><meta name="title" content="Are you ready for this Jelly? SceneXplain’s new algo kills hallucinations dead"><meta name="description" content="SceneXplain's state-of-the-art Jelly algorithm is more concise, readable and accurate than ever before, while killing hallucinations."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/are-you-ready-for-this-jelly-scenexplains-new-algo-kills-hallucinations-dead"><meta property="og:title" content="Are you ready for this Jelly? SceneXplain’s new algo kills hallucinations dead"><meta property="og:description" content="SceneXplain's state-of-the-art Jelly algorithm is more concise, readable and accurate than ever before, while killing hallucinations."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/image.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/are-you-ready-for-this-jelly-scenexplains-new-algo-kills-hallucinations-dead"><meta property="twitter:title" content="Are you ready for this Jelly? SceneXplain’s new algo kills hallucinations dead"><meta property="twitter:description" content="SceneXplain's state-of-the-art Jelly algorithm is more concise, readable and accurate than ever before, while killing hallucinations."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/image.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 56.044%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/image.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Are you ready for this Jelly? SceneXplain’s new algo kills hallucinations dead</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">SceneXplain's state-of-the-art Jelly algorithm is more concise, readable and accurate than ever before, while killing hallucinations.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 25, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Another month rolls by, and here at Jina AI we’re releasing a new, more refined algorithm for <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a>.</p><p>A while back, we introduced SceneXplain’s “Glide” algorithm, which nailed recognizing multilingual text in images, something other models are now only just introducing:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--1-.png" class="kg-image" alt="" width="447" height="844"></figure><p></p><p>But that was then. This is now. So, what comes next? Fixing hallucination, that’s what.</p><h2 id="what-is-hallucination-in-computer-vision">What is hallucination in computer vision?</h2><p>You may already be familiar with AI hallucination when it comes to LLMs, for example, <a href="https://www.nytimes.com/2023/06/08/nyregion/lawyer-chatgpt-sanctions.html?ref=jina-ai-gmbh.ghost.io">ChatGPT hallucinating papers and sources that don’t exist in reality</a>.</p><blockquote class="kg-blockquote-alt"><strong>"[ChatGPT is an] omniscient, eager-to-please intern who sometimes lies to you"</strong><br>Professor Ethan Mollick of <a href="https://en.wikipedia.org/wiki/Wharton_School_of_the_University_of_Pennsylvania?ref=jina-ai-gmbh.ghost.io">Wharton</a></blockquote><p>Likewise, image generation models (like Midjourney) often hallucinate unwanted details (or unwanted fingers for that matter.)</p><p><a href="https://gagadget.com/en/how-it-works/210102-the-unattainable-pinnacle-of-art-why-does-midjourney-artificial-intelligence-draw-6-fingers-on-hands-and-how/?ref=jina-ai-gmbh.ghost.io">The unattainable pinnacle of art: why does Midjourney artificial intelligence draw 6 fingers on hands and how can it be fixed?</a></p><p>In short, hallucination is AI models generating false information.</p><p>SceneXplain often fell victim to this in our prior algorithms, hallucinating skateboarders, and occasionally Naruto:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--2-.png" class="kg-image" alt="" width="640" height="380" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Untitled--2-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--2-.png 640w"><figcaption><span style="white-space: pre-wrap;">SceneXplain’s Aqua algorithm: In a whimsical and enchanting scene, Totoro and a young girl share an umbrella in the rain. The iconic character from Studio Ghibli's beloved film stands alongside the girl, offering shelter from the downpour. The atmosphere is both heartwarming and magical, as Totoro's presence infuses the moment with a sense of wonder and delight. Meanwhile, </span><b><strong style="white-space: pre-wrap;">Naruto makes a surprising appearance in the rain-soaked setting</strong></b><span style="white-space: pre-wrap;">, adding another layer of intrigue to this captivating tableau. This charming depiction brings together two distinct worlds, bridging the gap between Japanese animation and manga to create an unforgettable moment of friendship and adventure.</span></figcaption></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--3-.png" class="kg-image" alt="" width="446" height="612"></figure><h2 id="what-causes-hallucination-in-computer-vision">What causes hallucination in computer vision?</h2><p>In humans, hallucination is caused by errors in perception, faulty expectations, neurological defects, or maybe just a dose of Scarecrow’s fear gas. In computer vision, it can often come about through issues with training data or the way an image is processed before generation or (in the case of SceneXplain) captioning.</p><h3 id="slicing-and-dicing-the-elephant-in-the-room">Slicing and dicing: the elephant in the room</h3><p>When it comes to image captioning, you often want a high level of detail. A common approach is to slice an image into several pieces, generate a caption for each piece, then merge the captions together into a final description. Sounds like a pretty sensible approach, right? By focusing on each segment and then combining results, we should get a better description overall.</p><p>Except...you ever heard the tale of the blind men and the elephant?</p><blockquote>Six blind men encounter an elephant for the first time and each touches a different part of the animal. One feels the trunk and thinks it's a snake, another touches a leg and believes it's a tree, and so on with the tusk (a spear), ear (a mat), tail (a rope), and side (a wall). Amidst much debate, they all insist they're correct, not realizing they're all describing the same elephant.</blockquote><p>If we want to understand an image by slicing it into different parts we can face exactly the same issue. If we were to draw what the blind men experience, we'd create a picture of a snake wrapped in a blanket next to a tree, along with a bunch of other elements. In short, many <em>elements</em>, but no <em>elephant</em>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/image-2.png" class="kg-image" alt="" width="1170" height="656" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/image-2.png 1170w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Midjourney's interpretation of the blind men's elephant</span></figcaption></figure><p>Likewise, in captioning, let's say we split up one image of three men into several segments. In each segment, there may be some part (arm, leg, side of head) of a different man. When it comes time to combine those segment descriptions (<code>a man's face</code>, <code>a man's leg</code>, <code>a man's arm</code>, etc), how many men would be seen? Are these all part of one man? Are they each a part of different men? If so, how many? And without the context of the rest of the image, just what is that patch of fuzz in the top-left section?</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/man-grid.png" class="kg-image" alt="" width="600" height="853" srcset="https://jina-ai-gmbh.ghost.io/content/images/2023/10/man-grid.png 600w"><figcaption><span style="white-space: pre-wrap;">Adapted from Pexels.com (</span><a href="https://www.pexels.com/photo/man-in-white-dress-shirt-holding-suit-jacket-1043474/?ref=jina-ai-gmbh.ghost.io"><span style="white-space: pre-wrap;">https://www.pexels.com/photo/man-in-white-dress-shirt-holding-suit-jacket-1043474/</span></a><span style="white-space: pre-wrap;">)</span></figcaption></figure><p>If the model splits everything up too much, it can hallucinate things that just aren't there. If it doesn't split things, the overall description may be too vague to be useful.</p><h3 id="ambiguity-thats-a-cutepuppy">Ambiguity: That's a cute...puppy?</h3><p>Many models rely on multimodality - that is translating text-to-image (like using a prompt to generate an image in Midjourney) or image-to-text (like generating a caption from an image in SceneXplain). Ambiguous text or images can therefore cause problems.</p><p>Take the phrase "salmon swimming in a river." Most humans would imagine fish swimming up a river. AI on the other hand can see some ambiguity:</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://www.reddit.com/r/technicallythetruth/comments/y26t6x/ai_asked_to_draw_salmon_swimming_in_river/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/image-1.png" class="kg-image" alt="" width="750" height="426" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/image-1.png 750w" sizes="(min-width: 720px) 720px"></a><figcaption><span style="white-space: pre-wrap;">Via Reddit</span></figcaption></figure><p>Likewise, sometimes images can be ambiguous:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--7-.png" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Untitled--7-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/Untitled--7-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/10/Untitled--7-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--7-.png 2048w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Duck or rabbit?</span></figcaption></figure><p>This isn't just applicable to traditional optical illusions or Rorschach tests. A <a href="https://www.insider.com/viral-puppy-looks-like-mix-between-dog-and-cat-2020-3?ref=jina-ai-gmbh.ghost.io">cute little fuzzball</a> could be a puppy OR a kitten. Running it by the model just once may result in a misclassification. Several tries may be needed to consistently see that puppy as a puppy.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--8-.png" class="kg-image" alt="" width="700" height="525" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Untitled--8-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--8-.png 700w"><figcaption><span style="white-space: pre-wrap;">Dog or cat? (Via Business Insider)</span></figcaption></figure><p>And let’s not even get started on <a href="https://en.m.wikipedia.org/wiki/The_dress?ref=jina-ai-gmbh.ghost.io">that damn dress</a>.</p><h3 id="ocr-occasionally-crappy-recognition">OCR: Occasionally Crappy Recognition</h3><p>If you've got this far in the article, you probably think you're a pretty hot reader. Go on, give yourself a big pat on the back. You should really share some of your knowledge on <a href="http://expertsexchange.com/?ref=jina-ai-gmbh.ghost.io">expertsexchange.com</a>. It's a site I use every day, sometimes several times. To exchange information with other experts.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">If you don't see why I'm bringing this up, re-read that URL</div></div><p>It's not just a lack of clear word spacing that can trip you up. Take keming (uh, kerning) for example.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text"> In typography, kerning is the process of adjusting the spacing between characters in a proportional font, usually to achieve a visually pleasing result.</div></div><p>Bad kerning can have interesting results:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://cdn.mos.cms.futurecdn.net/9cdc770ee6d32d569f4dfa1d7e44029e-1200-80.jpg.webp" class="kg-image" alt="10 flickering lights"><figcaption><span style="white-space: pre-wrap;">10 flickering lights</span></figcaption></figure><p>If these things are ambiguous to readers like you, just imagine how confused an AI model can get!</p><h2 id="how-does-scenexplain-fix-hallucination">How does SceneXplain fix hallucination?</h2><p>SceneXplain’s new Jelly algorithm aims to eliminate these hallucinations, using the following methods:</p><ol><li>A simplified processing pipeline. Our prior algorithms had much more complex pipelines, meaning more places for things to go wrong. Jelly pares this back with a new end-to-end approach to image labeling that produces detailed image captions with much fewer hallucinations.</li><li>Self-consistency: We’ve implemented an advanced prompt technique (self-consistency) to get the most consistent and accurate caption for any given image.</li><li>OCR improvements: We've improved Jelly’s text recognition capabilities which leads to fewer hallucinations and better captions.</li></ol><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Hallucination is seeing things that don’t exist. Just like people “see” ghosts. Since Jelly removes hallucinations you could call it the ultimate “Ghostbuster”. Cue the theme music.</div></div><h2 id="before-and-after">Before and After</h2><p>As you can see from the examples below:</p><ul><li>Glide suffers from way more hallucinations (highlighted in bold) than Jelly</li><li>Jelly provides more readable captions, lacking the elaborate flowery language of Glide</li></ul><h3 id="les-choristes">Les Choristes</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--4-.png" class="kg-image" alt="" width="764" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Untitled--4-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--4-.png 764w" sizes="(min-width: 720px) 720px"></figure><p><strong>Glide:</strong></p><blockquote>The image showcases a poster for a movie called "Les Choristes." The poster features the title "LES CHORISTES" prominently displayed in the center of the image. The names of the actors and director, including "GERARD JUGNOT," "FRANÇOIS BERLEAND," "KAD," and "CHRISTOPHE BARRATIER," are listed below the title.</blockquote><blockquote>The poster shows a group of people posing for a picture in various settings. On the left side of the image, a group of people in tuxedos can be seen standing in front of a tree. In the middle of the image, a group of children sits on a bench with a chalkboard. To the right of the children, <strong>another group of children is sitting in a classroom</strong>. They are separated by a group of boys who are sitting on a bench. Further to the right, a group of people is posing for another picture. <strong>Above all these scenes, there is a group of children sitting on a stage</strong>.</blockquote><blockquote><strong>The color scheme of the poster is predominantly white</strong>, with the title and texts in black. The actors' names are in smaller font compared to the title. The overall appearance suggests a heartwarming and collaborative movie involving children and adults in different settings, possibly related to music or education.</blockquote><blockquote>Additional details, such as the ratings "9.8" and "27.7.761," are included at the bottom right corner of the poster. The meaning of these numbers is unclear without further context.</blockquote><p><strong>Jelly:</strong></p><blockquote>The image is a movie poster for the French film "Les Choristes", directed by Christophe Barratier. The movie's title is printed in large letters under an archway. Beneath this are young boys and men, some sitting on a bench, and others standing. They are dressed in classic school-like clothing and are positioned at different heights, perhaps indicating different ages. In the lower corners of the poster, the names of actors Gérard Jugnot, François Berléand, and Kad are printed. The poster has a vintage feel, possibly due to its color scheme and the classic clothing of the characters.</blockquote><h3 id="liberty-leading-the-people">Liberty leading the people</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--5-.png" class="kg-image" alt="" width="464" height="367"></figure><p><strong>Glide:</strong></p><blockquote>The artwork depicts a scene with a strong patriotic theme. The central focus of the painting showcases a woman holding the French flag, her figure dominating the composition. Her proud stance and the vibrant colors of the flag capture the viewer's attention. Surrounding her, several other characters are depicted, each with their own distinct role. A man is shown holding a rifle, signifying the presence of armed conflict. In another section, <strong>a group of men is seen together on a boat</strong>, suggesting a collective effort or journey. Additionally, <strong>a man on a separate boat is featured</strong>, adding further depth to the narrative. <strong>A woman with a knife and a man with a gun are shown</strong>, reflecting a sense of danger and potential violence. The artwork overall conveys a sense of patriotism, conflict, and tension through its composition and subject matter.</blockquote><p><strong>Jelly:</strong></p><blockquote>This image is a painting titled "Liberty Leading the People", created in 1830 by the French artist Eugène Delacroix. The painting depicts a woman symbolizing France and the revolution, standing on the bodies of prostrate figures signifying defeated enemies. She is dressed in a <strong>blue</strong> dress, holding a French flag in her left hand, symbolizing the French republic and democracy. In her right hand, she is likely holding a weapon, possibly a sword. The painting represents a moment from the French Revolution, showcasing the spirit of the people resisting tyranny.</blockquote><h3 id="emojis">Emojis</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--6-.png" class="kg-image" alt="" width="1024" height="537" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Untitled--6-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/Untitled--6-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--6-.png 1024w" sizes="(min-width: 720px) 720px"></figure><p><strong>Glide:</strong></p><blockquote>A playful scene unfolds on a vibrant green grassy expanse, as a group of colorful emoji balls gathers together. These enchanting characters fill the frame, showcasing a wide array of expressive emotions and witty designs. In the center, a striking <strong>red and yellow ball</strong> stands out with its angry face emblazoned upon its surface. Positioned nearby, lying comfortably on the grass, two yellow emoji balls exude a relaxed demeanor. To the right, a buoyant <strong>blue and yellow ball</strong> features a cheerful smiley face that adds a touch of delight and cheerfulness to the mix. On the left, <strong>two</strong> yellow balls adorned with sunglasses mirror each other's fashionable style while resting peacefully in the grass. Amidst the lively atmosphere, a <strong>yellow and blue plush toy makes its presence known with a sad expression</strong>, attracting sympathy and affection. Additionally, a yellow and red emoji doll captivates attention with a heartfelt kiss imprinted upon its face. Further accentuating this whimsical scene, a lone yellow face with big expressive eyes captures the viewer's gaze, radiating a sense of curiosity and intrigue. Lastly, <strong>a yellow teddy bear</strong> wearing sunglasses and a friendly smile completes the array of delightful characters, inviting joy and warmth into the playful world they inhabit.</blockquote><p><strong>Jelly:</strong></p><blockquote>The image shows a group of six stress balls with different emoji faces on them, situated on a green grassy surface. Each stress ball displays a unique emoji expression and they come in varied colors including yellow, red, and blue. The background of the image is blurred, ensuring the focus is on these stress balls.</blockquote><p>Want to see more examples of how SceneXplain algorithms stack up? Check them out here:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/benchmark?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><h2 id="get-your-jelly-on">Get your Jelly on</h2><p>As you can see, Jelly gives you captions that are more concise, readable, and <strong>accurate</strong> than ever before. Wave goodbye to hallucinations and say hello to detailed, precise descriptions of your images.</p><p>To get started with Jelly (or any other SceneXplain algorithm), sign up for a free account at <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">scenex.jina.ai</a> and start captioning your images!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fare-you-ready-for-this-jelly-scenexplains-new-algo-kills-hallucinations-dead%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 56.044%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/image.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Are you ready for this Jelly? SceneXplain’s new algo kills hallucinations dead</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">SceneXplain's state-of-the-art Jelly algorithm is more concise, readable and accurate than ever before, while killing hallucinations.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 25, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Another month rolls by, and here at Jina AI we’re releasing a new, more refined algorithm for <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a>.</p><p>A while back, we introduced SceneXplain’s “Glide” algorithm, which nailed recognizing multilingual text in images, something other models are now only just introducing:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--1-.png" class="kg-image" alt="" width="447" height="844"></figure><p></p><p>But that was then. This is now. So, what comes next? Fixing hallucination, that’s what.</p><h2 id="what-is-hallucination-in-computer-vision">What is hallucination in computer vision?</h2><p>You may already be familiar with AI hallucination when it comes to LLMs, for example, <a href="https://www.nytimes.com/2023/06/08/nyregion/lawyer-chatgpt-sanctions.html?ref=jina-ai-gmbh.ghost.io">ChatGPT hallucinating papers and sources that don’t exist in reality</a>.</p><blockquote class="kg-blockquote-alt"><strong>"[ChatGPT is an] omniscient, eager-to-please intern who sometimes lies to you"</strong><br>Professor Ethan Mollick of <a href="https://en.wikipedia.org/wiki/Wharton_School_of_the_University_of_Pennsylvania?ref=jina-ai-gmbh.ghost.io">Wharton</a></blockquote><p>Likewise, image generation models (like Midjourney) often hallucinate unwanted details (or unwanted fingers for that matter.)</p><p><a href="https://gagadget.com/en/how-it-works/210102-the-unattainable-pinnacle-of-art-why-does-midjourney-artificial-intelligence-draw-6-fingers-on-hands-and-how/?ref=jina-ai-gmbh.ghost.io">The unattainable pinnacle of art: why does Midjourney artificial intelligence draw 6 fingers on hands and how can it be fixed?</a></p><p>In short, hallucination is AI models generating false information.</p><p>SceneXplain often fell victim to this in our prior algorithms, hallucinating skateboarders, and occasionally Naruto:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--2-.png" class="kg-image" alt="" width="640" height="380" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Untitled--2-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--2-.png 640w"><figcaption><span style="white-space: pre-wrap;">SceneXplain’s Aqua algorithm: In a whimsical and enchanting scene, Totoro and a young girl share an umbrella in the rain. The iconic character from Studio Ghibli's beloved film stands alongside the girl, offering shelter from the downpour. The atmosphere is both heartwarming and magical, as Totoro's presence infuses the moment with a sense of wonder and delight. Meanwhile, </span><b><strong style="white-space: pre-wrap;">Naruto makes a surprising appearance in the rain-soaked setting</strong></b><span style="white-space: pre-wrap;">, adding another layer of intrigue to this captivating tableau. This charming depiction brings together two distinct worlds, bridging the gap between Japanese animation and manga to create an unforgettable moment of friendship and adventure.</span></figcaption></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--3-.png" class="kg-image" alt="" width="446" height="612"></figure><h2 id="what-causes-hallucination-in-computer-vision">What causes hallucination in computer vision?</h2><p>In humans, hallucination is caused by errors in perception, faulty expectations, neurological defects, or maybe just a dose of Scarecrow’s fear gas. In computer vision, it can often come about through issues with training data or the way an image is processed before generation or (in the case of SceneXplain) captioning.</p><h3 id="slicing-and-dicing-the-elephant-in-the-room">Slicing and dicing: the elephant in the room</h3><p>When it comes to image captioning, you often want a high level of detail. A common approach is to slice an image into several pieces, generate a caption for each piece, then merge the captions together into a final description. Sounds like a pretty sensible approach, right? By focusing on each segment and then combining results, we should get a better description overall.</p><p>Except...you ever heard the tale of the blind men and the elephant?</p><blockquote>Six blind men encounter an elephant for the first time and each touches a different part of the animal. One feels the trunk and thinks it's a snake, another touches a leg and believes it's a tree, and so on with the tusk (a spear), ear (a mat), tail (a rope), and side (a wall). Amidst much debate, they all insist they're correct, not realizing they're all describing the same elephant.</blockquote><p>If we want to understand an image by slicing it into different parts we can face exactly the same issue. If we were to draw what the blind men experience, we'd create a picture of a snake wrapped in a blanket next to a tree, along with a bunch of other elements. In short, many <em>elements</em>, but no <em>elephant</em>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/image-2.png" class="kg-image" alt="" width="1170" height="656" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/image-2.png 1170w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Midjourney's interpretation of the blind men's elephant</span></figcaption></figure><p>Likewise, in captioning, let's say we split up one image of three men into several segments. In each segment, there may be some part (arm, leg, side of head) of a different man. When it comes time to combine those segment descriptions (<code>a man's face</code>, <code>a man's leg</code>, <code>a man's arm</code>, etc), how many men would be seen? Are these all part of one man? Are they each a part of different men? If so, how many? And without the context of the rest of the image, just what is that patch of fuzz in the top-left section?</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/man-grid.png" class="kg-image" alt="" width="600" height="853" srcset="https://jina-ai-gmbh.ghost.io/content/images/2023/10/man-grid.png 600w"><figcaption><span style="white-space: pre-wrap;">Adapted from Pexels.com (</span><a href="https://www.pexels.com/photo/man-in-white-dress-shirt-holding-suit-jacket-1043474/?ref=jina-ai-gmbh.ghost.io"><span style="white-space: pre-wrap;">https://www.pexels.com/photo/man-in-white-dress-shirt-holding-suit-jacket-1043474/</span></a><span style="white-space: pre-wrap;">)</span></figcaption></figure><p>If the model splits everything up too much, it can hallucinate things that just aren't there. If it doesn't split things, the overall description may be too vague to be useful.</p><h3 id="ambiguity-thats-a-cutepuppy">Ambiguity: That's a cute...puppy?</h3><p>Many models rely on multimodality - that is translating text-to-image (like using a prompt to generate an image in Midjourney) or image-to-text (like generating a caption from an image in SceneXplain). Ambiguous text or images can therefore cause problems.</p><p>Take the phrase "salmon swimming in a river." Most humans would imagine fish swimming up a river. AI on the other hand can see some ambiguity:</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://www.reddit.com/r/technicallythetruth/comments/y26t6x/ai_asked_to_draw_salmon_swimming_in_river/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/image-1.png" class="kg-image" alt="" width="750" height="426" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/image-1.png 750w" sizes="(min-width: 720px) 720px"></a><figcaption><span style="white-space: pre-wrap;">Via Reddit</span></figcaption></figure><p>Likewise, sometimes images can be ambiguous:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--7-.png" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Untitled--7-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/Untitled--7-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/10/Untitled--7-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--7-.png 2048w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Duck or rabbit?</span></figcaption></figure><p>This isn't just applicable to traditional optical illusions or Rorschach tests. A <a href="https://www.insider.com/viral-puppy-looks-like-mix-between-dog-and-cat-2020-3?ref=jina-ai-gmbh.ghost.io">cute little fuzzball</a> could be a puppy OR a kitten. Running it by the model just once may result in a misclassification. Several tries may be needed to consistently see that puppy as a puppy.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--8-.png" class="kg-image" alt="" width="700" height="525" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Untitled--8-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--8-.png 700w"><figcaption><span style="white-space: pre-wrap;">Dog or cat? (Via Business Insider)</span></figcaption></figure><p>And let’s not even get started on <a href="https://en.m.wikipedia.org/wiki/The_dress?ref=jina-ai-gmbh.ghost.io">that damn dress</a>.</p><h3 id="ocr-occasionally-crappy-recognition">OCR: Occasionally Crappy Recognition</h3><p>If you've got this far in the article, you probably think you're a pretty hot reader. Go on, give yourself a big pat on the back. You should really share some of your knowledge on <a href="http://expertsexchange.com/?ref=jina-ai-gmbh.ghost.io">expertsexchange.com</a>. It's a site I use every day, sometimes several times. To exchange information with other experts.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">If you don't see why I'm bringing this up, re-read that URL</div></div><p>It's not just a lack of clear word spacing that can trip you up. Take keming (uh, kerning) for example.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text"> In typography, kerning is the process of adjusting the spacing between characters in a proportional font, usually to achieve a visually pleasing result.</div></div><p>Bad kerning can have interesting results:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://cdn.mos.cms.futurecdn.net/9cdc770ee6d32d569f4dfa1d7e44029e-1200-80.jpg.webp" class="kg-image" alt="10 flickering lights"><figcaption><span style="white-space: pre-wrap;">10 flickering lights</span></figcaption></figure><p>If these things are ambiguous to readers like you, just imagine how confused an AI model can get!</p><h2 id="how-does-scenexplain-fix-hallucination">How does SceneXplain fix hallucination?</h2><p>SceneXplain’s new Jelly algorithm aims to eliminate these hallucinations, using the following methods:</p><ol><li>A simplified processing pipeline. Our prior algorithms had much more complex pipelines, meaning more places for things to go wrong. Jelly pares this back with a new end-to-end approach to image labeling that produces detailed image captions with much fewer hallucinations.</li><li>Self-consistency: We’ve implemented an advanced prompt technique (self-consistency) to get the most consistent and accurate caption for any given image.</li><li>OCR improvements: We've improved Jelly’s text recognition capabilities which leads to fewer hallucinations and better captions.</li></ol><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Hallucination is seeing things that don’t exist. Just like people “see” ghosts. Since Jelly removes hallucinations you could call it the ultimate “Ghostbuster”. Cue the theme music.</div></div><h2 id="before-and-after">Before and After</h2><p>As you can see from the examples below:</p><ul><li>Glide suffers from way more hallucinations (highlighted in bold) than Jelly</li><li>Jelly provides more readable captions, lacking the elaborate flowery language of Glide</li></ul><h3 id="les-choristes">Les Choristes</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--4-.png" class="kg-image" alt="" width="764" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Untitled--4-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--4-.png 764w" sizes="(min-width: 720px) 720px"></figure><p><strong>Glide:</strong></p><blockquote>The image showcases a poster for a movie called "Les Choristes." The poster features the title "LES CHORISTES" prominently displayed in the center of the image. The names of the actors and director, including "GERARD JUGNOT," "FRANÇOIS BERLEAND," "KAD," and "CHRISTOPHE BARRATIER," are listed below the title.</blockquote><blockquote>The poster shows a group of people posing for a picture in various settings. On the left side of the image, a group of people in tuxedos can be seen standing in front of a tree. In the middle of the image, a group of children sits on a bench with a chalkboard. To the right of the children, <strong>another group of children is sitting in a classroom</strong>. They are separated by a group of boys who are sitting on a bench. Further to the right, a group of people is posing for another picture. <strong>Above all these scenes, there is a group of children sitting on a stage</strong>.</blockquote><blockquote><strong>The color scheme of the poster is predominantly white</strong>, with the title and texts in black. The actors' names are in smaller font compared to the title. The overall appearance suggests a heartwarming and collaborative movie involving children and adults in different settings, possibly related to music or education.</blockquote><blockquote>Additional details, such as the ratings "9.8" and "27.7.761," are included at the bottom right corner of the poster. The meaning of these numbers is unclear without further context.</blockquote><p><strong>Jelly:</strong></p><blockquote>The image is a movie poster for the French film "Les Choristes", directed by Christophe Barratier. The movie's title is printed in large letters under an archway. Beneath this are young boys and men, some sitting on a bench, and others standing. They are dressed in classic school-like clothing and are positioned at different heights, perhaps indicating different ages. In the lower corners of the poster, the names of actors Gérard Jugnot, François Berléand, and Kad are printed. The poster has a vintage feel, possibly due to its color scheme and the classic clothing of the characters.</blockquote><h3 id="liberty-leading-the-people">Liberty leading the people</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--5-.png" class="kg-image" alt="" width="464" height="367"></figure><p><strong>Glide:</strong></p><blockquote>The artwork depicts a scene with a strong patriotic theme. The central focus of the painting showcases a woman holding the French flag, her figure dominating the composition. Her proud stance and the vibrant colors of the flag capture the viewer's attention. Surrounding her, several other characters are depicted, each with their own distinct role. A man is shown holding a rifle, signifying the presence of armed conflict. In another section, <strong>a group of men is seen together on a boat</strong>, suggesting a collective effort or journey. Additionally, <strong>a man on a separate boat is featured</strong>, adding further depth to the narrative. <strong>A woman with a knife and a man with a gun are shown</strong>, reflecting a sense of danger and potential violence. The artwork overall conveys a sense of patriotism, conflict, and tension through its composition and subject matter.</blockquote><p><strong>Jelly:</strong></p><blockquote>This image is a painting titled "Liberty Leading the People", created in 1830 by the French artist Eugène Delacroix. The painting depicts a woman symbolizing France and the revolution, standing on the bodies of prostrate figures signifying defeated enemies. She is dressed in a <strong>blue</strong> dress, holding a French flag in her left hand, symbolizing the French republic and democracy. In her right hand, she is likely holding a weapon, possibly a sword. The painting represents a moment from the French Revolution, showcasing the spirit of the people resisting tyranny.</blockquote><h3 id="emojis">Emojis</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--6-.png" class="kg-image" alt="" width="1024" height="537" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Untitled--6-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/Untitled--6-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Untitled--6-.png 1024w" sizes="(min-width: 720px) 720px"></figure><p><strong>Glide:</strong></p><blockquote>A playful scene unfolds on a vibrant green grassy expanse, as a group of colorful emoji balls gathers together. These enchanting characters fill the frame, showcasing a wide array of expressive emotions and witty designs. In the center, a striking <strong>red and yellow ball</strong> stands out with its angry face emblazoned upon its surface. Positioned nearby, lying comfortably on the grass, two yellow emoji balls exude a relaxed demeanor. To the right, a buoyant <strong>blue and yellow ball</strong> features a cheerful smiley face that adds a touch of delight and cheerfulness to the mix. On the left, <strong>two</strong> yellow balls adorned with sunglasses mirror each other's fashionable style while resting peacefully in the grass. Amidst the lively atmosphere, a <strong>yellow and blue plush toy makes its presence known with a sad expression</strong>, attracting sympathy and affection. Additionally, a yellow and red emoji doll captivates attention with a heartfelt kiss imprinted upon its face. Further accentuating this whimsical scene, a lone yellow face with big expressive eyes captures the viewer's gaze, radiating a sense of curiosity and intrigue. Lastly, <strong>a yellow teddy bear</strong> wearing sunglasses and a friendly smile completes the array of delightful characters, inviting joy and warmth into the playful world they inhabit.</blockquote><p><strong>Jelly:</strong></p><blockquote>The image shows a group of six stress balls with different emoji faces on them, situated on a green grassy surface. Each stress ball displays a unique emoji expression and they come in varied colors including yellow, red, and blue. The background of the image is blurred, ensuring the focus is on these stress balls.</blockquote><p>Want to see more examples of how SceneXplain algorithms stack up? Check them out here:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/benchmark?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><h2 id="get-your-jelly-on">Get your Jelly on</h2><p>As you can see, Jelly gives you captions that are more concise, readable, and <strong>accurate</strong> than ever before. Wave goodbye to hallucinations and say hello to detailed, precise descriptions of your images.</p><p>To get started with Jelly (or any other SceneXplain algorithm), sign up for a free account at <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">scenex.jina.ai</a> and start captioning your images!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fare-you-ready-for-this-jelly-scenexplains-new-algo-kills-hallucinations-dead%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Artificial General Intelligence is Cursed, And Science Fiction isn't Helping</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">AI is cursed by intellectual hubris, moving goalposts, bad incentives, and science fiction. Recent talk about Artificial General Intelligence only highlights those curses.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 20, 2023 • 13 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Many, many, many, (too many <em>many</em>’s) years ago, I was a student taking <em>Introduction to Artificial Intelligence</em> at Stanford. <a href="https://en.wikipedia.org/wiki/Daphne_Koller?ref=jina-ai-gmbh.ghost.io">Daphne Koller</a> was my teacher, and my textbook was a first edition <a href="https://aima.cs.berkeley.edu/?ref=jina-ai-gmbh.ghost.io"><em>Artificial Intelligence: A Modern Approach</em></a> by <a href="https://en.wikipedia.org/wiki/Stuart_J._Russell?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Stuart Russell</a> and <a href="https://en.wikipedia.org/wiki/Peter_Norvig?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Peter Norvig</a>, which still sits on the shelf in my office.</p><p>A lot of us working in AI today have that textbook on our shelves.</p><p>That’s why a <a href="https://www.noemamag.com/artificial-general-intelligence-is-already-here/?ref=jina-ai-gmbh.ghost.io">recent article in <em>Noema Magazine</em></a> by <a href="https://en.wikipedia.org/wiki/Blaise_Ag%C3%BCera_y_Arcas?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Blaise Agüera y Arcas</a> of Google Research and Peter Norvig, provocatively titled <em>Artificial General Intelligence Is Already Here</em> caught so much attention.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.noemamag.com/artificial-general-intelligence-is-already-here/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Artificial General Intelligence Is Already Here | NOEMA</div><div class="kg-bookmark-description">Today’s most advanced AI models have many flaws, but decades from now, they will be recognized as the first true examples of artificial general intelligence.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.noemamag.com/wp-content/uploads/2020/06/cropped-ms-icon-310x310-1-180x180.png" alt=""><span class="kg-bookmark-author">NOEMA</span><span class="kg-bookmark-publisher">Blaise Agüera y Arcas</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://noemamag.imgix.net/2023/10/Noema_Card-display-2000x1000-0-00-04-04.jpg?fit=crop&amp;fm=pjpg&amp;h=628&amp;ixlib=php-3.3.1&amp;w=1200&amp;wpsize=noema-social-facebook&amp;s=2e1793c1499718ac74749479e3989c10" alt=""></div></a></figure><p>To summarize their claim, the core elements of general intelligence are already met by recent large language models: They can perform with human competence at tasks outside of their explicit training over a wide range of domains. Although hardly without flaws, human performance is hardly flawless either. Therefore, we should acknowledge that these systems have achieved “general intelligence.”</p><p>The rest of the article is, frankly, mostly taking down strawmen and rehashing old fights from the 90s. Honestly, the people who graduated from university in the last twenty years never fought in the Great Symbolicist-Connectionist War. That conflict ended a long time ago, and any Symbolicist bitter-enders who’ve survived into the age of GPT should be allowed to stay in their thatched jungle huts, collecting nuts and fruits and proclaiming their loyalties to Fodor, Pinker, and Chomsky somewhere far away where it doesn’t have to bother anyone.</p><p>I fought in that conflict (for the Connectionists, thank you), and on behalf of myself and the other veterans, please give it a rest! (<a href="http://garymarcus.com/index.html?ref=jina-ai-gmbh.ghost.io">Gary Marcus</a>, I mean you too!)</p><p>“Artificial General Intelligence” (AGI) is, to put it mildly, a controversial concept in AI research. The word is of recent vintage, dating to about the turn of the 21st century, and comes from an attempt to make clearer an idea that has circulated in AI since, arguably, before the invention of computers. It’s gone by a lot of names over the years: “true AI,” “real AI”, “strong AI,” “human-equivalent AI,” etc. The history of attempts to define it in some testable way is, to say the least, not encouraging, but it doesn’t seem to stop anyone from trying.</p><h2 id="the-curses-of-ai">The Curses of AI</h2><p>Artificial intelligence is a cursed field.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--3--1.png" class="kg-image" alt="" width="1050" height="1050" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--3--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--3--1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--3--1.png 1050w" sizes="(min-width: 720px) 720px"></figure><p>The word was coined by <a href="https://en.wikipedia.org/wiki/John_McCarthy_(computer_scientist)?ref=jina-ai-gmbh.ghost.io">John McCarthy</a> in 1956, in large part to distinguish it from “cybernetics,” a label associated with <a href="https://en.wikipedia.org/wiki/Norbert_Wiener?ref=jina-ai-gmbh.ghost.io">Norbert Wiener</a>, who saw it as an interdisciplinary field with political implications that did not appeal to McCarthy and his colleagues. So, from the very beginning, AI has been associated with intellectual hubris and disinterest in social consequences, willfully distancing itself from the humanities — the study of human works — while purporting to build machines that do the work of humans.</p><p>That is one of AI's great curses: There is an expansive, argumentative, routinely acrimonious literature on the nature of intelligence and human intellectual abilities, dating back centuries and even millennia, and discussions of artificial intelligence reference it approximately never. How exactly are you going to discuss “artificial intelligence” if you can’t say what it means for something to be intelligent, or how you would demonstrate that?</p><p>Agüera y Arcas of Google and Norvig are not especially clear on how they’ve defined “general intelligence” despite having a section titled <em>“What Is General Intelligence?”</em></p><p>Broadly, their claim seems to be:</p><ol><li>General intelligences can do more than one kind of thing.</li><li>General intelligences can do things that their designers didn’t specifically intend for them to be able to do.</li><li>General intelligences can do things that are specified in your instructions to them rather than their programming.</li></ol><p>This is my summary, and perhaps I have misunderstood them, but the section where they explain this goes on a number of tangents that make it hard to identify what they intend to say. They appear to be using the label “general intelligence” to contrast with “narrow intelligence,” another new term (I can’t find reference to it before the 2010s) that seems to have the same relationship to what we used to call “weak AI” as “general intelligence” has to “strong AI.”</p><p>They define it as follows:</p><blockquote>Narrowly intelligent systems typically perform a single or predetermined set of tasks, for which they are explicitly trained. Even multitask learning yields only narrow intelligence because the models still operate within the confines of tasks envisioned by the engineers.</blockquote><p>They contrast this with “general intelligence”:</p><blockquote>By contrast, frontier language models can perform competently at pretty much any information task that can be done by humans, can be posed and answered using natural language, and has quantifiable performance.</blockquote><p>This approach poses some obvious problems. It defines artificial general intelligence to exist only when engineers have poor imaginations. That doesn’t seem quite right.</p><p>The most frequently cited example of an AI model performing outside of its explicit training (a.k.a. <em>zero-shot learning</em>) is the “zebra” example: Let us say we have a multimodal AI model that has never had a picture of a zebra or mention of a zebra anywhere in its training data. So we tell it that a zebra is a horse with stripes, and then we present it with pictures, some of zebras, some not, and ask it if each one is a zebra.</p><p>The current generation of multimodal models is capable of doing a good job of this.</p><p>I don’t know if this is exactly what Agüera y Arcas and Norvig have in mind as performing outside of “the confines of tasks envisioned by the engineers” because they give no examples, nor does the article they link to on this subject. (”A general AI model can perform tasks the designers never&nbsp;<a href="https://www.quantamagazine.org/the-unpredictable-abilities-emerging-from-large-ai-models-20230316/?ref=jina-ai-gmbh.ghost.io">envisioned</a>.”) But this kind of zero-shot learning does seem to be what they mean.</p><p>However, it's not clear that this really is an example of going outside of the tasks envisioned by the model's designers. Given that the model was explicitly trained to recognize horses and stripes and to connect the features it finds in images to natural language words and statements, it was explicitly trained to handle all parts of the problem. So is it right to say it’s exceeded the bounds of “narrow intelligence?”</p><p>Other zero-shot learning examples suffer from the same problem.</p><p>Also, unexpected correct results from computers have been around for some time. As an example, <a href="https://www.jpl.nasa.gov/news/remote-agent-experiment-meets-all-objectives?ref=jina-ai-gmbh.ghost.io">this article from 1999</a> shows a logistic planner in a NASA space probe doing something that not only was correct and unexpected but that the engineers could never have had in mind when they designed it.</p><p>But there’s an even larger problem with defining artificial general intelligence this way.</p><p>Let’s consider the large language models, like ChatGPT. What were the tasks its engineers designed it to do? Only one task: Add the next word to a text.</p><p>The web interface to ChatGPT obscures what happens behind the scenes, but ChatGPT works like this:</p><blockquote>Iteration 1:<br>    User Input: <strong>Knock, knock.</strong> <br>    GPT Output: <strong>Who’s</strong><br><br>Iteration 2:<br>    GPT Input: <strong>Knock, knock. Who’s</strong> <br>    GPT Output: <strong>there</strong><br><br>Iteration 3: <br>    GPT Input: <strong>Knock, knock. Who’s there</strong> <br>    GPT Output: <strong>?</strong><br><br>Return to user: <strong>“Who’s there?”</strong></blockquote><p>That’s all it does! You see it writing poetry, answering questions, or whatever else you like, but under the surface, it’s a sequence of identical simple operations to append a word to a text.</p><p>We could say that ChatGPT does just one task, the one it was explicitly designed for.</p><p>So, is this a single-task ability or multi-task abilities? Is it doing more than the engineers designed it to do, or only exactly the one thing they designed it to do?</p><p>It depends on how you choose to look at it. This kind of ambiguity is not trivial to resolve.</p><p>The article highlights “[a] healthy skepticism about metrics for AGI” as a legitimate concern. However, the problem with “general intelligence” isn’t metrics and thresholds. It’s definitions. AI’s lack of clear definitions of its terms is the direct cause of AI’s second great curse: Moving goalposts.</p><p>Goalpost-moving is so central to AI as an enterprise that Professor Koller introduced me to it in her introductory class long ago, I think on, like, Week 3.</p><p>Every time researchers solve some problem in AI, it’s redefined as not needing intelligence. As <a href="https://en.wikipedia.org/wiki/Pamela_McCorduck?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Pamela McCorduck</a> puts it in her influential history of AI:</p><blockquote>Practical AI successes, computational programs that actually achieved intelligent behavior, were soon assimilated into whatever application domain they were found to be useful, and became silent partners alongside other problem-solving approaches, which left AI researchers to deal only with the “failures,” the tough nuts that couldn’t yet be cracked. Once in use, successful AI systems were simply considered valuable automatic helpers. [<a href="https://doi.org/10.1201/9780429258985?ref=jina-ai-gmbh.ghost.io">McCorduck 2004</a>]</blockquote><p>Or, in shorter words, attributed to <a href="https://en.wikipedia.org/wiki/Larry_Tesler?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Larry Tesler</a> (the inventor of copy-paste functionality):</p><blockquote>AI is whatever hasn't been done yet.</blockquote><p>AI is a <a href="https://en.wikipedia.org/wiki/Red_Queen%27s_race?ref=jina-ai-gmbh.ghost.io">Red Queen’s Race</a> where no matter how fast you run, the finish line moves away even faster. The history of AI is a history of failure because we excise the successes from it. Never mind that AI research was already years ago bringing us decent spellcheckers, functional machine translations, and visual object recognition, among other accomplishments of modern technology.</p><p>Or that half the world today runs on logistic planners that started life in the 1960s as AI research in automated theorem proving. Yes, your “supply chain” is already AI from end to end. AI didn’t get rid of the drudgery of trucking and manually loading and unloading goods. It got rid of the comfy office job of scheduling.</p><p>In the history of AI goalpost-moving, Agüera y Arcas and Norvig’s contribution is somewhat novel: We’re used to moving the goalposts of “real” AI to make them ever harder to reach. They’ve moved them to say we’ve already passed them.</p><p>The cause of the moving goalposts is more complex: AI is cursed with bad incentives. It lends itself to hype. We might blame this on the grants process and academic pressures to overpromise, or on late capitalism and the way the tech investor class likes to chase after the latest shiny thing in hopes of owning a “disruptive” new technology.</p><p>But I put a lot of the blame on AI’s final curse: Science fiction.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--6-.png" class="kg-image" alt="" width="700" height="700" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--6-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--6-.png 700w"></figure><p>Now, understand me: This is not a criticism of the makers of science fiction; it’s a criticism of its consumers. I have been watching and reading science fiction since I was five years old, and I love it. It’s a popular genre, beloved by millions, if not billions, of people.</p><p>But the ideas people have in their heads about AI, including the people who do AI research, have been so thoroughly colonized by fictitious machines that it has become difficult to separate legitimate debates from the dramatic visions of novelists and movie makers.</p><p>Ideas about “artificial general intelligence” or “real” AI owe far more to science fiction than to science. It’s not the responsibility of the Issac Asimovs, the Stanley Kubriks, or the James Camerons of the world to police their imaginations or ours. It is the responsibility of AI professionals — researchers, marketers, investors, and corporate frontmen — to understand and make clear that “<a href="https://en.wikipedia.org/wiki/Positronic_brain?ref=jina-ai-gmbh.ghost.io">positronic brains</a>,” <a href="https://en.wikipedia.org/wiki/HAL_9000?ref=jina-ai-gmbh.ghost.io">HAL 9000</a>, and <a href="https://en.wikipedia.org/wiki/The_Terminator?ref=jina-ai-gmbh.ghost.io">killer robots with inexplicable Austrian accents</a> have no place in engineering.</p><p>We move the goalposts in AI because every accomplishment ends up disappointing us when it doesn’t live up to our vision of AI. Rational beings might interrogate their visions of AI rather than move around the goalposts and say: “This time, it’s different!”</p><p>Humans have deep prejudices that they struggle to recognize. Agüera y Arcas and Norvig recognize this in their mention of the “<a href="https://en.wikipedia.org/wiki/Being_There?ref=jina-ai-gmbh.ghost.io">Chauncey Gardiner effect</a>.” For younger readers who don’t know the works of Peter Sellers and Hal Ashby, we might also call this the “Rita Leeds effect” after Charlize Theron’s role in <a href="https://en.wikipedia.org/wiki/Arrested_Development_(season_3)?ref=jina-ai-gmbh.ghost.io">season three of <em>Arrested Development</em></a>. It’s the same schtick.</p><p>Until the 1970s, there were serious social scientists who believed that black people, at least American ones, were systematically intellectually stunted and pointed to the way they spoke English as proof. Even today, plenty of people view African American Vernacular English (usually abbreviated as AAVE because who has time to spell that out?) as “broken” or “defective” or indicative of poor education.</p><p>Among linguists, no one of any importance today thinks that. We recognize AAVE as a fully functional variant form of English, just as well-suited to accurate and effective communication as standard English or any of its other variants. It has no relationship to cognitive abilities whatsoever.</p><p>Yet, the prejudice against it remains.</p><p>When we evaluate ChatGPT as “real” AI, or at least on the path to “real” AI, we are demonstrating the same prejudice, turned around. That should give us some pause. It should lead us to ask if <em>anything</em> we think makes software intelligent is really intelligence or just manipulating our prejudices. Is there any way to objectively judge intelligence at all? We may never be able to fully dismiss our prejudices.</p><p>It does not take a lot of interaction with ChatGPT to see it fall short of our science-fiction-based visions for AI. It can do some neat tricks, maybe even some useful ones, but it’s not <a href="https://en.wikipedia.org/wiki/WALL-E?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">WALL-E</a>, or <a href="https://en.wikipedia.org/wiki/C-3PO?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">C-3PO</a>, or <a href="https://en.wikipedia.org/wiki/Data_(Star_Trek)?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Commander Data</a>. It’s not even Arnold Schwarzenegger's iconic but not terribly verbal T-800, although I don’t doubt you could readily integrate ChatGPT with a text-to-speech model that has a thick Austrian accent and pretend.</p><p>Changing the labels on things doesn’t change things, at least not in any simple way. We could move the goalposts for “artificial general intelligence” in such a way that we could say we’ve already accomplished that, but that will not make today’s AI models more satisfactory to people looking for HAL 9000. It would just render the label “general intelligence” meaningless.</p><p>People would still want something we can’t give them. Something we might never be able to give them.</p><h2 id="are-humans-still-special">Are Humans Still Special?</h2><p>Among the strawmen Agüera y Arcas and Norvig take on in a whole section is <em>“Human (Or Biological) Exceptionalism.”</em> People believe all kinds of things, but unless you count religious notions of the “soul”, it is hard to believe this is a commonly held position among AI professionals. More likely, most of them don’t think about it at all.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--5-.png" class="kg-image" alt="" width="700" height="700" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--5-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--5-.png 700w"></figure><p>The lesson we should be learning from recent AI is that it is difficult to identify a human skill that is absolutely impossible for a machine to perform. We cannot make AI models do everything a human can do yet, but we can no longer rule anything out.</p><p>This realization should end some of the bad ideas we have inherited from the past. We know today that animals have languages much like our own and that computers can learn language with a shocking facility. Noam Chomsky may not be dead yet, but ChatGPT has put the final nails in the coffin of his life’s work.</p><p>We have known since Galileo that humanity does not live in the center of the universe. We have known for roughly two centuries that the universe existed for billions of years before people. We have known for some time that humans are not made special by the use of reason and language, as Descartes thought, as we find both among animals and note their frequent absence in humans.</p><p>AI research is removing the idea that humans are special because of some trick we can do, but that does not remove the specialness of humanity. Consider that we celebrate people who can run a mile in under four minutes. Yet, my 20-year-old cheap French-made car can do a mile in about 30 seconds if I really put my foot on the pedal.</p><p>We care about human accomplishment in ways that differ from how we care about pure performance benchmarks. We’ll still prefer our human performers over AI, for the same reason I don’t win Olympic medals with my old Citroën.</p><p>We imagine AI taking away the drudgery of human life, but we do not yet have robots that can restock shelves at Walmart. On the other hand, we now have AI models that can sing like <a href="https://en.wikipedia.org/wiki/%C3%89dith_Piaf?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Edith Piaf</a> and, if someone really tried, could probably dance like <a href="https://en.wikipedia.org/wiki/Shakira?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Shakira </a>or play the guitar like <a href="https://en.wikipedia.org/wiki/Jimi_Hendrix?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Jimi Hendrix</a>.</p><p>This is progress. It’s an accomplishment of significant value. But it’s not the AI we wanted. Unless we rethink the whole program of AI research, we’ll need to move the goalposts again.</p><h2 id="real-ai-instead-of-%E2%80%9Creal%E2%80%9D-ai">Real AI instead of “Real” AI</h2><p>Jina AI is a business. We don’t sell fantasy, we sell AI models. There’s no place for “artificial general intelligence” in what we do. We may love science fiction, but we deal in science fact.</p><p>“Past performance is not a guarantee of future returns.” Maybe it’ll be different this time. Maybe we won’t dismiss our successes as not “real” intelligence. Maybe we’ll get over our science fiction dreams for once. Maybe this hype cycle won’t lead to another AI Winter.</p><p>Maybe, but I won’t bet on it.</p><p>Someday, we might have something that looks more like our visions of “real” AI. Perhaps in 50 years? 100? History does not encourage optimism about it. But regardless, it won’t happen in a timeframe that pays any bills.</p><p>Moving around the goalposts of AI won’t change that.</p><p>Our interest is business cases. We want AI to add to your bottom line. At Jina AI, we want to hear about your business processes and discuss how really existing AI models can fit into them. We know the limits of this technology intimately, but we also know its genuine potential.</p><p>Contact us via our&nbsp;<a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">website</a>&nbsp;or join our&nbsp;<a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">community on Discord</a>&nbsp;to talk about what <em>real </em>AI can do for your business.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI - Your Portal to Multimodal AI</div><div class="kg-bookmark-description">Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. Navigating enterprise mazes &amp; startup vibes. Where's search headed next?</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">September 01, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/generativejina_mad_men_tv_serie_a_girl_is_looking_at_a_selectio_42a73443-5825-4394-a7ef-9c08294d29b6.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/fine-tuning-gpt-3-5-turbo-a-costly-mirage" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 25, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_modern_geometric_abstract_pattern_featuring_pu_24e4060e-dc76-4186-afb7-94d18d266b41.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/the-boundless-horizon-of-ai-its-not-just-about-the-size" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Beyond Sheer Scale: Navigating AI Alignment Odyssey</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">AI’s march forward isn't just about bigger models, but ensuring they harmonize with human values. Journey with us through the challenges, revelations, and aspirations at the forefront of AI safety and ethics.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">August 24, 2023 • 8 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_retrowave_sabattier_filter_sanriocore_in_the_sty_7881ce67-ea8f-417f-a204-bd101a3f58c0.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Artificial General Intelligence is Cursed, And Science Fiction isn't Helping</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">AI is cursed by intellectual hubris, moving goalposts, bad incentives, and science fiction. Recent talk about Artificial General Intelligence only highlights those curses.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 20, 2023 • 13 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Many, many, many, (too many <em>many</em>’s) years ago, I was a student taking <em>Introduction to Artificial Intelligence</em> at Stanford. <a href="https://en.wikipedia.org/wiki/Daphne_Koller?ref=jina-ai-gmbh.ghost.io">Daphne Koller</a> was my teacher, and my textbook was a first edition <a href="https://aima.cs.berkeley.edu/?ref=jina-ai-gmbh.ghost.io"><em>Artificial Intelligence: A Modern Approach</em></a> by <a href="https://en.wikipedia.org/wiki/Stuart_J._Russell?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Stuart Russell</a> and <a href="https://en.wikipedia.org/wiki/Peter_Norvig?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Peter Norvig</a>, which still sits on the shelf in my office.</p><p>A lot of us working in AI today have that textbook on our shelves.</p><p>That’s why a <a href="https://www.noemamag.com/artificial-general-intelligence-is-already-here/?ref=jina-ai-gmbh.ghost.io">recent article in <em>Noema Magazine</em></a> by <a href="https://en.wikipedia.org/wiki/Blaise_Ag%C3%BCera_y_Arcas?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Blaise Agüera y Arcas</a> of Google Research and Peter Norvig, provocatively titled <em>Artificial General Intelligence Is Already Here</em> caught so much attention.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.noemamag.com/artificial-general-intelligence-is-already-here/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Artificial General Intelligence Is Already Here | NOEMA</div><div class="kg-bookmark-description">Today’s most advanced AI models have many flaws, but decades from now, they will be recognized as the first true examples of artificial general intelligence.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.noemamag.com/wp-content/uploads/2020/06/cropped-ms-icon-310x310-1-180x180.png" alt=""><span class="kg-bookmark-author">NOEMA</span><span class="kg-bookmark-publisher">Blaise Agüera y Arcas</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://noemamag.imgix.net/2023/10/Noema_Card-display-2000x1000-0-00-04-04.jpg?fit=crop&amp;fm=pjpg&amp;h=628&amp;ixlib=php-3.3.1&amp;w=1200&amp;wpsize=noema-social-facebook&amp;s=2e1793c1499718ac74749479e3989c10" alt=""></div></a></figure><p>To summarize their claim, the core elements of general intelligence are already met by recent large language models: They can perform with human competence at tasks outside of their explicit training over a wide range of domains. Although hardly without flaws, human performance is hardly flawless either. Therefore, we should acknowledge that these systems have achieved “general intelligence.”</p><p>The rest of the article is, frankly, mostly taking down strawmen and rehashing old fights from the 90s. Honestly, the people who graduated from university in the last twenty years never fought in the Great Symbolicist-Connectionist War. That conflict ended a long time ago, and any Symbolicist bitter-enders who’ve survived into the age of GPT should be allowed to stay in their thatched jungle huts, collecting nuts and fruits and proclaiming their loyalties to Fodor, Pinker, and Chomsky somewhere far away where it doesn’t have to bother anyone.</p><p>I fought in that conflict (for the Connectionists, thank you), and on behalf of myself and the other veterans, please give it a rest! (<a href="http://garymarcus.com/index.html?ref=jina-ai-gmbh.ghost.io">Gary Marcus</a>, I mean you too!)</p><p>“Artificial General Intelligence” (AGI) is, to put it mildly, a controversial concept in AI research. The word is of recent vintage, dating to about the turn of the 21st century, and comes from an attempt to make clearer an idea that has circulated in AI since, arguably, before the invention of computers. It’s gone by a lot of names over the years: “true AI,” “real AI”, “strong AI,” “human-equivalent AI,” etc. The history of attempts to define it in some testable way is, to say the least, not encouraging, but it doesn’t seem to stop anyone from trying.</p><h2 id="the-curses-of-ai">The Curses of AI</h2><p>Artificial intelligence is a cursed field.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--3--1.png" class="kg-image" alt="" width="1050" height="1050" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--3--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--3--1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--3--1.png 1050w" sizes="(min-width: 720px) 720px"></figure><p>The word was coined by <a href="https://en.wikipedia.org/wiki/John_McCarthy_(computer_scientist)?ref=jina-ai-gmbh.ghost.io">John McCarthy</a> in 1956, in large part to distinguish it from “cybernetics,” a label associated with <a href="https://en.wikipedia.org/wiki/Norbert_Wiener?ref=jina-ai-gmbh.ghost.io">Norbert Wiener</a>, who saw it as an interdisciplinary field with political implications that did not appeal to McCarthy and his colleagues. So, from the very beginning, AI has been associated with intellectual hubris and disinterest in social consequences, willfully distancing itself from the humanities — the study of human works — while purporting to build machines that do the work of humans.</p><p>That is one of AI's great curses: There is an expansive, argumentative, routinely acrimonious literature on the nature of intelligence and human intellectual abilities, dating back centuries and even millennia, and discussions of artificial intelligence reference it approximately never. How exactly are you going to discuss “artificial intelligence” if you can’t say what it means for something to be intelligent, or how you would demonstrate that?</p><p>Agüera y Arcas of Google and Norvig are not especially clear on how they’ve defined “general intelligence” despite having a section titled <em>“What Is General Intelligence?”</em></p><p>Broadly, their claim seems to be:</p><ol><li>General intelligences can do more than one kind of thing.</li><li>General intelligences can do things that their designers didn’t specifically intend for them to be able to do.</li><li>General intelligences can do things that are specified in your instructions to them rather than their programming.</li></ol><p>This is my summary, and perhaps I have misunderstood them, but the section where they explain this goes on a number of tangents that make it hard to identify what they intend to say. They appear to be using the label “general intelligence” to contrast with “narrow intelligence,” another new term (I can’t find reference to it before the 2010s) that seems to have the same relationship to what we used to call “weak AI” as “general intelligence” has to “strong AI.”</p><p>They define it as follows:</p><blockquote>Narrowly intelligent systems typically perform a single or predetermined set of tasks, for which they are explicitly trained. Even multitask learning yields only narrow intelligence because the models still operate within the confines of tasks envisioned by the engineers.</blockquote><p>They contrast this with “general intelligence”:</p><blockquote>By contrast, frontier language models can perform competently at pretty much any information task that can be done by humans, can be posed and answered using natural language, and has quantifiable performance.</blockquote><p>This approach poses some obvious problems. It defines artificial general intelligence to exist only when engineers have poor imaginations. That doesn’t seem quite right.</p><p>The most frequently cited example of an AI model performing outside of its explicit training (a.k.a. <em>zero-shot learning</em>) is the “zebra” example: Let us say we have a multimodal AI model that has never had a picture of a zebra or mention of a zebra anywhere in its training data. So we tell it that a zebra is a horse with stripes, and then we present it with pictures, some of zebras, some not, and ask it if each one is a zebra.</p><p>The current generation of multimodal models is capable of doing a good job of this.</p><p>I don’t know if this is exactly what Agüera y Arcas and Norvig have in mind as performing outside of “the confines of tasks envisioned by the engineers” because they give no examples, nor does the article they link to on this subject. (”A general AI model can perform tasks the designers never&nbsp;<a href="https://www.quantamagazine.org/the-unpredictable-abilities-emerging-from-large-ai-models-20230316/?ref=jina-ai-gmbh.ghost.io">envisioned</a>.”) But this kind of zero-shot learning does seem to be what they mean.</p><p>However, it's not clear that this really is an example of going outside of the tasks envisioned by the model's designers. Given that the model was explicitly trained to recognize horses and stripes and to connect the features it finds in images to natural language words and statements, it was explicitly trained to handle all parts of the problem. So is it right to say it’s exceeded the bounds of “narrow intelligence?”</p><p>Other zero-shot learning examples suffer from the same problem.</p><p>Also, unexpected correct results from computers have been around for some time. As an example, <a href="https://www.jpl.nasa.gov/news/remote-agent-experiment-meets-all-objectives?ref=jina-ai-gmbh.ghost.io">this article from 1999</a> shows a logistic planner in a NASA space probe doing something that not only was correct and unexpected but that the engineers could never have had in mind when they designed it.</p><p>But there’s an even larger problem with defining artificial general intelligence this way.</p><p>Let’s consider the large language models, like ChatGPT. What were the tasks its engineers designed it to do? Only one task: Add the next word to a text.</p><p>The web interface to ChatGPT obscures what happens behind the scenes, but ChatGPT works like this:</p><blockquote>Iteration 1:<br>    User Input: <strong>Knock, knock.</strong> <br>    GPT Output: <strong>Who’s</strong><br><br>Iteration 2:<br>    GPT Input: <strong>Knock, knock. Who’s</strong> <br>    GPT Output: <strong>there</strong><br><br>Iteration 3: <br>    GPT Input: <strong>Knock, knock. Who’s there</strong> <br>    GPT Output: <strong>?</strong><br><br>Return to user: <strong>“Who’s there?”</strong></blockquote><p>That’s all it does! You see it writing poetry, answering questions, or whatever else you like, but under the surface, it’s a sequence of identical simple operations to append a word to a text.</p><p>We could say that ChatGPT does just one task, the one it was explicitly designed for.</p><p>So, is this a single-task ability or multi-task abilities? Is it doing more than the engineers designed it to do, or only exactly the one thing they designed it to do?</p><p>It depends on how you choose to look at it. This kind of ambiguity is not trivial to resolve.</p><p>The article highlights “[a] healthy skepticism about metrics for AGI” as a legitimate concern. However, the problem with “general intelligence” isn’t metrics and thresholds. It’s definitions. AI’s lack of clear definitions of its terms is the direct cause of AI’s second great curse: Moving goalposts.</p><p>Goalpost-moving is so central to AI as an enterprise that Professor Koller introduced me to it in her introductory class long ago, I think on, like, Week 3.</p><p>Every time researchers solve some problem in AI, it’s redefined as not needing intelligence. As <a href="https://en.wikipedia.org/wiki/Pamela_McCorduck?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Pamela McCorduck</a> puts it in her influential history of AI:</p><blockquote>Practical AI successes, computational programs that actually achieved intelligent behavior, were soon assimilated into whatever application domain they were found to be useful, and became silent partners alongside other problem-solving approaches, which left AI researchers to deal only with the “failures,” the tough nuts that couldn’t yet be cracked. Once in use, successful AI systems were simply considered valuable automatic helpers. [<a href="https://doi.org/10.1201/9780429258985?ref=jina-ai-gmbh.ghost.io">McCorduck 2004</a>]</blockquote><p>Or, in shorter words, attributed to <a href="https://en.wikipedia.org/wiki/Larry_Tesler?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Larry Tesler</a> (the inventor of copy-paste functionality):</p><blockquote>AI is whatever hasn't been done yet.</blockquote><p>AI is a <a href="https://en.wikipedia.org/wiki/Red_Queen%27s_race?ref=jina-ai-gmbh.ghost.io">Red Queen’s Race</a> where no matter how fast you run, the finish line moves away even faster. The history of AI is a history of failure because we excise the successes from it. Never mind that AI research was already years ago bringing us decent spellcheckers, functional machine translations, and visual object recognition, among other accomplishments of modern technology.</p><p>Or that half the world today runs on logistic planners that started life in the 1960s as AI research in automated theorem proving. Yes, your “supply chain” is already AI from end to end. AI didn’t get rid of the drudgery of trucking and manually loading and unloading goods. It got rid of the comfy office job of scheduling.</p><p>In the history of AI goalpost-moving, Agüera y Arcas and Norvig’s contribution is somewhat novel: We’re used to moving the goalposts of “real” AI to make them ever harder to reach. They’ve moved them to say we’ve already passed them.</p><p>The cause of the moving goalposts is more complex: AI is cursed with bad incentives. It lends itself to hype. We might blame this on the grants process and academic pressures to overpromise, or on late capitalism and the way the tech investor class likes to chase after the latest shiny thing in hopes of owning a “disruptive” new technology.</p><p>But I put a lot of the blame on AI’s final curse: Science fiction.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--6-.png" class="kg-image" alt="" width="700" height="700" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--6-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--6-.png 700w"></figure><p>Now, understand me: This is not a criticism of the makers of science fiction; it’s a criticism of its consumers. I have been watching and reading science fiction since I was five years old, and I love it. It’s a popular genre, beloved by millions, if not billions, of people.</p><p>But the ideas people have in their heads about AI, including the people who do AI research, have been so thoroughly colonized by fictitious machines that it has become difficult to separate legitimate debates from the dramatic visions of novelists and movie makers.</p><p>Ideas about “artificial general intelligence” or “real” AI owe far more to science fiction than to science. It’s not the responsibility of the Issac Asimovs, the Stanley Kubriks, or the James Camerons of the world to police their imaginations or ours. It is the responsibility of AI professionals — researchers, marketers, investors, and corporate frontmen — to understand and make clear that “<a href="https://en.wikipedia.org/wiki/Positronic_brain?ref=jina-ai-gmbh.ghost.io">positronic brains</a>,” <a href="https://en.wikipedia.org/wiki/HAL_9000?ref=jina-ai-gmbh.ghost.io">HAL 9000</a>, and <a href="https://en.wikipedia.org/wiki/The_Terminator?ref=jina-ai-gmbh.ghost.io">killer robots with inexplicable Austrian accents</a> have no place in engineering.</p><p>We move the goalposts in AI because every accomplishment ends up disappointing us when it doesn’t live up to our vision of AI. Rational beings might interrogate their visions of AI rather than move around the goalposts and say: “This time, it’s different!”</p><p>Humans have deep prejudices that they struggle to recognize. Agüera y Arcas and Norvig recognize this in their mention of the “<a href="https://en.wikipedia.org/wiki/Being_There?ref=jina-ai-gmbh.ghost.io">Chauncey Gardiner effect</a>.” For younger readers who don’t know the works of Peter Sellers and Hal Ashby, we might also call this the “Rita Leeds effect” after Charlize Theron’s role in <a href="https://en.wikipedia.org/wiki/Arrested_Development_(season_3)?ref=jina-ai-gmbh.ghost.io">season three of <em>Arrested Development</em></a>. It’s the same schtick.</p><p>Until the 1970s, there were serious social scientists who believed that black people, at least American ones, were systematically intellectually stunted and pointed to the way they spoke English as proof. Even today, plenty of people view African American Vernacular English (usually abbreviated as AAVE because who has time to spell that out?) as “broken” or “defective” or indicative of poor education.</p><p>Among linguists, no one of any importance today thinks that. We recognize AAVE as a fully functional variant form of English, just as well-suited to accurate and effective communication as standard English or any of its other variants. It has no relationship to cognitive abilities whatsoever.</p><p>Yet, the prejudice against it remains.</p><p>When we evaluate ChatGPT as “real” AI, or at least on the path to “real” AI, we are demonstrating the same prejudice, turned around. That should give us some pause. It should lead us to ask if <em>anything</em> we think makes software intelligent is really intelligence or just manipulating our prejudices. Is there any way to objectively judge intelligence at all? We may never be able to fully dismiss our prejudices.</p><p>It does not take a lot of interaction with ChatGPT to see it fall short of our science-fiction-based visions for AI. It can do some neat tricks, maybe even some useful ones, but it’s not <a href="https://en.wikipedia.org/wiki/WALL-E?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">WALL-E</a>, or <a href="https://en.wikipedia.org/wiki/C-3PO?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">C-3PO</a>, or <a href="https://en.wikipedia.org/wiki/Data_(Star_Trek)?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Commander Data</a>. It’s not even Arnold Schwarzenegger's iconic but not terribly verbal T-800, although I don’t doubt you could readily integrate ChatGPT with a text-to-speech model that has a thick Austrian accent and pretend.</p><p>Changing the labels on things doesn’t change things, at least not in any simple way. We could move the goalposts for “artificial general intelligence” in such a way that we could say we’ve already accomplished that, but that will not make today’s AI models more satisfactory to people looking for HAL 9000. It would just render the label “general intelligence” meaningless.</p><p>People would still want something we can’t give them. Something we might never be able to give them.</p><h2 id="are-humans-still-special">Are Humans Still Special?</h2><p>Among the strawmen Agüera y Arcas and Norvig take on in a whole section is <em>“Human (Or Biological) Exceptionalism.”</em> People believe all kinds of things, but unless you count religious notions of the “soul”, it is hard to believe this is a commonly held position among AI professionals. More likely, most of them don’t think about it at all.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--5-.png" class="kg-image" alt="" width="700" height="700" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--5-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/LINES-ALBUM-COVER-LIGHT-POP-MUSIC--5-.png 700w"></figure><p>The lesson we should be learning from recent AI is that it is difficult to identify a human skill that is absolutely impossible for a machine to perform. We cannot make AI models do everything a human can do yet, but we can no longer rule anything out.</p><p>This realization should end some of the bad ideas we have inherited from the past. We know today that animals have languages much like our own and that computers can learn language with a shocking facility. Noam Chomsky may not be dead yet, but ChatGPT has put the final nails in the coffin of his life’s work.</p><p>We have known since Galileo that humanity does not live in the center of the universe. We have known for roughly two centuries that the universe existed for billions of years before people. We have known for some time that humans are not made special by the use of reason and language, as Descartes thought, as we find both among animals and note their frequent absence in humans.</p><p>AI research is removing the idea that humans are special because of some trick we can do, but that does not remove the specialness of humanity. Consider that we celebrate people who can run a mile in under four minutes. Yet, my 20-year-old cheap French-made car can do a mile in about 30 seconds if I really put my foot on the pedal.</p><p>We care about human accomplishment in ways that differ from how we care about pure performance benchmarks. We’ll still prefer our human performers over AI, for the same reason I don’t win Olympic medals with my old Citroën.</p><p>We imagine AI taking away the drudgery of human life, but we do not yet have robots that can restock shelves at Walmart. On the other hand, we now have AI models that can sing like <a href="https://en.wikipedia.org/wiki/%C3%89dith_Piaf?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Edith Piaf</a> and, if someone really tried, could probably dance like <a href="https://en.wikipedia.org/wiki/Shakira?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Shakira </a>or play the guitar like <a href="https://en.wikipedia.org/wiki/Jimi_Hendrix?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Jimi Hendrix</a>.</p><p>This is progress. It’s an accomplishment of significant value. But it’s not the AI we wanted. Unless we rethink the whole program of AI research, we’ll need to move the goalposts again.</p><h2 id="real-ai-instead-of-%E2%80%9Creal%E2%80%9D-ai">Real AI instead of “Real” AI</h2><p>Jina AI is a business. We don’t sell fantasy, we sell AI models. There’s no place for “artificial general intelligence” in what we do. We may love science fiction, but we deal in science fact.</p><p>“Past performance is not a guarantee of future returns.” Maybe it’ll be different this time. Maybe we won’t dismiss our successes as not “real” intelligence. Maybe we’ll get over our science fiction dreams for once. Maybe this hype cycle won’t lead to another AI Winter.</p><p>Maybe, but I won’t bet on it.</p><p>Someday, we might have something that looks more like our visions of “real” AI. Perhaps in 50 years? 100? History does not encourage optimism about it. But regardless, it won’t happen in a timeframe that pays any bills.</p><p>Moving around the goalposts of AI won’t change that.</p><p>Our interest is business cases. We want AI to add to your bottom line. At Jina AI, we want to hear about your business processes and discuss how really existing AI models can fit into them. We know the limits of this technology intimately, but we also know its genuine potential.</p><p>Contact us via our&nbsp;<a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">website</a>&nbsp;or join our&nbsp;<a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">community on Discord</a>&nbsp;to talk about what <em>real </em>AI can do for your business.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI - Your Portal to Multimodal AI</div><div class="kg-bookmark-description">Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. Navigating enterprise mazes &amp; startup vibes. Where's search headed next?</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">September 01, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/generativejina_mad_men_tv_serie_a_girl_is_looking_at_a_selectio_42a73443-5825-4394-a7ef-9c08294d29b6.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/fine-tuning-gpt-3-5-turbo-a-costly-mirage" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 25, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_modern_geometric_abstract_pattern_featuring_pu_24e4060e-dc76-4186-afb7-94d18d266b41.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/the-boundless-horizon-of-ai-its-not-just-about-the-size" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Beyond Sheer Scale: Navigating AI Alignment Odyssey</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">AI’s march forward isn't just about bigger models, but ensuring they harmonize with human values. Journey with us through the challenges, revelations, and aspirations at the forefront of AI safety and ethics.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">August 24, 2023 • 8 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_retrowave_sabattier_filter_sanriocore_in_the_sty_7881ce67-ea8f-417f-a204-bd101a3f58c0.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>AI-Powered 3D Asset Management with Neural Search</title><meta charset="utf-8"><meta name="title" content="AI-Powered 3D Asset Management with Neural Search"><meta name="description" content="Using Asset Ovi, a 3D model repository based on Neural Search, you can just upload a 3D model to search for similar ones, or click on an existing model to find other models like it."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/asset_ovi"><meta property="og:title" content="AI-Powered 3D Asset Management with Neural Search"><meta property="og:description" content="Using Asset Ovi, a 3D model repository based on Neural Search, you can just upload a 3D model to search for similar ones, or click on an existing model to find other models like it."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Copy-of-EAH-Template.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/asset_ovi"><meta property="twitter:title" content="AI-Powered 3D Asset Management with Neural Search"><meta property="twitter:description" content="Using Asset Ovi, a 3D model repository based on Neural Search, you can just upload a 3D model to search for similar ones, or click on an existing model to find other models like it."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Copy-of-EAH-Template.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>AI-Powered 3D Asset Management with Neural Search</title><meta charset="utf-8"><meta name="title" content="AI-Powered 3D Asset Management with Neural Search"><meta name="description" content="Using Asset Ovi, a 3D model repository based on Neural Search, you can just upload a 3D model to search for similar ones, or click on an existing model to find other models like it."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/asset_ovi"><meta property="og:title" content="AI-Powered 3D Asset Management with Neural Search"><meta property="og:description" content="Using Asset Ovi, a 3D model repository based on Neural Search, you can just upload a 3D model to search for similar ones, or click on an existing model to find other models like it."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Copy-of-EAH-Template.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/asset_ovi"><meta property="twitter:title" content="AI-Powered 3D Asset Management with Neural Search"><meta property="twitter:description" content="Using Asset Ovi, a 3D model repository based on Neural Search, you can just upload a 3D model to search for similar ones, or click on an existing model to find other models like it."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Copy-of-EAH-Template.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">AI-Powered 3D Asset Management with Neural Search</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Using Asset Ovi, a 3D model repository based on Neural Search, you can just upload a 3D model to search for similar ones, or click on an existing model to find other models like it.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image--1-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/SaZhang.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Haiwei Li, Sa Zhang</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 16, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Imagine that as a video game designer, &nbsp;you want to use a 3D dragon model in your game. Before, you could do this in two ways:</p><ol><li>Make complex 3D models by yourself or take photos of dragon models from multiple angles.</li><li>Go to a 3D model repository to look for a dragon, but then you would have to search using keywords and hope the uploader had put it in their description. </li></ol><p>This is fine if you're willing to look through hundreds, maybe thousands of 3D dragons. But if you want a specific kind of dragon? An Asian-style dragon instead of a Western? Something more snake-like? Or more dinosaur-like? You might spend hours hunting for good matches to what you have in mind.</p><p>Now, by using <a href="https://assetovi.yahaha.com/?utm_campaign=jina-news&amp;utm_source=jina&amp;utm_medium=post">Asset Ovi</a>, a 3D model repository based on <a href="http://jina.ai/?ref=jina-ai-gmbh.ghost.io">Neural Search</a>, you can just upload a 3D model to search for similar ones, or click on an existing model to find other models like it.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Asset_Ovi_big-1.png" class="kg-image" alt="" width="1600" height="895" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Asset_Ovi_big-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Asset_Ovi_big-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Asset_Ovi_big-1.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>Despite the rapidly growing demand for 3D models from game designers, there is no mature solution for finding 3D assets stored in repositories. Most search engines are text-based: They can only match text queries with text descriptions and keyword lists. They say a picture is worth a thousand words, so a 3D model must be worth at least as many. Keyword lists and text descriptions are rarely more than a sentence or two. They could never capture all the information about a model that is relevant to a search.</p><p>Even the most experienced user can easily spend hours hunting in asset repositories, without ever finding what they need and without knowing if what they are looking for is or is not there.</p><p>To solve this problem, we have deployed Neural Search in Asset Ovi, using Jina AI's ground-breaking multimodal information retrieval framework to compare 3D models to other 3D models, without needing detailed descriptions or thousands of keywords.</p><p>Asset Ovi's Neural Search technology supports two search methods:</p><ol><li>Upload model search. Users upload their own 3D models, from which we extract 3D mesh data and then use Jina's Neural Search technology to identify similar models based. The similarity is not based on gross shapes and colors but on AI-driven recognition of what kind of thing the mesh is modeling.</li><li>Search based on models already stored in Asset Ovi. This proceeds the same way that the user upload search does, except it receives a model ID from the user and works with the already stored model matching it.</li></ol><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/02/ovi_video.mp4" poster="https://img.spacergif.org/v1/1920x1080/0a/spacer.png" width="1920" height="1080" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/02/Assetovi-1.png') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>As shown in the above video, uploading a 3D model retrieves similar models.</figcaption></figure><p>Before integrating Jina's Neural Search solution, we spent a lot of time and labor manually tagging models and providing them with descriptions for our text-based search system. Jina cooperated with us in extending its already mature image search technology to 3D models.</p><p>The most critical challenge is to develop an efficient 3D model representation method and similarity matching algorithm to ensure the stable representation and classification of any 3D mode.</p><p>For this reason, Jina AI's team of engineers <a href="https://cloud.jina.ai/executor/1mfkv18z?ref=jina-ai-gmbh.ghost.io">developed technology for encoding 3D models into vectors for high-level understanding</a>.</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://lh4.googleusercontent.com/3rmqR7CaLNJ4-N0sZN5z_62xGwBSLYhvSKsExo9bo16NPUClJKYXtBBYbSVLymGUDYFKOjI0xI_QcyoQqVqf8VWjUgoZMzlbka7ScfSpHAUTCVGBrlMNUMl7Axipbv_yOzkBPnmJ8gLw46hgntCAMZI" class="kg-image" alt="" width="624" height="336"></figure><p>The business process of model search can be roughly divided into the following processes.</p><ol><li><strong>Load 3D model:</strong> The 3D model is loaded (supported by GLB, GLTF, and other formats), and the point clouds are extracted and preprocessed.</li><li><strong>Feature Extraction:</strong> To output a feature vector from 3D mesh data, we use the PointConv model.</li><li><strong>Similarity retrieval:</strong> normalized feature vectors are indexed into the PostgreSQL database, and the HNSW algorithm is used to find high-dimensional vector similarity in a given dataset.</li></ol><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://lh4.googleusercontent.com/tFnoEQS1sfAyCQgwhhTnqZ0YA0FBYQ-GRuSHrlRgFezlhU4LqRY-_kEEFyqwQMJLtEGWmwO5dRz5p5QQo_OpfO3elvfSUf7Hh_NbNEOCKaHEPpN8QqWtFc8cPA82AWte1u01JAfiZQji5StDaP1xRf0" class="kg-image" alt="" width="624" height="204"></figure><p>After building the whole process, we can use the tools provided by Jina to export the Kubernetes deployment file with one click and then deploy it directly on a cloud service or cluster.</p><p>YAHAHA currently has hundreds of thousands of creator users. To make it easier for users of our huge model repository to find exactly what they are looking for, we have made the following efforts.</p><ol><li><strong>3D direct preview</strong>: Asset repositories like Unity Asset Store and CGTrader display objects in 2D, making it hard to see how they will render as 3D objects. Asset Ovi now gives users a real 3D preview, without compromising model creators’ intellectual property by transmitting the full mesh to the viewer’s browser.</li></ol><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/UQ9NErEllj4cJmkiL9hV_hofkBQSULFgh2NOSe_Cvy9rY4Ej5Cbp2ilqa2lXLpeilKtTnwjG4d6gReaorwLBfXCbwtqEn3eUIHFx9XNk8Kn1e3Z-vXcQ0-HT7AhZzXvh3F8KuErzj-AMWbU5u-CvW64" class="kg-image" alt="" width="557" height="311"></figure><ol><li><strong>Rendering effect</strong>: In order to ensure that what you see is what you get, we made sure that website rendering matched the client rendering as closely as possible, especially for Unity.</li><li><strong>Neural Search</strong>: We have indexed millions of models. Thanks to Jina, we no longer have to manually tag all models. Our searches are performed in an AI-driven way that no longer needs keywords.</li></ol><p>Neural Search empowers Asset Ovi users by giving them powerful search capabilities, greatly improving their efficiency and user experience in finding suitable models. In the future, we will also make Asset Ovi an affiliate program of the Unity Asset Store to help Unity developers efficiently find the relevant materials they need to create games on the Unity Asset Store. We will also cooperate with resource websites such as Sketchfab and CGTrader to help all users, developers, and artists alike, to find the resources they need more easily.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fasset_ovi%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Copy-of-EAH-Template.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Using Asset Ovi, a 3D model repository based on Neural Search, you can just upload a 3D model to search for similar ones, or click on an existing model to find other models like it.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image--1-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/SaZhang.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Haiwei Li, Sa Zhang</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 16, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Imagine that as a video game designer, &nbsp;you want to use a 3D dragon model in your game. Before, you could do this in two ways:</p><ol><li>Make complex 3D models by yourself or take photos of dragon models from multiple angles.</li><li>Go to a 3D model repository to look for a dragon, but then you would have to search using keywords and hope the uploader had put it in their description. </li></ol><p>This is fine if you're willing to look through hundreds, maybe thousands of 3D dragons. But if you want a specific kind of dragon? An Asian-style dragon instead of a Western? Something more snake-like? Or more dinosaur-like? You might spend hours hunting for good matches to what you have in mind.</p><p>Now, by using <a href="https://assetovi.yahaha.com/?utm_campaign=jina-news&amp;utm_source=jina&amp;utm_medium=post">Asset Ovi</a>, a 3D model repository based on <a href="http://jina.ai/?ref=jina-ai-gmbh.ghost.io">Neural Search</a>, you can just upload a 3D model to search for similar ones, or click on an existing model to find other models like it.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Asset_Ovi_big-1.png" class="kg-image" alt="" width="1600" height="895" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Asset_Ovi_big-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Asset_Ovi_big-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Asset_Ovi_big-1.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>Despite the rapidly growing demand for 3D models from game designers, there is no mature solution for finding 3D assets stored in repositories. Most search engines are text-based: They can only match text queries with text descriptions and keyword lists. They say a picture is worth a thousand words, so a 3D model must be worth at least as many. Keyword lists and text descriptions are rarely more than a sentence or two. They could never capture all the information about a model that is relevant to a search.</p><p>Even the most experienced user can easily spend hours hunting in asset repositories, without ever finding what they need and without knowing if what they are looking for is or is not there.</p><p>To solve this problem, we have deployed Neural Search in Asset Ovi, using Jina AI's ground-breaking multimodal information retrieval framework to compare 3D models to other 3D models, without needing detailed descriptions or thousands of keywords.</p><p>Asset Ovi's Neural Search technology supports two search methods:</p><ol><li>Upload model search. Users upload their own 3D models, from which we extract 3D mesh data and then use Jina's Neural Search technology to identify similar models based. The similarity is not based on gross shapes and colors but on AI-driven recognition of what kind of thing the mesh is modeling.</li><li>Search based on models already stored in Asset Ovi. This proceeds the same way that the user upload search does, except it receives a model ID from the user and works with the already stored model matching it.</li></ol><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/02/ovi_video.mp4" poster="https://img.spacergif.org/v1/1920x1080/0a/spacer.png" width="1920" height="1080" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/02/Assetovi-1.png') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>As shown in the above video, uploading a 3D model retrieves similar models.</figcaption></figure><p>Before integrating Jina's Neural Search solution, we spent a lot of time and labor manually tagging models and providing them with descriptions for our text-based search system. Jina cooperated with us in extending its already mature image search technology to 3D models.</p><p>The most critical challenge is to develop an efficient 3D model representation method and similarity matching algorithm to ensure the stable representation and classification of any 3D mode.</p><p>For this reason, Jina AI's team of engineers <a href="https://cloud.jina.ai/executor/1mfkv18z?ref=jina-ai-gmbh.ghost.io">developed technology for encoding 3D models into vectors for high-level understanding</a>.</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://lh4.googleusercontent.com/3rmqR7CaLNJ4-N0sZN5z_62xGwBSLYhvSKsExo9bo16NPUClJKYXtBBYbSVLymGUDYFKOjI0xI_QcyoQqVqf8VWjUgoZMzlbka7ScfSpHAUTCVGBrlMNUMl7Axipbv_yOzkBPnmJ8gLw46hgntCAMZI" class="kg-image" alt="" width="624" height="336"></figure><p>The business process of model search can be roughly divided into the following processes.</p><ol><li><strong>Load 3D model:</strong> The 3D model is loaded (supported by GLB, GLTF, and other formats), and the point clouds are extracted and preprocessed.</li><li><strong>Feature Extraction:</strong> To output a feature vector from 3D mesh data, we use the PointConv model.</li><li><strong>Similarity retrieval:</strong> normalized feature vectors are indexed into the PostgreSQL database, and the HNSW algorithm is used to find high-dimensional vector similarity in a given dataset.</li></ol><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://lh4.googleusercontent.com/tFnoEQS1sfAyCQgwhhTnqZ0YA0FBYQ-GRuSHrlRgFezlhU4LqRY-_kEEFyqwQMJLtEGWmwO5dRz5p5QQo_OpfO3elvfSUf7Hh_NbNEOCKaHEPpN8QqWtFc8cPA82AWte1u01JAfiZQji5StDaP1xRf0" class="kg-image" alt="" width="624" height="204"></figure><p>After building the whole process, we can use the tools provided by Jina to export the Kubernetes deployment file with one click and then deploy it directly on a cloud service or cluster.</p><p>YAHAHA currently has hundreds of thousands of creator users. To make it easier for users of our huge model repository to find exactly what they are looking for, we have made the following efforts.</p><ol><li><strong>3D direct preview</strong>: Asset repositories like Unity Asset Store and CGTrader display objects in 2D, making it hard to see how they will render as 3D objects. Asset Ovi now gives users a real 3D preview, without compromising model creators’ intellectual property by transmitting the full mesh to the viewer’s browser.</li></ol><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/UQ9NErEllj4cJmkiL9hV_hofkBQSULFgh2NOSe_Cvy9rY4Ej5Cbp2ilqa2lXLpeilKtTnwjG4d6gReaorwLBfXCbwtqEn3eUIHFx9XNk8Kn1e3Z-vXcQ0-HT7AhZzXvh3F8KuErzj-AMWbU5u-CvW64" class="kg-image" alt="" width="557" height="311"></figure><ol><li><strong>Rendering effect</strong>: In order to ensure that what you see is what you get, we made sure that website rendering matched the client rendering as closely as possible, especially for Unity.</li><li><strong>Neural Search</strong>: We have indexed millions of models. Thanks to Jina, we no longer have to manually tag all models. Our searches are performed in an AI-driven way that no longer needs keywords.</li></ol><p>Neural Search empowers Asset Ovi users by giving them powerful search capabilities, greatly improving their efficiency and user experience in finding suitable models. In the future, we will also make Asset Ovi an affiliate program of the Unity Asset Store to help Unity developers efficiently find the relevant materials they need to create games on the Unity Asset Store. We will also cooperate with resource websites such as Sketchfab and CGTrader to help all users, developers, and artists alike, to find the resources they need more easily.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fasset_ovi%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Auto-GPT Unmasked: The Hype and Hard Truths of Its Production Pitfalls</title><meta charset="utf-8"><meta name="title" content="Auto-GPT Unmasked: The Hype and Hard Truths of Its Production Pitfalls"><meta name="description" content="Auto-GPT: A groundbreaking project or just another overhyped AI experiment? In this blog post, we unravel the truth behind the buzz and reveal the limitations that make this project unsuitable for real-world applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/auto-gpt-unmasked-hype-hard-truths-production-pitfalls"><meta property="og:title" content="Auto-GPT Unmasked: The Hype and Hard Truths of Its Production Pitfalls"><meta property="og:description" content="Auto-GPT: A groundbreaking project or just another overhyped AI experiment? In this blog post, we unravel the truth behind the buzz and reveal the limitations that make this project unsuitable for real-world applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/generativejina_a_hq_illustration_of_Divide-and-Conquer_algorith_61aea026-11fe-4595-83b8-94a6bf1dcff2-1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/auto-gpt-unmasked-hype-hard-truths-production-pitfalls"><meta property="twitter:title" content="Auto-GPT Unmasked: The Hype and Hard Truths of Its Production Pitfalls"><meta property="twitter:description" content="Auto-GPT: A groundbreaking project or just another overhyped AI experiment? In this blog post, we unravel the truth behind the buzz and reveal the limitations that make this project unsuitable for real-world applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/generativejina_a_hq_illustration_of_Divide-and-Conquer_algorith_61aea026-11fe-4595-83b8-94a6bf1dcff2-1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Auto-GPT Unmasked: The Hype and Hard Truths of Its Production Pitfalls</title><meta charset="utf-8"><meta name="title" content="Auto-GPT Unmasked: The Hype and Hard Truths of Its Production Pitfalls"><meta name="description" content="Auto-GPT: A groundbreaking project or just another overhyped AI experiment? In this blog post, we unravel the truth behind the buzz and reveal the limitations that make this project unsuitable for real-world applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/auto-gpt-unmasked-hype-hard-truths-production-pitfalls"><meta property="og:title" content="Auto-GPT Unmasked: The Hype and Hard Truths of Its Production Pitfalls"><meta property="og:description" content="Auto-GPT: A groundbreaking project or just another overhyped AI experiment? In this blog post, we unravel the truth behind the buzz and reveal the limitations that make this project unsuitable for real-world applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/generativejina_a_hq_illustration_of_Divide-and-Conquer_algorith_61aea026-11fe-4595-83b8-94a6bf1dcff2-1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/auto-gpt-unmasked-hype-hard-truths-production-pitfalls"><meta property="twitter:title" content="Auto-GPT Unmasked: The Hype and Hard Truths of Its Production Pitfalls"><meta property="twitter:description" content="Auto-GPT: A groundbreaking project or just another overhyped AI experiment? In this blog post, we unravel the truth behind the buzz and reveal the limitations that make this project unsuitable for real-world applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/generativejina_a_hq_illustration_of_Divide-and-Conquer_algorith_61aea026-11fe-4595-83b8-94a6bf1dcff2-1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Auto-GPT Unmasked: The Hype and Hard Truths of Its Production Pitfalls</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Auto-GPT: A groundbreaking project or just another overhyped AI experiment? In this blog post, we unravel the truth behind the buzz and reveal the limitations that make this project unsuitable for real-world applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 13, 2023 • 13 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The tech world has recently been abuzz with the astounding rise of Auto-GPT, an experimental open-source application built on the cutting-edge GPT-4 language model. In a mere seven days, this project has skyrocketed to fame, amassing an incredible 44,000 GitHub stars and captivating the open-source community. Auto-GPT envisions a future where autonomous AI-driven tasks are the norm, achieved by chaining together Large Language Model (LLM) thoughts.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/Torantulino/Auto-GPT?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - Torantulino/Auto-GPT: An experimental open-source attempt to make GPT-4 fully autonomous.</div><div class="kg-bookmark-description">An experimental open-source attempt to make GPT-4 fully autonomous. - GitHub - Torantulino/Auto-GPT: An experimental open-source attempt to make GPT-4 fully autonomous.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">Torantulino</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/1b07225531431455c927223519d2802a098dee0339467edb06b6d4bd6d5fd41b/Torantulino/Auto-GPT" alt=""></div></a></figure><p>However, every overnight success comes with its fair share of growing pains. As we celebrate Auto-GPT's rapid ascent, it's crucial to take a step back and scrutinize its potential shortcomings. In this article, we will delve deep into the limitations and challenges that this AI wonderkid faces in its pursuit of production readiness. So, fasten your seatbelts and join us on this riveting journey as we navigate the twists and turns on Auto-GPT's path to stardom.</p><h2 id="how-does-auto-gpt-work">How does Auto-GPT work?</h2><p>Auto-GPT has been making waves in the AI world, and for a good reason. It's like giving GPT-based models a memory and a body, allowing them to tackle tasks independently and even learn from their experiences. To help you understand how Auto-GPT works, let's break it down using simple metaphors.</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/04/228855501-2f5777cf-755b-4407-a643-c7299e5b6419.mp4" poster="https://img.spacergif.org/v1/1280x764/0a/spacer.png" width="1280" height="764" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/04/media-thumbnail-ember927.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>The demo video of Auto-GPT (Source: https://github.com/Torantulino/Auto-GPT)</figcaption></figure><p>Imagine Auto-GPT as a resourceful robot. You assign it a mission, and it comes up with a plan to accomplish it. If the mission requires browsing the internet or using new data, Auto-GPT adapts its strategy until the task is complete. It's like having a personal assistant that can handle various tasks, such as analyzing markets, customer service, marketing, finance, and more.</p><p>Four main components make this robot tick:</p><ol><li>Architecture: Auto-GPT is built using the powerful GPT-4 and GPT-3.5 language models, which serve as the robot's brain, helping it think and reason.</li><li>Autonomous Iterations: This is like the robot's ability to learn from its mistakes. Auto-GPT can review its work, build on its previous efforts, and use its history to produce more accurate results.</li><li>Memory Management: Integration with vector databases, a memory storage solution, enables Auto-GPT to preserve context and make better decisions. This is like equipping the robot with a long-term memory to remember past experiences.</li><li>Multi-functionality: Auto-GPT's capabilities, such as file manipulation, web browsing, and data retrieval, make it versatile and set it apart from previous AI advancements. It's like giving the robot multiple skills to handle a broader range of tasks.</li></ol><p>So, Auto-GPT is an AI-powered robot that promises a remarkable range of tasks, learning from its experiences, and continuously improving its performance. However, <strong>it's important to recognize that these enticing prospects may not yet translate into true capabilities that Auto-GPT can deliver.</strong> As we explore its limitations and challenges, we'll focus on the following key areas:</p><ul><li>Sky-High Costs: A Barrier to Task Completion</li><li>Merging Worlds: The Development and Production Conundrum</li><li>The Looping Quagmire: Why Auto-GPT Gets Stuck</li><li>The Vector DB: An Overkill Solution</li><li>The Birth of Agent Mechanisms: A Work in Progress</li></ul><p>By delving into these critical aspects, we'll provide a balanced perspective on Auto-GPT's potential for production readiness.</p><h2 id="sky-high-costs-a-barrier-to-task-completion">Sky-High Costs: A Barrier to Task Completion</h2><p>While Auto-GPT promises remarkable capabilities, one significant obstacle to its adoption in production environments is its prohibitive cost. As tasks are accomplished through a chain of thoughts, each step requires a call to the expensive GPT-4 model, <strong>which often maxes out tokens in order to provide better reasoning and prompting.</strong></p><figure class="kg-card kg-code-card"><pre><code class="language-txt hljs language-plaintext">VUEGPT THOUGHTS: Let's start by checking if there are any updates to VueJS. If there are, we can update to the latest version and proceed. Otherwise, we can move on to creating the TODO list website application.
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Auto-GPT: A groundbreaking project or just another overhyped AI experiment? In this blog post, we unravel the truth behind the buzz and reveal the limitations that make this project unsuitable for real-world applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 13, 2023 • 13 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The tech world has recently been abuzz with the astounding rise of Auto-GPT, an experimental open-source application built on the cutting-edge GPT-4 language model. In a mere seven days, this project has skyrocketed to fame, amassing an incredible 44,000 GitHub stars and captivating the open-source community. Auto-GPT envisions a future where autonomous AI-driven tasks are the norm, achieved by chaining together Large Language Model (LLM) thoughts.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/Torantulino/Auto-GPT?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - Torantulino/Auto-GPT: An experimental open-source attempt to make GPT-4 fully autonomous.</div><div class="kg-bookmark-description">An experimental open-source attempt to make GPT-4 fully autonomous. - GitHub - Torantulino/Auto-GPT: An experimental open-source attempt to make GPT-4 fully autonomous.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">Torantulino</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/1b07225531431455c927223519d2802a098dee0339467edb06b6d4bd6d5fd41b/Torantulino/Auto-GPT" alt=""></div></a></figure><p>However, every overnight success comes with its fair share of growing pains. As we celebrate Auto-GPT's rapid ascent, it's crucial to take a step back and scrutinize its potential shortcomings. In this article, we will delve deep into the limitations and challenges that this AI wonderkid faces in its pursuit of production readiness. So, fasten your seatbelts and join us on this riveting journey as we navigate the twists and turns on Auto-GPT's path to stardom.</p><h2 id="how-does-auto-gpt-work">How does Auto-GPT work?</h2><p>Auto-GPT has been making waves in the AI world, and for a good reason. It's like giving GPT-based models a memory and a body, allowing them to tackle tasks independently and even learn from their experiences. To help you understand how Auto-GPT works, let's break it down using simple metaphors.</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/04/228855501-2f5777cf-755b-4407-a643-c7299e5b6419.mp4" poster="https://img.spacergif.org/v1/1280x764/0a/spacer.png" width="1280" height="764" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/04/media-thumbnail-ember927.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>The demo video of Auto-GPT (Source: https://github.com/Torantulino/Auto-GPT)</figcaption></figure><p>Imagine Auto-GPT as a resourceful robot. You assign it a mission, and it comes up with a plan to accomplish it. If the mission requires browsing the internet or using new data, Auto-GPT adapts its strategy until the task is complete. It's like having a personal assistant that can handle various tasks, such as analyzing markets, customer service, marketing, finance, and more.</p><p>Four main components make this robot tick:</p><ol><li>Architecture: Auto-GPT is built using the powerful GPT-4 and GPT-3.5 language models, which serve as the robot's brain, helping it think and reason.</li><li>Autonomous Iterations: This is like the robot's ability to learn from its mistakes. Auto-GPT can review its work, build on its previous efforts, and use its history to produce more accurate results.</li><li>Memory Management: Integration with vector databases, a memory storage solution, enables Auto-GPT to preserve context and make better decisions. This is like equipping the robot with a long-term memory to remember past experiences.</li><li>Multi-functionality: Auto-GPT's capabilities, such as file manipulation, web browsing, and data retrieval, make it versatile and set it apart from previous AI advancements. It's like giving the robot multiple skills to handle a broader range of tasks.</li></ol><p>So, Auto-GPT is an AI-powered robot that promises a remarkable range of tasks, learning from its experiences, and continuously improving its performance. However, <strong>it's important to recognize that these enticing prospects may not yet translate into true capabilities that Auto-GPT can deliver.</strong> As we explore its limitations and challenges, we'll focus on the following key areas:</p><ul><li>Sky-High Costs: A Barrier to Task Completion</li><li>Merging Worlds: The Development and Production Conundrum</li><li>The Looping Quagmire: Why Auto-GPT Gets Stuck</li><li>The Vector DB: An Overkill Solution</li><li>The Birth of Agent Mechanisms: A Work in Progress</li></ul><p>By delving into these critical aspects, we'll provide a balanced perspective on Auto-GPT's potential for production readiness.</p><h2 id="sky-high-costs-a-barrier-to-task-completion">Sky-High Costs: A Barrier to Task Completion</h2><p>While Auto-GPT promises remarkable capabilities, one significant obstacle to its adoption in production environments is its prohibitive cost. As tasks are accomplished through a chain of thoughts, each step requires a call to the expensive GPT-4 model, <strong>which often maxes out tokens in order to provide better reasoning and prompting.</strong></p><figure class="kg-card kg-code-card"><pre><code class="language-txt">VUEGPT THOUGHTS: Let's start by checking if there are any updates to VueJS. If there are, we can update to the latest version and proceed. Otherwise, we can move on to creating the TODO list website application.
 REASONING: Starting with the most updated and stable version of the framework will ensure our project has the latest features, bug fixes and is properly supported. Creating the TODO list website application is our primary goal, so we can move on to that if there are no updates.
 PLAN: 
 -  Check for VueJS updates
@@ -19,8 +19,8 @@
 -  If no updates, move on to creating the TODO list website application
 CRITICISM: None
 NEXT ACTION:  COMMAND = google ARGUMENTS = {'input': 'VueJS latest version update'}
-Enter 'y' to authorise command, 'y -N' to run N continuous commands, 'n' to exit program, or enter feedback for VueGPT...</code></pre><figcaption>One step of the chain of thoughts for VueGPT: an Auto-GPT created AI that is designed to create website applications using Vue JS</figcaption></figure><p>GPT-4 tokens are far from cheap. According to OpenAI, the GPT-4 model with an 8K context window charges $0.03 per 1,000 tokens for prompts and $0.06 per 1,000 tokens for results. Let's break down the cost of each step in the chain of thoughts, assuming that each action maxes out the context window of 8,000 tokens, with 80% being prompts and 20% being results.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://openai.com/pricing?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Pricing</div><div class="kg-bookmark-description">Simple and flexible. Only pay for what you use.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://openai.com/favicon.ico" alt=""><span class="kg-bookmark-author">Notion</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://openaicom.imgix.net/7ef54590-0045-4fb6-9f03-9643e08f0d94/stangel-2022-0423.jpg?auto=compress%2Cformat&amp;fit=min&amp;fm=jpg&amp;q=80&amp;rect=0%2C540%2C3840%2C2160" alt=""></div></a></figure><p>For 8,000 tokens:</p><ul><li>Prompts (80%): 6,400 tokens</li><li>Results (20%): 1,600 tokens</li></ul><p>Cost of prompts: 6,400 tokens x $0.03/1,000 tokens = $0.192 Cost of results: 1,600 tokens x $0.06/1,000 tokens = $0.096</p><blockquote class="kg-blockquote-alt">Total cost per step: $0.192 + $0.096 = $0.288</blockquote><p>It's not uncommon for Auto-GPT to <strong>take an average of 50 steps to complete a small task.</strong> So, the cost of completing a single task would be:</p><blockquote class="kg-blockquote-alt"><strong>Task cost: 50 steps x $0.288/step = $14.4</strong></blockquote><p>The cost of completing a single task quickly adds up to a considerable amount, making Auto-GPT's current implementation impractical for many users and organizations.</p><h2 id="merging-worlds-the-development-and-production-conundrum">Merging Worlds: The Development and Production Conundrum</h2><p>Upon first glance, one might consider $14.4 a reasonable price to find a Christmas recipe. However, the real issue emerges when you realize you must pay another $14.4 to find a recipe for Thanksgiving by following the same chain of thought again. It becomes clear that generating recipes for Christmas or Thanksgiving should differ by only one "parameter": the festival. The initial $14.4 is spent on developing a method for creating a recipe. Once established, spending the same amount again to adjust the parameter seems illogical. This uncovers a fundamental problem with Auto-GPT: <strong>it fails to separate development and production.</strong></p><p>When using Auto-GPT, <em>the development phase</em> is deemed complete once a goal is achieved and a chain of thoughts is derived. However, there is no way to "<em>serialize</em>" the chain of actions into a reusable function for later use, i.e., <em>bringing it into production</em>. Consequently, users must start from scratch of development each time they want to solve a problem. This inefficiency wastes time and money and presents an unrealistic expectation compared to how we approach problem-solving in the real world.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-23.png" class="kg-image" alt="" width="622" height="417" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-23.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-23.png 622w"><figcaption>Imagine playing Minecraft and building everything from scratch every time you start the game or playing StarCraft and always beginning with your tech tree rooted at the base level. This level of inefficiency would make these games unenjoyable and frustrating.</figcaption></figure><p>Unfortunately, Auto-GPT's current implementation <strong>does not allow this separation of development and production</strong>. It cannot "serialize" the chain of actions into a reusable function, forcing users to pay the full $14.4 again for a seemingly minor change in requirements. This economic inefficiency raises questions about the practicality of Auto-GPT in real-world production environments. It underscores its limitations in providing a sustainable and cost-effective solution for large problem-solving.</p><h2 id="the-looping-quagmire-why-auto-gpt-gets-stuck">The Looping Quagmire: Why Auto-GPT Gets Stuck</h2><p>You might think that if $14.4 can genuinely solve a problem, then it's still worth it. However, many users have reported that Auto-GPT frequently gets stuck in a loop, rendering it unable to solve real problems. Several tweets reveal instances where Auto-GPT remained stuck in a loop even after an entire night of processing chains of thought. These cases highlight the reality that, in many situations, Auto-GPT cannot provide the solution it promises.</p><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 766px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1646486202550304769&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fauto-gpt-unmasked-hype-hard-truths-production-pitfalls%2F&amp;sessionId=fb6d3e6c54a655e9be60ae4cd143af726f8f6a59&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1646486202550304769"></iframe></div>
+Enter 'y' to authorise command, 'y -N' to run N continuous commands, 'n' to exit program, or enter feedback for VueGPT...</code></pre><figcaption>One step of the chain of thoughts for VueGPT: an Auto-GPT created AI that is designed to create website applications using Vue JS</figcaption></figure><p>GPT-4 tokens are far from cheap. According to OpenAI, the GPT-4 model with an 8K context window charges $0.03 per 1,000 tokens for prompts and $0.06 per 1,000 tokens for results. Let's break down the cost of each step in the chain of thoughts, assuming that each action maxes out the context window of 8,000 tokens, with 80% being prompts and 20% being results.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://openai.com/pricing?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Pricing</div><div class="kg-bookmark-description">Simple and flexible. Only pay for what you use.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://openai.com/favicon.ico" alt=""><span class="kg-bookmark-author">Notion</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://openaicom.imgix.net/7ef54590-0045-4fb6-9f03-9643e08f0d94/stangel-2022-0423.jpg?auto=compress%2Cformat&amp;fit=min&amp;fm=jpg&amp;q=80&amp;rect=0%2C540%2C3840%2C2160" alt=""></div></a></figure><p>For 8,000 tokens:</p><ul><li>Prompts (80%): 6,400 tokens</li><li>Results (20%): 1,600 tokens</li></ul><p>Cost of prompts: 6,400 tokens x $0.03/1,000 tokens = $0.192 Cost of results: 1,600 tokens x $0.06/1,000 tokens = $0.096</p><blockquote class="kg-blockquote-alt">Total cost per step: $0.192 + $0.096 = $0.288</blockquote><p>It's not uncommon for Auto-GPT to <strong>take an average of 50 steps to complete a small task.</strong> So, the cost of completing a single task would be:</p><blockquote class="kg-blockquote-alt"><strong>Task cost: 50 steps x $0.288/step = $14.4</strong></blockquote><p>The cost of completing a single task quickly adds up to a considerable amount, making Auto-GPT's current implementation impractical for many users and organizations.</p><h2 id="merging-worlds-the-development-and-production-conundrum">Merging Worlds: The Development and Production Conundrum</h2><p>Upon first glance, one might consider $14.4 a reasonable price to find a Christmas recipe. However, the real issue emerges when you realize you must pay another $14.4 to find a recipe for Thanksgiving by following the same chain of thought again. It becomes clear that generating recipes for Christmas or Thanksgiving should differ by only one "parameter": the festival. The initial $14.4 is spent on developing a method for creating a recipe. Once established, spending the same amount again to adjust the parameter seems illogical. This uncovers a fundamental problem with Auto-GPT: <strong>it fails to separate development and production.</strong></p><p>When using Auto-GPT, <em>the development phase</em> is deemed complete once a goal is achieved and a chain of thoughts is derived. However, there is no way to "<em>serialize</em>" the chain of actions into a reusable function for later use, i.e., <em>bringing it into production</em>. Consequently, users must start from scratch of development each time they want to solve a problem. This inefficiency wastes time and money and presents an unrealistic expectation compared to how we approach problem-solving in the real world.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-23.png" class="kg-image" alt="" width="622" height="417" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-23.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-23.png 622w"><figcaption>Imagine playing Minecraft and building everything from scratch every time you start the game or playing StarCraft and always beginning with your tech tree rooted at the base level. This level of inefficiency would make these games unenjoyable and frustrating.</figcaption></figure><p>Unfortunately, Auto-GPT's current implementation <strong>does not allow this separation of development and production</strong>. It cannot "serialize" the chain of actions into a reusable function, forcing users to pay the full $14.4 again for a seemingly minor change in requirements. This economic inefficiency raises questions about the practicality of Auto-GPT in real-world production environments. It underscores its limitations in providing a sustainable and cost-effective solution for large problem-solving.</p><h2 id="the-looping-quagmire-why-auto-gpt-gets-stuck">The Looping Quagmire: Why Auto-GPT Gets Stuck</h2><p>You might think that if $14.4 can genuinely solve a problem, then it's still worth it. However, many users have reported that Auto-GPT frequently gets stuck in a loop, rendering it unable to solve real problems. Several tweets reveal instances where Auto-GPT remained stuck in a loop even after an entire night of processing chains of thought. These cases highlight the reality that, in many situations, Auto-GPT cannot provide the solution it promises.</p><figure class="kg-card kg-embed-card"><blockquote class="twitter-tweet"><p lang="en" dir="ltr">So I used it multiple times yesterday and here’s what I found… it never completes a task. It just always finds reasons to dig deeper and do more research. It never gets to a point to where it actually completes a single goal requested. I let it go for hours. Lol 😂</p>— Timothy Alan (@_timothyalan_) <a href="https://twitter.com/_timothyalan_/status/1646486202550304769?ref_src=twsrc%5Etfw&amp;ref=jina-ai-gmbh.ghost.io">April 13, 2023</a></blockquote>
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-</figure><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-1" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 779px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-1&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1646293160342204417&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fauto-gpt-unmasked-hype-hard-truths-production-pitfalls%2F&amp;sessionId=fb6d3e6c54a655e9be60ae4cd143af726f8f6a59&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1646293160342204417"></iframe></div>
+</figure><figure class="kg-card kg-embed-card"><blockquote class="twitter-tweet"><p lang="en" dir="ltr">I don't think AutoGPT will solve any problems. Just like I give gpt4 a coding problem and the output code has bug. I feed it back the runtime error, and it will just give the wrong code again and again. Repeating such loop over 20 times 30 times doesn't solve it at all.</p>— Kushiro (@kushirosea) <a href="https://twitter.com/kushirosea/status/1646293160342204417?ref_src=twsrc%5Etfw&amp;ref=jina-ai-gmbh.ghost.io">April 12, 2023</a></blockquote>
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-</figure><h3 id="why-does-auto-gpt-get-stuck-in-these-loops">Why does Auto-GPT get stuck in these loops? </h3><p>To understand this, one can think of Auto-GPT as <strong>relying on GPT to utilize a very simple programming language to solve tasks</strong>. The success of solving a task depends on two factors: the range of functions available in that programming language and the divide-and-conquer ability of GPT, i.e. how well GPT can decompose the task into the predefined programming language. Unfortunately, both of these factors are currently inadequate.</p><p>The limited functions provided by Auto-GPT can be observed in its source code. For example, it offers functions for searching the web, managing memory, interacting with files, executing code, and generating images. However, this restricted set of functions narrows the scope of tasks Auto-GPT can perform effectively. Additionally, the decomposition and reasoning abilities of GPT are still constrained. Although GPT-4 has significantly improved over GPT-3.5, its reasoning capability is far from perfect, further limiting Auto-GPT's problem-solving capacities.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/Torantulino/Auto-GPT/blob/361fed4e3222d5794833ffed8bf8e193f0bae8e3/scripts/prompt.py?ref=jina-ai-gmbh.ghost.io#L22-L42"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Auto-GPT/prompt.py at 361fed4e3222d5794833ffed8bf8e193f0bae8e3 · Torantulino/Auto-GPT</div><div class="kg-bookmark-description">An experimental open-source attempt to make GPT-4 fully autonomous. - Auto-GPT/prompt.py at 361fed4e3222d5794833ffed8bf8e193f0bae8e3 · Torantulino/Auto-GPT</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">Torantulino</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/1ba17d7e601598dd9475f92e9b8c04073f0b6c3ebcdbe7afe30314799feb64cc/Torantulino/Auto-GPT" alt=""></div></a><figcaption>Functions, or commands that can be used by Auto-GPT</figcaption></figure><p>This situation is similar to trying to build a complex game like StarCraft using Python. While Python is a powerful language, decomposing StarCraft into Python functions is extremely challenging. Alternatively, it's like attempting to create an instant messaging app using BASIC, a language lacking the necessary network communication functions. In essence, the combination of a limited function set and GPT-4's constrained reasoning ability results in a looping quagmire that prevents Auto-GPT from delivering the expected outcomes in many cases.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-24.png" class="kg-image" alt="" width="400" height="311"><figcaption>Building StarCraft via Python is probably overshooting. But <strong>Void Infinity</strong>, built on top of the Python PyGame library, is a real-time strategy game where you control the planets of a solar system to build a fleet and destroy your enemy. Source: https://www.pygame.org/project-Void+Infinity-2195-3815.html</figcaption></figure><h3 id="human-vs-gpt-on-divide-and-conquer">Human vs. GPT on divide-and-conquer</h3><p>Divide-and-Conquer is the key to Auto-GPT. While GPT-3.5/4 has shown significant advancements over its predecessors, it still falls short of human-level reasoning capabilities when employing divide-and-conquer techniques. Challenges such as inadequate problem decomposition, difficulty in identifying appropriate base cases, and the lack of adaptability and learning all contribute to the limitations of GPT-3.5/4 in solving complex problems using divide-and-conquer methods.</p><ol><li><strong>Inadequate problem decomposition:</strong> The effectiveness of a divide-and-conquer approach largely depends on the ability to break down complex problems into smaller, manageable subproblems. GPT-3.5/4, despite its improvements, still struggles to consistently and effectively decompose problems in a manner that allows for efficient and accurate solutions. Human reasoning can often identify multiple ways to decompose a problem, while GPT-3.5/4 may not have the same level of adaptability or creativity.</li><li><strong>Difficulty in identifying appropriate base cases:</strong> Humans can intuitively choose appropriate ones that lead to efficient solutions. In contrast, GPT-3.5/4 may struggle to identify the most effective base cases for a given problem, which can significantly impact the overall efficiency and accuracy of the divide-and-conquer process.</li><li><strong>Insufficient understanding of problem context: </strong>While humans can leverage their domain knowledge and contextual understanding to tackle complex problems better, GPT-3.5/4 is limited by its pre-trained knowledge and may lack the necessary context to efficiently solve certain problems using divide-and-conquer techniques.</li><li><strong>Handling overlapping subproblems:</strong> Humans can often recognize when solving overlapping subproblems and strategically reuse previously computed solutions. GPT-3.5/4, on the other hand, may not always have the same level of awareness and may end up redundantly solving the same subproblems multiple times, leading to inefficient solutions.</li></ol><h2 id="the-vector-db-an-overkill-solution">The Vector DB: An Overkill Solution</h2><p>Auto-GPT relies on vector databases for faster k-nearest neighbor (kNN) searches. These databases retrieve earlier chains of thoughts, incorporating them into the current query context for GPT to provide a memory effect. However, given Auto-GPT's constraints and limitations, this approach has been criticized as excessive and unnecessarily resource-intensive.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/Torantulino/Auto-GPT/blob/master/scripts/memory/__init__.py?ref=jina-ai-gmbh.ghost.io#L30"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Auto-GPT/__init__.py at master · Torantulino/Auto-GPT</div><div class="kg-bookmark-description">An experimental open-source attempt to make GPT-4 fully autonomous. - Auto-GPT/__init__.py at master · Torantulino/Auto-GPT</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">Torantulino</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/6b0ba3ca3485bef05d5f5e9e1b057328e06e68d8de74c8f20b0f215846c38430/Torantulino/Auto-GPT" alt=""></div></a></figure><p>The main argument against using vector databases stems from the cost constraints associated with Auto-GPT's chain of thoughts. A 50-step chain of thoughts would cost 14.4 dollars, while a 1000-step chain would cost significantly more. As a result, the memory size or length of the chain of thought rarely exceeds four digits. In such cases, an exhaustive search (i.e., the dot product between a 256-dim vector and a 10,000 x 256 matrix) for the nearest neighbor proves to be sufficiently efficient, taking less than one second to complete. In contrast, each GPT-4 call takes approximately 10 seconds to process, making the system GPT-bound rather than database-bound.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://jina.ai/news/benchmark-vector-search-databases-with-one-million-data/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Benchmark Vector Search Databases with One Million Data</div><div class="kg-bookmark-description">In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here’s a comprehensive benchmark to help guide you.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--33-.png" alt=""></div></a><figcaption>Exhaustive search over one million vectors takes 2.7s. And how often can the "long memory" in Auto-GPT be longer than one million?</figcaption></figure><p>Although vector databases may offer some advantages in specific scenarios, their implementation within the Auto-GPT system for accelerating kNN "long memory" searches appears to be an unnecessary extravagance and an overkill solution. The primary justification for using vector databases in this context seems to be the user-friendly sugar syntax available out-of-the-box.</p><h2 id="the-birth-of-agent-mechanisms-a-work-in-progress">The Birth of Agent Mechanisms: A Work in Progress</h2><p>Auto-GPT introduces a very intriguing concept by allowing the spawning of agents to delegate tasks. However, this mechanism is still in its early stages, and its potential remains largely untapped. There are several ways to enhance and expand upon the current agent system, opening up new possibilities for more efficient and dynamic interactions.</p><p>One potential improvement is the introduction of <strong>asynchronous agents.</strong> By incorporating <code>async-await</code> patterns, agents can operate concurrently without blocking one another, significantly improving the overall efficiency and responsiveness of the system. This concept draws inspiration from modern programming paradigms that have adopted asynchronous methods to manage multiple tasks simultaneously.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-25.png" class="kg-image" alt="" width="1200" height="630" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-25.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-25.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-25.png 1200w" sizes="(min-width: 720px) 720px"><figcaption>Using async agents can improve efficiency significantly. Source: https://scoutapm.com/blog/async-javascript</figcaption></figure><p>Another promising direction is enabling <strong>intercommunication between agents</strong>. By allowing agents to communicate and collaborate, they can work together to solve complex problems more effectively. This approach resembles the concept of <a href="https://en.wikipedia.org/wiki/Inter-process_communication?ref=jina-ai-gmbh.ghost.io">IPC in programming</a>, where multiple threads/processes can share information and resources to achieve a common goal.</p><h3 id="generative-agents-are-the-future">Generative agents are the future</h3><p>As the GPT-powered agent continues to evolve, the future seems bright for this innovative approach. New research, such as the paper "Generative Agents: Interactive Simulacra of Human Behavior" by Park et al., highlights the potential of agent-based systems in simulating believable human behavior. Generative agents, as proposed in the paper, can interact in complex and engaging ways, forming opinions, initiating conversations, and even autonomously planning and attending events. This work further supports the argument that agent mechanisms have a promising future in AI development.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2304.03442?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Generative Agents: Interactive Simulacra of Human Behavior</div><div class="kg-bookmark-description">Believable proxies of human behavior can empower interactive applicationsranging from immersive environments to rehearsal spaces for interpersonalcommunication to prototyping tools. In this paper, we introduce generativeagents--computational software agents that simulate believable human behavior…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Joon Sung Park</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/1681120489528.gif" class="kg-image" alt="" width="800" height="450" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/1681120489528.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/1681120489528.gif 800w" sizes="(min-width: 720px) 720px"></figure><p>Auto-GPT can unlock new possibilities for more efficient and dynamic problem-solving capabilities by embracing the paradigm shift towards asynchronous programming and fostering inter-agent communication. Incorporating the architectural and interaction patterns introduced in the "Generative Agents" paper can lead to a fusion of large language models with computational, interactive agents. This combination has the potential to revolutionize how tasks are delegated and executed within AI frameworks and enable more believable simulations of human behavior. The development and exploration of agent systems can contribute significantly to advancing AI applications, providing more robust and dynamic solutions to complex problems.</p><h2 id="conclusion">Conclusion</h2><p>In conclusion, the buzz surrounding Auto-GPT raises important questions about the state of AI research and the role of public understanding in driving hype around emerging technologies. As we have demonstrated, Auto-GPT's limitations in reasoning capabilities, the overkill use of vector databases, and the early-stage development of agent mechanisms reveal that it is far from being a practical solution. Yet, it has managed to capture the general public's imagination, who may lack a deep understanding of its inner workings.</p><p>The hype around Auto-GPT serves as a sobering reminder of how shallow understanding can lead to inflated expectations, ultimately culminating in a distorted perception of AI's true capabilities. As a society, we must be vigilant in questioning the narratives that surround emerging technologies and strive to foster critical thinking and informed discussions.</p><p>That said, Auto-GPT does point to a promising direction for the future of AI: generative agent systems. As we move forward, let us learn from the lessons of the Auto-GPT hype and focus on nurturing a more nuanced and informed dialogue around AI research. By doing so, we can harness the transformative power of generative agent systems and continue to push the boundaries of AI capabilities, shaping a future where technology truly benefits humanity.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Insights</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fauto-gpt-unmasked-hype-hard-truths-production-pitfalls%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. 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Where's search headed next?</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">September 01, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/generativejina_mad_men_tv_serie_a_girl_is_looking_at_a_selectio_42a73443-5825-4394-a7ef-9c08294d29b6.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/fine-tuning-gpt-3-5-turbo-a-costly-mirage" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 25, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_modern_geometric_abstract_pattern_featuring_pu_24e4060e-dc76-4186-afb7-94d18d266b41.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+</figure><h3 id="why-does-auto-gpt-get-stuck-in-these-loops">Why does Auto-GPT get stuck in these loops? </h3><p>To understand this, one can think of Auto-GPT as <strong>relying on GPT to utilize a very simple programming language to solve tasks</strong>. The success of solving a task depends on two factors: the range of functions available in that programming language and the divide-and-conquer ability of GPT, i.e. how well GPT can decompose the task into the predefined programming language. Unfortunately, both of these factors are currently inadequate.</p><p>The limited functions provided by Auto-GPT can be observed in its source code. For example, it offers functions for searching the web, managing memory, interacting with files, executing code, and generating images. However, this restricted set of functions narrows the scope of tasks Auto-GPT can perform effectively. Additionally, the decomposition and reasoning abilities of GPT are still constrained. Although GPT-4 has significantly improved over GPT-3.5, its reasoning capability is far from perfect, further limiting Auto-GPT's problem-solving capacities.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/Torantulino/Auto-GPT/blob/361fed4e3222d5794833ffed8bf8e193f0bae8e3/scripts/prompt.py?ref=jina-ai-gmbh.ghost.io#L22-L42"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Auto-GPT/prompt.py at 361fed4e3222d5794833ffed8bf8e193f0bae8e3 · Torantulino/Auto-GPT</div><div class="kg-bookmark-description">An experimental open-source attempt to make GPT-4 fully autonomous. - Auto-GPT/prompt.py at 361fed4e3222d5794833ffed8bf8e193f0bae8e3 · Torantulino/Auto-GPT</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">Torantulino</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/1ba17d7e601598dd9475f92e9b8c04073f0b6c3ebcdbe7afe30314799feb64cc/Torantulino/Auto-GPT" alt=""></div></a><figcaption>Functions, or commands that can be used by Auto-GPT</figcaption></figure><p>This situation is similar to trying to build a complex game like StarCraft using Python. While Python is a powerful language, decomposing StarCraft into Python functions is extremely challenging. Alternatively, it's like attempting to create an instant messaging app using BASIC, a language lacking the necessary network communication functions. In essence, the combination of a limited function set and GPT-4's constrained reasoning ability results in a looping quagmire that prevents Auto-GPT from delivering the expected outcomes in many cases.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-24.png" class="kg-image" alt="" width="400" height="311"><figcaption>Building StarCraft via Python is probably overshooting. But <strong>Void Infinity</strong>, built on top of the Python PyGame library, is a real-time strategy game where you control the planets of a solar system to build a fleet and destroy your enemy. Source: https://www.pygame.org/project-Void+Infinity-2195-3815.html</figcaption></figure><h3 id="human-vs-gpt-on-divide-and-conquer">Human vs. GPT on divide-and-conquer</h3><p>Divide-and-Conquer is the key to Auto-GPT. While GPT-3.5/4 has shown significant advancements over its predecessors, it still falls short of human-level reasoning capabilities when employing divide-and-conquer techniques. Challenges such as inadequate problem decomposition, difficulty in identifying appropriate base cases, and the lack of adaptability and learning all contribute to the limitations of GPT-3.5/4 in solving complex problems using divide-and-conquer methods.</p><ol><li><strong>Inadequate problem decomposition:</strong> The effectiveness of a divide-and-conquer approach largely depends on the ability to break down complex problems into smaller, manageable subproblems. GPT-3.5/4, despite its improvements, still struggles to consistently and effectively decompose problems in a manner that allows for efficient and accurate solutions. Human reasoning can often identify multiple ways to decompose a problem, while GPT-3.5/4 may not have the same level of adaptability or creativity.</li><li><strong>Difficulty in identifying appropriate base cases:</strong> Humans can intuitively choose appropriate ones that lead to efficient solutions. In contrast, GPT-3.5/4 may struggle to identify the most effective base cases for a given problem, which can significantly impact the overall efficiency and accuracy of the divide-and-conquer process.</li><li><strong>Insufficient understanding of problem context: </strong>While humans can leverage their domain knowledge and contextual understanding to tackle complex problems better, GPT-3.5/4 is limited by its pre-trained knowledge and may lack the necessary context to efficiently solve certain problems using divide-and-conquer techniques.</li><li><strong>Handling overlapping subproblems:</strong> Humans can often recognize when solving overlapping subproblems and strategically reuse previously computed solutions. GPT-3.5/4, on the other hand, may not always have the same level of awareness and may end up redundantly solving the same subproblems multiple times, leading to inefficient solutions.</li></ol><h2 id="the-vector-db-an-overkill-solution">The Vector DB: An Overkill Solution</h2><p>Auto-GPT relies on vector databases for faster k-nearest neighbor (kNN) searches. These databases retrieve earlier chains of thoughts, incorporating them into the current query context for GPT to provide a memory effect. However, given Auto-GPT's constraints and limitations, this approach has been criticized as excessive and unnecessarily resource-intensive.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/Torantulino/Auto-GPT/blob/master/scripts/memory/__init__.py?ref=jina-ai-gmbh.ghost.io#L30"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Auto-GPT/__init__.py at master · Torantulino/Auto-GPT</div><div class="kg-bookmark-description">An experimental open-source attempt to make GPT-4 fully autonomous. - Auto-GPT/__init__.py at master · Torantulino/Auto-GPT</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">Torantulino</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/6b0ba3ca3485bef05d5f5e9e1b057328e06e68d8de74c8f20b0f215846c38430/Torantulino/Auto-GPT" alt=""></div></a></figure><p>The main argument against using vector databases stems from the cost constraints associated with Auto-GPT's chain of thoughts. A 50-step chain of thoughts would cost 14.4 dollars, while a 1000-step chain would cost significantly more. As a result, the memory size or length of the chain of thought rarely exceeds four digits. In such cases, an exhaustive search (i.e., the dot product between a 256-dim vector and a 10,000 x 256 matrix) for the nearest neighbor proves to be sufficiently efficient, taking less than one second to complete. In contrast, each GPT-4 call takes approximately 10 seconds to process, making the system GPT-bound rather than database-bound.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://jina.ai/news/benchmark-vector-search-databases-with-one-million-data/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Benchmark Vector Search Databases with One Million Data</div><div class="kg-bookmark-description">In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here’s a comprehensive benchmark to help guide you.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--33-.png" alt=""></div></a><figcaption>Exhaustive search over one million vectors takes 2.7s. And how often can the "long memory" in Auto-GPT be longer than one million?</figcaption></figure><p>Although vector databases may offer some advantages in specific scenarios, their implementation within the Auto-GPT system for accelerating kNN "long memory" searches appears to be an unnecessary extravagance and an overkill solution. The primary justification for using vector databases in this context seems to be the user-friendly sugar syntax available out-of-the-box.</p><h2 id="the-birth-of-agent-mechanisms-a-work-in-progress">The Birth of Agent Mechanisms: A Work in Progress</h2><p>Auto-GPT introduces a very intriguing concept by allowing the spawning of agents to delegate tasks. However, this mechanism is still in its early stages, and its potential remains largely untapped. There are several ways to enhance and expand upon the current agent system, opening up new possibilities for more efficient and dynamic interactions.</p><p>One potential improvement is the introduction of <strong>asynchronous agents.</strong> By incorporating <code>async-await</code> patterns, agents can operate concurrently without blocking one another, significantly improving the overall efficiency and responsiveness of the system. This concept draws inspiration from modern programming paradigms that have adopted asynchronous methods to manage multiple tasks simultaneously.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-25.png" class="kg-image" alt="" width="1200" height="630" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-25.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-25.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-25.png 1200w" sizes="(min-width: 720px) 720px"><figcaption>Using async agents can improve efficiency significantly. Source: https://scoutapm.com/blog/async-javascript</figcaption></figure><p>Another promising direction is enabling <strong>intercommunication between agents</strong>. By allowing agents to communicate and collaborate, they can work together to solve complex problems more effectively. This approach resembles the concept of <a href="https://en.wikipedia.org/wiki/Inter-process_communication?ref=jina-ai-gmbh.ghost.io">IPC in programming</a>, where multiple threads/processes can share information and resources to achieve a common goal.</p><h3 id="generative-agents-are-the-future">Generative agents are the future</h3><p>As the GPT-powered agent continues to evolve, the future seems bright for this innovative approach. New research, such as the paper "Generative Agents: Interactive Simulacra of Human Behavior" by Park et al., highlights the potential of agent-based systems in simulating believable human behavior. Generative agents, as proposed in the paper, can interact in complex and engaging ways, forming opinions, initiating conversations, and even autonomously planning and attending events. This work further supports the argument that agent mechanisms have a promising future in AI development.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2304.03442?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Generative Agents: Interactive Simulacra of Human Behavior</div><div class="kg-bookmark-description">Believable proxies of human behavior can empower interactive applicationsranging from immersive environments to rehearsal spaces for interpersonalcommunication to prototyping tools. In this paper, we introduce generativeagents--computational software agents that simulate believable human behavior…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Joon Sung Park</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/1681120489528.gif" class="kg-image" alt="" width="800" height="450" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/1681120489528.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/1681120489528.gif 800w" sizes="(min-width: 720px) 720px"></figure><p>Auto-GPT can unlock new possibilities for more efficient and dynamic problem-solving capabilities by embracing the paradigm shift towards asynchronous programming and fostering inter-agent communication. Incorporating the architectural and interaction patterns introduced in the "Generative Agents" paper can lead to a fusion of large language models with computational, interactive agents. This combination has the potential to revolutionize how tasks are delegated and executed within AI frameworks and enable more believable simulations of human behavior. The development and exploration of agent systems can contribute significantly to advancing AI applications, providing more robust and dynamic solutions to complex problems.</p><h2 id="conclusion">Conclusion</h2><p>In conclusion, the buzz surrounding Auto-GPT raises important questions about the state of AI research and the role of public understanding in driving hype around emerging technologies. As we have demonstrated, Auto-GPT's limitations in reasoning capabilities, the overkill use of vector databases, and the early-stage development of agent mechanisms reveal that it is far from being a practical solution. Yet, it has managed to capture the general public's imagination, who may lack a deep understanding of its inner workings.</p><p>The hype around Auto-GPT serves as a sobering reminder of how shallow understanding can lead to inflated expectations, ultimately culminating in a distorted perception of AI's true capabilities. As a society, we must be vigilant in questioning the narratives that surround emerging technologies and strive to foster critical thinking and informed discussions.</p><p>That said, Auto-GPT does point to a promising direction for the future of AI: generative agent systems. As we move forward, let us learn from the lessons of the Auto-GPT hype and focus on nurturing a more nuanced and informed dialogue around AI research. 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diff --git a/news/benchmark-vector-search-databases-with-one-million-data/index.html b/news/benchmark-vector-search-databases-with-one-million-data/index.html
index 27afe54eb98..66de06744d3 100644
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@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Benchmark Vector Search Databases with One Million Data</title><meta charset="utf-8"><meta name="title" content="Benchmark Vector Search Databases with One Million Data"><meta name="description" content="In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here's a comprehensive benchmark to help guide you."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/benchmark-vector-search-databases-with-one-million-data"><meta property="og:title" content="Benchmark Vector Search Databases with One Million Data"><meta property="og:description" content="In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here's a comprehensive benchmark to help guide you."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--33-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/benchmark-vector-search-databases-with-one-million-data"><meta property="twitter:title" content="Benchmark Vector Search Databases with One Million Data"><meta property="twitter:description" content="In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here's a comprehensive benchmark to help guide you."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--33-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Benchmark Vector Search Databases with One Million Data</title><meta charset="utf-8"><meta name="title" content="Benchmark Vector Search Databases with One Million Data"><meta name="description" content="In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here's a comprehensive benchmark to help guide you."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/benchmark-vector-search-databases-with-one-million-data"><meta property="og:title" content="Benchmark Vector Search Databases with One Million Data"><meta property="og:description" content="In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here's a comprehensive benchmark to help guide you."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--33-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/benchmark-vector-search-databases-with-one-million-data"><meta property="twitter:title" content="Benchmark Vector Search Databases with One Million Data"><meta property="twitter:description" content="In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here's a comprehensive benchmark to help guide you."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--33-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Benchmark Vector Search Databases with One Million Data</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here's a comprehensive benchmark to help guide you.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 15, 2022 • 33 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In DocArray, Documents inside a DocumentArray can live in a <a href="https://docarray.jina.ai/advanced/document-store/?ref=jina-ai-gmbh.ghost.io">document store</a> instead of in memory. The benefit of using an external store over an in-memory store is often about longer persistence and faster retrieval.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docarray.jina.ai/advanced/document-store/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Document Store</div><div class="kg-bookmark-description">Documents inside a DocumentArray can live in a document store instead of in memory, e.g. in SQLite, Redis. The benefit of using an external store over an in-memory store is often about longer persistence and faster retrieval. The look-and-feel of a DocumentArray with external store is almost the ...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docarray.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">DocArray 0.18.2 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docarray.jina.ai/_static/banner.png" alt=""></div></a></figure><p>Today, DocArray supports six external stores including <a href="https://docarray.jina.ai/advanced/document-store/sqlite/?ref=jina-ai-gmbh.ghost.io">SQLite</a>, <a href="https://docarray.jina.ai/advanced/document-store/weaviate/?ref=jina-ai-gmbh.ghost.io">Weaviate</a>, <a href="https://docarray.jina.ai/advanced/document-store/qdrant/?ref=jina-ai-gmbh.ghost.io">Qdrant</a>, <a href="https://docarray.jina.ai/advanced/document-store/elasticsearch/?ref=jina-ai-gmbh.ghost.io">Elasticsearch</a>, <a href="https://docarray.jina.ai/advanced/document-store/redis/?ref=jina-ai-gmbh.ghost.io">Redis</a> and <a href="https://docarray.jina.ai/advanced/document-store/annlite/?ref=jina-ai-gmbh.ghost.io">AnnLite</a>. Apart from SQLite, all other backends support approximate nearest neighbour search. The look-and-feel of a DocumentArray with an external store is <strong>almost the same</strong> as a regular in-memory DocumentArray. This lets you easily switch between backends under the same DocArray idiom. For example, to use Elasticsearch as the backend, simply:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Benchmark Vector Search Databases with One Million Data</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here's a comprehensive benchmark to help guide you.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 15, 2022 • 33 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In DocArray, Documents inside a DocumentArray can live in a <a href="https://docarray.jina.ai/advanced/document-store/?ref=jina-ai-gmbh.ghost.io">document store</a> instead of in memory. The benefit of using an external store over an in-memory store is often about longer persistence and faster retrieval.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docarray.jina.ai/advanced/document-store/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Document Store</div><div class="kg-bookmark-description">Documents inside a DocumentArray can live in a document store instead of in memory, e.g. in SQLite, Redis. The benefit of using an external store over an in-memory store is often about longer persistence and faster retrieval. The look-and-feel of a DocumentArray with external store is almost the ...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docarray.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">DocArray 0.18.2 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docarray.jina.ai/_static/banner.png" alt=""></div></a></figure><p>Today, DocArray supports six external stores including <a href="https://docarray.jina.ai/advanced/document-store/sqlite/?ref=jina-ai-gmbh.ghost.io">SQLite</a>, <a href="https://docarray.jina.ai/advanced/document-store/weaviate/?ref=jina-ai-gmbh.ghost.io">Weaviate</a>, <a href="https://docarray.jina.ai/advanced/document-store/qdrant/?ref=jina-ai-gmbh.ghost.io">Qdrant</a>, <a href="https://docarray.jina.ai/advanced/document-store/elasticsearch/?ref=jina-ai-gmbh.ghost.io">Elasticsearch</a>, <a href="https://docarray.jina.ai/advanced/document-store/redis/?ref=jina-ai-gmbh.ghost.io">Redis</a> and <a href="https://docarray.jina.ai/advanced/document-store/annlite/?ref=jina-ai-gmbh.ghost.io">AnnLite</a>. Apart from SQLite, all other backends support approximate nearest neighbour search. The look-and-feel of a DocumentArray with an external store is <strong>almost the same</strong> as a regular in-memory DocumentArray. This lets you easily switch between backends under the same DocArray idiom. For example, to use Elasticsearch as the backend, simply:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
 
 da = DocumentArray(storage=<span class="hljs-string">'elasticsearch'</span>, config={<span class="hljs-string">'n_dim'</span>: <span class="hljs-number">128</span>})</code></pre><p>Or if you want to use Qdrant, you can just change one parameter:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
 
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Join Tech Job Fair on Nov 10 and Meet Our Team</title><meta charset="utf-8"><meta name="title" content="Join Tech Job Fair on Nov 10 and Meet Our Team"><meta name="description" content="Jina AI is happy to announce that on the 10th of November we will participate in the Berlin Tech Job Fair. You'll have a chance to learn from the top experts in the IT/digital industries and network with peers!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/berlin-tech-job-fair"><meta property="og:title" content="Join Tech Job Fair on Nov 10 and Meet Our Team"><meta property="og:description" content="Jina AI is happy to announce that on the 10th of November we will participate in the Berlin Tech Job Fair. You'll have a chance to learn from the top experts in the IT/digital industries and network with peers!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Florian-Hoenicke-Jina-NOW-Team-Lead.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/berlin-tech-job-fair"><meta property="twitter:title" content="Join Tech Job Fair on Nov 10 and Meet Our Team"><meta property="twitter:description" content="Jina AI is happy to announce that on the 10th of November we will participate in the Berlin Tech Job Fair. You'll have a chance to learn from the top experts in the IT/digital industries and network with peers!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Florian-Hoenicke-Jina-NOW-Team-Lead.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Florian-Hoenicke-Jina-NOW-Team-Lead.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Join Tech Job Fair on Nov 10 and Meet Our Team</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI is happy to announce that on the 10th of November we will participate in the Berlin Tech Job Fair. You'll have a chance to learn from the top experts in the IT/digital industries and network with peers!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 19, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina AI is happy to announce that on the 10th of November we will participate in the Berlin Tech Job Fair. The job fair provides a great opportunity to find or explore a new career in engineering and open source. You'll also have the chance to learn from the top experts in the IT/digital industries and network with peers.</p><p>Learn more about the Fair below: </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://techjobsfair.com/exhibitor/jina-ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI GmbH Tech Jobs Fair</div><div class="kg-bookmark-description">🧠 Commercial open source software company on MLOps platform for multimodal and neural search.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://techjobsfair.com/wp-content/themes/techjobsfair/assets/images/favicon-icon.png" alt=""><span class="kg-bookmark-author">Tech Jobs Fair</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://techjobsfair.com/wp-content/uploads/blog-images/opengraph_seo_1200x630.png" alt=""></div></a></figure><p>If you join, come by our booth and ask us anything you want. Our team members will be happy to answer your questions in regard to open job positions, working culture, flexible working hours, remote work settings, and anything you want to know about us and our team! </p><p>Alongside all of this, we're happy to share the benefits of working at Jina and what it is like to be part of our multicultural diverse team.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.77778 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/PXL_20220523_142408560-1.jpg" width="2000" height="1125" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/PXL_20220523_142408560-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/PXL_20220523_142408560-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/PXL_20220523_142408560-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/PXL_20220523_142408560-1.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_1537.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_1537.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_1537.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/IMG_1537.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/IMG_1537.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_5395.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_5395.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_5395.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/IMG_5395.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/IMG_5395.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.77778 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/PXL_20220923_151641882.jpg" width="2000" height="1125" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/PXL_20220923_151641882.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/PXL_20220923_151641882.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/PXL_20220923_151641882.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/PXL_20220923_151641882.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Jina AI's team</figcaption></figure><p>We're also glad to discuss a range of things, such as our different products, our contributions to the open-source community, the company's background, and how we built our company up in the midst of the pandemic. </p><p><strong>Want to check open positions? </strong>See the link below: </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jobs.lever.co/jina-ai?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI jobs</div><div class="kg-bookmark-description">Job openings at Jina AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jobs.lever.co/favicon.ico" alt=""><span class="kg-bookmark-author">Jina AI logo</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://lever-client-logos.s3.us-west-2.amazonaws.com/4347e16d-b068-4137-be7c-fedb5d3d7a9a-1662540212135.png" alt=""></div></a></figure><p><strong>Want to learn more about Jina AI and contribute to the project?</strong> Check the link below: </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI</div><div class="kg-bookmark-description">A Neural Search Company. MLOps platform for neural search &amp; creative AI applications. - Jina AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://avatars.githubusercontent.com/u/60539444?s=280&amp;v=4" alt=""></div></a></figure><div class="kg-card kg-button-card kg-align-center"><a href="https://jina.ai/slack/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Join our Slack Community</a></div><p></p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fberlin-tech-job-fair%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Florian-Hoenicke-Jina-NOW-Team-Lead.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Join Tech Job Fair on Nov 10 and Meet Our Team</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI is happy to announce that on the 10th of November we will participate in the Berlin Tech Job Fair. You'll have a chance to learn from the top experts in the IT/digital industries and network with peers!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 19, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina AI is happy to announce that on the 10th of November we will participate in the Berlin Tech Job Fair. The job fair provides a great opportunity to find or explore a new career in engineering and open source. You'll also have the chance to learn from the top experts in the IT/digital industries and network with peers.</p><p>Learn more about the Fair below: </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://techjobsfair.com/exhibitor/jina-ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI GmbH Tech Jobs Fair</div><div class="kg-bookmark-description">🧠 Commercial open source software company on MLOps platform for multimodal and neural search.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://techjobsfair.com/wp-content/themes/techjobsfair/assets/images/favicon-icon.png" alt=""><span class="kg-bookmark-author">Tech Jobs Fair</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://techjobsfair.com/wp-content/uploads/blog-images/opengraph_seo_1200x630.png" alt=""></div></a></figure><p>If you join, come by our booth and ask us anything you want. Our team members will be happy to answer your questions in regard to open job positions, working culture, flexible working hours, remote work settings, and anything you want to know about us and our team! </p><p>Alongside all of this, we're happy to share the benefits of working at Jina and what it is like to be part of our multicultural diverse team.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.77778 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/PXL_20220523_142408560-1.jpg" width="2000" height="1125" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/PXL_20220523_142408560-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/PXL_20220523_142408560-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/PXL_20220523_142408560-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/PXL_20220523_142408560-1.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_1537.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_1537.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_1537.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/IMG_1537.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/IMG_1537.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_5395.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_5395.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_5395.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/IMG_5395.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/IMG_5395.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.77778 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/PXL_20220923_151641882.jpg" width="2000" height="1125" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/PXL_20220923_151641882.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/PXL_20220923_151641882.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/PXL_20220923_151641882.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/PXL_20220923_151641882.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Jina AI's team</figcaption></figure><p>We're also glad to discuss a range of things, such as our different products, our contributions to the open-source community, the company's background, and how we built our company up in the midst of the pandemic. </p><p><strong>Want to check open positions? </strong>See the link below: </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jobs.lever.co/jina-ai?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI jobs</div><div class="kg-bookmark-description">Job openings at Jina AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jobs.lever.co/favicon.ico" alt=""><span class="kg-bookmark-author">Jina AI logo</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://lever-client-logos.s3.us-west-2.amazonaws.com/4347e16d-b068-4137-be7c-fedb5d3d7a9a-1662540212135.png" alt=""></div></a></figure><p><strong>Want to learn more about Jina AI and contribute to the project?</strong> Check the link below: </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI</div><div class="kg-bookmark-description">A Neural Search Company. MLOps platform for neural search &amp; creative AI applications. - Jina AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://avatars.githubusercontent.com/u/60539444?s=280&amp;v=4" alt=""></div></a></figure><div class="kg-card kg-button-card kg-align-center"><a href="https://jina.ai/slack/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Join our Slack Community</a></div><p></p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fberlin-tech-job-fair%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; 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+++ b/news/bestbanner-0-6-unleash-the-power-of-social-marketing-with-these-stunning-banners-and-titles/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>BestBanner 0.6: Unleash the Power of Social Marketing with Stunning Banners &amp; Titles</title><meta charset="utf-8"><meta name="title" content="BestBanner 0.6: Unleash the Power of Social Marketing with Stunning Banners &amp; Titles"><meta name="description" content="The latest BestBanner release will transform your banner generation experience! Just paste in your content, and let BestBanner surprise you."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/bestbanner-0-6-unleash-the-power-of-social-marketing-with-these-stunning-banners-and-titles"><meta property="og:title" content="BestBanner 0.6: Unleash the Power of Social Marketing with Stunning Banners &amp; Titles"><meta property="og:description" content="The latest BestBanner release will transform your banner generation experience! Just paste in your content, and let BestBanner surprise you."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-2.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/bestbanner-0-6-unleash-the-power-of-social-marketing-with-these-stunning-banners-and-titles"><meta property="twitter:title" content="BestBanner 0.6: Unleash the Power of Social Marketing with Stunning Banners &amp; Titles"><meta property="twitter:description" content="The latest BestBanner release will transform your banner generation experience! Just paste in your content, and let BestBanner surprise you."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-2.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>BestBanner 0.6: Unleash the Power of Social Marketing with Stunning Banners &amp; Titles</title><meta charset="utf-8"><meta name="title" content="BestBanner 0.6: Unleash the Power of Social Marketing with Stunning Banners &amp; Titles"><meta name="description" content="The latest BestBanner release will transform your banner generation experience! Just paste in your content, and let BestBanner surprise you."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/bestbanner-0-6-unleash-the-power-of-social-marketing-with-these-stunning-banners-and-titles"><meta property="og:title" content="BestBanner 0.6: Unleash the Power of Social Marketing with Stunning Banners &amp; Titles"><meta property="og:description" content="The latest BestBanner release will transform your banner generation experience! Just paste in your content, and let BestBanner surprise you."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-2.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/bestbanner-0-6-unleash-the-power-of-social-marketing-with-these-stunning-banners-and-titles"><meta property="twitter:title" content="BestBanner 0.6: Unleash the Power of Social Marketing with Stunning Banners &amp; Titles"><meta property="twitter:description" content="The latest BestBanner release will transform your banner generation experience! Just paste in your content, and let BestBanner surprise you."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-2.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">BestBanner 0.6: Unleash the Power of Social Marketing with Stunning Banners &amp; Titles</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The latest BestBanner release will transform your banner generation experience! Just paste in your content, and let BestBanner surprise you.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Me.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Andrei Ungureanu, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 14, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the buzzing world of social marketing, what captures clicks and ignites engagement? It's an eye-catching banner, an irresistible title, and a snappy excerpt. BestBanner 0.6.0 is your all-in-one solution to create these essential elements effortlessly. Transform your content and stand out in the social marketing landscape with <a href="http://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">bestbanner.jina.ai</a>!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">BestBanner - Text to Banners, No Prompts Needed!</div><div class="kg-bookmark-description">BestBanner revolutionizes the way you create banner images. Generate stunning blog banners, eye-catching social media banners, and engaging ad banners effortlessly. Simply input your article text, and watch as our advanced multimodal AI crafts a unique and captivating image, tailored specifically to…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://bestbanner.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-publisher">BestBanner</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://bestbanner.jina.ai/banner.png" alt=""></div></a></figure><p>BestBanner 0.6 heralds an era of better, faster, and more visually compelling banner creation. Not only have we significantly improved the core generation process, but we've also expanded our feature set. We’re particularly excited to unveil two major additions: <strong>Selectable Styles</strong> and <strong>AI-Generated Titles and Descriptions</strong>.</p><h3 id="selectable-styles"><strong>Selectable Styles</strong></h3><p>To give users a new level of customization, we now offer three unique banner styles, <strong>Photographic</strong>, <strong>Minimalist</strong>, and <strong>Flat</strong>.</p><p>To showcase this feature, we’ve benchmarked BestBanner against the brand-new <a href="https://stability.ai/stablediffusion?ref=jina-ai-gmbh.ghost.io">Stable Diffusion XL</a> (SD-XL for short). Based on our previous approach, we inputted an entire article into BestBanner, while using just one to two opening sentences for Stable Diffusion XL. To keep in line with the trends, we went with this fantastic article about the Barbienheimer saga (<a href="https://medium.com/@sham.mov/barbienheimer-the-double-feature-that-will-bring-back-cinema-as-an-experience-2477136f2896?ref=jina-ai-gmbh.ghost.io">‘Barbienheimer’ : The double feature that will bring back Cinema as an experience</a>).</p><p>To ensure parity, we mimicked BestBanner’s styles (as much as possible) in SD-XL by using specific styling keywords:</p><ul><li><strong>Photographic</strong>: <code>photographic style, ultra-realistic, 8k, uhd</code></li><li><strong>Minimalist</strong>: <code>minimalist style, simple shapes, simple background</code></li><li><strong>Flat</strong>: <code>illustration style, flat design, simple shapes</code></li></ul><p>Let’s have a look at the results. For both SD-XL and BestBanner we generated two images in each style: "flat", "minimalist" and "photographic".</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/sd-xl.png" class="kg-image" alt="" width="672" height="1008" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/sd-xl.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/sd-xl.png 672w"><figcaption>SD-XL images</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/bestbanner.png" class="kg-image" alt="" width="672" height="1008" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/bestbanner.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/bestbanner.png 672w"><figcaption>BestBanner images</figcaption></figure><p>The results from Stable Diffusion XL were impressive. Their latest offering dishes out some seriously stunning visuals, giving tough competition to stalwarts like Midjourney. Although SD-XL faced minor hiccups in replicating the illustrative flair of the “Flat” style, its results were commendable. Content diversity was where SD-XL slightly faltered, fixating on just the Barbie doll without any nod to Oppenheimer or the cinematic aspect.</p><p>BestBanner, in comparison, showcased not only its prowess in generating exquisite images but also excelled in adhering to the chosen styles. Our “Flat” design emerged as a favorite for many. Moreover, the content representation was richer, illustrating elements from both Barbie and Oppenheimer and offering a more varied palette of compositions.</p><p><strong>The takeaway?</strong> BestBanner’s new style selection feature strikes the right balance between user choice and AI-powered creativity. While you control the aesthetic, BestBanner artfully crafts the content, ensuring a harmonious blend. And stay tuned – our iterative process means more styles and features are on the horizon!</p><h3 id="ai-generated-titles-and-descriptions"><strong>AI Generated Titles and Descriptions</strong></h3><p>Capturing attention in the digital realm hinges on a compelling title and description. BestBanner's latest feature does exactly that, generating titles and descriptions that don't just engage but resonate across languages.</p><p>Beyond the immediate appeal, a larger play is at work. When sharing content on social platforms, <a href="https://ogp.me/?ref=jina-ai-gmbh.ghost.io">Open Graph</a> (OG) meta tags determine how your content appears. Specifically, 'og-title' and 'og-description' tags are vital for presenting your content in its best light, ensuring your articles and posts are both clickable and shareable. BestBanner seamlessly aligns with this framework, enhancing your content's presentation on platforms like Medium.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-12.png" class="kg-image" alt="Untitled" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled-12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Untitled-12.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-12.png 1024w" sizes="(min-width: 720px) 720px"></figure><p>Just head to the “Social Preview” section after clicking on a generated banner to access this feature 😉</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-1-1.png" class="kg-image" alt="Screen Shot 2023-08-08 at 16.21.42_clipdrop-enhance_clipdrop-enhance.png" width="612" height="732" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled-1-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-1-1.png 612w"></figure><h3 id="conclusion"><strong>Conclusion</strong></h3><p>BestBanner 0.6 is more than just an upgrade – it's a game-changer for social marketing.</p><p>In the dynamic world of social network marketing, where captivating banners, titles, and excerpts are the difference between being overlooked and being clicked, BestBanner stands out as the essential tool for specialists.</p><p>Our latest features, like Selectable Styles and AI-Generated Titles and Descriptions, are designed with the modern marketer in mind. This release underscores our commitment to fusing intuitive design with cutting-edge innovation.</p><p>If you aim to enhance your brand's visibility and influence on social platforms, look no further than <a href="http://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io">bestbanner.jina.ai</a></p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">BestBanner - Text to Banners, No Prompts Needed!</div><div class="kg-bookmark-description">BestBanner revolutionizes the way you create banner images. Generate stunning blog banners, eye-catching social media banners, and engaging ad banners effortlessly. Simply input your article text, and watch as our advanced multimodal AI crafts a unique and captivating image, tailored specifically to…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://bestbanner.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-publisher">BestBanner</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://bestbanner.jina.ai/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fbestbanner-0-6-unleash-the-power-of-social-marketing-with-these-stunning-banners-and-titles%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">BestBanner 0.6: Unleash the Power of Social Marketing with Stunning Banners &amp; Titles</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The latest BestBanner release will transform your banner generation experience! Just paste in your content, and let BestBanner surprise you.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Me.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Andrei Ungureanu, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 14, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the buzzing world of social marketing, what captures clicks and ignites engagement? It's an eye-catching banner, an irresistible title, and a snappy excerpt. BestBanner 0.6.0 is your all-in-one solution to create these essential elements effortlessly. Transform your content and stand out in the social marketing landscape with <a href="http://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">bestbanner.jina.ai</a>!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">BestBanner - Text to Banners, No Prompts Needed!</div><div class="kg-bookmark-description">BestBanner revolutionizes the way you create banner images. Generate stunning blog banners, eye-catching social media banners, and engaging ad banners effortlessly. Simply input your article text, and watch as our advanced multimodal AI crafts a unique and captivating image, tailored specifically to…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://bestbanner.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-publisher">BestBanner</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://bestbanner.jina.ai/banner.png" alt=""></div></a></figure><p>BestBanner 0.6 heralds an era of better, faster, and more visually compelling banner creation. Not only have we significantly improved the core generation process, but we've also expanded our feature set. We’re particularly excited to unveil two major additions: <strong>Selectable Styles</strong> and <strong>AI-Generated Titles and Descriptions</strong>.</p><h3 id="selectable-styles"><strong>Selectable Styles</strong></h3><p>To give users a new level of customization, we now offer three unique banner styles, <strong>Photographic</strong>, <strong>Minimalist</strong>, and <strong>Flat</strong>.</p><p>To showcase this feature, we’ve benchmarked BestBanner against the brand-new <a href="https://stability.ai/stablediffusion?ref=jina-ai-gmbh.ghost.io">Stable Diffusion XL</a> (SD-XL for short). Based on our previous approach, we inputted an entire article into BestBanner, while using just one to two opening sentences for Stable Diffusion XL. To keep in line with the trends, we went with this fantastic article about the Barbienheimer saga (<a href="https://medium.com/@sham.mov/barbienheimer-the-double-feature-that-will-bring-back-cinema-as-an-experience-2477136f2896?ref=jina-ai-gmbh.ghost.io">‘Barbienheimer’ : The double feature that will bring back Cinema as an experience</a>).</p><p>To ensure parity, we mimicked BestBanner’s styles (as much as possible) in SD-XL by using specific styling keywords:</p><ul><li><strong>Photographic</strong>: <code>photographic style, ultra-realistic, 8k, uhd</code></li><li><strong>Minimalist</strong>: <code>minimalist style, simple shapes, simple background</code></li><li><strong>Flat</strong>: <code>illustration style, flat design, simple shapes</code></li></ul><p>Let’s have a look at the results. For both SD-XL and BestBanner we generated two images in each style: "flat", "minimalist" and "photographic".</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/sd-xl.png" class="kg-image" alt="" width="672" height="1008" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/sd-xl.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/sd-xl.png 672w"><figcaption>SD-XL images</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/bestbanner.png" class="kg-image" alt="" width="672" height="1008" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/bestbanner.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/bestbanner.png 672w"><figcaption>BestBanner images</figcaption></figure><p>The results from Stable Diffusion XL were impressive. Their latest offering dishes out some seriously stunning visuals, giving tough competition to stalwarts like Midjourney. Although SD-XL faced minor hiccups in replicating the illustrative flair of the “Flat” style, its results were commendable. Content diversity was where SD-XL slightly faltered, fixating on just the Barbie doll without any nod to Oppenheimer or the cinematic aspect.</p><p>BestBanner, in comparison, showcased not only its prowess in generating exquisite images but also excelled in adhering to the chosen styles. Our “Flat” design emerged as a favorite for many. Moreover, the content representation was richer, illustrating elements from both Barbie and Oppenheimer and offering a more varied palette of compositions.</p><p><strong>The takeaway?</strong> BestBanner’s new style selection feature strikes the right balance between user choice and AI-powered creativity. While you control the aesthetic, BestBanner artfully crafts the content, ensuring a harmonious blend. And stay tuned – our iterative process means more styles and features are on the horizon!</p><h3 id="ai-generated-titles-and-descriptions"><strong>AI Generated Titles and Descriptions</strong></h3><p>Capturing attention in the digital realm hinges on a compelling title and description. BestBanner's latest feature does exactly that, generating titles and descriptions that don't just engage but resonate across languages.</p><p>Beyond the immediate appeal, a larger play is at work. When sharing content on social platforms, <a href="https://ogp.me/?ref=jina-ai-gmbh.ghost.io">Open Graph</a> (OG) meta tags determine how your content appears. Specifically, 'og-title' and 'og-description' tags are vital for presenting your content in its best light, ensuring your articles and posts are both clickable and shareable. BestBanner seamlessly aligns with this framework, enhancing your content's presentation on platforms like Medium.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-12.png" class="kg-image" alt="Untitled" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled-12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Untitled-12.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-12.png 1024w" sizes="(min-width: 720px) 720px"></figure><p>Just head to the “Social Preview” section after clicking on a generated banner to access this feature 😉</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-1-1.png" class="kg-image" alt="Screen Shot 2023-08-08 at 16.21.42_clipdrop-enhance_clipdrop-enhance.png" width="612" height="732" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled-1-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-1-1.png 612w"></figure><h3 id="conclusion"><strong>Conclusion</strong></h3><p>BestBanner 0.6 is more than just an upgrade – it's a game-changer for social marketing.</p><p>In the dynamic world of social network marketing, where captivating banners, titles, and excerpts are the difference between being overlooked and being clicked, BestBanner stands out as the essential tool for specialists.</p><p>Our latest features, like Selectable Styles and AI-Generated Titles and Descriptions, are designed with the modern marketer in mind. This release underscores our commitment to fusing intuitive design with cutting-edge innovation.</p><p>If you aim to enhance your brand's visibility and influence on social platforms, look no further than <a href="http://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io">bestbanner.jina.ai</a></p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">BestBanner - Text to Banners, No Prompts Needed!</div><div class="kg-bookmark-description">BestBanner revolutionizes the way you create banner images. Generate stunning blog banners, eye-catching social media banners, and engaging ad banners effortlessly. Simply input your article text, and watch as our advanced multimodal AI crafts a unique and captivating image, tailored specifically to…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://bestbanner.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-publisher">BestBanner</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://bestbanner.jina.ai/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fbestbanner-0-6-unleash-the-power-of-social-marketing-with-these-stunning-banners-and-titles%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Beyond Pixels to Prose: SceneXplain's New Algorithm Breathes Audible Life into Images</title><meta charset="utf-8"><meta name="title" content="Beyond Pixels to Prose: SceneXplain's New Algorithm Breathes Audible Life into Images"><meta name="description" content="Discover the power of SceneXplain's Hearth Algorithm: turning images into captivating narratives. Dive deep into the tech behind it, explore real-world examples, and grasp its potential. Journey beyond pixels to stories at SceneXplain!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/beyond-pixels-to-prose-scenexplains-hearth-algorithm-breathes-audible-life-into-images"><meta property="og:title" content="Beyond Pixels to Prose: SceneXplain's New Algorithm Breathes Audible Life into Images"><meta property="og:description" content="Discover the power of SceneXplain's Hearth Algorithm: turning images into captivating narratives. Dive deep into the tech behind it, explore real-world examples, and grasp its potential. Journey beyond pixels to stories at SceneXplain!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_an_image_of_an_abstract_graph_in_motion_in_the_s_ae1f674c-ac1a-448c-837e-5d2735748e45.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/beyond-pixels-to-prose-scenexplains-hearth-algorithm-breathes-audible-life-into-images"><meta property="twitter:title" content="Beyond Pixels to Prose: SceneXplain's New Algorithm Breathes Audible Life into Images"><meta property="twitter:description" content="Discover the power of SceneXplain's Hearth Algorithm: turning images into captivating narratives. Dive deep into the tech behind it, explore real-world examples, and grasp its potential. Journey beyond pixels to stories at SceneXplain!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_an_image_of_an_abstract_graph_in_motion_in_the_s_ae1f674c-ac1a-448c-837e-5d2735748e45.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Beyond Pixels to Prose: SceneXplain's New Algorithm Breathes Audible Life into Images</title><meta charset="utf-8"><meta name="title" content="Beyond Pixels to Prose: SceneXplain's New Algorithm Breathes Audible Life into Images"><meta name="description" content="Discover the power of SceneXplain's Hearth Algorithm: turning images into captivating narratives. Dive deep into the tech behind it, explore real-world examples, and grasp its potential. Journey beyond pixels to stories at SceneXplain!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/beyond-pixels-to-prose-scenexplains-hearth-algorithm-breathes-audible-life-into-images"><meta property="og:title" content="Beyond Pixels to Prose: SceneXplain's New Algorithm Breathes Audible Life into Images"><meta property="og:description" content="Discover the power of SceneXplain's Hearth Algorithm: turning images into captivating narratives. Dive deep into the tech behind it, explore real-world examples, and grasp its potential. Journey beyond pixels to stories at SceneXplain!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_an_image_of_an_abstract_graph_in_motion_in_the_s_ae1f674c-ac1a-448c-837e-5d2735748e45.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/beyond-pixels-to-prose-scenexplains-hearth-algorithm-breathes-audible-life-into-images"><meta property="twitter:title" content="Beyond Pixels to Prose: SceneXplain's New Algorithm Breathes Audible Life into Images"><meta property="twitter:description" content="Discover the power of SceneXplain's Hearth Algorithm: turning images into captivating narratives. Dive deep into the tech behind it, explore real-world examples, and grasp its potential. Journey beyond pixels to stories at SceneXplain!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_an_image_of_an_abstract_graph_in_motion_in_the_s_ae1f674c-ac1a-448c-837e-5d2735748e45.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Beyond Pixels to Prose: SceneXplain's New Algorithm Breathes Audible Life into Images</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Discover the power of SceneXplain's Hearth Algorithm: turning images into captivating narratives. Dive deep into the tech behind it, explore real-world examples, and grasp its potential. Journey beyond pixels to stories at SceneXplain!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 21, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Imagine walking through a dimly lit gallery, where walls are adorned with timeless black-and-white photographs. One image, in particular, catches your eye. A soldier hugging his daughter tightly, possibly seeing her for the last time before heading to war. Tears glisten on the child's cheeks, and even though the image stands still, you can almost hear the whispered promises, the choked-back tears, the soft lullaby sung to offer solace.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_A_soldier_hugging_his_daughter_tightly_possibly__160fb9dc-a02a-4159-8919-0ea2c18fee19.png" class="kg-image" alt="" width="1456" height="816" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/generativejina_A_soldier_hugging_his_daughter_tightly_possibly__160fb9dc-a02a-4159-8919-0ea2c18fee19.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/generativejina_A_soldier_hugging_his_daughter_tightly_possibly__160fb9dc-a02a-4159-8919-0ea2c18fee19.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_A_soldier_hugging_his_daughter_tightly_possibly__160fb9dc-a02a-4159-8919-0ea2c18fee19.png 1456w" sizes="(min-width: 720px) 720px"></figure><blockquote class="kg-blockquote-alt">Now, what if you really could hear that story?</blockquote><div class="kg-card kg-audio-card"><img loading="lazy" src="" alt="audio-thumbnail" class="kg-audio-thumbnail kg-audio-hide"><div class="kg-audio-thumbnail placeholder"><svg width="24" height="24" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.5 15.33a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0ZM15 13.83a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.486 6.81A2.25 2.25 0 0 1 17.25 9v5.579a.75.75 0 0 1-1.5 0v-5.58a.75.75 0 0 0-.932-.727.755.755 0 0 1-.059.013l-4.465.744a.75.75 0 0 0-.544.72v6.33a.75.75 0 0 1-1.5 0v-6.33a2.25 2.25 0 0 1 1.763-2.194l4.473-.746Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3 1.5a.75.75 0 0 0-.75.75v19.5a.75.75 0 0 0 .75.75h18a.75.75 0 0 0 .75-.75V5.133a.75.75 0 0 0-.225-.535l-.002-.002-3-2.883A.75.75 0 0 0 18 1.5H3ZM1.409.659A2.25 2.25 0 0 1 3 0h15a2.25 2.25 0 0 1 1.568.637l.003.002 3 2.883a2.25 2.25 0 0 1 .679 1.61V21.75A2.25 2.25 0 0 1 21 24H3a2.25 2.25 0 0 1-2.25-2.25V2.25c0-.597.237-1.169.659-1.591Z"></path></svg></div><div class="kg-audio-player-container" style="--buffered-width:29.2308%;"><audio src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/audios_2853aecf-c13a-4441-a015-872636858b0a_en.wav" preload="metadata"></audio><div class="kg-audio-title">Audio story generated by SceneXplain Hearth algorithm from the above image</div><div class="kg-audio-player"><button class="kg-audio-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-audio-pause-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-audio-current-time">0:00</span><div class="kg-audio-time">/<span class="kg-audio-duration">1:05</span></div><input type="range" class="kg-audio-seek-slider" max="65" value="0"><button class="kg-audio-playback-rate">1×</button><button class="kg-audio-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-audio-mute-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-audio-volume-slider" max="100" value="100"></div></div></div><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/videos_e9e038cc-dde3-459c-aa87-980a26005e44_dialog_en.mp4" poster="https://img.spacergif.org/v1/750x419/0a/spacer.png" width="750" height="419" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember779.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><p>In today's digital age, while short video content has surged, powerful still images often remain trapped in silence. SceneXplain's <code>Hearth</code> algorithm breaks these barriers, giving a voice to the voiceless. It's not merely about observing a moment but immersing oneself in its rich auditory tapestry. With <code>Hearth</code>, every picture has a story to tell and a song to sing, encapsulating the essence of short videos from a static frame.</p><h2 id="why-did-scenexplain-create-the-hearth-algorithm">Why Did SceneXplain Create the <code>Hearth</code> Algorithm?</h2><p>As our digital ecosystem swiftly gravitates towards compact and impactful narratives, the potency of short, immersive content cannot be overlooked. These snippets of visual and auditory tales have become the preferred consumption mode for global audiences. But amidst this video-driven narrative, there remains a vast reservoir of untapped potential: the silent world of static images. These encompass art, history, personal memories, and countless unspoken tales. Recognizing this gap, SceneXplain birthed the <code>Hearth</code> algorithm. It's more than just an enhancement; it's a revolution—bestowing a voice upon the silent and ensuring every image shares its intrinsic story.</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/scenexplain-generate-story.mp4" poster="https://img.spacergif.org/v1/1530x964/0a/spacer.png" width="1530" height="964" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember661.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>How to use SceneXplain's Hearth algorithm to generate audible story from images</figcaption></figure><h2 id="which-industries-can-benefit-from-scenexplains-hearth">Which Industries Can Benefit from SceneXplain's <code>Hearth</code>?</h2><p>The impact and versatility of SceneXplain's <code>Hearth</code> ripple across numerous sectors:</p><ul><li><strong>Film &amp; Entertainment</strong>: Envision a world where directors and scriptwriters utilize Hearth to add depth to their storyboarded visuals, melding sight and sound to create a richer pre-production canvas.</li><li><strong>Marketing &amp; Advertising</strong>: In today's bustling market, capturing attention within moments is paramount. SceneXplain's Hearth equips brands with the tools to morph static campaign images into gripping auditory narratives, fostering deeper connections with audiences.</li><li><strong>Education</strong>: The future of teaching is dynamic. With SceneXplain's Hearth, educators can transition from traditional visuals to interactive auditory experiences, be it through historical recounts or intricate scientific processes.</li><li><strong>Content Creation</strong>: Digital storytellers of the modern age have a new ally. With Hearth, they can augment their visual tales with resonant audio narratives, enhancing engagement and solidifying their space in the vast digital landscape.</li></ul><h2 id="decoding-the-hearth-algorithm-the-nexus-of-visual-understanding-and-auditory-storytelling">Decoding the Hearth Algorithm: The Nexus of Visual Understanding and Auditory Storytelling</h2><p>The <code>Hearth</code> Algorithm's design embodies a meticulous blend of parallelized tasks and sequential steps, ensuring optimal performance while achieving nuanced narrative generation. Our architecture diagram above provides a holistic view of the entire process. Here’s a breakdown of how the magic happens:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/mermaid-diagram-2023-08-21-152542.svg" class="kg-image" alt="" width="149" height="150"></figure><h3 id="1-scene-understanding-building-on-a-legacy-of-excellence"><br>1. <strong><strong>Scene Understanding: Building on a Legacy of Excellence</strong></strong></h3><p>Our journey to advanced scene understanding isn't new. In a previous <a href="https://chat.openai.com/c/7d981ba7-c2bc-463e-bc58-ed13f668afb2?ref=jina-ai-gmbh.ghost.io#">blog post</a>, we discussed the advent of AI-powered multimodal understanding, where we highlighted the role of image captioning algorithms in decoding complex visual information. These tools had matured beyond crafting basic captions; they could analyze scenes and provide enriched descriptions. One standout contender in this domain was SceneXplain.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-vs-minigpt4-a-comprehensive-benchmark-of-top-5-image-captioning-algorithms-for-understanding-complex-scenes/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain vs. MiniGPT4: A Comprehensive Benchmark of Top 5 Image Captioning Algorithms for Understanding Complex Scenes</div><div class="kg-bookmark-description">Uncover the future of image captioning as SceneXplain and its rivals face off in an epic showdown. Explore their impact on accessibility, SEO, and storytelling, and dive into our intriguing results to witness the cutting-edge capabilities of these algorithms.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150443.130.png" alt=""></div></a></figure><p>SceneXplain, our state-of-the-art image captioning solution, was already heralded for its exceptional abilities to leverage large language models (LLMs), producing sophisticated, contextual, and intricately detailed textual descriptions for diverse visual content. As we introduce the <code>Hearth</code> Algorithm, it is essential to recognize that this isn't a mere continuation of SceneXplain's legacy, but a significant step forward.</p><p>In the current algorithm, upon receiving an image, SceneXplain simultaneously discerns the primary subjects and contexts, as well as extracting underlying emotions and intricate details from the visuals. These parallel processes use evolved computer vision techniques combined with our legacy understanding methods to grasp the image's essence and nuances.</p><pre><code class="language-python hljs"><span class="hljs-keyword">def</span> <span class="hljs-title function_">scene_understanding</span>(<span class="hljs-params">image_input</span>):
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Discover the power of SceneXplain's Hearth Algorithm: turning images into captivating narratives. Dive deep into the tech behind it, explore real-world examples, and grasp its potential. Journey beyond pixels to stories at SceneXplain!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 21, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Imagine walking through a dimly lit gallery, where walls are adorned with timeless black-and-white photographs. One image, in particular, catches your eye. A soldier hugging his daughter tightly, possibly seeing her for the last time before heading to war. Tears glisten on the child's cheeks, and even though the image stands still, you can almost hear the whispered promises, the choked-back tears, the soft lullaby sung to offer solace.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_A_soldier_hugging_his_daughter_tightly_possibly__160fb9dc-a02a-4159-8919-0ea2c18fee19.png" class="kg-image" alt="" width="1456" height="816" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/generativejina_A_soldier_hugging_his_daughter_tightly_possibly__160fb9dc-a02a-4159-8919-0ea2c18fee19.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/generativejina_A_soldier_hugging_his_daughter_tightly_possibly__160fb9dc-a02a-4159-8919-0ea2c18fee19.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_A_soldier_hugging_his_daughter_tightly_possibly__160fb9dc-a02a-4159-8919-0ea2c18fee19.png 1456w" sizes="(min-width: 720px) 720px"></figure><blockquote class="kg-blockquote-alt">Now, what if you really could hear that story?</blockquote><div class="kg-card kg-audio-card"><img loading="lazy" src="" alt="audio-thumbnail" class="kg-audio-thumbnail kg-audio-hide"><div class="kg-audio-thumbnail placeholder"><svg width="24" height="24" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.5 15.33a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0ZM15 13.83a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.486 6.81A2.25 2.25 0 0 1 17.25 9v5.579a.75.75 0 0 1-1.5 0v-5.58a.75.75 0 0 0-.932-.727.755.755 0 0 1-.059.013l-4.465.744a.75.75 0 0 0-.544.72v6.33a.75.75 0 0 1-1.5 0v-6.33a2.25 2.25 0 0 1 1.763-2.194l4.473-.746Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3 1.5a.75.75 0 0 0-.75.75v19.5a.75.75 0 0 0 .75.75h18a.75.75 0 0 0 .75-.75V5.133a.75.75 0 0 0-.225-.535l-.002-.002-3-2.883A.75.75 0 0 0 18 1.5H3ZM1.409.659A2.25 2.25 0 0 1 3 0h15a2.25 2.25 0 0 1 1.568.637l.003.002 3 2.883a2.25 2.25 0 0 1 .679 1.61V21.75A2.25 2.25 0 0 1 21 24H3a2.25 2.25 0 0 1-2.25-2.25V2.25c0-.597.237-1.169.659-1.591Z"></path></svg></div><div class="kg-audio-player-container"><audio src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/audios_2853aecf-c13a-4441-a015-872636858b0a_en.wav" preload="metadata"></audio><div class="kg-audio-title">Audio story generated by SceneXplain Hearth algorithm from the above image</div><div class="kg-audio-player"><button class="kg-audio-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-audio-pause-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-audio-current-time">0:00</span><div class="kg-audio-time">/<span class="kg-audio-duration">1:05</span></div><input type="range" class="kg-audio-seek-slider" max="100" value="0"><button class="kg-audio-playback-rate">1×</button><button class="kg-audio-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-audio-mute-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-audio-volume-slider" max="100" value="100"></div></div></div><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/videos_e9e038cc-dde3-459c-aa87-980a26005e44_dialog_en.mp4" poster="https://img.spacergif.org/v1/750x419/0a/spacer.png" width="750" height="419" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember779.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><p>In today's digital age, while short video content has surged, powerful still images often remain trapped in silence. SceneXplain's <code>Hearth</code> algorithm breaks these barriers, giving a voice to the voiceless. It's not merely about observing a moment but immersing oneself in its rich auditory tapestry. With <code>Hearth</code>, every picture has a story to tell and a song to sing, encapsulating the essence of short videos from a static frame.</p><h2 id="why-did-scenexplain-create-the-hearth-algorithm">Why Did SceneXplain Create the <code>Hearth</code> Algorithm?</h2><p>As our digital ecosystem swiftly gravitates towards compact and impactful narratives, the potency of short, immersive content cannot be overlooked. These snippets of visual and auditory tales have become the preferred consumption mode for global audiences. But amidst this video-driven narrative, there remains a vast reservoir of untapped potential: the silent world of static images. These encompass art, history, personal memories, and countless unspoken tales. Recognizing this gap, SceneXplain birthed the <code>Hearth</code> algorithm. It's more than just an enhancement; it's a revolution—bestowing a voice upon the silent and ensuring every image shares its intrinsic story.</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/scenexplain-generate-story.mp4" poster="https://img.spacergif.org/v1/1530x964/0a/spacer.png" width="1530" height="964" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember661.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>How to use SceneXplain's Hearth algorithm to generate audible story from images</figcaption></figure><h2 id="which-industries-can-benefit-from-scenexplains-hearth">Which Industries Can Benefit from SceneXplain's <code>Hearth</code>?</h2><p>The impact and versatility of SceneXplain's <code>Hearth</code> ripple across numerous sectors:</p><ul><li><strong>Film &amp; Entertainment</strong>: Envision a world where directors and scriptwriters utilize Hearth to add depth to their storyboarded visuals, melding sight and sound to create a richer pre-production canvas.</li><li><strong>Marketing &amp; Advertising</strong>: In today's bustling market, capturing attention within moments is paramount. SceneXplain's Hearth equips brands with the tools to morph static campaign images into gripping auditory narratives, fostering deeper connections with audiences.</li><li><strong>Education</strong>: The future of teaching is dynamic. With SceneXplain's Hearth, educators can transition from traditional visuals to interactive auditory experiences, be it through historical recounts or intricate scientific processes.</li><li><strong>Content Creation</strong>: Digital storytellers of the modern age have a new ally. With Hearth, they can augment their visual tales with resonant audio narratives, enhancing engagement and solidifying their space in the vast digital landscape.</li></ul><h2 id="decoding-the-hearth-algorithm-the-nexus-of-visual-understanding-and-auditory-storytelling">Decoding the Hearth Algorithm: The Nexus of Visual Understanding and Auditory Storytelling</h2><p>The <code>Hearth</code> Algorithm's design embodies a meticulous blend of parallelized tasks and sequential steps, ensuring optimal performance while achieving nuanced narrative generation. Our architecture diagram above provides a holistic view of the entire process. Here’s a breakdown of how the magic happens:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/mermaid-diagram-2023-08-21-152542.svg" class="kg-image" alt="" width="149" height="150"></figure><h3 id="1-scene-understanding-building-on-a-legacy-of-excellence"><br>1. <strong><strong>Scene Understanding: Building on a Legacy of Excellence</strong></strong></h3><p>Our journey to advanced scene understanding isn't new. In a previous <a href="https://chat.openai.com/c/7d981ba7-c2bc-463e-bc58-ed13f668afb2?ref=jina-ai-gmbh.ghost.io#">blog post</a>, we discussed the advent of AI-powered multimodal understanding, where we highlighted the role of image captioning algorithms in decoding complex visual information. These tools had matured beyond crafting basic captions; they could analyze scenes and provide enriched descriptions. One standout contender in this domain was SceneXplain.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-vs-minigpt4-a-comprehensive-benchmark-of-top-5-image-captioning-algorithms-for-understanding-complex-scenes/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain vs. MiniGPT4: A Comprehensive Benchmark of Top 5 Image Captioning Algorithms for Understanding Complex Scenes</div><div class="kg-bookmark-description">Uncover the future of image captioning as SceneXplain and its rivals face off in an epic showdown. Explore their impact on accessibility, SEO, and storytelling, and dive into our intriguing results to witness the cutting-edge capabilities of these algorithms.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150443.130.png" alt=""></div></a></figure><p>SceneXplain, our state-of-the-art image captioning solution, was already heralded for its exceptional abilities to leverage large language models (LLMs), producing sophisticated, contextual, and intricately detailed textual descriptions for diverse visual content. As we introduce the <code>Hearth</code> Algorithm, it is essential to recognize that this isn't a mere continuation of SceneXplain's legacy, but a significant step forward.</p><p>In the current algorithm, upon receiving an image, SceneXplain simultaneously discerns the primary subjects and contexts, as well as extracting underlying emotions and intricate details from the visuals. These parallel processes use evolved computer vision techniques combined with our legacy understanding methods to grasp the image's essence and nuances.</p><pre><code class="language-python">def scene_understanding(image_input):
     subjects_and_contexts = get_subject_and_object(image_input)
     emotions_and_details = detect_emotions_and_details(image_input)
-    <span class="hljs-keyword">return</span> subjects_and_contexts, emotions_and_details
-</code></pre><h3 id="2-leveraging-large-language-models-llms">2. Leveraging Large Language Models (LLMs)</h3><p>Once the scene is well-understood, Hearth taps into the prowess of advanced LLMs. Using clues from the image, the LLM simultaneously conceptualizes the characters and the setting while deriving the mood and dynamics of the scene.</p><pre><code class="language-python hljs"><span class="hljs-keyword">def</span> <span class="hljs-title function_">llm_processing</span>(<span class="hljs-params">subjects_and_contexts, emotions_and_details</span>):
+    return subjects_and_contexts, emotions_and_details
+</code></pre><h3 id="2-leveraging-large-language-models-llms">2. Leveraging Large Language Models (LLMs)</h3><p>Once the scene is well-understood, Hearth taps into the prowess of advanced LLMs. Using clues from the image, the LLM simultaneously conceptualizes the characters and the setting while deriving the mood and dynamics of the scene.</p><pre><code class="language-python">def llm_processing(subjects_and_contexts, emotions_and_details):
     characters_and_setting = derive_characters_and_setting(subjects_and_contexts)
     mood_and_dynamics = define_mood_and_dynamics(emotions_and_details)
-    <span class="hljs-keyword">return</span> characters_and_setting, mood_and_dynamics
-</code></pre><h3 id="3-narrative-construction-storyline-and-dialogues">3. Narrative Construction: Storyline and Dialogues</h3><p>With the foundation set, the algorithm crafts a riveting storyline and corresponding dialogues. This phase synthesizes the mood, characters, and settings to spin a tale fitting the selected genre.</p><pre><code class="language-python hljs"><span class="hljs-keyword">def</span> <span class="hljs-title function_">narrative_construction</span>(<span class="hljs-params">characters_and_setting, mood_and_dynamics, genre</span>):
+    return characters_and_setting, mood_and_dynamics
+</code></pre><h3 id="3-narrative-construction-storyline-and-dialogues">3. Narrative Construction: Storyline and Dialogues</h3><p>With the foundation set, the algorithm crafts a riveting storyline and corresponding dialogues. This phase synthesizes the mood, characters, and settings to spin a tale fitting the selected genre.</p><pre><code class="language-python">def narrative_construction(characters_and_setting, mood_and_dynamics, genre):
     storyline = generate_storyline(characters_and_setting, mood_and_dynamics, genre)
     dialogues = create_dialogues(characters_and_setting, mood_and_dynamics, genre)
-    <span class="hljs-keyword">return</span> storyline, dialogues
-</code></pre><h3 id="4-voiceover-emotion-embedding-ssml">4. Voiceover Emotion Embedding (SSML)</h3><p>Narratives gain a deeper dimension with emotional voiceovers. The Hearth algorithm assigns appropriate emotions to the voiceovers, ensuring the tale is not just told, but felt.</p><pre><code class="language-python hljs"><span class="hljs-keyword">def</span> <span class="hljs-title function_">ssml_voiceover_embedding</span>(<span class="hljs-params">storyline, dialogues</span>):
+    return storyline, dialogues
+</code></pre><h3 id="4-voiceover-emotion-embedding-ssml">4. Voiceover Emotion Embedding (SSML)</h3><p>Narratives gain a deeper dimension with emotional voiceovers. The Hearth algorithm assigns appropriate emotions to the voiceovers, ensuring the tale is not just told, but felt.</p><pre><code class="language-python">def ssml_voiceover_embedding(storyline, dialogues):
     ssml_output = generate_emotional_ssml(storyline, dialogues)
-    <span class="hljs-keyword">return</span> ssml_output
-</code></pre><h3 id="5-narrative-review-and-audio-generation">5. Narrative Review and Audio Generation</h3><p>The story undergoes a review to ensure logical coherence and relevance to the original scene. Once approved, the narrative is sent to Azure's Text-to-Speech service, transforming the text into an immersive audio experience.</p><pre><code class="language-python hljs"><span class="hljs-keyword">def</span> <span class="hljs-title function_">audio_generation</span>(<span class="hljs-params">ssml_output</span>):
+    return ssml_output
+</code></pre><h3 id="5-narrative-review-and-audio-generation">5. Narrative Review and Audio Generation</h3><p>The story undergoes a review to ensure logical coherence and relevance to the original scene. Once approved, the narrative is sent to Azure's Text-to-Speech service, transforming the text into an immersive audio experience.</p><pre><code class="language-python">def audio_generation(ssml_output):
     reviewed_story = review_narrative(ssml_output)
     audio_output = azure_tts(reviewed_story)
-    <span class="hljs-keyword">return</span> audio_output
-</code></pre><p>With the above steps, SceneXplain's <code>Hearth</code> Algorithm demonstrates its ability to convert a mere image into an emotionally charged, audibly narrated story, all while preserving the integrity and essence of the original visual.</p><h2 id="examples-seeing-the-hearth-algorithm-in-action">Examples: Seeing the Hearth Algorithm in Action</h2><p>While an intricate algorithm and tech-talk can illustrate the prowess of Hearth, the true test lies in real-world application. Let's dive into four handpicked examples to truly appreciate the intricacy and brilliance of the stories our algorithm crafts:</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/videos_3f6e89d8-7bfe-4b52-924d-992ba9f5ce66_dialog_en.mp4" poster="https://img.spacergif.org/v1/750x563/0a/spacer.png" width="750" height="563" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember883.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/videos_5e41311d-5e33-4de2-8350-b13af0528941_dialog_en--2-.mp4" poster="https://img.spacergif.org/v1/750x500/0a/spacer.png" width="750" height="500" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember909.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/videos_c6b24826-f270-4779-b46e-955e44a0f39c_dialog_en.mp4" poster="https://img.spacergif.org/v1/750x421/0a/spacer.png" width="750" height="421" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember921.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/videos_e8bc3099-d773-4e32-9f5f-72d93cf40fca_dialog_en.mp4" poster="https://img.spacergif.org/v1/750x750/0a/spacer.png" width="750" height="750" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember933.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>The stories above encapsulate the heart of Hearth Algorithm. Not only do they spin a rich tale with unexpected twists and turns, but they also bring the scene to life through vivid character dialogues. Each character, endowed with distinct characteristics and tones, reflects the depth of understanding derived from the image description.</p><h2 id="known-limitations">Known Limitations</h2><p>In our pursuit of elevating the capabilities of SceneXplain through the Hearth Algorithm, it's vital to be transparent about its current challenges, all while focusing on the nuances of our unique tech stack. Here's an introspective look:</p><ul><li><strong>Hallucination Issues:</strong> The concept of models "hallucinating" isn't unfamiliar in deep learning. Specifically, when using algorithms that deeply integrate with LLMs, such as our SceneXplain model, there's a possibility of generating details not present in the source image. This emanates from LLMs being optimized for vast and diverse datasets, sometimes leading them to infer beyond the provided data. However, the field is continuously evolving. By refining SceneXplain's training mechanisms and incorporating more targeted fine-tuning, we aspire to curb such over-generalizations.</li><li><strong>Speed Constraints:</strong> Precision comes at a price: time. The Hearth Algorithm, in its essence, utilizes LLMs, image captioning frameworks like BLIP2 and multimodal embeddings like CLIP. The richness of the narratives it produces is tied to the computational depth it delves into. But as with any AI challenge, it paves the way for innovation. Techniques such as model pruning, tailored for SceneXplain, could optimize its execution speed, enabling faster story derivations without sacrificing their nuance.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/clip-as-service?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/clip-as-service: 🏄 Embed/reason/rank images and sentences with CLIP models</div><div class="kg-bookmark-description">🏄 Embed/reason/rank images and sentences with CLIP models - GitHub - jina-ai/clip-as-service: 🏄 Embed/reason/rank images and sentences with CLIP models</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/157198623/4f792a2e-d529-4f08-80f1-61a55592d781" alt=""></div></a></figure><ul><li><strong>Over-Ethical Content Production:</strong> It's been observed that the Hearth Algorithm, possibly influenced by the ethically-filtered data it was trained on, leans heavily towards generating highly politically correct content. This has inadvertently made it challenging for the model to craft genres like horror, even when explicitly prompted. This isn't a drawback of the ethical stance but more of a fine-tuning nuance. As we progress, integrating more diverse fine-tuning processes, centered around specific genres while maintaining ethical bounds, can help SceneXplain strike a more balanced narrative approach.</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-6.png" class="kg-image" alt="" width="986" height="1566" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-6.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-6.png 986w" sizes="(min-width: 720px) 720px"><figcaption>Unfortunately, it is extremely hard to generate all story genres even if the users specified so.</figcaption></figure><p>At SceneXplain, our commitment is steadfast: refine, innovate, and evolve. With the brilliant minds in the community and our dedicated team, these challenges merely represent the next set of puzzles to solve in our AI journey.</p><h2 id="conclusion"><br>Conclusion</h2><p>The intersection of large language models and image captioning technologies represents an exciting frontier in AI. With SceneXplain's <code>Hearth</code> Algorithm, we've embarked on a journey to bridge the gap between visual information and its narrative counterpart. While our current achievements set benchmarks in image storytelling, our journey is ongoing, underscored by continuous learning, adaptation, and innovation.</p><p>The possibilities of this technology extend far beyond mere image captioning. Imagine content creators gaining inspiration from a single image, educators drawing stories to elucidate complex concepts, or businesses creating engaging multimedia content seamlessly. The horizon is vast, and with every challenge we overcome, we move a step closer to making these visions a reality.</p><p>We invite you to experience the future of image storytelling firsthand. Dive into the rich narratives, witness the intricate character developments, and immerse yourself in the plots crafted meticulously by the Hearth Algorithm. Visit <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">https://scenex.jina.ai</a> to explore, and together, let's shape the future narrative of visual content. Your feedback and experiences are invaluable in guiding our next strides. Join us on this captivating journey.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fbeyond-pixels-to-prose-scenexplains-hearth-algorithm-breathes-audible-life-into-images%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+    return audio_output
+</code></pre><p>With the above steps, SceneXplain's <code>Hearth</code> Algorithm demonstrates its ability to convert a mere image into an emotionally charged, audibly narrated story, all while preserving the integrity and essence of the original visual.</p><h2 id="examples-seeing-the-hearth-algorithm-in-action">Examples: Seeing the Hearth Algorithm in Action</h2><p>While an intricate algorithm and tech-talk can illustrate the prowess of Hearth, the true test lies in real-world application. Let's dive into four handpicked examples to truly appreciate the intricacy and brilliance of the stories our algorithm crafts:</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/videos_3f6e89d8-7bfe-4b52-924d-992ba9f5ce66_dialog_en.mp4" poster="https://img.spacergif.org/v1/750x563/0a/spacer.png" width="750" height="563" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember883.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/videos_5e41311d-5e33-4de2-8350-b13af0528941_dialog_en--2-.mp4" poster="https://img.spacergif.org/v1/750x500/0a/spacer.png" width="750" height="500" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember909.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/videos_c6b24826-f270-4779-b46e-955e44a0f39c_dialog_en.mp4" poster="https://img.spacergif.org/v1/750x421/0a/spacer.png" width="750" height="421" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember921.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/videos_e8bc3099-d773-4e32-9f5f-72d93cf40fca_dialog_en.mp4" poster="https://img.spacergif.org/v1/750x750/0a/spacer.png" width="750" height="750" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember933.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>The stories above encapsulate the heart of Hearth Algorithm. Not only do they spin a rich tale with unexpected twists and turns, but they also bring the scene to life through vivid character dialogues. Each character, endowed with distinct characteristics and tones, reflects the depth of understanding derived from the image description.</p><h2 id="known-limitations">Known Limitations</h2><p>In our pursuit of elevating the capabilities of SceneXplain through the Hearth Algorithm, it's vital to be transparent about its current challenges, all while focusing on the nuances of our unique tech stack. Here's an introspective look:</p><ul><li><strong>Hallucination Issues:</strong> The concept of models "hallucinating" isn't unfamiliar in deep learning. Specifically, when using algorithms that deeply integrate with LLMs, such as our SceneXplain model, there's a possibility of generating details not present in the source image. This emanates from LLMs being optimized for vast and diverse datasets, sometimes leading them to infer beyond the provided data. However, the field is continuously evolving. By refining SceneXplain's training mechanisms and incorporating more targeted fine-tuning, we aspire to curb such over-generalizations.</li><li><strong>Speed Constraints:</strong> Precision comes at a price: time. The Hearth Algorithm, in its essence, utilizes LLMs, image captioning frameworks like BLIP2 and multimodal embeddings like CLIP. The richness of the narratives it produces is tied to the computational depth it delves into. But as with any AI challenge, it paves the way for innovation. Techniques such as model pruning, tailored for SceneXplain, could optimize its execution speed, enabling faster story derivations without sacrificing their nuance.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/clip-as-service?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/clip-as-service: 🏄 Embed/reason/rank images and sentences with CLIP models</div><div class="kg-bookmark-description">🏄 Embed/reason/rank images and sentences with CLIP models - GitHub - jina-ai/clip-as-service: 🏄 Embed/reason/rank images and sentences with CLIP models</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/157198623/4f792a2e-d529-4f08-80f1-61a55592d781" alt=""></div></a></figure><ul><li><strong>Over-Ethical Content Production:</strong> It's been observed that the Hearth Algorithm, possibly influenced by the ethically-filtered data it was trained on, leans heavily towards generating highly politically correct content. This has inadvertently made it challenging for the model to craft genres like horror, even when explicitly prompted. This isn't a drawback of the ethical stance but more of a fine-tuning nuance. As we progress, integrating more diverse fine-tuning processes, centered around specific genres while maintaining ethical bounds, can help SceneXplain strike a more balanced narrative approach.</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-6.png" class="kg-image" alt="" width="986" height="1566" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-6.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-6.png 986w" sizes="(min-width: 720px) 720px"><figcaption>Unfortunately, it is extremely hard to generate all story genres even if the users specified so.</figcaption></figure><p>At SceneXplain, our commitment is steadfast: refine, innovate, and evolve. With the brilliant minds in the community and our dedicated team, these challenges merely represent the next set of puzzles to solve in our AI journey.</p><h2 id="conclusion"><br>Conclusion</h2><p>The intersection of large language models and image captioning technologies represents an exciting frontier in AI. With SceneXplain's <code>Hearth</code> Algorithm, we've embarked on a journey to bridge the gap between visual information and its narrative counterpart. While our current achievements set benchmarks in image storytelling, our journey is ongoing, underscored by continuous learning, adaptation, and innovation.</p><p>The possibilities of this technology extend far beyond mere image captioning. Imagine content creators gaining inspiration from a single image, educators drawing stories to elucidate complex concepts, or businesses creating engaging multimedia content seamlessly. The horizon is vast, and with every challenge we overcome, we move a step closer to making these visions a reality.</p><p>We invite you to experience the future of image storytelling firsthand. Dive into the rich narratives, witness the intricate character developments, and immerse yourself in the plots crafted meticulously by the Hearth Algorithm. Visit <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">https://scenex.jina.ai</a> to explore, and together, let's shape the future narrative of visual content. Your feedback and experiences are invaluable in guiding our next strides. Join us on this captivating journey.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fbeyond-pixels-to-prose-scenexplains-hearth-algorithm-breathes-audible-life-into-images%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Boosting AI Model Performance: Fine-tuning with Synthetic Data for Enhanced Results</title><meta charset="utf-8"><meta name="title" content="Boosting AI Model Performance: Fine-tuning with Synthetic Data for Enhanced Results"><meta name="description" content="Using Finetuner for data synthesis means that adapting your AI-powered information retrieval system to your domain is now as easy as collecting your logs."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/boosting-ai-model-performance-fine-tuning-with-synthetic-data-for-enhanced-results"><meta property="og:title" content="Boosting AI Model Performance: Fine-tuning with Synthetic Data for Enhanced Results"><meta property="og:description" content="Using Finetuner for data synthesis means that adapting your AI-powered information retrieval system to your domain is now as easy as collecting your logs."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Blog_images_-19-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/boosting-ai-model-performance-fine-tuning-with-synthetic-data-for-enhanced-results"><meta property="twitter:title" content="Boosting AI Model Performance: Fine-tuning with Synthetic Data for Enhanced Results"><meta property="twitter:description" content="Using Finetuner for data synthesis means that adapting your AI-powered information retrieval system to your domain is now as easy as collecting your logs."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Blog_images_-19-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="21dd995b-1089-42bd-b0ba-d699f3d4c1fe" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="21dd995b-1089-42bd-b0ba-d699f3d4c1fe" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Boosting AI Model Performance: Fine-tuning with Synthetic Data for Enhanced Results</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Using Finetuner for data synthesis means that adapting your AI-powered information retrieval system to your domain is now as easy as collecting your logs.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 07, 2023 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Search has never been easy for smaller enterprises. Operating a high-quality information retrieval system can be an expensive and demanding proposition. Many small businesses — even many large ones — accept mediocre performance from off-the-shelf software or outsource the problem to Google or some other service provider.</p><p>There are some good reasons for this. Information retrieval (IR) is not a simple application.</p><ul><li>Word matching is a fairly simple application, but if you sell shoes and your customer searches for <em>trainers</em>, but all you have is <em>sneakers</em><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong>,</strong></strong></strong></strong></strong></strong></strong></strong></strong></strong> you will quickly find that word matching is not a good way to do search.</li><li>Even when words match, how would your search engine know if a request for a “face mask” is for a protective face covering against contagious disease or for a Halloween costume?</li><li>If someone searches for <em>surfing</em>, what they expect is very different if you’re a travel agency than if you sell clothes.</li></ul><p>Enterprise-level search solutions require a lot of tweaks for specific use cases, demanding a lot of expertise and understanding of how search solutions work. And those tweaks have to be regularly updated for new information and new products.</p><p>The <a href="https://jina.ai/news/what-is-neural-search-and-learn-to-build-a-neural-search-engine/?ref=jina-ai-gmbh.ghost.io">AI-driven neural search revolution</a> has changed a lot about IR, but so far, it hasn’t really done much to solve this problem. <a href="https://www.notion.so/Sponsor-perk-job-listings-provide-to-org-0a27e903a7574087b6ea3aca5477ce68?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">One recent paper</a> tried to use an AI model trained on data from before 2017 with a set of documents about COVID-19, and the results were very poor. Neural search still requires domain adaptation: The model still has to learn your subject area, business model, and documents to work properly.</p><p>The great thing about machine learning is that it doesn’t need detailed or specific information about your use case. It just needs enough good examples to learn from. We’re going to show you how to use Jina AI’s <a href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner</a> to learn from your existing search logs without any labeling and without even knowing which of your documents best matches the queries in your logs.</p><h2 id="how-ai-driven-information-retrieval-works"><strong>How AI-driven information retrieval works</strong></h2><p>Information retrieval means identifying items in a database in response to a query. For example, when you put words into the input box of an internet search engine, you get back a set of URLs (and possibly other things) from the search engine’s database that, hopefully, are the ones most relevant to the words you put in.</p><p>IR as a field of applied computer science dates back to the earliest days of computers, and people have used many different algorithms and techniques to do the actual work of matching queries to digital data items (typically called <em>documents</em>, although they could be any kind of digital media, not just text). The most widely used model, the one most IR systems derive from, is called the <a href="https://en.wikipedia.org/wiki/Vector_space_model?ref=jina-ai-gmbh.ghost.io">vector space model</a>, originally developed in the <a href="https://doi.org/10.1145/364955.364990?ref=jina-ai-gmbh.ghost.io">early 1960s at IBM</a>.</p><p>This model is based on a very simple idea: Every document is represented by a unique vector (often called an <em>embedding</em> if it comes from an AI model) in some high-dimensional space and queries are translated into vectors (<em>embeddings</em>) in this same space. Query matches are those documents whose vectors are closest, or close enough, to the query vector. The problem of identifying those documents is just a question of measuring the distances between the two vectors, usually by measuring the angle between them:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Blog_images_-20--1.png" class="kg-image" alt="Document d is a better match for query q than document d because the angle between d and q is smaller than the angle between d and q" width="1600" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Blog_images_-20--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/Blog_images_-20--1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Blog_images_-20--1.png 1600w" sizes="(min-width: 720px) 720px"><figcaption>Document <em>d₁</em> is a better match for query <em>q</em> than document <em>d₂</em> because the angle between <em>d₁</em> and <em>q</em> is smaller than the angle between <em>d₂</em> and <em>q.</em></figcaption></figure><p>The problem is how you translate documents and queries into vectors.</p><p>Traditional vector-based information retrieval techniques like <a href="https://en.wikipedia.org/wiki/Okapi_BM25?ref=jina-ai-gmbh.ghost.io">BM25</a> didn’t have AI models to make their vectors, but nowadays, models like <a href="https://www.sbert.net/?ref=jina-ai-gmbh.ghost.io">SBERT</a> do the same job directly: A neural network takes documents and queries as inputs and produces vectors as output. The fundamental problem, however, is the same: Queries and the documents that they match have to be close together in the output vector space. With traditional search technologies, you fiddle with the weights and inputs by hand to make that work. With an AI model, you use fine-tuning and make the computer do those adjustments based on examples.</p><h2 id="synthetic-training-data"><strong>Synthetic Training Data</strong></h2><p>If you’ve been operating an IR service — even a mediocre one — you already have the kind of data you need to adapt an AI model to your domain. Your search logs are full of user queries, and you have the documents that they need to match. That’s all you need. You don’t even need to know which queries match which results.</p><p>This works by creating synthetic training data from your queries and documents. There are five steps to the process:</p><ol><li>Collect your queries by extracting them from your search logs or whatever way you store them, along with whatever documents you are serving through your search system.</li><li>Use a pre-trained text encoder model (for example, SBERT) to encode the queries and documents.</li><li>Identify the best matching results for each query (by default, we use the 100 best matches) by calculating the distance between queries and documents.</li><li>Use a cross-encoder to give a score to each query-result pair. We use a model trained on the <a href="https://microsoft.github.io/msmarco/?ref=jina-ai-gmbh.ghost.io">MS-MARCO dataset</a> specifically to score pairs of natural language questions and answers.</li><li>Use the resulting data to fine-tune your AI model.</li></ol><p>With Finetuner, you can do this with <em>just two calls</em> to the Jina AI Cloud.</p><h2 id="finetuner-synthesis"><strong>Finetuner Synthesis</strong></h2><p>For the first step, you need your queries and documents. Extract them from your logs and archives by whatever means those systems require. Assemble them as <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray</a> objects, as lists, or in a CSV file. See the page <a href="https://finetuner.jina.ai/walkthrough/create-training-data/?ref=jina-ai-gmbh.ghost.io">Preparing Training Data</a> in the Finetuner documentation for more on this subject.</p><p>Currently, Finetuner only supports queries and natural language documents in English.</p><p>You should have query data and documents in separate objects:</p><pre><code class="language-python hljs">my_queries = &lt;your query data&gt;
-my_documents = &lt;your documents&gt;</code></pre><p>The <code>finetuner.synthesize</code> function from Jina AI’s Finetuner performs the next three steps in a batch. You must specify your query and document data as arguments:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> finetuner
-<span class="hljs-keyword">from</span> finetuner.model <span class="hljs-keyword">import</span> synthesis_model_en
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Boosting AI Model Performance: Fine-tuning with Synthetic Data for Enhanced Results</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Using Finetuner for data synthesis means that adapting your AI-powered information retrieval system to your domain is now as easy as collecting your logs.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 07, 2023 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Search has never been easy for smaller enterprises. Operating a high-quality information retrieval system can be an expensive and demanding proposition. Many small businesses — even many large ones — accept mediocre performance from off-the-shelf software or outsource the problem to Google or some other service provider.</p><p>There are some good reasons for this. Information retrieval (IR) is not a simple application.</p><ul><li>Word matching is a fairly simple application, but if you sell shoes and your customer searches for <em>trainers</em>, but all you have is <em>sneakers</em><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong>,</strong></strong></strong></strong></strong></strong></strong></strong></strong></strong> you will quickly find that word matching is not a good way to do search.</li><li>Even when words match, how would your search engine know if a request for a “face mask” is for a protective face covering against contagious disease or for a Halloween costume?</li><li>If someone searches for <em>surfing</em>, what they expect is very different if you’re a travel agency than if you sell clothes.</li></ul><p>Enterprise-level search solutions require a lot of tweaks for specific use cases, demanding a lot of expertise and understanding of how search solutions work. And those tweaks have to be regularly updated for new information and new products.</p><p>The <a href="https://jina.ai/news/what-is-neural-search-and-learn-to-build-a-neural-search-engine/?ref=jina-ai-gmbh.ghost.io">AI-driven neural search revolution</a> has changed a lot about IR, but so far, it hasn’t really done much to solve this problem. <a href="https://www.notion.so/Sponsor-perk-job-listings-provide-to-org-0a27e903a7574087b6ea3aca5477ce68?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">One recent paper</a> tried to use an AI model trained on data from before 2017 with a set of documents about COVID-19, and the results were very poor. Neural search still requires domain adaptation: The model still has to learn your subject area, business model, and documents to work properly.</p><p>The great thing about machine learning is that it doesn’t need detailed or specific information about your use case. It just needs enough good examples to learn from. We’re going to show you how to use Jina AI’s <a href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner</a> to learn from your existing search logs without any labeling and without even knowing which of your documents best matches the queries in your logs.</p><h2 id="how-ai-driven-information-retrieval-works"><strong>How AI-driven information retrieval works</strong></h2><p>Information retrieval means identifying items in a database in response to a query. For example, when you put words into the input box of an internet search engine, you get back a set of URLs (and possibly other things) from the search engine’s database that, hopefully, are the ones most relevant to the words you put in.</p><p>IR as a field of applied computer science dates back to the earliest days of computers, and people have used many different algorithms and techniques to do the actual work of matching queries to digital data items (typically called <em>documents</em>, although they could be any kind of digital media, not just text). The most widely used model, the one most IR systems derive from, is called the <a href="https://en.wikipedia.org/wiki/Vector_space_model?ref=jina-ai-gmbh.ghost.io">vector space model</a>, originally developed in the <a href="https://doi.org/10.1145/364955.364990?ref=jina-ai-gmbh.ghost.io">early 1960s at IBM</a>.</p><p>This model is based on a very simple idea: Every document is represented by a unique vector (often called an <em>embedding</em> if it comes from an AI model) in some high-dimensional space and queries are translated into vectors (<em>embeddings</em>) in this same space. Query matches are those documents whose vectors are closest, or close enough, to the query vector. The problem of identifying those documents is just a question of measuring the distances between the two vectors, usually by measuring the angle between them:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Blog_images_-20--1.png" class="kg-image" alt="Document d is a better match for query q than document d because the angle between d and q is smaller than the angle between d and q" width="1600" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Blog_images_-20--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/Blog_images_-20--1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Blog_images_-20--1.png 1600w" sizes="(min-width: 720px) 720px"><figcaption>Document <em>d₁</em> is a better match for query <em>q</em> than document <em>d₂</em> because the angle between <em>d₁</em> and <em>q</em> is smaller than the angle between <em>d₂</em> and <em>q.</em></figcaption></figure><p>The problem is how you translate documents and queries into vectors.</p><p>Traditional vector-based information retrieval techniques like <a href="https://en.wikipedia.org/wiki/Okapi_BM25?ref=jina-ai-gmbh.ghost.io">BM25</a> didn’t have AI models to make their vectors, but nowadays, models like <a href="https://www.sbert.net/?ref=jina-ai-gmbh.ghost.io">SBERT</a> do the same job directly: A neural network takes documents and queries as inputs and produces vectors as output. The fundamental problem, however, is the same: Queries and the documents that they match have to be close together in the output vector space. With traditional search technologies, you fiddle with the weights and inputs by hand to make that work. With an AI model, you use fine-tuning and make the computer do those adjustments based on examples.</p><h2 id="synthetic-training-data"><strong>Synthetic Training Data</strong></h2><p>If you’ve been operating an IR service — even a mediocre one — you already have the kind of data you need to adapt an AI model to your domain. Your search logs are full of user queries, and you have the documents that they need to match. That’s all you need. You don’t even need to know which queries match which results.</p><p>This works by creating synthetic training data from your queries and documents. There are five steps to the process:</p><ol><li>Collect your queries by extracting them from your search logs or whatever way you store them, along with whatever documents you are serving through your search system.</li><li>Use a pre-trained text encoder model (for example, SBERT) to encode the queries and documents.</li><li>Identify the best matching results for each query (by default, we use the 100 best matches) by calculating the distance between queries and documents.</li><li>Use a cross-encoder to give a score to each query-result pair. We use a model trained on the <a href="https://microsoft.github.io/msmarco/?ref=jina-ai-gmbh.ghost.io">MS-MARCO dataset</a> specifically to score pairs of natural language questions and answers.</li><li>Use the resulting data to fine-tune your AI model.</li></ol><p>With Finetuner, you can do this with <em>just two calls</em> to the Jina AI Cloud.</p><h2 id="finetuner-synthesis"><strong>Finetuner Synthesis</strong></h2><p>For the first step, you need your queries and documents. Extract them from your logs and archives by whatever means those systems require. Assemble them as <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray</a> objects, as lists, or in a CSV file. See the page <a href="https://finetuner.jina.ai/walkthrough/create-training-data/?ref=jina-ai-gmbh.ghost.io">Preparing Training Data</a> in the Finetuner documentation for more on this subject.</p><p>Currently, Finetuner only supports queries and natural language documents in English.</p><p>You should have query data and documents in separate objects:</p><pre><code class="language-python">my_queries = &lt;your query data&gt;
+my_documents = &lt;your documents&gt;</code></pre><p>The <code>finetuner.synthesize</code> function from Jina AI’s Finetuner performs the next three steps in a batch. You must specify your query and document data as arguments:</p><pre><code class="language-python">import finetuner
+from finetuner.model import synthesis_model_en
 
 synthesis_run = finetuner.synthesize(
     query_data=my_queries,
     corpus_data=my_documents,
     models=synthesis_model_en,
-)</code></pre><p>This does the entire data synthesis job, producing query-document pairs with scores. Once it’s done, your synthetic data is stored on <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a>. You can see it by logging in there and going to the <a href="https://cloud.jina.ai/user/storage?ref=jina-ai-gmbh.ghost.io">Storage section</a>:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled.png" class="kg-image" alt="Untitled" width="1087" height="811" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Untitled.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/Untitled.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled.png 1087w" sizes="(min-width: 720px) 720px"></figure><p>You can also get the dataset name of the synthetic training data from the <code>train_data</code> member of the synthesis run object:</p><p><code><code>train_data_name = synthesis_run.train_data</code></code></p><p>You can download the synthetic data from the Jina AI Cloud and inspect it or store it for future use:</p><pre><code class="language-python hljs">train_data_name = synthesis_run.train_data</code></pre><p>Then, <a href="https://finetuner.jina.ai/walkthrough/run-job/?ref=jina-ai-gmbh.ghost.io">run Finetuner</a> on this new synthetic data:</p><pre><code class="language-python hljs">train_data = DocumentArray.pull(train_data_name)
-train_data.summary()</code></pre><p>Training will take some time, likely several hours, depending on the number of examples. See the <a href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner documentation</a> for information on how to monitor the status of your Finetuner run. Once finished, you can now download your domain-adapted neural search model:</p><pre><code class="language-python hljs">training_run.save_artifact(<span class="hljs-string">'my_adapted_model'</span>)</code></pre><p>Using Finetuner means that adapting your AI-powered IR system to your domain is now as easy as collecting your logs. The process is quick and simple enough to run regularly when you update your website.</p><p>Keeping your IR system up-to-date with your products is critical for e-commerce businesses.</p><ul><li>It ensures that the most recent and relevant products or services are promptly visible to customers.</li><li>It promotes customer satisfaction and retention, as clients can quickly find what they're searching for.</li><li>Frequent updates help businesses remain agile in managing their inventories, especially when new products are launched or existing ones are discontinued.</li><li>Regular model updates contribute to a smoother, more efficient user experience.</li><li>It helps reduce the potential for AI models to make mistakes that could negatively impact customer trust.</li></ul><p>Using Finetuner is an investment in customer satisfaction, business agility, and operational efficiency.</p><p>To learn more about data synthesis via Finetuner, see the<a href="https://finetuner.jina.ai/notebooks/data_synthesis/?ref=jina-ai-gmbh.ghost.io"> documentation on the Finetuner website</a>, including a <a href="https://colab.research.google.com/drive/1sX5K0eophlHXu1S7joysZJUj1zfh28Gi?usp=sharing&amp;ref=jina-ai-gmbh.ghost.io">notebook</a> you can use to try it out yourself.</p><p>To learn more about Finetuner, we have a <a href="https://jina.ai/news/fine-tuning-how-to-get-the-most-of-your-ai-investments/?ref=jina-ai-gmbh.ghost.io">non-technical introduction on our website</a>. You can also visit the <a href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner website</a> or <a href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io">GitHub page</a> and join us on the <a href="https://discord.com/channels/1106542220112302130/1107964848102449272?ref=jina-ai-gmbh.ghost.io">Finetuner announcements</a> and <a href="https://discord.com/channels/1106542220112302130/1106560212875350076?ref=jina-ai-gmbh.ghost.io">support</a> channels on our Discord community. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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+)</code></pre><p>This does the entire data synthesis job, producing query-document pairs with scores. Once it’s done, your synthetic data is stored on <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a>. You can see it by logging in there and going to the <a href="https://cloud.jina.ai/user/storage?ref=jina-ai-gmbh.ghost.io">Storage section</a>:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled.png" class="kg-image" alt="Untitled" width="1087" height="811" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Untitled.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/Untitled.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled.png 1087w" sizes="(min-width: 720px) 720px"></figure><p>You can also get the dataset name of the synthetic training data from the <code>train_data</code> member of the synthesis run object:</p><p><code><code>train_data_name = synthesis_run.train_data</code></code></p><p>You can download the synthetic data from the Jina AI Cloud and inspect it or store it for future use:</p><pre><code class="language-python">train_data_name = synthesis_run.train_data</code></pre><p>Then, <a href="https://finetuner.jina.ai/walkthrough/run-job/?ref=jina-ai-gmbh.ghost.io">run Finetuner</a> on this new synthetic data:</p><pre><code class="language-python">train_data = DocumentArray.pull(train_data_name)
+train_data.summary()</code></pre><p>Training will take some time, likely several hours, depending on the number of examples. See the <a href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner documentation</a> for information on how to monitor the status of your Finetuner run. Once finished, you can now download your domain-adapted neural search model:</p><pre><code class="language-python">training_run.save_artifact('my_adapted_model')</code></pre><p>Using Finetuner means that adapting your AI-powered IR system to your domain is now as easy as collecting your logs. The process is quick and simple enough to run regularly when you update your website.</p><p>Keeping your IR system up-to-date with your products is critical for e-commerce businesses.</p><ul><li>It ensures that the most recent and relevant products or services are promptly visible to customers.</li><li>It promotes customer satisfaction and retention, as clients can quickly find what they're searching for.</li><li>Frequent updates help businesses remain agile in managing their inventories, especially when new products are launched or existing ones are discontinued.</li><li>Regular model updates contribute to a smoother, more efficient user experience.</li><li>It helps reduce the potential for AI models to make mistakes that could negatively impact customer trust.</li></ul><p>Using Finetuner is an investment in customer satisfaction, business agility, and operational efficiency.</p><p>To learn more about data synthesis via Finetuner, see the<a href="https://finetuner.jina.ai/notebooks/data_synthesis/?ref=jina-ai-gmbh.ghost.io"> documentation on the Finetuner website</a>, including a <a href="https://colab.research.google.com/drive/1sX5K0eophlHXu1S7joysZJUj1zfh28Gi?usp=sharing&amp;ref=jina-ai-gmbh.ghost.io">notebook</a> you can use to try it out yourself.</p><p>To learn more about Finetuner, we have a <a href="https://jina.ai/news/fine-tuning-how-to-get-the-most-of-your-ai-investments/?ref=jina-ai-gmbh.ghost.io">non-technical introduction on our website</a>. You can also visit the <a href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner website</a> or <a href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io">GitHub page</a> and join us on the <a href="https://discord.com/channels/1106542220112302130/1107964848102449272?ref=jina-ai-gmbh.ghost.io">Finetuner announcements</a> and <a href="https://discord.com/channels/1106542220112302130/1106560212875350076?ref=jina-ai-gmbh.ghost.io">support</a> channels on our Discord community. We also provide personal assistance and support to customers via our <a href="https://finetunerplus.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner+ service</a> to make the process of adapting and using AI in your business as smooth as possible.</p><h2 id="get-in-touch">Get in touch</h2><p>Talk to us and keep the conversation going by joining the Jina AI Discord!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Jina AI Discord</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fboosting-ai-model-performance-fine-tuning-with-synthetic-data-for-enhanced-results%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Brand Engagement Reimagined: AI-Powered Sentiment Analysis with SceneXplain</title><meta charset="utf-8"><meta name="title" content="Brand Engagement Reimagined: AI-Powered Sentiment Analysis with SceneXplain"><meta name="description" content="Digging deep into images to uncover sentiment and brand can be a wild ride. Tackle it with SceneXplain, and you've got yourself a business power-up, ready to take the market by storm"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/brand-engagement-reimagined-ai-powered-sentiment-analysis-with-scenexplain"><meta property="og:title" content="Brand Engagement Reimagined: AI-Powered Sentiment Analysis with SceneXplain"><meta property="og:description" content="Digging deep into images to uncover sentiment and brand can be a wild ride. Tackle it with SceneXplain, and you've got yourself a business power-up, ready to take the market by storm"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Sentiment-analysis.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/brand-engagement-reimagined-ai-powered-sentiment-analysis-with-scenexplain"><meta property="twitter:title" content="Brand Engagement Reimagined: AI-Powered Sentiment Analysis with SceneXplain"><meta property="twitter:description" content="Digging deep into images to uncover sentiment and brand can be a wild ride. Tackle it with SceneXplain, and you've got yourself a business power-up, ready to take the market by storm"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Sentiment-analysis.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Brand Engagement Reimagined: AI-Powered Sentiment Analysis with SceneXplain</title><meta charset="utf-8"><meta name="title" content="Brand Engagement Reimagined: AI-Powered Sentiment Analysis with SceneXplain"><meta name="description" content="Digging deep into images to uncover sentiment and brand can be a wild ride. Tackle it with SceneXplain, and you've got yourself a business power-up, ready to take the market by storm"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/brand-engagement-reimagined-ai-powered-sentiment-analysis-with-scenexplain"><meta property="og:title" content="Brand Engagement Reimagined: AI-Powered Sentiment Analysis with SceneXplain"><meta property="og:description" content="Digging deep into images to uncover sentiment and brand can be a wild ride. Tackle it with SceneXplain, and you've got yourself a business power-up, ready to take the market by storm"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Sentiment-analysis.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/brand-engagement-reimagined-ai-powered-sentiment-analysis-with-scenexplain"><meta property="twitter:title" content="Brand Engagement Reimagined: AI-Powered Sentiment Analysis with SceneXplain"><meta property="twitter:description" content="Digging deep into images to uncover sentiment and brand can be a wild ride. Tackle it with SceneXplain, and you've got yourself a business power-up, ready to take the market by storm"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Sentiment-analysis.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Brand Engagement Reimagined: AI-Powered Sentiment Analysis with SceneXplain</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Digging deep into images to uncover sentiment and brand can be a wild ride. Tackle it with SceneXplain, and you've got yourself a business power-up, ready to take the market by storm</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 03, 2023 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>We've been putting a lot of work into SceneXplain recently, especially the visual question-answering. If you're not familiar with it, SceneXplain uses AI to generate textual descriptions from images. It's designed with a user-friendly interface and offers API integration, making it accessible for application integration. Instead of simply providing captions, it aims to produce <a href="https://jina.ai/news/scenexplain-unleash-advanced-image-captioning-storytelling/?ref=jina-ai-gmbh.ghost.io">more descriptive narratives about image content</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><p>In this post, we'll explore how we can use the feature to perform image sentiment analysis for brand social listening.</p><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">🔤</div><div class="kg-callout-text">In a future post, we’ll dive into performing sentiment analysis on text too. In the meantime, it works essentially the same, so feel free to try it out on PromptPerfect!</div></div><p>Due to pesky copyrights and trademarks, we'll avoid any <em>real</em> brands, and use a <a href="https://en.wikipedia.org/wiki/Fictional_brand?ref=jina-ai-gmbh.ghost.io">fictional brand</a>, Duff Beer (from <em>The Simpsons</em>), as our first example.</p><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">🖼️</div><div class="kg-callout-text">Halfway through writing this post, I found some brand photos I can use for free. I'll include some of those after the Duff Beer, and we'll use SceneXplain's API to do our sentiment analysis.</div></div><h2 id="what-is-sentiment-analysis">What is sentiment analysis?</h2><p>I'm more of a geek than a marketer, so I'll let <a href="https://en.wikipedia.org/wiki/Sentiment_analysis?ref=jina-ai-gmbh.ghost.io">Wikipedia</a> do the talking:</p><blockquote>Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine. With the rise of deep language models, such as RoBERTa, also more difficult data domains can be analyzed, e.g., news texts where authors typically express their opinion/sentiment less explicitly.</blockquote><p>One of the key challenges in sentiment analysis is removing noise from the image we're looking at. If you're looking at a picture of happy people drinking beer at an outdoor festival, you generally don't care about the shape of the clouds or whether the bartender is wearing a T-shirt or a polo shirt. You care about the people (are they happy? Are they miserable?) and the brand of the beer (is it your brand or a competitor's?)</p><h2 id="visual-question-answering-for-understanding-images">Visual question answering for understanding images</h2><p>Let's start by asking a simple question about an image: <code>Is there beer in this picture?</code></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/maxresdefault.jpg" class="kg-image" alt="" width="1280" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/maxresdefault.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/maxresdefault.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/maxresdefault.jpg 1280w" sizes="(min-width: 720px) 720px"></figure><p>And the output from SceneXplain is:</p><pre><code class="language-text hljs language-plaintext">Yes, there are bottles and cans of Duff beer visible in the image.
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Digging deep into images to uncover sentiment and brand can be a wild ride. Tackle it with SceneXplain, and you've got yourself a business power-up, ready to take the market by storm</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 03, 2023 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>We've been putting a lot of work into SceneXplain recently, especially the visual question-answering. If you're not familiar with it, SceneXplain uses AI to generate textual descriptions from images. It's designed with a user-friendly interface and offers API integration, making it accessible for application integration. Instead of simply providing captions, it aims to produce <a href="https://jina.ai/news/scenexplain-unleash-advanced-image-captioning-storytelling/?ref=jina-ai-gmbh.ghost.io">more descriptive narratives about image content</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><p>In this post, we'll explore how we can use the feature to perform image sentiment analysis for brand social listening.</p><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">🔤</div><div class="kg-callout-text">In a future post, we’ll dive into performing sentiment analysis on text too. In the meantime, it works essentially the same, so feel free to try it out on PromptPerfect!</div></div><p>Due to pesky copyrights and trademarks, we'll avoid any <em>real</em> brands, and use a <a href="https://en.wikipedia.org/wiki/Fictional_brand?ref=jina-ai-gmbh.ghost.io">fictional brand</a>, Duff Beer (from <em>The Simpsons</em>), as our first example.</p><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">🖼️</div><div class="kg-callout-text">Halfway through writing this post, I found some brand photos I can use for free. I'll include some of those after the Duff Beer, and we'll use SceneXplain's API to do our sentiment analysis.</div></div><h2 id="what-is-sentiment-analysis">What is sentiment analysis?</h2><p>I'm more of a geek than a marketer, so I'll let <a href="https://en.wikipedia.org/wiki/Sentiment_analysis?ref=jina-ai-gmbh.ghost.io">Wikipedia</a> do the talking:</p><blockquote>Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine. With the rise of deep language models, such as RoBERTa, also more difficult data domains can be analyzed, e.g., news texts where authors typically express their opinion/sentiment less explicitly.</blockquote><p>One of the key challenges in sentiment analysis is removing noise from the image we're looking at. If you're looking at a picture of happy people drinking beer at an outdoor festival, you generally don't care about the shape of the clouds or whether the bartender is wearing a T-shirt or a polo shirt. You care about the people (are they happy? Are they miserable?) and the brand of the beer (is it your brand or a competitor's?)</p><h2 id="visual-question-answering-for-understanding-images">Visual question answering for understanding images</h2><p>Let's start by asking a simple question about an image: <code>Is there beer in this picture?</code></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/maxresdefault.jpg" class="kg-image" alt="" width="1280" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/maxresdefault.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/maxresdefault.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/maxresdefault.jpg 1280w" sizes="(min-width: 720px) 720px"></figure><p>And the output from SceneXplain is:</p><pre><code class="language-text">Yes, there are bottles and cans of Duff beer visible in the image.
 Homer Simpson is holding a bottle of Duff beer, and a can of 
-Duff beer is resting on the grass in front of an open field.</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-15.png" class="kg-image" alt="" width="594" height="680"></figure><p>That's nice but not super useful if we want to do batch analysis on images. In a case like that, we'd want a standardized output so we can perform deeper analysis later on. We'd want something like <code>True</code> or <code>False</code>. So let's change the prompt to <code>Return "True" if there is beer in the picture. Otherwise, return "False"</code>. Now SceneXplain simply returns <code>True</code> for the image above:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-16.png" class="kg-image" alt="" width="600" height="656" srcset="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-16.png 600w"></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">🧠</div><div class="kg-callout-text">In cases where we want very simple output, the default model may give too much information. I changed to the "Flash" model for the above example.</div></div><p>We can also do things like getting a detailed description of the image:</p><pre><code class="language-text hljs language-plaintext">Please identify and describe the beer brand, location and atmosphere 
+Duff beer is resting on the grass in front of an open field.</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-15.png" class="kg-image" alt="" width="594" height="680"></figure><p>That's nice but not super useful if we want to do batch analysis on images. In a case like that, we'd want a standardized output so we can perform deeper analysis later on. We'd want something like <code>True</code> or <code>False</code>. So let's change the prompt to <code>Return "True" if there is beer in the picture. Otherwise, return "False"</code>. Now SceneXplain simply returns <code>True</code> for the image above:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-16.png" class="kg-image" alt="" width="600" height="656" srcset="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-16.png 600w"></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">🧠</div><div class="kg-callout-text">In cases where we want very simple output, the default model may give too much information. I changed to the "Flash" model for the above example.</div></div><p>We can also do things like getting a detailed description of the image:</p><pre><code class="language-text">Please identify and describe the beer brand, location and atmosphere 
 from the photo. Your answer should provide enough detail and 
 description to allow us to understand the scenario accurately. 
 You can provide any relevant information such as backstory, 
-scene analysis, participant interactions, etc.</code></pre><p>That gives us:</p><pre><code class="language-text hljs language-plaintext">The beer brand in the image is the iconic Duff beer, which is a
+scene analysis, participant interactions, etc.</code></pre><p>That gives us:</p><pre><code class="language-text">The beer brand in the image is the iconic Duff beer, which is a
 fictional beer brand featured in the animated television series,
 The Simpsons. The location is an outdoor setting with a whimsical
 blue sky, fluffy clouds, and the Simpsons family gathered in a
@@ -29,64 +29,64 @@
 the iconic Simpsons logo assumes the word "Duff," emphasizing
 the refreshing energy of the moment. The family, including
 Marge, Bart, Lisa, and Maggie, stands together, collectively
-enjoying the outdoors.</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-18.png" class="kg-image" alt="" width="588" height="786"></figure><p>As you can see, there's a little bit of hallucination going on (as is normal with these kinds of AI models). I can't see any of the Simpsons’ family members (outside of Homer) or the logo assuming anything. But the general gist is there, with the details that are important for sentiment analysis.</p><p>But enough with the cartoons - let’s test this on some real photos and in a real-world use case via the API and working with JSON.</p><h2 id="analyzing-brand-sentiment-via-api">Analyzing brand sentiment via API</h2><p>Alas, we do not live in Springfield like the Simpsons. No dodgy nuclear reactors or Duff Beer for us. But we can make do with some real-world brands to quench our thirst.</p><p>We'll use <a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io"><strong>SceneXplain's API</strong></a> to easily analyze some photos in bulk. In our case we'll use Python, though JavaScript and cURL access are also available. Here are the images we'll analyze:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.666667 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-1267305.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-1267305.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-1267305.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-1267305.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-1267305.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.666667 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-2076755.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-2076755.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-2076755.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-2076755.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-2076755.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-3922817.jpeg" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-3922817.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-3922817.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-3922817.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-3922817.jpeg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-3922818.jpeg" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-3922818.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-3922818.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-3922818.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-3922818.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-5935229.jpeg" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-5935229.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-5935229.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-5935229.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-5935229.jpeg 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>To follow along with this code, you'll need a secret key, which you can generate from SceneXplain's API page:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-17.png" class="kg-image" alt="" width="849" height="193" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-17.png 849w" sizes="(min-width: 720px) 720px"></figure><p>Now for some code. First, let's set our question:</p><pre><code class="language-python hljs">question = <span class="hljs-string">"""
+enjoying the outdoors.</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-18.png" class="kg-image" alt="" width="588" height="786"></figure><p>As you can see, there's a little bit of hallucination going on (as is normal with these kinds of AI models). I can't see any of the Simpsons’ family members (outside of Homer) or the logo assuming anything. But the general gist is there, with the details that are important for sentiment analysis.</p><p>But enough with the cartoons - let’s test this on some real photos and in a real-world use case via the API and working with JSON.</p><h2 id="analyzing-brand-sentiment-via-api">Analyzing brand sentiment via API</h2><p>Alas, we do not live in Springfield like the Simpsons. No dodgy nuclear reactors or Duff Beer for us. But we can make do with some real-world brands to quench our thirst.</p><p>We'll use <a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io"><strong>SceneXplain's API</strong></a> to easily analyze some photos in bulk. In our case we'll use Python, though JavaScript and cURL access are also available. Here are the images we'll analyze:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-1267305.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-1267305.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-1267305.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-1267305.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-1267305.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-2076755.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-2076755.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-2076755.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-2076755.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-2076755.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-3922817.jpeg" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-3922817.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-3922817.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-3922817.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-3922817.jpeg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-3922818.jpeg" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-3922818.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-3922818.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-3922818.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-3922818.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-5935229.jpeg" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-5935229.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-5935229.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-5935229.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-5935229.jpeg 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>To follow along with this code, you'll need a secret key, which you can generate from SceneXplain's API page:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-17.png" class="kg-image" alt="" width="849" height="193" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-17.png 849w" sizes="(min-width: 720px) 720px"></figure><p>Now for some code. First, let's set our question:</p><pre><code class="language-python">question = """
 Identify the brands, scene attributes and sentiment categories (positive, negative, neutral), 
 and provide a response in the following JSON format:
 
 ---format begin---
 {"brands": [brand], "scene": scene, "sentiment": sentiment}
 --format end---
-"""</span></code></pre><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">We're strictly specifying the answer format that we want using a single example for in-context learning. This ensures consistent, parsable output.</div></div><p>Next up, we pass along our image URLs, setting the <code>question_answer</code> flag and <code>question</code>:</p><pre><code class="language-python hljs">data = {
-    <span class="hljs-string">"data"</span>: [
-        {<span class="hljs-string">"image"</span>: <span class="hljs-string">"https://images.pexels.com/photos/1267305/pexels-photo-1267305.jpeg"</span>, <span class="hljs-string">"features"</span>: [<span class="hljs-string">"question_answer"</span>], <span class="hljs-string">"question"</span>: question},
-        {<span class="hljs-string">"image"</span>: <span class="hljs-string">"https://images.pexels.com/photos/2076755/pexels-photo-2076755.jpeg"</span>, <span class="hljs-string">"features"</span>: [<span class="hljs-string">"question_answer"</span>], <span class="hljs-string">"question"</span>: question},
-        {<span class="hljs-string">"image"</span>: <span class="hljs-string">"https://images.pexels.com/photos/3922817/pexels-photo-3922817.jpeg"</span>, <span class="hljs-string">"features"</span>: [<span class="hljs-string">"question_answer"</span>], <span class="hljs-string">"question"</span>: question},
-        {<span class="hljs-string">"image"</span>: <span class="hljs-string">"https://images.pexels.com/photos/3922818/pexels-photo-3922818.jpeg"</span>, <span class="hljs-string">"features"</span>: [<span class="hljs-string">"question_answer"</span>], <span class="hljs-string">"question"</span>: question},
-        {<span class="hljs-string">"image"</span>: <span class="hljs-string">"https://images.pexels.com/photos/5935229/pexels-photo-5935229.jpeg"</span>, <span class="hljs-string">"features"</span>: [<span class="hljs-string">"question_answer"</span>], <span class="hljs-string">"question"</span>: question}
+"""</code></pre><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">We're strictly specifying the answer format that we want using a single example for in-context learning. This ensures consistent, parsable output.</div></div><p>Next up, we pass along our image URLs, setting the <code>question_answer</code> flag and <code>question</code>:</p><pre><code class="language-python">data = {
+    "data": [
+        {"image": "https://images.pexels.com/photos/1267305/pexels-photo-1267305.jpeg", "features": ["question_answer"], "question": question},
+        {"image": "https://images.pexels.com/photos/2076755/pexels-photo-2076755.jpeg", "features": ["question_answer"], "question": question},
+        {"image": "https://images.pexels.com/photos/3922817/pexels-photo-3922817.jpeg", "features": ["question_answer"], "question": question},
+        {"image": "https://images.pexels.com/photos/3922818/pexels-photo-3922818.jpeg", "features": ["question_answer"], "question": question},
+        {"image": "https://images.pexels.com/photos/5935229/pexels-photo-5935229.jpeg", "features": ["question_answer"], "question": question}
     ]
-}</code></pre><p>And now we pass all of that to SceneXplain:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> http.client
-<span class="hljs-keyword">import</span> json
+}</code></pre><p>And now we pass all of that to SceneXplain:</p><pre><code class="language-python">import http.client
+import json
 
 headers = {
-    <span class="hljs-string">"x-api-key"</span>: <span class="hljs-string">f"token <span class="hljs-subst">{YOUR_GENERATED_SECRET}</span>"</span>,
-    <span class="hljs-string">"content-type"</span>: <span class="hljs-string">"application/json"</span>,
+    "x-api-key": f"token {YOUR_GENERATED_SECRET}",
+    "content-type": "application/json",
 }
 
-connection = http.client.HTTPSConnection(<span class="hljs-string">'us-central1-causal-diffusion.cloudfunctions.net'</span>)
-connection.request(<span class="hljs-string">"POST"</span>, <span class="hljs-string">"/describe"</span>, json.dumps(data), headers)
+connection = http.client.HTTPSConnection('us-central1-causal-diffusion.cloudfunctions.net')
+connection.request("POST", "/describe", json.dumps(data), headers)
 response = connection.getresponse()
 
-response_data = response.read().decode(<span class="hljs-string">"utf-8"</span>)
-scenes = json.loads(response_data)[<span class="hljs-string">'result'</span>]
+response_data = response.read().decode("utf-8")
+scenes = json.loads(response_data)['result']
 
-connection.close()</code></pre><p>While our response object is JSON, within that response is SceneXplain's answer to our question. This is always in a plain string, so let's cast that to JSON to make it easier to work with:</p><pre><code class="language-python hljs"><span class="hljs-keyword">for</span> scene <span class="hljs-keyword">in</span> scenes:
-    scene[<span class="hljs-string">'answer'</span>] = json.loads(scene[<span class="hljs-string">'answer'</span>])</code></pre><p>Last but not least, let's see what we've got:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> pprint <span class="hljs-keyword">import</span> pprint
+connection.close()</code></pre><p>While our response object is JSON, within that response is SceneXplain's answer to our question. This is always in a plain string, so let's cast that to JSON to make it easier to work with:</p><pre><code class="language-python">for scene in scenes:
+    scene['answer'] = json.loads(scene['answer'])</code></pre><p>Last but not least, let's see what we've got:</p><pre><code class="language-python">from pprint import pprint
 
-pprint([scene[<span class="hljs-string">'answer'</span>] <span class="hljs-keyword">for</span> scene <span class="hljs-keyword">in</span> scenes])</code></pre><p>Here's the output:</p><pre><code class="language-python hljs">[{<span class="hljs-string">'brands'</span>: [<span class="hljs-string">'Hot Lizard IPA'</span>],
-  <span class="hljs-string">'scene'</span>: <span class="hljs-string">'upscale pub with patrons enjoying drinks and ambiance, featuring '</span>
-           <span class="hljs-string">'neon beer signs and a bartender pouring beer into a glass with '</span>
-           <span class="hljs-string">'precision'</span>,
-  <span class="hljs-string">'sentiment'</span>: <span class="hljs-string">'positive'</span>},
- {<span class="hljs-string">'brands'</span>: [<span class="hljs-string">'Heineken'</span>],
-  <span class="hljs-string">'scene'</span>: <span class="hljs-string">'urban street scene with a young woman holding a beer bottle and a '</span>
-           <span class="hljs-string">'skateboarder moving behind her, drinking Heineken beer'</span>,
-  <span class="hljs-string">'sentiment'</span>: <span class="hljs-string">'neutral'</span>},
- {<span class="hljs-string">'brands'</span>: [<span class="hljs-string">'Heineken'</span>],
-  <span class="hljs-string">'scene'</span>: <span class="hljs-string">'friends celebrating with Heineken beer and wine glasses, creating '</span>
-           <span class="hljs-string">'a warm and joyful atmosphere'</span>,
-  <span class="hljs-string">'sentiment'</span>: <span class="hljs-string">'positive'</span>},
- {<span class="hljs-string">'brands'</span>: [<span class="hljs-string">'Budweiser'</span>],
-  <span class="hljs-string">'scene'</span>: <span class="hljs-string">'social gathering in a cozy, dimly lit lounge with friends raising '</span>
-           <span class="hljs-string">'glasses of frothy golden beer in joyful celebration'</span>,
-  <span class="hljs-string">'sentiment'</span>: <span class="hljs-string">'positive'</span>},
- {<span class="hljs-string">'brands'</span>: [],
-  <span class="hljs-string">'scene'</span>: <span class="hljs-string">"rooftop party with friends enjoying each other's company and city "</span>
-           <span class="hljs-string">'view'</span>,
-  <span class="hljs-string">'sentiment'</span>: <span class="hljs-string">'positive'</span>}]</code></pre><p>As you can see, it's <em>pretty</em> good:</p><ul><li>It usually picks up the brand and sentiment, though there is the occasional hallucination when it comes to the scene descriptions.</li><li>In cases where there is no visible beer brand (like in the crowd image of people raising their bottles), it returns an empty list for <code>brands</code>.</li><li>It <em>did</em> screw up the 'Hopadillo' brand, consistently calling it 'Hot Lizard' during my testing. This may be down to it being a niche brand (with limited training data) and the image model doing the best of a bad job by guessing "Hot Lizard", which are actually words in its training set.</li></ul><h2 id="detecting-brand-variants-and-localization">Detecting brand variants and localization</h2><p>Out of interest, I looked into how well this works with branding edge cases - for example a Chinese Coca-Cola can, or a customized Coca-Cola can:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.666667 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/pexels-photo-4417766.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/pexels-photo-4417766.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/pexels-photo-4417766.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/pexels-photo-4417766.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/pexels-photo-4417766.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/pexels-photo-4575406.jpeg" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/pexels-photo-4575406.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/pexels-photo-4575406.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/pexels-photo-4575406.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/pexels-photo-4575406.jpeg 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>For those, we got the results:</p><pre><code class="hljs language-bash">[{<span class="hljs-string">'brands'</span>: [<span class="hljs-string">'Coca-Cola'</span>],
-  <span class="hljs-string">'scene'</span>: <span class="hljs-string">'a display of Coca-Cola cans adorned with Chinese writing featuring '</span>
-           <span class="hljs-string">'the iconic Coca-Cola logo on a sleek black surface'</span>,
-  <span class="hljs-string">'sentiment'</span>: <span class="hljs-string">'positive'</span>},
-  {<span class="hljs-string">'brands'</span>: [<span class="hljs-string">'Coca-Cola'</span>],
-  <span class="hljs-string">'scene'</span>: <span class="hljs-string">'A coffee cup and a can of Coca-Cola on a blue surface with a red '</span>
-           <span class="hljs-string">"background and 'My Hero' sign in the back."</span>,
-  <span class="hljs-string">'sentiment'</span>: <span class="hljs-string">'neutral'</span>}]</code></pre><p>As we can see, brand detection is on point. We get good results for testing negative sentiments too. </p><p>With code like the above and SceneXplain's API, you can easily do bulk analysis of images to get deeper insights into how consumers see your brand. This allows you to identify prevalent patterns, trends, or themes that may be influencing consumer perception and engagement. By understanding this, you can tailor your marketing strategy to enhance positive aspects and address any identified issues, ultimately optimizing your brand's reach and impact.</p><h2 id="what-else-can-scenexplain-do">What else can SceneXplain do?</h2><p>Dive into some of our prior blog posts to find out!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/making-visuals-vocal-scenexplains-impact-on-product-image-accessibility/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Making Visuals Vocal: SceneXplain’s Impact on Product Image Accessibility</div><div class="kg-bookmark-description">SceneXplain transforms product images into audio descriptions, ensuring visual content isn’t just seen, but also heard and understood. It’s a step forward in creating an inclusive digital world for everyone</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Blog-images--9-.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-vs-minigpt4-a-comprehensive-benchmark-of-top-5-image-captioning-algorithms-for-understanding-complex-scenes?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain vs. MiniGPT4: A Comprehensive Benchmark of Top 5 Image Captioning Algorithms for Understanding Complex Scenes</div><div class="kg-bookmark-description">Uncover the future of image captioning as SceneXplain and its rivals face off in an epic showdown. Explore their impact on accessibility, SEO, and storytelling, and dive into our intriguing results to witness the cutting-edge capabilities of these algorithms.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150443.130.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</div><div class="kg-bookmark-description">Explore SceneXplain’s impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-unleash-advanced-image-captioning-storytelling?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain: Unleash the Advanced Image Captioning &amp; Storytelling</div><div class="kg-bookmark-description">Uncover the game-changing potential of SceneXplain, an advanced image captioning solution powered by LLMs. Check out the benchmark against Midjourney, CLIP, BLIP2, and other alternatives. Dive into our blog post and experience the revolution firsthand!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates--98-.png" alt=""></div></a></figure><h2 id="get-started-with-scenexplain-and-sentiment-analysis">Get started with SceneXplain and sentiment analysis</h2><p>To analyze those sentiments and optimize your brand strategy, sign up on SceneXplain now, and join the discussion on our <a href="https://discord.com/channels/1106542220112302130/1106544027601469461?ref=jina-ai-gmbh.ghost.io">Discord server</a>.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Sign up for SceneXplain</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fbrand-engagement-reimagined-ai-powered-sentiment-analysis-with-scenexplain%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; 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\ No newline at end of file
+pprint([scene['answer'] for scene in scenes])</code></pre><p>Here's the output:</p><pre><code class="language-python">[{'brands': ['Hot Lizard IPA'],
+  'scene': 'upscale pub with patrons enjoying drinks and ambiance, featuring '
+           'neon beer signs and a bartender pouring beer into a glass with '
+           'precision',
+  'sentiment': 'positive'},
+ {'brands': ['Heineken'],
+  'scene': 'urban street scene with a young woman holding a beer bottle and a '
+           'skateboarder moving behind her, drinking Heineken beer',
+  'sentiment': 'neutral'},
+ {'brands': ['Heineken'],
+  'scene': 'friends celebrating with Heineken beer and wine glasses, creating '
+           'a warm and joyful atmosphere',
+  'sentiment': 'positive'},
+ {'brands': ['Budweiser'],
+  'scene': 'social gathering in a cozy, dimly lit lounge with friends raising '
+           'glasses of frothy golden beer in joyful celebration',
+  'sentiment': 'positive'},
+ {'brands': [],
+  'scene': "rooftop party with friends enjoying each other's company and city "
+           'view',
+  'sentiment': 'positive'}]</code></pre><p>As you can see, it's <em>pretty</em> good:</p><ul><li>It usually picks up the brand and sentiment, though there is the occasional hallucination when it comes to the scene descriptions.</li><li>In cases where there is no visible beer brand (like in the crowd image of people raising their bottles), it returns an empty list for <code>brands</code>.</li><li>It <em>did</em> screw up the 'Hopadillo' brand, consistently calling it 'Hot Lizard' during my testing. This may be down to it being a niche brand (with limited training data) and the image model doing the best of a bad job by guessing "Hot Lizard", which are actually words in its training set.</li></ul><h2 id="detecting-brand-variants-and-localization">Detecting brand variants and localization</h2><p>Out of interest, I looked into how well this works with branding edge cases - for example a Chinese Coca-Cola can, or a customized Coca-Cola can:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/pexels-photo-4417766.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/pexels-photo-4417766.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/pexels-photo-4417766.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/pexels-photo-4417766.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/pexels-photo-4417766.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/pexels-photo-4575406.jpeg" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/pexels-photo-4575406.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/pexels-photo-4575406.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/pexels-photo-4575406.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/pexels-photo-4575406.jpeg 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>For those, we got the results:</p><pre><code>[{'brands': ['Coca-Cola'],
+  'scene': 'a display of Coca-Cola cans adorned with Chinese writing featuring '
+           'the iconic Coca-Cola logo on a sleek black surface',
+  'sentiment': 'positive'},
+  {'brands': ['Coca-Cola'],
+  'scene': 'A coffee cup and a can of Coca-Cola on a blue surface with a red '
+           "background and 'My Hero' sign in the back.",
+  'sentiment': 'neutral'}]</code></pre><p>As we can see, brand detection is on point. We get good results for testing negative sentiments too. </p><p>With code like the above and SceneXplain's API, you can easily do bulk analysis of images to get deeper insights into how consumers see your brand. This allows you to identify prevalent patterns, trends, or themes that may be influencing consumer perception and engagement. By understanding this, you can tailor your marketing strategy to enhance positive aspects and address any identified issues, ultimately optimizing your brand's reach and impact.</p><h2 id="what-else-can-scenexplain-do">What else can SceneXplain do?</h2><p>Dive into some of our prior blog posts to find out!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/making-visuals-vocal-scenexplains-impact-on-product-image-accessibility/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Making Visuals Vocal: SceneXplain’s Impact on Product Image Accessibility</div><div class="kg-bookmark-description">SceneXplain transforms product images into audio descriptions, ensuring visual content isn’t just seen, but also heard and understood. It’s a step forward in creating an inclusive digital world for everyone</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Blog-images--9-.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-vs-minigpt4-a-comprehensive-benchmark-of-top-5-image-captioning-algorithms-for-understanding-complex-scenes?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain vs. MiniGPT4: A Comprehensive Benchmark of Top 5 Image Captioning Algorithms for Understanding Complex Scenes</div><div class="kg-bookmark-description">Uncover the future of image captioning as SceneXplain and its rivals face off in an epic showdown. Explore their impact on accessibility, SEO, and storytelling, and dive into our intriguing results to witness the cutting-edge capabilities of these algorithms.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150443.130.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</div><div class="kg-bookmark-description">Explore SceneXplain’s impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-unleash-advanced-image-captioning-storytelling?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain: Unleash the Advanced Image Captioning &amp; Storytelling</div><div class="kg-bookmark-description">Uncover the game-changing potential of SceneXplain, an advanced image captioning solution powered by LLMs. Check out the benchmark against Midjourney, CLIP, BLIP2, and other alternatives. Dive into our blog post and experience the revolution firsthand!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates--98-.png" alt=""></div></a></figure><h2 id="get-started-with-scenexplain-and-sentiment-analysis">Get started with SceneXplain and sentiment analysis</h2><p>To analyze those sentiments and optimize your brand strategy, sign up on SceneXplain now, and join the discussion on our <a href="https://discord.com/channels/1106542220112302130/1106544027601469461?ref=jina-ai-gmbh.ghost.io">Discord server</a>.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Sign up for SceneXplain</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fbrand-engagement-reimagined-ai-powered-sentiment-analysis-with-scenexplain%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="ab0e238e-b763-4df9-a4a8-12f324842088" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="ab0e238e-b763-4df9-a4a8-12f324842088" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Building a Streaming API for Llama 2: Real-time AI with Jina and DocArray</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Tired of paying for ChatGPT? Want to have your own streaming AI chatbot, with your own engineered prompts running on your own servers or cloud? With Llama2, DocArray, and Jina, you can set it up in a few minutes!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 75.6836%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/IMG-1054.PNG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Saba Sturua, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 23, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Large language models based on the Transformer architecture have revolutionized AI technology recently. Transformers are versatile and useful for various tasks, but they all have the property that they process their input all at once and generate output one word at a time. This can lead to frustrating delays, inefficient processing, and technical difficulties from time-outs because you cannot know in advance how long a transformer-based model will take to complete its output.</p><p>To overcome this, it would be better to stream the results.</p><p><a href="http://docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray</a> and <a href="https://docs.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina</a> provide a streaming mechanism designed for AI models. This article will show you how to use them to stream interaction with the <a href="https://huggingface.co/spaces/huggingface-projects/llama-2-7b-chat?ref=jina-ai-gmbh.ghost.io">Llama-2-Chat model</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://ai.meta.com/llama/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Llama 2 - Meta AI</div><div class="kg-bookmark-description">Llama 2 — The next generation of our open source large language model, available for free for research and commercial use.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.xx.fbcdn.net/rsrc.php/v3/y4/r/WUJbsVI4ruF.png" alt=""><span class="kg-bookmark-author">Meta AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scontent.xx.fbcdn.net/v/t39.2365-6/339747481_605860888081792_7990206924580773203_n.jpg?_nc_cat=111&amp;ccb=1-7&amp;_nc_sid=ad8a9d&amp;_nc_ohc=obONCzNgQiYAX9f9ZSE&amp;_nc_ht=scontent.xx&amp;oh=00_AfAIgAy7yOiFCi0EKT75xDhwmNKufrDpp9z06ZEYhfMAig&amp;oe=64FEFE3F" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/spaces/huggingface-projects/llama-2-7b-chat?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Llama 2 7B Chat - a Hugging Face Space by huggingface-projects</div><div class="kg-bookmark-description">Discover amazing ML apps made by the community</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""><span class="kg-bookmark-author">a Hugging Face Space by huggingface-projects</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/spaces/huggingface-projects/llama-2-7b-chat.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">This article comes with <a href="https://colab.research.google.com/github/jina-ai/workshops/blob/llama2/notebooks/llama2_streaming/llama2_streaming.ipynb?ref=jina-ai-gmbh.ghost.io">a Google Colab notebook</a> you can use to try it out yourself.</div></div><h2 id="getting-access-to-the-llama-2-chat-model">Getting Access to the Llama-2-chat Model</h2><p>Before starting, you will need permission from Meta to download the model from Hugging Face.</p><ul><li>First, you will need a Hugging Face account. You can sign up for one for free <a href="https://huggingface.co/join?ref=jina-ai-gmbh.ghost.io">on the Hugging Face website</a>.</li><li>Next, you will need to request permission from Meta. You can make the request <a href="https://huggingface.co/meta-llama/Llama-2-7b-chat-hf?ref=jina-ai-gmbh.ghost.io">from the model card page for Llama 2 at Hugging Face</a>, when you are logged in with your Hugging Face credentials.</li></ul><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">This request may take <strong>one to two days to process</strong>.</div></div><ul><li>Finally, request a token from Hugging Face from <a href="https://huggingface.co/settings/tokens?ref=jina-ai-gmbh.ghost.io">your settings page</a>. You will need this token to download the model.</li></ul><p>You will need the token to access Hugging Face models via the <code>transformers</code> interface. Before running the code in this article, you should log in using the command <code>huggingface-cli</code>:</p><pre><code class="hljs language-javascript">% huggingface-cli login
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Building a Streaming API for Llama 2: Real-time AI with Jina and DocArray</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Tired of paying for ChatGPT? Want to have your own streaming AI chatbot, with your own engineered prompts running on your own servers or cloud? With Llama2, DocArray, and Jina, you can set it up in a few minutes!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 75.6836%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/IMG-1054.PNG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Saba Sturua, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 23, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Large language models based on the Transformer architecture have revolutionized AI technology recently. Transformers are versatile and useful for various tasks, but they all have the property that they process their input all at once and generate output one word at a time. This can lead to frustrating delays, inefficient processing, and technical difficulties from time-outs because you cannot know in advance how long a transformer-based model will take to complete its output.</p><p>To overcome this, it would be better to stream the results.</p><p><a href="http://docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray</a> and <a href="https://docs.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina</a> provide a streaming mechanism designed for AI models. This article will show you how to use them to stream interaction with the <a href="https://huggingface.co/spaces/huggingface-projects/llama-2-7b-chat?ref=jina-ai-gmbh.ghost.io">Llama-2-Chat model</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://ai.meta.com/llama/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Llama 2 - Meta AI</div><div class="kg-bookmark-description">Llama 2 — The next generation of our open source large language model, available for free for research and commercial use.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.xx.fbcdn.net/rsrc.php/v3/y4/r/WUJbsVI4ruF.png" alt=""><span class="kg-bookmark-author">Meta AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scontent.xx.fbcdn.net/v/t39.2365-6/339747481_605860888081792_7990206924580773203_n.jpg?_nc_cat=111&amp;ccb=1-7&amp;_nc_sid=ad8a9d&amp;_nc_ohc=obONCzNgQiYAX9f9ZSE&amp;_nc_ht=scontent.xx&amp;oh=00_AfAIgAy7yOiFCi0EKT75xDhwmNKufrDpp9z06ZEYhfMAig&amp;oe=64FEFE3F" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/spaces/huggingface-projects/llama-2-7b-chat?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Llama 2 7B Chat - a Hugging Face Space by huggingface-projects</div><div class="kg-bookmark-description">Discover amazing ML apps made by the community</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""><span class="kg-bookmark-author">a Hugging Face Space by huggingface-projects</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/spaces/huggingface-projects/llama-2-7b-chat.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">This article comes with <a href="https://colab.research.google.com/github/jina-ai/workshops/blob/llama2/notebooks/llama2_streaming/llama2_streaming.ipynb?ref=jina-ai-gmbh.ghost.io">a Google Colab notebook</a> you can use to try it out yourself.</div></div><h2 id="getting-access-to-the-llama-2-chat-model">Getting Access to the Llama-2-chat Model</h2><p>Before starting, you will need permission from Meta to download the model from Hugging Face.</p><ul><li>First, you will need a Hugging Face account. You can sign up for one for free <a href="https://huggingface.co/join?ref=jina-ai-gmbh.ghost.io">on the Hugging Face website</a>.</li><li>Next, you will need to request permission from Meta. You can make the request <a href="https://huggingface.co/meta-llama/Llama-2-7b-chat-hf?ref=jina-ai-gmbh.ghost.io">from the model card page for Llama 2 at Hugging Face</a>, when you are logged in with your Hugging Face credentials.</li></ul><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">This request may take <strong>one to two days to process</strong>.</div></div><ul><li>Finally, request a token from Hugging Face from <a href="https://huggingface.co/settings/tokens?ref=jina-ai-gmbh.ghost.io">your settings page</a>. You will need this token to download the model.</li></ul><p>You will need the token to access Hugging Face models via the <code>transformers</code> interface. Before running the code in this article, you should log in using the command <code>huggingface-cli</code>:</p><pre><code class="hljs language-javascript">% huggingface-cli login
     
     _|    _|  _|    _|    _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|_|_|_|    _|_|      _|_|_|  _|_|_|_|
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@@ -165,4 +165,4 @@
 3. Talking to someone: Sharing your feelings with a trusted friend, family 
    member, or mental health professional can provide emotional support and help
    you find healthy ways
-</code></pre><p>You can adapt this code to any prompt or extend it to support a fully two-way conversation.</p><h2 id="run-your-own-ai-chat-service">Run Your Own AI Chat Service</h2><p>With the release of Llama 2 and its chat-trained models, you can use Jina and DocArray to create and operate your own chat service with just a few classes and functions.</p><p>You can use a cloud service provider, for example, <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a>, &nbsp;and control the entire technology stack, never paying external API fees or worrying about your data privacy. The smallest model is small enough to run in-house on a well-resourced GPU machine, eliminating even cloud dependencies if desired.</p><p>Llama 2’s separation of system prompts from user input gives you an additional layer of control, letting you do your own prompt engineering and in-context learning and building it into the service.</p><p>The possibilities are endless.</p><h2 id="get-involved">Get Involved</h2><p>To learn more, check out the websites for <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI</a> and <a href="http://docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray</a>. &nbsp;You can also contact us and the Jina user community via <a href="https://discord.gg/WaMp6PVPgR?ref=jina-ai-gmbh.ghost.io">Discord</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI - Your Portal to Multimodal AI</div><div class="kg-bookmark-description">Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. 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+</code></pre><p>You can adapt this code to any prompt or extend it to support a fully two-way conversation.</p><h2 id="run-your-own-ai-chat-service">Run Your Own AI Chat Service</h2><p>With the release of Llama 2 and its chat-trained models, you can use Jina and DocArray to create and operate your own chat service with just a few classes and functions.</p><p>You can use a cloud service provider, for example, <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a>, &nbsp;and control the entire technology stack, never paying external API fees or worrying about your data privacy. The smallest model is small enough to run in-house on a well-resourced GPU machine, eliminating even cloud dependencies if desired.</p><p>Llama 2’s separation of system prompts from user input gives you an additional layer of control, letting you do your own prompt engineering and in-context learning and building it into the service.</p><p>The possibilities are endless.</p><h2 id="get-involved">Get Involved</h2><p>To learn more, check out the websites for <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI</a> and <a href="http://docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray</a>. &nbsp;You can also contact us and the Jina user community via <a href="https://discord.gg/WaMp6PVPgR?ref=jina-ai-gmbh.ghost.io">Discord</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI - Your Portal to Multimodal AI</div><div class="kg-bookmark-description">Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. We aim to democratize access to the limitless potential of AI-generated creativity and innovation, empowering individuals and businesses alike.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-author">Your Portal to Multimodal AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/banner.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="http://docarray.org/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">docarray.github.io</div><div class="kg-bookmark-description">homepage of docarray</div><div class="kg-bookmark-metadata"><span class="kg-bookmark-author">docarray.github.io</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://github.com/docarray/docarray/blob/main/docs/assets/logo-dark.svg?raw=true" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fbuilding-a-streaming-api-for-llama-2-real-time-ai-with-jina-and-docarray%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</title><meta charset="utf-8"><meta name="title" content="Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain"><meta name="description" content="See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain"><meta property="og:title" content="Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain"><meta property="og:description" content="See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain"><meta property="twitter:title" content="Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain"><meta property="twitter:description" content="See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Miruna Nedelcu</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 30, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p></p><h2 id="client-overview">Client Overview</h2><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Screenshot-2023-10-27-at-10.58.59.png" class="kg-image" alt="" width="1295" height="189" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Screenshot-2023-10-27-at-10.58.59.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/Screenshot-2023-10-27-at-10.58.59.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Screenshot-2023-10-27-at-10.58.59.png 1295w" sizes="(min-width: 720px) 720px"></figure><p>Our client, a leading European e-commerce platform, specializing in fashion and lifestyle, offers a wide range of clothing, footwear, and accessories. Their platform features an extensive selection of emerging and well-known brands, with a total of around two million product images, spanning all their product categories. </p><p><strong>The client's vision was clear</strong>: automatically generate basic and specific descriptions for all these images and, more importantly, categorize them with detailed tags to<em> improve user experience and enhance search result quality.</em></p><h2 id="why-they-started-looking-for-a-new-solution">Why They Started Looking For A New Solution</h2><p></p><blockquote>"We were facing significant challenges in managing our vast catalog of product images. Manual image description generation was too time-consuming. We needed a solution to save time and resources and provide comprehensive product tagging. SceneXplain was the game-changer that helped us achieve this." - Sales Director</blockquote><p><strong>1. Efficiently Generating Descriptions</strong>: With two million images to manage, creating descriptions for each one manually was a time–consuming and inefficient task. It took roughly a week for them to write descriptions for the first seven thousand images. The client sought an automated solution to save valuable time and resources.</p><p><strong>2. Better Product Tagging</strong>: They wanted a comprehensive tagging system that went beyond general descriptions. They needed to categorize products by attributes such as color, gender, and more, all while maintaining a consistent schema for easy management.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Try SceneXplain Now</span></p></figcaption></figure><h2 id="how-scenexplains-api-saved-time-and-effort">How SceneXplain's API Saved Time And Effort </h2><p>SceneXplain addressed these challenges with a two-fold strategy:</p><p><strong>1. Automated Image Description</strong>: SceneXplain leveraged its powerful API to enable batch image uploads, eliminating the need to process each image one by one. Using SceneXplain’s API, the client achieved high-quality image descriptions, reducing the time and effort required to manually craft descriptions. When they usually spent over two weeks on getting the description of 14k of their images, now with batch upload that number decreased by 75%.</p><p><strong>2. Comprehensive Tagging with JSON Schema</strong>: SceneXplain’s JSON schema system enabled the client to automatically categorize images with a fine-grained tag scheme optimized for their product search system. Using SceneXplain, their tagging system progressed from a few categories to a multifaceted system with highly detailed descriptive labels, making it easy to manage and optimize their product listings</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Try SceneXplain Now</span></p></figcaption></figure><h2 id="conclusion"><strong>Conclusion</strong></h2><p>At SceneXplain, we're on a mission to empower businesses with innovative solutions that enhance user experience.</p><p>We're dedicated to delivering results and exceeding expectations, and we're proud to have earned high satisfaction and recognition from our clients.</p><p>Join us on this journey to make technology and digital content accessible to all!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fcase-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/graph-embedding-101-unraveling-the-magic-of-relational-data" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Graph Embedding 101: Unraveling the Magic of Relational Data</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Graphs → everywhere. Social. Knowledge. Molecular. Critical infrastructure. Complex hairy ball visuals. Hard for machines.
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="e0126c60-ffff-46a9-bd16-18069a3fe225" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="e0126c60-ffff-46a9-bd16-18069a3fe225" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Miruna Nedelcu</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 30, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p></p><h2 id="client-overview">Client Overview</h2><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Screenshot-2023-10-27-at-10.58.59.png" class="kg-image" alt="" width="1295" height="189" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Screenshot-2023-10-27-at-10.58.59.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/Screenshot-2023-10-27-at-10.58.59.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Screenshot-2023-10-27-at-10.58.59.png 1295w" sizes="(min-width: 720px) 720px"></figure><p>Our client, a leading European e-commerce platform, specializing in fashion and lifestyle, offers a wide range of clothing, footwear, and accessories. Their platform features an extensive selection of emerging and well-known brands, with a total of around two million product images, spanning all their product categories. </p><p><strong>The client's vision was clear</strong>: automatically generate basic and specific descriptions for all these images and, more importantly, categorize them with detailed tags to<em> improve user experience and enhance search result quality.</em></p><h2 id="why-they-started-looking-for-a-new-solution">Why They Started Looking For A New Solution</h2><p></p><blockquote>"We were facing significant challenges in managing our vast catalog of product images. Manual image description generation was too time-consuming. We needed a solution to save time and resources and provide comprehensive product tagging. SceneXplain was the game-changer that helped us achieve this." - Sales Director</blockquote><p><strong>1. Efficiently Generating Descriptions</strong>: With two million images to manage, creating descriptions for each one manually was a time–consuming and inefficient task. It took roughly a week for them to write descriptions for the first seven thousand images. The client sought an automated solution to save valuable time and resources.</p><p><strong>2. Better Product Tagging</strong>: They wanted a comprehensive tagging system that went beyond general descriptions. They needed to categorize products by attributes such as color, gender, and more, all while maintaining a consistent schema for easy management.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Try SceneXplain Now</span></p></figcaption></figure><h2 id="how-scenexplains-api-saved-time-and-effort">How SceneXplain's API Saved Time And Effort </h2><p>SceneXplain addressed these challenges with a two-fold strategy:</p><p><strong>1. Automated Image Description</strong>: SceneXplain leveraged its powerful API to enable batch image uploads, eliminating the need to process each image one by one. Using SceneXplain’s API, the client achieved high-quality image descriptions, reducing the time and effort required to manually craft descriptions. When they usually spent over two weeks on getting the description of 14k of their images, now with batch upload that number decreased by 75%.</p><p><strong>2. Comprehensive Tagging with JSON Schema</strong>: SceneXplain’s JSON schema system enabled the client to automatically categorize images with a fine-grained tag scheme optimized for their product search system. Using SceneXplain, their tagging system progressed from a few categories to a multifaceted system with highly detailed descriptive labels, making it easy to manage and optimize their product listings</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Try SceneXplain Now</span></p></figcaption></figure><h2 id="conclusion"><strong>Conclusion</strong></h2><p>At SceneXplain, we're on a mission to empower businesses with innovative solutions that enhance user experience.</p><p>We're dedicated to delivering results and exceeding expectations, and we're proud to have earned high satisfaction and recognition from our clients.</p><p>Join us on this journey to make technology and digital content accessible to all!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fcase-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/graph-embedding-101-unraveling-the-magic-of-relational-data" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Graph Embedding 101: Unraveling the Magic of Relational Data</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Graphs → everywhere. Social. Knowledge. Molecular. Critical infrastructure. Complex hairy ball visuals. Hard for machines.
 
-Now graph embeddings vectorize nodes. Distill graphs into geometry. Embeddings work magic. AI devours graphs.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 29, 2023 • 10 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_purple_and_green_network_graphs_on_purple_backgr_8f3f4431-5317-4b2e-a2b7-44e206c14b26.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+Now graph embeddings vectorize nodes. Distill graphs into geometry. Embeddings work magic. AI devours graphs.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 29, 2023 • 10 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_purple_and_green_network_graphs_on_purple_backgr_8f3f4431-5317-4b2e-a2b7-44e206c14b26.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Celebrating a Year of Community Growth and Accomplishment</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">In true open source fashion, we want to highlight how you, our community, have been instrumental in our collective accomplishments! </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 23, 2022 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><br>2022 has been a very special year, not only because of our major updates to Jina AI, but also because we are so proud and grateful to have a globally talented, diverse, and fast-growing community!</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/02-Communit-Growth-Figures.jpg" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/02-Communit-Growth-Figures.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/02-Communit-Growth-Figures.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/02-Communit-Growth-Figures.jpg 1440w" sizes="(min-width: 720px) 720px"></figure><p>In true open source fashion, we want to highlight how you, our community, have been instrumental in our collective accomplishments and have contributed greatly to this wonderful year.</p><h2 id="star-power">Star Power <br></h2><p>It has been a transformative year for the Jina AI codebase, and we are so thankful to the developers who have starred and contributed to our projects. From fixing the simplest typo to the biggest pull requests, it all contributes to what the Jina AI projects are today. We'd like to give an extra special thank you to everyone who submitted one of the <strong>thousands of PRs merged</strong> this year!</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/W6HVJ0nTPib2ZAWvu11Fx5SV0oKBNn70aq0uOGGoADrRdd9vIRJgKk5GoMVC0ZZOkjwxdi1k6XLpXThUNcY5PMLAKVbnKHEjkynNQKHKs6drfis10CWxQWEUHA1Ma-UoeLu6FgBki4YBk1MUF2ruOplwakjYCA9TqMNPZscvVjeV-YPhb-D7-tyBhPiPZg" class="kg-image" alt="" width="602" height="301"></figure><h2 id="memorable-community-events">Memorable community events!<br></h2><p>Our Engineering All Hands (EAH) and J-Tech Talk are open to everyone in the tech community, or anyone who wants to learn more about the future of neural search. This year, we have hosted <strong>19 sessions </strong>and gathered over <strong>18,000 participants </strong>from every corner of the world to share tech insights and learn about new technologies.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh4.googleusercontent.com/ioGqYwBdlsvT-bOH9nFe5cfRC4eBtIyunFX6uuhukUTdrJBEAK7t6MoJiwPNWdbaYw4o7ZiDDO5rPO8qBgHQqvSaPLuB-01O4q0tluxpC1cGdC08iu-3kT-dY_PokLObjs2t_5PBhYFR7WMO77eJWWxjHjixr8tQTaDp4LnUN5IeHQ0iu0RfxWM0p_bzKw" class="kg-image" alt="" width="602" height="339"></figure><p>We are always amazed by the incredible projects that our community showcases at these events, and we are proud to create a warm atmosphere for sharing such inspiring initiatives.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/V4Sz6klXZMRv-46i1XYMj1fhCFvSWgYc6Mn89KVnfIl-MmogEXOsM1f3q0iHhSM4NdeVoWfqkr7GuFmiM1scVd3itDy3v9OFTx69DrT5aEGmpTiKnXz8awYfNKpEQUxQBiTO0eZoIMmWWeOo9Xw3FRBuiyl22FdcHwMQH7Dx_A9XHeB0c5Fi3BiRia_Vgw" class="kg-image" alt="" width="602" height="339"></figure><p>We also host Office Hours on a monthly basis. During these meet-ups, we answer community questions, gather feedback on the latest features, and learn about how people are using Jina AI in their projects. We have been delighted to host <strong>9 sessions</strong> and welcome over <strong>867 community members</strong> from around the world to work together with our amazing engineering team to solve technical problems and explore Jina AI features.<br></p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_02056.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_02056.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_02056.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_02056.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_02056.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.11421 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00237--1-.jpg" width="2000" height="1795" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00237--1-.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00237--1-.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00237--1-.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00237--1-.jpg 2386w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_02776.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_02776.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_02776.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_02776.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_02776.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.31752 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_01188--1-.jpg" width="2000" height="1518" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_01188--1-.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_01188--1-.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_01188--1-.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_01188--1-.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_01279.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_01279.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_01279.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_01279.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_01279.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.31579 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_02944--1-.jpg" width="2000" height="1520" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_02944--1-.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_02944--1-.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_02944--1-.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_02944--1-.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Jina AI 2022 Annual Event&nbsp;</figcaption></figure><p>Just a few weeks ago, we held the Jina AI Annual Event. We were delighted to have the opportunity to gather our beloved developer community, partners, and friends to celebrate the memories we’ve created and outlook for a greater upcoming 2023!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/jina-ai-annual-event/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Tech Talk and Cheer: Celebrating the Holidays at Our 2022 Annual Christmas Party</div><div class="kg-bookmark-description">The holiday season is upon us! As we reflect on this past year, we made a huge difference together with the support from our team, community members, and our partners.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/find-your-1.png" alt=""></div></a></figure><p>On top of all this, we took the chance to participate in and sponsor numerous events across Europe for the first time. It was a thrilling and rewarding experience for us, as we were able to connect with a wide variety of people from diverse industries and backgrounds. We are eager to continue attending and supporting more of them in the future!</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Image-from-iOS.jpeg" width="1600" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Image-from-iOS.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Image-from-iOS.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Image-from-iOS.jpeg 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.75 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/pasted-image-3.jpeg" width="1080" height="1440" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/pasted-image-3.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/pasted-image-3.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/pasted-image-3.jpeg 1080w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.21521 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/pasted-image-2.jpeg" width="1310" height="1078" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/pasted-image-2.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/pasted-image-2.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/pasted-image-2.jpeg 1310w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/pasted-image-0.jpeg" width="1440" height="1080" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/pasted-image-0.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/pasted-image-0.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/pasted-image-0.jpeg 1440w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Top left to bottom right: PyData Berlin, PyCon DE (Jina AI Team with Sebastián, Fast API), PyCon Italy, OSSummit Dublin</figcaption></figure><h2 id="our-community-is-a-driving-force-of-positive-social-impact"><br>Our community is a driving force of positive social impact!<br></h2><p>On March 7th, we launched 'Impact Tech, She Can', a campaign to invite female friends from diverse backgrounds and professions to participate in online dialogues, amplify female voices, inspire others, and encourage more women to come to the forefront and be seen and heard. </p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/TzfNC9MTn5MpZbunOA9UbXAbvAVQqZI2klTGFkOyWys0xQAUt0-Uu3x3zswtLm-DbrWsmkUvRLu36zsxnUAvIr7ENqJBPRrluMI5wiqPbzyyc_vGgylb-FayobBOy5xz1V9sjI0Iq-R42FmSK9TjD6clVOFH9HcgAXloQsetQPM-AMRinDRZSdyGEfzmww" class="kg-image" alt="" width="602" height="301"></figure><p>This initiative welcomed over<strong> 600 attendees </strong>and reached many more people with this message. Building upon the event that took place in China, we are dedicated to reinforcing this message and supporting more women in tech, across the globe, in 2023!</p><h2 id="we-also-found-our-community-champions">We also found our community champions!<br></h2><p>The open-source community is filled with passionate, dedicated individuals who are committed to improving the world through their contributions. The power of open source lies in its ability to bring people together and to drive positive change. In October, we launched the Jina AI Community Advocates Program. Through JCAP, we aim to recognize and reward the achievements of our community champions, while also supporting them to improve their technical advocacy skills and bring the Jina AI team and community closer together. You can read more about the Advocacy program in this blog:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/from-zero-to-hero-at-jina-ai-community/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">New Community Reward Program is Coming!</div><div class="kg-bookmark-description">We are excited to introduce a new Reward Plan to recognize active community members! You can gain credits by engaging with the community. How? Read on!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Swag-Plan.png" alt=""></div></a></figure><p>A huge shout-out to our first ever JCAP members, <a href="https://www.linkedin.com/in/gfissore/?ref=jina-ai-gmbh.ghost.io">Giancarlo Fissore</a>, <a href="https://www.linkedin.com/in/onwuka-ijeoma/?ref=jina-ai-gmbh.ghost.io">Ijeoma Onwuka</a> &amp; <a href="https://twitter.com/Rishi0812?ref=jina-ai-gmbh.ghost.io">Rishi R</a> we are so humbled and proud of your actions in the community!</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.77778 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled--2-.png" width="1600" height="900" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Untitled--2-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Untitled--2-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled--2-.png 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.6 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled--1-.png" width="1600" height="1000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Untitled--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Untitled--1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled--1-.png 1600w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>In the new year, we are committed to investing even more into our community advocacy program and initiatives in order to empower our global community to achieve their goals and reach their full potential. If you would like to join us on this journey, you can <a href="https://docs.google.com/forms/d/e/1FAIpQLSfNmnIjZvDXIjVqrWRdK92DLgKPluXWLwLd1Sgt7A3HEaN9Kw/viewform?usp=send_form&amp;ref=jina-ai-gmbh.ghost.io">apply to join JCAP through this application.</a> <br><br>We are excited to see what we can accomplish together in the coming year—Happy Holidays to all!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fcelebrating-a-year-of-community-growth-and-accomplishment%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Celebrating a Year of Community Growth and Accomplishment</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">In true open source fashion, we want to highlight how you, our community, have been instrumental in our collective accomplishments! </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 23, 2022 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><br>2022 has been a very special year, not only because of our major updates to Jina AI, but also because we are so proud and grateful to have a globally talented, diverse, and fast-growing community!</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/02-Communit-Growth-Figures.jpg" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/02-Communit-Growth-Figures.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/02-Communit-Growth-Figures.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/02-Communit-Growth-Figures.jpg 1440w" sizes="(min-width: 720px) 720px"></figure><p>In true open source fashion, we want to highlight how you, our community, have been instrumental in our collective accomplishments and have contributed greatly to this wonderful year.</p><h2 id="star-power">Star Power <br></h2><p>It has been a transformative year for the Jina AI codebase, and we are so thankful to the developers who have starred and contributed to our projects. From fixing the simplest typo to the biggest pull requests, it all contributes to what the Jina AI projects are today. We'd like to give an extra special thank you to everyone who submitted one of the <strong>thousands of PRs merged</strong> this year!</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/W6HVJ0nTPib2ZAWvu11Fx5SV0oKBNn70aq0uOGGoADrRdd9vIRJgKk5GoMVC0ZZOkjwxdi1k6XLpXThUNcY5PMLAKVbnKHEjkynNQKHKs6drfis10CWxQWEUHA1Ma-UoeLu6FgBki4YBk1MUF2ruOplwakjYCA9TqMNPZscvVjeV-YPhb-D7-tyBhPiPZg" class="kg-image" alt="" width="602" height="301"></figure><h2 id="memorable-community-events">Memorable community events!<br></h2><p>Our Engineering All Hands (EAH) and J-Tech Talk are open to everyone in the tech community, or anyone who wants to learn more about the future of neural search. This year, we have hosted <strong>19 sessions </strong>and gathered over <strong>18,000 participants </strong>from every corner of the world to share tech insights and learn about new technologies.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh4.googleusercontent.com/ioGqYwBdlsvT-bOH9nFe5cfRC4eBtIyunFX6uuhukUTdrJBEAK7t6MoJiwPNWdbaYw4o7ZiDDO5rPO8qBgHQqvSaPLuB-01O4q0tluxpC1cGdC08iu-3kT-dY_PokLObjs2t_5PBhYFR7WMO77eJWWxjHjixr8tQTaDp4LnUN5IeHQ0iu0RfxWM0p_bzKw" class="kg-image" alt="" width="602" height="339"></figure><p>We are always amazed by the incredible projects that our community showcases at these events, and we are proud to create a warm atmosphere for sharing such inspiring initiatives.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/V4Sz6klXZMRv-46i1XYMj1fhCFvSWgYc6Mn89KVnfIl-MmogEXOsM1f3q0iHhSM4NdeVoWfqkr7GuFmiM1scVd3itDy3v9OFTx69DrT5aEGmpTiKnXz8awYfNKpEQUxQBiTO0eZoIMmWWeOo9Xw3FRBuiyl22FdcHwMQH7Dx_A9XHeB0c5Fi3BiRia_Vgw" class="kg-image" alt="" width="602" height="339"></figure><p>We also host Office Hours on a monthly basis. During these meet-ups, we answer community questions, gather feedback on the latest features, and learn about how people are using Jina AI in their projects. We have been delighted to host <strong>9 sessions</strong> and welcome over <strong>867 community members</strong> from around the world to work together with our amazing engineering team to solve technical problems and explore Jina AI features.<br></p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_02056.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_02056.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_02056.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_02056.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_02056.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.11421 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00237--1-.jpg" width="2000" height="1795" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00237--1-.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00237--1-.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00237--1-.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00237--1-.jpg 2386w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_02776.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_02776.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_02776.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_02776.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_02776.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.31752 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_01188--1-.jpg" width="2000" height="1518" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_01188--1-.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_01188--1-.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_01188--1-.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_01188--1-.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_01279.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_01279.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_01279.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_01279.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_01279.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.31579 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_02944--1-.jpg" width="2000" height="1520" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_02944--1-.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_02944--1-.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_02944--1-.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_02944--1-.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Jina AI 2022 Annual Event&nbsp;</figcaption></figure><p>Just a few weeks ago, we held the Jina AI Annual Event. We were delighted to have the opportunity to gather our beloved developer community, partners, and friends to celebrate the memories we’ve created and outlook for a greater upcoming 2023!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/jina-ai-annual-event/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Tech Talk and Cheer: Celebrating the Holidays at Our 2022 Annual Christmas Party</div><div class="kg-bookmark-description">The holiday season is upon us! As we reflect on this past year, we made a huge difference together with the support from our team, community members, and our partners.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/find-your-1.png" alt=""></div></a></figure><p>On top of all this, we took the chance to participate in and sponsor numerous events across Europe for the first time. It was a thrilling and rewarding experience for us, as we were able to connect with a wide variety of people from diverse industries and backgrounds. We are eager to continue attending and supporting more of them in the future!</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Image-from-iOS.jpeg" width="1600" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Image-from-iOS.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Image-from-iOS.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Image-from-iOS.jpeg 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.75 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/pasted-image-3.jpeg" width="1080" height="1440" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/pasted-image-3.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/pasted-image-3.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/pasted-image-3.jpeg 1080w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.21521 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/pasted-image-2.jpeg" width="1310" height="1078" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/pasted-image-2.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/pasted-image-2.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/pasted-image-2.jpeg 1310w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/pasted-image-0.jpeg" width="1440" height="1080" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/pasted-image-0.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/pasted-image-0.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/pasted-image-0.jpeg 1440w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Top left to bottom right: PyData Berlin, PyCon DE (Jina AI Team with Sebastián, Fast API), PyCon Italy, OSSummit Dublin</figcaption></figure><h2 id="our-community-is-a-driving-force-of-positive-social-impact"><br>Our community is a driving force of positive social impact!<br></h2><p>On March 7th, we launched 'Impact Tech, She Can', a campaign to invite female friends from diverse backgrounds and professions to participate in online dialogues, amplify female voices, inspire others, and encourage more women to come to the forefront and be seen and heard. </p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh5.googleusercontent.com/TzfNC9MTn5MpZbunOA9UbXAbvAVQqZI2klTGFkOyWys0xQAUt0-Uu3x3zswtLm-DbrWsmkUvRLu36zsxnUAvIr7ENqJBPRrluMI5wiqPbzyyc_vGgylb-FayobBOy5xz1V9sjI0Iq-R42FmSK9TjD6clVOFH9HcgAXloQsetQPM-AMRinDRZSdyGEfzmww" class="kg-image" alt="" width="602" height="301"></figure><p>This initiative welcomed over<strong> 600 attendees </strong>and reached many more people with this message. Building upon the event that took place in China, we are dedicated to reinforcing this message and supporting more women in tech, across the globe, in 2023!</p><h2 id="we-also-found-our-community-champions">We also found our community champions!<br></h2><p>The open-source community is filled with passionate, dedicated individuals who are committed to improving the world through their contributions. The power of open source lies in its ability to bring people together and to drive positive change. In October, we launched the Jina AI Community Advocates Program. Through JCAP, we aim to recognize and reward the achievements of our community champions, while also supporting them to improve their technical advocacy skills and bring the Jina AI team and community closer together. You can read more about the Advocacy program in this blog:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/from-zero-to-hero-at-jina-ai-community/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">New Community Reward Program is Coming!</div><div class="kg-bookmark-description">We are excited to introduce a new Reward Plan to recognize active community members! You can gain credits by engaging with the community. How? Read on!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Swag-Plan.png" alt=""></div></a></figure><p>A huge shout-out to our first ever JCAP members, <a href="https://www.linkedin.com/in/gfissore/?ref=jina-ai-gmbh.ghost.io">Giancarlo Fissore</a>, <a href="https://www.linkedin.com/in/onwuka-ijeoma/?ref=jina-ai-gmbh.ghost.io">Ijeoma Onwuka</a> &amp; <a href="https://twitter.com/Rishi0812?ref=jina-ai-gmbh.ghost.io">Rishi R</a> we are so humbled and proud of your actions in the community!</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.77778 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled--2-.png" width="1600" height="900" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Untitled--2-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Untitled--2-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled--2-.png 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.6 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled--1-.png" width="1600" height="1000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Untitled--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Untitled--1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled--1-.png 1600w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>In the new year, we are committed to investing even more into our community advocacy program and initiatives in order to empower our global community to achieve their goals and reach their full potential. If you would like to join us on this journey, you can <a href="https://docs.google.com/forms/d/e/1FAIpQLSfNmnIjZvDXIjVqrWRdK92DLgKPluXWLwLd1Sgt7A3HEaN9Kw/viewform?usp=send_form&amp;ref=jina-ai-gmbh.ghost.io">apply to join JCAP through this application.</a> <br><br>We are excited to see what we can accomplish together in the coming year—Happy Holidays to all!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fcelebrating-a-year-of-community-growth-and-accomplishment%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; 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diff --git a/news/clip-as-service-0-8-0-update/index.html b/news/clip-as-service-0-8-0-update/index.html
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--- a/news/clip-as-service-0-8-0-update/index.html
+++ b/news/clip-as-service-0-8-0-update/index.html
@@ -31,9 +31,9 @@
 Release time: 2022-10-12 08:11:40
 
 
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">CLIP-as-service 0.8.0 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a micro-service into neural search solutions.
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a micro-service into neural search solutions.
 
 Release 💫 Patch v0.8.0 · jina-ai/clip-as-serviceRelease Note (0.8.0) Release time: 2022-10-12 08:11:40 🙇 We’d like to thank all contributors for this new release! In particular,numb3r3, Jie Fu, Ziniu Yu, felix-wang, Jina Dev Bot, 🙇🆕 New...GitHubjina-ai
 
@@ -55,7 +55,7 @@
 Release time: 2022-10-12 08:11:40
 
 
-This release co</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 12, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a micro-service into neural search solutions.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/clip-as-service/releases/tag/v0.8.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v0.8.0 · jina-ai/clip-as-service</div><div class="kg-bookmark-description">Release Note (0.8.0) Release time: 2022-10-12 08:11:40 🙇 We’d like to thank all contributors for this new release! In particular,numb3r3, Jie Fu, Ziniu Yu, felix-wang, Jina Dev Bot, 🙇🆕 New...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/cadae15a73c74311306b2e383e8429fe90e1be446031a4a1e4f2265b0c978028/jina-ai/clip-as-service/releases/tag/v0.8.0" alt=""></div></a><figcaption>Full release note with links to pull requests</figcaption></figure><h1 id="release-note-080">Release Note (0.8.0)</h1>
+This release co</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 12, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a micro-service into neural search solutions.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/clip-as-service/releases/tag/v0.8.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v0.8.0 · jina-ai/clip-as-service</div><div class="kg-bookmark-description">Release Note (0.8.0) Release time: 2022-10-12 08:11:40 🙇 We’d like to thank all contributors for this new release! In particular,numb3r3, Jie Fu, Ziniu Yu, felix-wang, Jina Dev Bot, 🙇🆕 New...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/cadae15a73c74311306b2e383e8429fe90e1be446031a4a1e4f2265b0c978028/jina-ai/clip-as-service/releases/tag/v0.8.0" alt=""></div></a><figcaption>Full release note with links to pull requests</figcaption></figure><h1 id="release-note-080">Release Note (0.8.0)</h1>
 <p><em>Release time: 2022-10-12 08:11:40</em></p>
 <p>This release contains 3 new features, 1 performance improvement, and 1 documentation improvement.</p>
 <h2 id="%F0%9F%86%95-features">🆕 Features</h2>
@@ -73,43 +73,43 @@ <h3 id="support-vit-b-32-vit-l-14-vit-h-14-and-vit-g-14-trained-on-laion-2b-825"
 <li>ViT-g-14::laion2b-s12b-b42k</li>
 </ul>
 <p>The ViT-H-14 model achieves 78.0% zero-shot top-1 accuracy on ImageNet and 73.4% on zero-shot image retrieval at Recall@5 on MS COCO. This is the best-performing open source CLIP model. To use the new models, simply specify the model name, e.g., <code>ViT-H-14::laion2b-s32b-b79k</code> in the Flow YAML.  For example:</p>
-<pre><code class="language-yaml hljs"><span class="hljs-attr">jtype:</span> <span class="hljs-string">Flow</span>
-<span class="hljs-attr">version:</span> <span class="hljs-string">'1'</span>
-<span class="hljs-attr">with:</span>
-  <span class="hljs-attr">port:</span> <span class="hljs-number">51000</span>
-<span class="hljs-attr">executors:</span>
-  <span class="hljs-bullet">-</span> <span class="hljs-attr">name:</span> <span class="hljs-string">clip_t</span>
-    <span class="hljs-attr">uses:</span>
-      <span class="hljs-attr">jtype:</span> <span class="hljs-string">CLIPEncoder</span>
-      <span class="hljs-attr">with:</span>
-        <span class="hljs-attr">name:</span> <span class="hljs-string">ViT-H-14::laion2b-s32b-b79k</span>
-      <span class="hljs-attr">metas:</span>
-        <span class="hljs-attr">py_modules:</span>
-          <span class="hljs-bullet">-</span> <span class="hljs-string">clip_server.executors.clip_torch</span>
+<pre><code class="language-yaml">jtype: Flow
+version: '1'
+with:
+  port: 51000
+executors:
+  - name: clip_t
+    uses:
+      jtype: CLIPEncoder
+      with:
+        name: ViT-H-14::laion2b-s32b-b79k
+      metas:
+        py_modules:
+          - clip_server.executors.clip_torch
 </code></pre>
 <p>Please refer to <a href="https://clip-as-service.jina.ai/user-guides/server/?ref=jina-ai-gmbh.ghost.io#model-support">model support</a> to see the full list of supported models.</p>
 <h3 id="in-place-result-in-clipclient-preserve-output-order-by-uuid-815">In-place result in <code>clip_client</code>; preserve output order by uuid (#815)</h3>
 <p>The <code>clip_client</code> module now supports in-place embedding. This means the result of a call to the CLIP server to get embeddings is stored in the input <code>DocumentArray</code>, instead of creating a new <code>DocumentArray</code>. Consequently, the <code>DocumentArray</code> returned by a call to <code>Client.encode</code> now has the same order as the input <code>DocumentArray</code>.</p>
 <p><strong>This could cause a breaking change if code depends on <code>Client.encode</code> to return a new <code>DocumentArray</code> instance.</strong></p>
 <p>If you run the following code, you can verify that the input <code>DocumentArray</code> now contains the embeddings and that the order is unchanged.</p>
-<pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray, Document
-<span class="hljs-keyword">from</span> clip_client <span class="hljs-keyword">import</span> Client
+<pre><code class="language-python">from docarray import DocumentArray, Document
+from clip_client import Client
 
-c = Client(<span class="hljs-string">'grpc://0.0.0.0:51000'</span>)
+c = Client('grpc://0.0.0.0:51000')
 
 da = [
-    Document(text=<span class="hljs-string">'she smiled, with pain'</span>),
-    Document(uri=<span class="hljs-string">'apple.png'</span>),
-    Document(uri=<span class="hljs-string">'apple.png'</span>).load_uri_to_image_tensor(),
-    Document(blob=<span class="hljs-built_in">open</span>(<span class="hljs-string">'apple.png'</span>, <span class="hljs-string">'rb'</span>).read()),
-    Document(uri=<span class="hljs-string">'https://clip-as-service.jina.ai/_static/favicon.png'</span>),
+    Document(text='she smiled, with pain'),
+    Document(uri='apple.png'),
+    Document(uri='apple.png').load_uri_to_image_tensor(),
+    Document(blob=open('apple.png', 'rb').read()),
+    Document(uri='https://clip-as-service.jina.ai/_static/favicon.png'),
     Document(
-        uri=<span class="hljs-string">'data:image/gif;base64,R0lGODlhEAAQAMQAAORHHOVSKudfOulrSOp3WOyDZu6QdvCchPGolfO0o/XBs/fNwfjZ0frl3/zy7////wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACH5BAkAABAALAAAAAAQABAAAAVVICSOZGlCQAosJ6mu7fiyZeKqNKToQGDsM8hBADgUXoGAiqhSvp5QAnQKGIgUhwFUYLCVDFCrKUE1lBavAViFIDlTImbKC5Gm2hB0SlBCBMQiB0UjIQA7'</span>
+        uri='data:image/gif;base64,R0lGODlhEAAQAMQAAORHHOVSKudfOulrSOp3WOyDZu6QdvCchPGolfO0o/XBs/fNwfjZ0frl3/zy7////wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACH5BAkAABAALAAAAAAQABAAAAVVICSOZGlCQAosJ6mu7fiyZeKqNKToQGDsM8hBADgUXoGAiqhSvp5QAnQKGIgUhwFUYLCVDFCrKUE1lBavAViFIDlTImbKC5Gm2hB0SlBCBMQiB0UjIQA7'
     ),
 ]
 
 c.encode(da)
-<span class="hljs-built_in">print</span>(da.embeddings)
+print(da.embeddings)
 </code></pre>
 <h2 id="%F0%9F%9A%80-performance">🚀 Performance</h2>
 <h3 id="drop-image-content-to-boost-latency-824">Drop image content to boost latency (#824)</h3>
@@ -124,4 +124,4 @@ <h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2>
 <li>Ziniu Yu (@ZiniuYu)</li>
 <li>Jie Fu (@jemmyshin)</li>
 </ul>
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>CLIP-as-service 0.8.1 Update</title><meta charset="utf-8"><meta name="title" content="CLIP-as-service 0.8.1 Update"><meta name="description" content="CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a micro-service into neural search solutions."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/clip-as-service-0-8-1-update"><meta property="og:title" content="CLIP-as-service 0.8.1 Update"><meta property="og:description" content="CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a micro-service into neural search solutions."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/clip-as-service-0-8-1-update"><meta property="twitter:title" content="CLIP-as-service 0.8.1 Update"><meta property="twitter:description" content="CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a micro-service into neural search solutions."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a micro-service into neural search solutions.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 15, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a micro-service into neural search solutions.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/clip-as-service/releases/tag/v0.8.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v0.8.1 · jina-ai/clip-as-service</div><div class="kg-bookmark-description">Release Note (0.8.1) Release time: 2022-11-15 11:15:48 🙇 We’d like to thank all contributors for this new release! In particular,YangXiuyu, Ziniu Yu, felix-wang, Jie Fu, Jina Dev Bot, numb3...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/4ec1fb42520da1272612b0029adffd88fa0f262d63e1520270f6aa92798e50e3/jina-ai/clip-as-service/releases/tag/v0.8.1" alt=""></div></a><figcaption>Full release note with links to pull requests</figcaption></figure><h2 id="release-note-081">Release Note (0.8.1)</h2><p>This release contains 1 new feature, 1 performance improvement, 2 bug fixes and 4 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="allow-custom-callback-in-clipclient-849">Allow custom callback in <code>clip_client</code> (<a href="https://github.com/jina-ai/clip-as-service/issues/849?ref=jina-ai-gmbh.ghost.io">#849</a>)</h3><p>This feature allows <code>clip_client</code> users to send a request to a server and then process the response with a custom callback function. There are three callbacks that users can process with custom functions: <code>on_done</code>, <code>on_error</code> and <code>on_always</code>.</p><p>The following code snippet shows how to send a request to a server and save the response to a database.</p><pre><code class="language-python">from clip_client import Client
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">CLIP-as-service 0.8.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a micro-service into neural search solutions.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 15, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a micro-service into neural search solutions.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/clip-as-service/releases/tag/v0.8.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v0.8.1 · jina-ai/clip-as-service</div><div class="kg-bookmark-description">Release Note (0.8.1) Release time: 2022-11-15 11:15:48 🙇 We’d like to thank all contributors for this new release! In particular,YangXiuyu, Ziniu Yu, felix-wang, Jie Fu, Jina Dev Bot, numb3...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/4ec1fb42520da1272612b0029adffd88fa0f262d63e1520270f6aa92798e50e3/jina-ai/clip-as-service/releases/tag/v0.8.1" alt=""></div></a><figcaption>Full release note with links to pull requests</figcaption></figure><h2 id="release-note-081">Release Note (0.8.1)</h2><p>This release contains 1 new feature, 1 performance improvement, 2 bug fixes and 4 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="allow-custom-callback-in-clipclient-849">Allow custom callback in <code>clip_client</code> (<a href="https://github.com/jina-ai/clip-as-service/issues/849?ref=jina-ai-gmbh.ghost.io">#849</a>)</h3><p>This feature allows <code>clip_client</code> users to send a request to a server and then process the response with a custom callback function. There are three callbacks that users can process with custom functions: <code>on_done</code>, <code>on_error</code> and <code>on_always</code>.</p><p>The following code snippet shows how to send a request to a server and save the response to a database.</p><pre><code class="language-python">from clip_client import Client
 
 db = {}
 
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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Cloud-Native Helps You Build Multimodal AI in Production: Here's How</title><meta charset="utf-8"><meta name="title" content="Cloud-Native Helps You Build Multimodal AI in Production: Here's How"><meta name="description" content="How would cloud-native actually help you on building multimodal AI in production? What is cloud-native anyway? Is it just a buzzword to get VC's money yet delivers an empty promise?"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/cloud-native-helps-you-build-multimodal-ai-in-production-here-is-how"><meta property="og:title" content="Cloud-Native Helps You Build Multimodal AI in Production: Here's How"><meta property="og:description" content="How would cloud-native actually help you on building multimodal AI in production? What is cloud-native anyway? Is it just a buzzword to get VC's money yet delivers an empty promise?"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--40-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/cloud-native-helps-you-build-multimodal-ai-in-production-here-is-how"><meta property="twitter:title" content="Cloud-Native Helps You Build Multimodal AI in Production: Here's How"><meta property="twitter:description" content="How would cloud-native actually help you on building multimodal AI in production? What is cloud-native anyway? Is it just a buzzword to get VC's money yet delivers an empty promise?"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--40-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Cloud-Native Helps You Build Multimodal AI in Production: Here's How</title><meta charset="utf-8"><meta name="title" content="Cloud-Native Helps You Build Multimodal AI in Production: Here's How"><meta name="description" content="How would cloud-native actually help you on building multimodal AI in production? What is cloud-native anyway? Is it just a buzzword to get VC's money yet delivers an empty promise?"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/cloud-native-helps-you-build-multimodal-ai-in-production-here-is-how"><meta property="og:title" content="Cloud-Native Helps You Build Multimodal AI in Production: Here's How"><meta property="og:description" content="How would cloud-native actually help you on building multimodal AI in production? What is cloud-native anyway? Is it just a buzzword to get VC's money yet delivers an empty promise?"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--40-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/cloud-native-helps-you-build-multimodal-ai-in-production-here-is-how"><meta property="twitter:title" content="Cloud-Native Helps You Build Multimodal AI in Production: Here's How"><meta property="twitter:description" content="How would cloud-native actually help you on building multimodal AI in production? What is cloud-native anyway? Is it just a buzzword to get VC's money yet delivers an empty promise?"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--40-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Cloud-Native Helps You Build Multimodal AI in Production: Here's How</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">How would cloud-native actually help you on building multimodal AI in production? What is cloud-native anyway? Is it just a buzzword to get VC's money yet delivers an empty promise?</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 24, 2022 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is the framework for building multimodal AI applications on the cloud. With Jina, developers can easily build high-performance <strong>cloud-native</strong> applications, services, and systems in production. But at this point, you're not buying those campaign words: How would cloud-native <em>actually</em> help you? What <em>is</em> cloud-native anyway? Is it just a buzzword to get VC's money yet delivers an empty promise?</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/c1rbgR_YFkkAAAAC/baby-throw.gif" class="kg-image" alt="" width="498" height="370"><figcaption>In a parallel universe, this is VC's logic when seeing the phrase "cloud-native". (Un?)Fortunately in our universe, VCs are much more rational.</figcaption></figure><p>In this article, we start with a project from Bob, a machine learning engineer who just joined an e-commerce company. Bob's task is to build a <strong>shop-the-look service,</strong> allowing users to upload a photo and search visually similar items from the stock. We will walk through Bob's development journey and then answer the questions above.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-13.png" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-13.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-13.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-13.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/image-13.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Source: Van Gils - Spring Summer 2019 collection on Behance. licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.&nbsp;</figcaption></figure><h2 id="bobs-development-journey">Bob's development journey</h2><p>Shop-the-look system sounds cool and deep learning-related, exactly what Bob's expertise is, so Bob quickly starts to prototype.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-14.png" class="kg-image" alt="" width="2000" height="1333" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-14.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-14.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/image-14.png 2400w" sizes="(min-width: 720px) 720px"></figure><h3 id="1-prototyping">1. Prototyping</h3><p>There are two modes to the shop-the-look system:</p><ul><li><strong>Indexing</strong>, which creates a visual representation of all items in stock.</li><li><strong>Search</strong>, which takes a user-uploaded photo and finds visually similar items in stock.</li></ul><p>The indexing part creates a visual representation of all the stock items. To do this, Bob has to extract features from the images to create the visual representation. These could be extracted using a convolutional neural network, then stored in a database.</p><p>The search takes a user-uploaded photo and finds visually similar items from stock. Bob needs to extract features from the user-uploaded photo using a convolutional neural network. Then, he can use a similarity metric (like cosine similarity) to find visually similar items from the stock.</p><p>At this point, Bob needs a deep learning framework like PyTorch, some key-value database like MongoDB, and possibly some vector search engine like Faiss or Elasticsearch. As a machine learning engineer, Bob is mostly familiar with PyTorch and prototyping. Bob is smart and full of energy, so there’s nothing he can’t learn. He easily glues them together as the first proof of concept (POC).</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/x3YvOVE3Bj4AAAAC/johnny-test-dukey.gif" class="kg-image" alt="" width="498" height="278"><figcaption>Prototype, the sexiest thing in the engineering world</figcaption></figure><h3 id="2-make-it-a-service">2. Make it a service</h3><p>Is it done? Oh <em>hell</em> no, it's just getting started. Instead of a bunch of Python functions, Bob's goal is to make it a web service so that its IO goes through the network. To do that, Bob needs to <em>refactor</em> the above logic in some web framework with some API so that it can be called by other services.</p><p>There are many ways to do this: One example would be to use the Django web framework. Bob creates an endpoint that accepts user-uploaded photos, then uses the above logic to find visually similar items from stock. Finally, results are returned to the user as a JSON object.</p><p>At this point, Bob has learned a few new things such as REST API, web service, and web framework, which seem to go beyond Bob's scope as a “machine learning engineer”. Bob wondered whether it was even worth learning them. But a machine learning <strong>engineer</strong> is an engineer, and learning new things is always good. But deep down Bob feels that his engineering skills may not be enough to make it into production. After some time, Bob managed to glue everything together.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/jKaI_6bMatMAAAAC/seattleacademy.gif" class="kg-image" alt="" width="320" height="180"><figcaption>SaaS, the sexiest thing in the business world.</figcaption></figure><h3 id="3-deploy-it-to-the-cloud">3. Deploy it to the cloud</h3><p>The product team is impressed by Bob's progress and asks him to deploy it on AWS to serve some real traffic for the A/B test. This is exciting because it means Bob's PoC will face the public and have real users. Bob encountered many problems while migrating from local to the cloud, mostly because of dependency issues, CUDA drivers, and GPU hassles. He finally solved them by wrapping everything in a 30GB Docker image. It's a <em>big</em> monolith container, but it is easy to deploy and manage.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://media.tenor.com/5Bz7lcqJClAAAAAC/debug-deploy-debug.gif" class="kg-image" alt="" width="498" height="344"></figure><h3 id="4-improve-scalability-and-performance">4. Improve scalability and performance</h3><p>Is it done now? Not yet. The product team wants to ensure certain scalability of the service in practice, meaning that feature extraction should be parallelized and concurrent user requests should be handled without lag. A certain QPS (query per second) is required by the product team.</p><p>Bob tried the straightforward <code>multiprocessing</code> and <code>threading</code>, but nothing works out of the box with his deep learning stack. Bob decides to learn more high-performance computing frameworks such as Dask or Ray and try to adopt them. After some trial and error, Bob finally glues everything together and makes them work. At this point, Bob feels exhausted as it diverges too far from his expertise.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/zJWcOTrPOWIAAAAC/gotta-go-fast-fast.gif" class="kg-image" alt="" width="460" height="498"><figcaption>Scalability is now so important that Bob is willing to give up the other two legs.</figcaption></figure><h3 id="5-ensure-availability-and-minimize-downtime">5. Ensure availability and minimize downtime</h3><p><em>“What if our database is down (due to an update) for a short time?”</em></p><p>So Bob designs some naive failsafe mechanism that he just learned from a blog post. Bob also picks up some AWS service in a rush to ensure availability of the service, hoping it can be fire-and-forget.</p><h3 id="6-gain-observability">6. Gain observability</h3><p><em>“How can I see the incoming traffic?”</em></p><p>Bob changes all <code>print</code> to <code>logger.info</code> and impatiently spins up a dashboard.</p><h3 id="7-solve-security-concern">7. Solve security concern</h3><p><em>“Can we add some authentication header to it?”</em></p><p><em>“Is this service prone to attack?”</em></p><p>At this point, Bob is burning out. It strays too far away from his expertise. Bob decides to hand over the project to a senior backend engineer, a new hire who has a lot of experience in infrastructure engineering and cloud services. She knows what she's doing and is willing to help Bob.</p><p>So Bob sits down with her, scrolling over the glued code and justifying all his tricks, and design decisions, and explaining all the caveats. The senior keeps nodding, and Bob sees it as some kind of recognition. Soon after, the senior takes a slow and thoughtful sip of her coffee and says:</p><p><em>“Why don’t we rewrite it?”</em></p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/7_Vyf1vOM08AAAAC/code.gif" class="kg-image" alt="" width="498" height="278"><figcaption>Bob's code from the senior's view</figcaption></figure><h2 id="lessons-learned">Lessons learned</h2><p>The above example is real because Bob could be you, me or any machine learning engineer. Most importantly, it reveals some gaps when developing a multimodal AI system in production:</p><ul><li><strong>First is the lack of a design pattern for such a system.</strong> It's unclear how you should represent, compute, store, and transmit the data with different modalities consistently; and how you can switch between different tools and avoid glue code.</li><li><strong>Second is the large gap between a proof-of-concept and a production system.</strong> For a production system, cloud-native techniques are often required to ensure the professionalism and scalability of the system. In particular, microservices, orchestration, containerization, and observability are four pillars of such a system. However, the learning curve is just too steep for many machine learning engineers, preventing them from building production-ready systems.</li><li><strong>The third is the long go-to-market time</strong>. If a company chooses the wrong tech stack, it takes longer to bring the product to market. This is because the company has to spend more time and resources on developing the product, refactoring it, and going back and forth. In addition, the wrong stack can cause problems with the product itself, raising the risk of the product being unsuccessful.</li></ul><h2 id="cloud-native-saves-the-world">Cloud-native saves the world</h2><p>"Cloud-native" is a term that refers to a system designed to run on the cloud. It consists of a group of concepts:</p><ul><li><strong>Microservices</strong>: The building blocks of a cloud-native system.</li><li><strong>Orchestration</strong>: The process of managing the microservices.</li><li><strong>Containerization</strong>: The process of packaging the microservices into containers.</li><li><strong>Observability</strong>: The process of monitoring the system.</li><li><strong>DevOps and CI/CD</strong>: The process of automating integration of the system.</li></ul><p>Sounds cool but irrelevant. Do we really need all of these?</p><p>Yes! The table below summarizes the reasons nicely:</p><table>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">How would cloud-native actually help you on building multimodal AI in production? What is cloud-native anyway? Is it just a buzzword to get VC's money yet delivers an empty promise?</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 24, 2022 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is the framework for building multimodal AI applications on the cloud. With Jina, developers can easily build high-performance <strong>cloud-native</strong> applications, services, and systems in production. But at this point, you're not buying those campaign words: How would cloud-native <em>actually</em> help you? What <em>is</em> cloud-native anyway? Is it just a buzzword to get VC's money yet delivers an empty promise?</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/c1rbgR_YFkkAAAAC/baby-throw.gif" class="kg-image" alt="" width="498" height="370"><figcaption>In a parallel universe, this is VC's logic when seeing the phrase "cloud-native". (Un?)Fortunately in our universe, VCs are much more rational.</figcaption></figure><p>In this article, we start with a project from Bob, a machine learning engineer who just joined an e-commerce company. Bob's task is to build a <strong>shop-the-look service,</strong> allowing users to upload a photo and search visually similar items from the stock. We will walk through Bob's development journey and then answer the questions above.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-13.png" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-13.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-13.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-13.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/image-13.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Source: Van Gils - Spring Summer 2019 collection on Behance. licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.&nbsp;</figcaption></figure><h2 id="bobs-development-journey">Bob's development journey</h2><p>Shop-the-look system sounds cool and deep learning-related, exactly what Bob's expertise is, so Bob quickly starts to prototype.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-14.png" class="kg-image" alt="" width="2000" height="1333" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-14.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-14.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/image-14.png 2400w" sizes="(min-width: 720px) 720px"></figure><h3 id="1-prototyping">1. Prototyping</h3><p>There are two modes to the shop-the-look system:</p><ul><li><strong>Indexing</strong>, which creates a visual representation of all items in stock.</li><li><strong>Search</strong>, which takes a user-uploaded photo and finds visually similar items in stock.</li></ul><p>The indexing part creates a visual representation of all the stock items. To do this, Bob has to extract features from the images to create the visual representation. These could be extracted using a convolutional neural network, then stored in a database.</p><p>The search takes a user-uploaded photo and finds visually similar items from stock. Bob needs to extract features from the user-uploaded photo using a convolutional neural network. Then, he can use a similarity metric (like cosine similarity) to find visually similar items from the stock.</p><p>At this point, Bob needs a deep learning framework like PyTorch, some key-value database like MongoDB, and possibly some vector search engine like Faiss or Elasticsearch. As a machine learning engineer, Bob is mostly familiar with PyTorch and prototyping. Bob is smart and full of energy, so there’s nothing he can’t learn. He easily glues them together as the first proof of concept (POC).</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/x3YvOVE3Bj4AAAAC/johnny-test-dukey.gif" class="kg-image" alt="" width="498" height="278"><figcaption>Prototype, the sexiest thing in the engineering world</figcaption></figure><h3 id="2-make-it-a-service">2. Make it a service</h3><p>Is it done? Oh <em>hell</em> no, it's just getting started. Instead of a bunch of Python functions, Bob's goal is to make it a web service so that its IO goes through the network. To do that, Bob needs to <em>refactor</em> the above logic in some web framework with some API so that it can be called by other services.</p><p>There are many ways to do this: One example would be to use the Django web framework. Bob creates an endpoint that accepts user-uploaded photos, then uses the above logic to find visually similar items from stock. Finally, results are returned to the user as a JSON object.</p><p>At this point, Bob has learned a few new things such as REST API, web service, and web framework, which seem to go beyond Bob's scope as a “machine learning engineer”. Bob wondered whether it was even worth learning them. But a machine learning <strong>engineer</strong> is an engineer, and learning new things is always good. But deep down Bob feels that his engineering skills may not be enough to make it into production. After some time, Bob managed to glue everything together.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/jKaI_6bMatMAAAAC/seattleacademy.gif" class="kg-image" alt="" width="320" height="180"><figcaption>SaaS, the sexiest thing in the business world.</figcaption></figure><h3 id="3-deploy-it-to-the-cloud">3. Deploy it to the cloud</h3><p>The product team is impressed by Bob's progress and asks him to deploy it on AWS to serve some real traffic for the A/B test. This is exciting because it means Bob's PoC will face the public and have real users. Bob encountered many problems while migrating from local to the cloud, mostly because of dependency issues, CUDA drivers, and GPU hassles. He finally solved them by wrapping everything in a 30GB Docker image. It's a <em>big</em> monolith container, but it is easy to deploy and manage.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://media.tenor.com/5Bz7lcqJClAAAAAC/debug-deploy-debug.gif" class="kg-image" alt="" width="498" height="344"></figure><h3 id="4-improve-scalability-and-performance">4. Improve scalability and performance</h3><p>Is it done now? Not yet. The product team wants to ensure certain scalability of the service in practice, meaning that feature extraction should be parallelized and concurrent user requests should be handled without lag. A certain QPS (query per second) is required by the product team.</p><p>Bob tried the straightforward <code>multiprocessing</code> and <code>threading</code>, but nothing works out of the box with his deep learning stack. Bob decides to learn more high-performance computing frameworks such as Dask or Ray and try to adopt them. After some trial and error, Bob finally glues everything together and makes them work. At this point, Bob feels exhausted as it diverges too far from his expertise.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/zJWcOTrPOWIAAAAC/gotta-go-fast-fast.gif" class="kg-image" alt="" width="460" height="498"><figcaption>Scalability is now so important that Bob is willing to give up the other two legs.</figcaption></figure><h3 id="5-ensure-availability-and-minimize-downtime">5. Ensure availability and minimize downtime</h3><p><em>“What if our database is down (due to an update) for a short time?”</em></p><p>So Bob designs some naive failsafe mechanism that he just learned from a blog post. Bob also picks up some AWS service in a rush to ensure availability of the service, hoping it can be fire-and-forget.</p><h3 id="6-gain-observability">6. Gain observability</h3><p><em>“How can I see the incoming traffic?”</em></p><p>Bob changes all <code>print</code> to <code>logger.info</code> and impatiently spins up a dashboard.</p><h3 id="7-solve-security-concern">7. Solve security concern</h3><p><em>“Can we add some authentication header to it?”</em></p><p><em>“Is this service prone to attack?”</em></p><p>At this point, Bob is burning out. It strays too far away from his expertise. Bob decides to hand over the project to a senior backend engineer, a new hire who has a lot of experience in infrastructure engineering and cloud services. She knows what she's doing and is willing to help Bob.</p><p>So Bob sits down with her, scrolling over the glued code and justifying all his tricks, and design decisions, and explaining all the caveats. The senior keeps nodding, and Bob sees it as some kind of recognition. Soon after, the senior takes a slow and thoughtful sip of her coffee and says:</p><p><em>“Why don’t we rewrite it?”</em></p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/7_Vyf1vOM08AAAAC/code.gif" class="kg-image" alt="" width="498" height="278"><figcaption>Bob's code from the senior's view</figcaption></figure><h2 id="lessons-learned">Lessons learned</h2><p>The above example is real because Bob could be you, me or any machine learning engineer. Most importantly, it reveals some gaps when developing a multimodal AI system in production:</p><ul><li><strong>First is the lack of a design pattern for such a system.</strong> It's unclear how you should represent, compute, store, and transmit the data with different modalities consistently; and how you can switch between different tools and avoid glue code.</li><li><strong>Second is the large gap between a proof-of-concept and a production system.</strong> For a production system, cloud-native techniques are often required to ensure the professionalism and scalability of the system. In particular, microservices, orchestration, containerization, and observability are four pillars of such a system. However, the learning curve is just too steep for many machine learning engineers, preventing them from building production-ready systems.</li><li><strong>The third is the long go-to-market time</strong>. If a company chooses the wrong tech stack, it takes longer to bring the product to market. This is because the company has to spend more time and resources on developing the product, refactoring it, and going back and forth. In addition, the wrong stack can cause problems with the product itself, raising the risk of the product being unsuccessful.</li></ul><h2 id="cloud-native-saves-the-world">Cloud-native saves the world</h2><p>"Cloud-native" is a term that refers to a system designed to run on the cloud. It consists of a group of concepts:</p><ul><li><strong>Microservices</strong>: The building blocks of a cloud-native system.</li><li><strong>Orchestration</strong>: The process of managing the microservices.</li><li><strong>Containerization</strong>: The process of packaging the microservices into containers.</li><li><strong>Observability</strong>: The process of monitoring the system.</li><li><strong>DevOps and CI/CD</strong>: The process of automating integration of the system.</li></ul><p>Sounds cool but irrelevant. Do we really need all of these?</p><p>Yes! The table below summarizes the reasons nicely:</p><table>
 <thead>
 <tr>
 <th>Characteristics of a multimodal AI system</th>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 50%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--7-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">COLING2022 Summary on Multimodal AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Last week I was in Gyeongju, Korea for the COLING2022 conference. COLING is the premier conference in computational linguistics held every two years. In this article, I will review the multimodal AI-related work in COLING 2022.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 21, 2022 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Last week I was in Gyeongju, Korea for the COLING2022 conference. COLING is the premier conference in computational linguistics held every two years. </p><p>The conference was very well organized, and the talks were very interesting. I learned a lot about the latest research in computational linguistics and NLP, such as automated writing evaluation and multi-hop question answering. I also had a chance to meet many old friends and make new ones at the Jina AI dinner event. </p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9203.jpg" width="1600" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_9203.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_9203.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9203.jpg 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9214-1.jpg" width="1600" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_9214-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_9214-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9214-1.jpg 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.750117 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9222.jpg" width="1600" height="2133" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_9222.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_9222.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9222.jpg 1600w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.75 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9291.jpg" width="1200" height="1600" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_9291.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_9291.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9291.jpg 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9295.jpg" width="1600" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_9295.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_9295.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9295.jpg 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9173.jpg" width="1600" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_9173.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_9173.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9173.jpg 1600w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption><p><span style="white-space: pre-wrap;">Dinner event hosted by Jina AI at COLING2022</span></p></figcaption></figure><p>In this article, I will review the multimodal AI-related work presented at COLING 2022. Despite being primarily an NLP conference, there were 26 presentations focused on multimodal AI, covering text-image, text-video, and text-speech domains. I would like to highlight three presentations that I found particularly interesting.</p><h2 id="are-visual-linguistic-models-commonsense-knowledge-bases">Are Visual-Linguistic Models Commonsense Knowledge Bases?</h2><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.491/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Are Visual-Linguistic Models Commonsense Knowledge Bases?</div><div class="kg-bookmark-description">Hsiu-Yu Yang, Carina Silberer. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.491.jpg" alt=""></div></a></figure><p>We have all seen the huge potential for pretrained language models (PTLMs) over the last few years. Models such as Transformer and GPT have been widely used in many downstream tasks due to their potential as a commonsense knowledge base. However, the text corpora used to train PTLMs can make them very biased, and this can make them inconsistent and not very robust. In this paper, Yang and Silberer suggest that text corpora alone may be insufficient for knowledge acquisition and raise important questions for visual-linguistic models like UNITER, VILBERT, and CLIP:</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">🤔</div><div class="kg-callout-text">Can a language model with a visual component represent our physical world better?</div></div><p>They address this problem with probing questions like this one:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-8.png" class="kg-image" alt="" width="704" height="350" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-8.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-8.png 704w"><figcaption><span style="white-space: pre-wrap;">Prompt-based zero-shot QA with visual input. QA pairs can be categorized into multiple commonsense dimensions to identify what sort of relational knowledge the model has acquired: part-whole, taxonomic, distinctness, similarity, quality, utility, creation, temporal, spatial, and desire. During experiments, the author selectively masks out image input to study the what commonsense knowledge the models have captured.</span></figcaption></figure><h3 id="which-dimensions-of-commonsense-do-visual-linguistic-models-possess-compared-to-text-only-ptlms">Which dimensions of commonsense do v<strong>isual-linguistic</strong> models possess compared to text-only PTLMs?</h3><p>Hsui-Yu shows that visual-linguistic (VL) models such as UNITER and VILBERT are better at <em>part-whole</em>, <em>spatial</em>, and <em>desire</em> dimensions but struggle with <em>taxonomic</em>, <em>distinctness,</em> and <em>temporal</em> dimension. In terms of <em>spatial </em>dimension, VL models consistently outperform RoBERTa by 8%. On non-visual related dimensions such as <em>taxonomic </em>and <em>temporal, </em>VL models underperform by 8%, which is understandable as taxonomy and temporality are rarely represented in images. When using real-world images for training VL, <em>distinctness </em>is also hard to learn because opposite concepts e.g. <em>flood </em>and <em>drought</em>, rarely come together in one picture.</p><h3 id="during-pretraining-does-explicit-visual-information-ie-images-benefit-commonsense-knowledge-encoding">During pretraining, does explicit visual information (i.e., images) benefit commonsense knowledge encoding? </h3><p>When adding a BERT pretrained with image captions, the advantage of VL models becomes less significant, even on the <em>spatial </em>dimension. This shows that image captions can already provide a good proxy for visual information. The only dimension that VL models outperform is <em>part-whole, </em>with a tiny margin though<em>.</em></p><h3 id="during-inference-is-explicit-visual-observation-ie-images-necessary-for-recalling-commonsense-knowledge">During inference, is explicit visual observation (i.e., images) necessary for recalling commonsense knowledge? </h3><p>The above experiments have not used the visual input during the zero-shot QA task, so a natural question is, will adding images help? The answer is no. Visual information just makes everything worse. In fact, experiments show that all dual-stream (textual + visual) models underperform compared to their text-only counterparts on <em>part-whole</em>, <em>spatial, taxonomic</em>, and <em>distinctness </em>dimensions. This suggests that the texts are the driving force for successful inference on purely linguistic tasks. </p><p>What I found interesting about this work is the demystifying of the multimodal model, showing that although state-of-the-art VL models do encode complementary knowledge types to pure language models, the way that they combine visual and textual signals is still very primitive and not human-like at all.</p><h2 id="dual-capsule-attention-mask-network-with-mutual-learning-for-visual-question-answering">Dual Capsule Attention Mask Network with Mutual Learning for Visual Question Answering</h2><p>It is worth mentioning that the probing task from the last work is <strong>not </strong>a visual question-answering (VQA) task, though it contains QA pairs and images. A formal VQA task looks like the following:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-9.png" class="kg-image" alt="" width="1124" height="578" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-9.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-9.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-9.png 1124w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">The goal of VQA is to answer questions related to the content of images correctly. It has a wide range of practical applications, such as helping people with visual impairments and human-computer Q&amp;A</span></figcaption></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.500/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Dual Capsule Attention Mask Network with Mutual Learning for Visual Question Answering</div><div class="kg-bookmark-description">Weidong Tian, Haodong Li, Zhong-Qiu Zhao. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.500.jpg" alt=""></div></a></figure><p>The challenge of the VQA task is how to leverage fine-grained features with critical information to ensure that feature extraction emphasizes the objects related to the questions. Let's see two examples below:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-10.png" class="kg-image" alt="" width="1486" height="706" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-10.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-10.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-10.png 1486w" sizes="(min-width: 720px) 720px"></figure><p>In the left example, the fine-grained features with attention have the critical information required for the answer inference, which helps the model generate the correct answer by eliminating irrelevant factors that could interfere. In the right example, unattended coarse-grained features contain the richer semantic information needed for a correct answer.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">🤔</div><div class="kg-callout-text">Can we combine global coarse-grained information and local fine-grained information to provide better information for the VQA task?</div></div><p>Weidong et al. address that in their paper. They propose a dual capsule attention mask network (DCAMN) with mutual learning for VQA.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-11.png" class="kg-image" alt="" width="2000" height="1115" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-11.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-11.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-11.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/image-11.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>DCAMN can process features at different granularities, taking global information into account and focusing on critical information. Combining different perspectives and granularities can improve the generalization capability of the model and make more accurate predictions. </p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-12.png" class="kg-image" alt="" width="1450" height="764" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-12.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-12.png 1450w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">DCAMN performance on three types of VQA: yes/no, number, and others</span></figcaption></figure><p>In addition, the proposed DCAMN can effectively fuse multimodal features and locate evidence, improving the interpretability of the network, as the picture below illustrates:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.947955 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-1.png" width="510" height="538" alt=""></div><div class="kg-gallery-image" style="flex: 0.840741 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2-1.png" width="454" height="540" alt=""></div></div></div></figure><p>The attention mechanism and the model's interpretability are of particular interest for explainable multimodal AI. </p><h2 id="in-the-wild-video-question-answering">In-the-Wild Video Question Answering</h2><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.496/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">In-the-Wild Video Question Answering</div><div class="kg-bookmark-description">Santiago Castro, Naihao Deng, Pingxuan Huang, Mihai Burzo, Rada Mihalcea. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.496.jpg" alt=""></div></a></figure><p>As a temporal extension of Visual QA, Video QA plays an important role in the development of intelligent AI systems, as it enables the effective processing of modality and temporal information. In the example below, given a long-video and a question, a video QA system first aims to generate open-ended answers. Second, it retrieves visual support for a given question and answer, which is represented by a span.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-13.png" class="kg-image" alt="" width="2000" height="660" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-13.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-13.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-13.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-13.png 2338w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Finding the relevant frames in a video for a given question-answer pair can help a system in its reasoning process, and is in line with ongoing efforts to build interpretable models</span></figcaption></figure><p>Much of the existing work on Video QA is based on the MovieQA (Tapaswi et al., 2016), and TVQA (Lei et al., 2018) datasets, which focus on common human activities in a multiple-choice setting. These datasets consist primarily of video from cooking videos or movies, making them very limited in domain.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-15.png" class="kg-image" alt="" width="2000" height="785" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-15.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-15.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/image-15.png 2400w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Comparison between WILDQA and other existing datasets. VE?: Whether the dataset provides “Video Evidences”?; MC: “Multiple Choice” question answering; OE: “Open Ended” question answering; ES: “Evidence Selection”.</span></figcaption></figure><p>Santiago et al. propose the WildQA dataset and tasks that focus on scenes recorded in the outside world in an open-ended setting, like the example below:</p><figure class="kg-card kg-video-card kg-width-regular kg-card-hascaption" data-kg-thumbnail="https://jina-ai-gmbh.ghost.io/content/images/2022/10/media-thumbnail-ember964.jpg" data-kg-custom-thumbnail="">
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">COLING2022 Summary on Multimodal AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Last week I was in Gyeongju, Korea for the COLING2022 conference. COLING is the premier conference in computational linguistics held every two years. In this article, I will review the multimodal AI-related work in COLING 2022.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 21, 2022 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Last week I was in Gyeongju, Korea for the COLING2022 conference. COLING is the premier conference in computational linguistics held every two years. </p><p>The conference was very well organized, and the talks were very interesting. I learned a lot about the latest research in computational linguistics and NLP, such as automated writing evaluation and multi-hop question answering. I also had a chance to meet many old friends and make new ones at the Jina AI dinner event. </p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9203.jpg" width="1600" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_9203.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_9203.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9203.jpg 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9214-1.jpg" width="1600" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_9214-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_9214-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9214-1.jpg 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.750117 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9222.jpg" width="1600" height="2133" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_9222.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_9222.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9222.jpg 1600w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.75 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9291.jpg" width="1200" height="1600" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_9291.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_9291.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9291.jpg 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9295.jpg" width="1600" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_9295.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_9295.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9295.jpg 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9173.jpg" width="1600" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/IMG_9173.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/IMG_9173.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/IMG_9173.jpg 1600w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption><p><span style="white-space: pre-wrap;">Dinner event hosted by Jina AI at COLING2022</span></p></figcaption></figure><p>In this article, I will review the multimodal AI-related work presented at COLING 2022. Despite being primarily an NLP conference, there were 26 presentations focused on multimodal AI, covering text-image, text-video, and text-speech domains. I would like to highlight three presentations that I found particularly interesting.</p><h2 id="are-visual-linguistic-models-commonsense-knowledge-bases">Are Visual-Linguistic Models Commonsense Knowledge Bases?</h2><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.491/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Are Visual-Linguistic Models Commonsense Knowledge Bases?</div><div class="kg-bookmark-description">Hsiu-Yu Yang, Carina Silberer. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.491.jpg" alt=""></div></a></figure><p>We have all seen the huge potential for pretrained language models (PTLMs) over the last few years. Models such as Transformer and GPT have been widely used in many downstream tasks due to their potential as a commonsense knowledge base. However, the text corpora used to train PTLMs can make them very biased, and this can make them inconsistent and not very robust. In this paper, Yang and Silberer suggest that text corpora alone may be insufficient for knowledge acquisition and raise important questions for visual-linguistic models like UNITER, VILBERT, and CLIP:</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">🤔</div><div class="kg-callout-text">Can a language model with a visual component represent our physical world better?</div></div><p>They address this problem with probing questions like this one:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-8.png" class="kg-image" alt="" width="704" height="350" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-8.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-8.png 704w"><figcaption><span style="white-space: pre-wrap;">Prompt-based zero-shot QA with visual input. QA pairs can be categorized into multiple commonsense dimensions to identify what sort of relational knowledge the model has acquired: part-whole, taxonomic, distinctness, similarity, quality, utility, creation, temporal, spatial, and desire. During experiments, the author selectively masks out image input to study the what commonsense knowledge the models have captured.</span></figcaption></figure><h3 id="which-dimensions-of-commonsense-do-visual-linguistic-models-possess-compared-to-text-only-ptlms">Which dimensions of commonsense do v<strong>isual-linguistic</strong> models possess compared to text-only PTLMs?</h3><p>Hsui-Yu shows that visual-linguistic (VL) models such as UNITER and VILBERT are better at <em>part-whole</em>, <em>spatial</em>, and <em>desire</em> dimensions but struggle with <em>taxonomic</em>, <em>distinctness,</em> and <em>temporal</em> dimension. In terms of <em>spatial </em>dimension, VL models consistently outperform RoBERTa by 8%. On non-visual related dimensions such as <em>taxonomic </em>and <em>temporal, </em>VL models underperform by 8%, which is understandable as taxonomy and temporality are rarely represented in images. When using real-world images for training VL, <em>distinctness </em>is also hard to learn because opposite concepts e.g. <em>flood </em>and <em>drought</em>, rarely come together in one picture.</p><h3 id="during-pretraining-does-explicit-visual-information-ie-images-benefit-commonsense-knowledge-encoding">During pretraining, does explicit visual information (i.e., images) benefit commonsense knowledge encoding? </h3><p>When adding a BERT pretrained with image captions, the advantage of VL models becomes less significant, even on the <em>spatial </em>dimension. This shows that image captions can already provide a good proxy for visual information. The only dimension that VL models outperform is <em>part-whole, </em>with a tiny margin though<em>.</em></p><h3 id="during-inference-is-explicit-visual-observation-ie-images-necessary-for-recalling-commonsense-knowledge">During inference, is explicit visual observation (i.e., images) necessary for recalling commonsense knowledge? </h3><p>The above experiments have not used the visual input during the zero-shot QA task, so a natural question is, will adding images help? The answer is no. Visual information just makes everything worse. In fact, experiments show that all dual-stream (textual + visual) models underperform compared to their text-only counterparts on <em>part-whole</em>, <em>spatial, taxonomic</em>, and <em>distinctness </em>dimensions. This suggests that the texts are the driving force for successful inference on purely linguistic tasks. </p><p>What I found interesting about this work is the demystifying of the multimodal model, showing that although state-of-the-art VL models do encode complementary knowledge types to pure language models, the way that they combine visual and textual signals is still very primitive and not human-like at all.</p><h2 id="dual-capsule-attention-mask-network-with-mutual-learning-for-visual-question-answering">Dual Capsule Attention Mask Network with Mutual Learning for Visual Question Answering</h2><p>It is worth mentioning that the probing task from the last work is <strong>not </strong>a visual question-answering (VQA) task, though it contains QA pairs and images. A formal VQA task looks like the following:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-9.png" class="kg-image" alt="" width="1124" height="578" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-9.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-9.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-9.png 1124w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">The goal of VQA is to answer questions related to the content of images correctly. It has a wide range of practical applications, such as helping people with visual impairments and human-computer Q&amp;A</span></figcaption></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.500/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Dual Capsule Attention Mask Network with Mutual Learning for Visual Question Answering</div><div class="kg-bookmark-description">Weidong Tian, Haodong Li, Zhong-Qiu Zhao. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.500.jpg" alt=""></div></a></figure><p>The challenge of the VQA task is how to leverage fine-grained features with critical information to ensure that feature extraction emphasizes the objects related to the questions. Let's see two examples below:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-10.png" class="kg-image" alt="" width="1486" height="706" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-10.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-10.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-10.png 1486w" sizes="(min-width: 720px) 720px"></figure><p>In the left example, the fine-grained features with attention have the critical information required for the answer inference, which helps the model generate the correct answer by eliminating irrelevant factors that could interfere. In the right example, unattended coarse-grained features contain the richer semantic information needed for a correct answer.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">🤔</div><div class="kg-callout-text">Can we combine global coarse-grained information and local fine-grained information to provide better information for the VQA task?</div></div><p>Weidong et al. address that in their paper. They propose a dual capsule attention mask network (DCAMN) with mutual learning for VQA.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-11.png" class="kg-image" alt="" width="2000" height="1115" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-11.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-11.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-11.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/image-11.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>DCAMN can process features at different granularities, taking global information into account and focusing on critical information. Combining different perspectives and granularities can improve the generalization capability of the model and make more accurate predictions. </p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-12.png" class="kg-image" alt="" width="1450" height="764" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-12.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-12.png 1450w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">DCAMN performance on three types of VQA: yes/no, number, and others</span></figcaption></figure><p>In addition, the proposed DCAMN can effectively fuse multimodal features and locate evidence, improving the interpretability of the network, as the picture below illustrates:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.947955 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-1.png" width="510" height="538" alt=""></div><div class="kg-gallery-image" style="flex: 0.840741 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2-1.png" width="454" height="540" alt=""></div></div></div></figure><p>The attention mechanism and the model's interpretability are of particular interest for explainable multimodal AI. </p><h2 id="in-the-wild-video-question-answering">In-the-Wild Video Question Answering</h2><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.496/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">In-the-Wild Video Question Answering</div><div class="kg-bookmark-description">Santiago Castro, Naihao Deng, Pingxuan Huang, Mihai Burzo, Rada Mihalcea. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.496.jpg" alt=""></div></a></figure><p>As a temporal extension of Visual QA, Video QA plays an important role in the development of intelligent AI systems, as it enables the effective processing of modality and temporal information. In the example below, given a long-video and a question, a video QA system first aims to generate open-ended answers. Second, it retrieves visual support for a given question and answer, which is represented by a span.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-13.png" class="kg-image" alt="" width="2000" height="660" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-13.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-13.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-13.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-13.png 2338w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Finding the relevant frames in a video for a given question-answer pair can help a system in its reasoning process, and is in line with ongoing efforts to build interpretable models</span></figcaption></figure><p>Much of the existing work on Video QA is based on the MovieQA (Tapaswi et al., 2016), and TVQA (Lei et al., 2018) datasets, which focus on common human activities in a multiple-choice setting. These datasets consist primarily of video from cooking videos or movies, making them very limited in domain.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-15.png" class="kg-image" alt="" width="2000" height="785" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-15.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-15.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/image-15.png 2400w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Comparison between WILDQA and other existing datasets. VE?: Whether the dataset provides “Video Evidences”?; MC: “Multiple Choice” question answering; OE: “Open Ended” question answering; ES: “Evidence Selection”.</span></figcaption></figure><p>Santiago et al. propose the WildQA dataset and tasks that focus on scenes recorded in the outside world in an open-ended setting, like the example below:</p><figure class="kg-card kg-video-card kg-width-regular kg-card-hascaption" data-kg-thumbnail="https://jina-ai-gmbh.ghost.io/content/images/2022/10/media-thumbnail-ember964.jpg" data-kg-custom-thumbnail="">
             <div class="kg-video-container">
                 <video src="https://jina-ai-gmbh.ghost.io/content/media/2022/10/Norwegian-Explorer_11-clip-54.mp4" poster="https://img.spacergif.org/v1/640x360/0a/spacer.png" width="640" height="360" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2022/10/media-thumbnail-ember964.jpg') 50% 50% / cover no-repeat;"></video>
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             <figcaption><p><span style="white-space: pre-wrap;">Q1: What kinds of bodies of water are there? A1: There are rivers and streams. Evidence: 0:07 - 0:14</span></p></figcaption>
-        </figure><h2 id="multi-task-learning-of-t5-model-with-i3d-features">Multi-Task Learning of T5 Model with I3D Features</h2><p>To solve WildQA, Santiago et al. concatenate the text features with the visual features and input the concatenated features to the T5 model. They extract <a href="https://iashin.ai/video_features/models/i3d/?ref=jina-ai-gmbh.ghost.io">I3D video features</a> and take one feature per second.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-16.png" class="kg-image" alt="" width="2000" height="1107" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-16.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-16.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-16.png 2270w" sizes="(min-width: 720px) 720px"></figure><p>T5 encoder outputs a sequence of the encoded states. Santiago et al. treat the subsequence corresponding to the visual features as the encoded hidden sequence for the video frames. They then multiply the sequence with two vectors to get the maximum likelihood prediction of the start and the end of the evidence, respectively.</p><p>The tasks of visual evidence selection and video question-answering can be jointly trained together by simply combining the two losses in a weighted-manner. </p><p>In the experiment, Santiago et al. propose multiple baselines including: randomly choosing answers from the dev set (i.e. Random); always predicting the most common answer in the dev set (i.e. Common); and retrieving the answers for the dev set question whose embedding has the highest cosine similarity to the test question (i.e. Closest).</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-17.png" class="kg-image" alt="" width="2000" height="701" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-17.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-17.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-17.png 2020w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Performance on video question-answering, measured by ROUGE score (left); and on video evidence selection (right) measured by Intersection-Over-Union. IOU is defined as the length of their intersection divided by the length of their union. The prediction is counted as a match if it overlaps with any of the ground truth spans by more than the threshold. They then use these partial matches to calculate an F1 score (i.e. IOU-F1 scores).</span></figcaption></figure><p>I noticed that introducing video information (T5 T+V) does not improve performance on video question-answering tasks, which confirms what Yang &amp; Silberer said in their work. This may also due to the types of questions in WildQA, which do not match commonsense knowledge. In the video evidence selection task, the T5 model is not even better than the random baseline. Adding multi-task learning does not help. In general, we can conclude WildQA is a pretty challenging task with a significant gap between the state-of-the-art multimodal model and human. </p><h2 id="other-interesting-multimodal-research">Other Interesting Multimodal Research</h2><h3 id="multimodal-social-media">Multimodal Social Media</h3><p>There are multiple research projects focusing on multimodality in the social media. For example, the upswing of text and image sharing on social media platforms during mass emergency situations has led to numerous opportunities to gain timely access to valuable information that can help disaster relief authorities act more quickly and more efficiently.</p><p>Iustin et al. extend the <a href="https://arxiv.org/abs/2001.07685?ref=jina-ai-gmbh.ghost.io">FixMatch algorithm</a> to a multimodal scenario and offer two extensions to the original approach relevant for text and multimodal datasets. They show that multimodal FixMatch can leverage inexpensive unlabeled data to improve performance on diaster classification tasks.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.239/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Multimodal Semi-supervised Learning for Disaster Tweet Classification</div><div class="kg-bookmark-description">Iustin Sirbu, Tiberiu Sosea, Cornelia Caragea, Doina Caragea, Traian Rebedea. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.239.jpg" alt=""></div></a></figure><p>Extracting spatial information from social media and tweets has also received substantial attention recently. Zhaomin et al. propose BERT+VGG16 multimodal model to determine whether people are located in the places they mention in their tweets.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.226/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Are People Located in the Places They Mention in Their Tweets? A Multimodal Approach</div><div class="kg-bookmark-description">Zhaomin Xiao, Eduardo Blanco. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.226.jpg" alt=""></div></a></figure><p>To better understand when the text and image are most beneficial, Zhaomin et al. perform a qualitative analysis of the errors made by the single-stream model, and how these errors are fixed by the dual-stream model. </p><p>Social media is a good place to conduct sentiment analysis. As a popular way to express emotion on social media, stickers &amp; memes in posts can supplement missing sentiments and help identify sentiments precisely. Stickers and memes, despite being represented as images or simple gifs, have very different semantics from real-world photos. Feng et al. point out three challenges when working with stickers/memes:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.591/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Towards Exploiting Sticker for Multimodal Sentiment Analysis in Social Media: A New Dataset and Baseline</div><div class="kg-bookmark-description">Feng Ge, Weizhao Li, Haopeng Ren, Yi Cai. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.591.jpg" alt=""></div></a></figure><ul><li>First, stickers may be inherently multimodal because they are embedded with texts. Same sticker with different sticker texts may vary significantly in sentiment.</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-18.png" class="kg-image" alt="" width="2000" height="1038" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-18.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-18.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-18.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/image-18.png 2400w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Millennial Humor on "Philosoraptor"</span></figcaption></figure><ul><li>Second, stickers are highly varied in style, preventing the models from learning robust representations.</li><li>Third, the way sentiment is fused together from text and stickers is complicated and sometimes inconsistent.</li></ul><p>This work actually reminds me a popular Youtube video explaining Gen Z humor and their meme behaviors:</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-text">Popular = Not Funny<br>Was popular = Funny<br>Ironic = Funny<br>Make no sense = Funny<br>Unfunny = Funny</div></div><p>There's nothing that Gen-Zers like more than changing and hating things. So perhaps our models on sentiment analysis have become obsolete? </p><figure class="kg-card kg-embed-card"><iframe width="200" height="113" src="https://www.youtube.com/embed/oVlspd9hxFA?start=61&amp;feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" title="Why is Gen Z Humor So Weird?"></iframe></figure><h3 id="text-gestures-multimodal">Text-Gestures Multimodal</h3><p>Communication is a multimodal process. Information from verbal and non-verbal modalities are mixed into one channel. It has been revealed from a long history of empirical studies that speakers’ expression in the visual modality, including gestures, body poses, eye contacts and other types of non-verbal behaviors, play critical roles in face-to-face communication, because they add subtle information that is hard to convey in verbal language.</p><p>Yang etc. consider gestures as non-verbal communication and prove that non-verbal communication also conforms to the principle of entropy rate constancy (ERC). Under this assumption, communication in any form (written or spoken) should optimize the rate of information transmission rate by keeping the overall entropy rate constant.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.12/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Gestures Are Used Rationally: Information Theoretic Evidence from Neural Sequential Models</div><div class="kg-bookmark-description">Yang Xu, Yang Cheng, Riya Bhatia. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.12.jpg" alt=""></div></a></figure><p>This means that the information encoded in hand gestures, albeit subtle, is actually organized in a rational way that enhances the decoding/understanding of information from a receiver’s perspective.</p><p>Artem etc. consider human gestures together with their corresponding utterances. They explore a multimodal approach to learning gesture embeddings through contrastive learning, and attempt to predict psycholinguistic categories and the language of the speaker from their gesture embeddings.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.488/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Towards Understanding the Relation between Gestures and Language</div><div class="kg-bookmark-description">Artem Abzaliev, Andrew Owens, Rada Mihalcea. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.488.jpg" alt=""></div></a></figure><h3 id="text-image-multimodal-but-via-topic-modelling">Text-Image Multimodal, but via Topic Modelling</h3><p>Perhaps the most surprising work to me is from Elaine et al., who present a novel neural multilingual and multimodal topic model that takes advantage of pretrained document and image embeddings to abstract the complexities between languages and modalities. Their work is based on the contextualized topic model, a family of topic models that uses contextualized document embeddings as input.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.355/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Multilingual and Multimodal Topic Modelling with Pretrained Embeddings</div><div class="kg-bookmark-description">Elaine Zosa, Lidia Pivovarova. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.355.jpg" alt=""></div></a></figure><p>It surprises me that after more than 12 years, Latent Dirichlet Allocation (LDA) models still show up in top conferences like COLING. After reading through the paper, I found a lot of adoption has been made over the last few years to make the original LDA more "deep". In fact, it is now called neural topic models (NTMs), which refers to a class of topic models that use neural networks to estimate the parameters of the topic-word and document-topic distributions.</p><h2 id="summary">Summary</h2><p>There has been some great work on multimodal AI presented at COLING this year. It is clear that this is a subject that is only going to continue to grow in importance, as I pointed out in the blog post below.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">The Paradigm Shift Towards Multimodal AI</div><div class="kg-bookmark-description">We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they’re right at the starting line of this paradigm shift, and build the applications of the future today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/7.png" alt=""></div></a></figure><p>Multimodal AI allows machines to better understand the world around them by processing data from multiple modalities (e.g. text, images, audio). This is an important step towards true artificial general intelligence, as it allows machines to more closely approximate the way humans process information.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fcoling2022%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; 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+        </figure><h2 id="multi-task-learning-of-t5-model-with-i3d-features">Multi-Task Learning of T5 Model with I3D Features</h2><p>To solve WildQA, Santiago et al. concatenate the text features with the visual features and input the concatenated features to the T5 model. They extract <a href="https://iashin.ai/video_features/models/i3d/?ref=jina-ai-gmbh.ghost.io">I3D video features</a> and take one feature per second.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-16.png" class="kg-image" alt="" width="2000" height="1107" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-16.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-16.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-16.png 2270w" sizes="(min-width: 720px) 720px"></figure><p>T5 encoder outputs a sequence of the encoded states. Santiago et al. treat the subsequence corresponding to the visual features as the encoded hidden sequence for the video frames. They then multiply the sequence with two vectors to get the maximum likelihood prediction of the start and the end of the evidence, respectively.</p><p>The tasks of visual evidence selection and video question-answering can be jointly trained together by simply combining the two losses in a weighted-manner. </p><p>In the experiment, Santiago et al. propose multiple baselines including: randomly choosing answers from the dev set (i.e. Random); always predicting the most common answer in the dev set (i.e. Common); and retrieving the answers for the dev set question whose embedding has the highest cosine similarity to the test question (i.e. Closest).</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-17.png" class="kg-image" alt="" width="2000" height="701" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-17.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-17.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-17.png 2020w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Performance on video question-answering, measured by ROUGE score (left); and on video evidence selection (right) measured by Intersection-Over-Union. IOU is defined as the length of their intersection divided by the length of their union. The prediction is counted as a match if it overlaps with any of the ground truth spans by more than the threshold. They then use these partial matches to calculate an F1 score (i.e. IOU-F1 scores).</span></figcaption></figure><p>I noticed that introducing video information (T5 T+V) does not improve performance on video question-answering tasks, which confirms what Yang &amp; Silberer said in their work. This may also due to the types of questions in WildQA, which do not match commonsense knowledge. In the video evidence selection task, the T5 model is not even better than the random baseline. Adding multi-task learning does not help. In general, we can conclude WildQA is a pretty challenging task with a significant gap between the state-of-the-art multimodal model and human. </p><h2 id="other-interesting-multimodal-research">Other Interesting Multimodal Research</h2><h3 id="multimodal-social-media">Multimodal Social Media</h3><p>There are multiple research projects focusing on multimodality in the social media. For example, the upswing of text and image sharing on social media platforms during mass emergency situations has led to numerous opportunities to gain timely access to valuable information that can help disaster relief authorities act more quickly and more efficiently.</p><p>Iustin et al. extend the <a href="https://arxiv.org/abs/2001.07685?ref=jina-ai-gmbh.ghost.io">FixMatch algorithm</a> to a multimodal scenario and offer two extensions to the original approach relevant for text and multimodal datasets. They show that multimodal FixMatch can leverage inexpensive unlabeled data to improve performance on diaster classification tasks.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.239/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Multimodal Semi-supervised Learning for Disaster Tweet Classification</div><div class="kg-bookmark-description">Iustin Sirbu, Tiberiu Sosea, Cornelia Caragea, Doina Caragea, Traian Rebedea. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.239.jpg" alt=""></div></a></figure><p>Extracting spatial information from social media and tweets has also received substantial attention recently. Zhaomin et al. propose BERT+VGG16 multimodal model to determine whether people are located in the places they mention in their tweets.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.226/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Are People Located in the Places They Mention in Their Tweets? A Multimodal Approach</div><div class="kg-bookmark-description">Zhaomin Xiao, Eduardo Blanco. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.226.jpg" alt=""></div></a></figure><p>To better understand when the text and image are most beneficial, Zhaomin et al. perform a qualitative analysis of the errors made by the single-stream model, and how these errors are fixed by the dual-stream model. </p><p>Social media is a good place to conduct sentiment analysis. As a popular way to express emotion on social media, stickers &amp; memes in posts can supplement missing sentiments and help identify sentiments precisely. Stickers and memes, despite being represented as images or simple gifs, have very different semantics from real-world photos. Feng et al. point out three challenges when working with stickers/memes:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.591/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Towards Exploiting Sticker for Multimodal Sentiment Analysis in Social Media: A New Dataset and Baseline</div><div class="kg-bookmark-description">Feng Ge, Weizhao Li, Haopeng Ren, Yi Cai. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.591.jpg" alt=""></div></a></figure><ul><li>First, stickers may be inherently multimodal because they are embedded with texts. Same sticker with different sticker texts may vary significantly in sentiment.</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-18.png" class="kg-image" alt="" width="2000" height="1038" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-18.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-18.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-18.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/image-18.png 2400w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Millennial Humor on "Philosoraptor"</span></figcaption></figure><ul><li>Second, stickers are highly varied in style, preventing the models from learning robust representations.</li><li>Third, the way sentiment is fused together from text and stickers is complicated and sometimes inconsistent.</li></ul><p>This work actually reminds me a popular Youtube video explaining Gen Z humor and their meme behaviors:</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-text">Popular = Not Funny<br>Was popular = Funny<br>Ironic = Funny<br>Make no sense = Funny<br>Unfunny = Funny</div></div><p>There's nothing that Gen-Zers like more than changing and hating things. So perhaps our models on sentiment analysis have become obsolete? </p><figure class="kg-card kg-embed-card"><iframe width="200" height="113" src="https://www.youtube.com/embed/oVlspd9hxFA?start=61&amp;feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" title="Why is Gen Z Humor So Weird?"></iframe></figure><h3 id="text-gestures-multimodal">Text-Gestures Multimodal</h3><p>Communication is a multimodal process. Information from verbal and non-verbal modalities are mixed into one channel. It has been revealed from a long history of empirical studies that speakers’ expression in the visual modality, including gestures, body poses, eye contacts and other types of non-verbal behaviors, play critical roles in face-to-face communication, because they add subtle information that is hard to convey in verbal language.</p><p>Yang etc. consider gestures as non-verbal communication and prove that non-verbal communication also conforms to the principle of entropy rate constancy (ERC). Under this assumption, communication in any form (written or spoken) should optimize the rate of information transmission rate by keeping the overall entropy rate constant.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.12/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Gestures Are Used Rationally: Information Theoretic Evidence from Neural Sequential Models</div><div class="kg-bookmark-description">Yang Xu, Yang Cheng, Riya Bhatia. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.12.jpg" alt=""></div></a></figure><p>This means that the information encoded in hand gestures, albeit subtle, is actually organized in a rational way that enhances the decoding/understanding of information from a receiver’s perspective.</p><p>Artem etc. consider human gestures together with their corresponding utterances. They explore a multimodal approach to learning gesture embeddings through contrastive learning, and attempt to predict psycholinguistic categories and the language of the speaker from their gesture embeddings.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.488/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Towards Understanding the Relation between Gestures and Language</div><div class="kg-bookmark-description">Artem Abzaliev, Andrew Owens, Rada Mihalcea. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.488.jpg" alt=""></div></a></figure><h3 id="text-image-multimodal-but-via-topic-modelling">Text-Image Multimodal, but via Topic Modelling</h3><p>Perhaps the most surprising work to me is from Elaine et al., who present a novel neural multilingual and multimodal topic model that takes advantage of pretrained document and image embeddings to abstract the complexities between languages and modalities. Their work is based on the contextualized topic model, a family of topic models that uses contextualized document embeddings as input.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.355/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Multilingual and Multimodal Topic Modelling with Pretrained Embeddings</div><div class="kg-bookmark-description">Elaine Zosa, Lidia Pivovarova. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.355.jpg" alt=""></div></a></figure><p>It surprises me that after more than 12 years, Latent Dirichlet Allocation (LDA) models still show up in top conferences like COLING. After reading through the paper, I found a lot of adoption has been made over the last few years to make the original LDA more "deep". In fact, it is now called neural topic models (NTMs), which refers to a class of topic models that use neural networks to estimate the parameters of the topic-word and document-topic distributions.</p><h2 id="summary">Summary</h2><p>There has been some great work on multimodal AI presented at COLING this year. It is clear that this is a subject that is only going to continue to grow in importance, as I pointed out in the blog post below.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">The Paradigm Shift Towards Multimodal AI</div><div class="kg-bookmark-description">We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they’re right at the starting line of this paradigm shift, and build the applications of the future today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/7.png" alt=""></div></a></figure><p>Multimodal AI allows machines to better understand the world around them by processing data from multiple modalities (e.g. text, images, audio). This is an important step towards true artificial general intelligence, as it allows machines to more closely approximate the way humans process information.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fcoling2022%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-facebook" aria-hidden="true" role="img"> </i></span></button></a><a data-v-ecd25db0="" href="https://reddit.com/submit?url=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fcoling2022%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with Reddit. (opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. All rights reserved.</div></div></div></div><footer class="q-footer q-layout__section--marginal fixed-bottom lock-blur bg-transparent print-hide"><div class="row"><div class="q-btn-group row no-wrap q-btn-group--flat inline col-12 col-md-6 justify-center"><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://discord.jina.ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-discord" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://github.com/jina-ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-github" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://huggingface.co/jinaai" target="_blank" style="font-size: 10px; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>From Confused to Confident: How Rationale Can Help You Make Better Decisions with AI</title><meta charset="utf-8"><meta name="title" content="From Confused to Confident: How Rationale Can Help You Make Better Decisions with AI"><meta name="description" content="Need help making decisions? Rationale is the impartial tool you need. No more endless reading or expensive consultants. Get the information you need without the bias."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/confused-confident-rationale-can-help-make-better-decisions-ai"><meta property="og:title" content="From Confused to Confident: How Rationale Can Help You Make Better Decisions with AI"><meta property="og:description" content="Need help making decisions? Rationale is the impartial tool you need. No more endless reading or expensive consultants. Get the information you need without the bias."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--14-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/confused-confident-rationale-can-help-make-better-decisions-ai"><meta property="twitter:title" content="From Confused to Confident: How Rationale Can Help You Make Better Decisions with AI"><meta property="twitter:description" content="Need help making decisions? Rationale is the impartial tool you need. No more endless reading or expensive consultants. Get the information you need without the bias."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--14-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">From Confused to Confident: How Rationale Can Help You Make Better Decisions with AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Need help making decisions? Rationale is the impartial tool you need. No more endless reading or expensive consultants. Get the information you need without the bias.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 06, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><blockquote class="kg-blockquote-alt">'Twas the night before Christmas, <br>And all through the house, <br>Not a creature was stirring, <br>Not even a mouse.</blockquote><blockquote>Scene: Jina AI's CEO, Han Xiao, sitting in front of a dwindling fireplace, typing feverishly into his laptop. His hair is disheveled and his five o'clock shadow is now looking more like eight o'clock. We zoom in on him to hear him tell his story</blockquote><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image.png" class="kg-image" alt="" width="1536" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image.png 1536w" sizes="(min-width: 720px) 720px"><figcaption>Han Xiao, an (AI) artist’s rendition, Midjourney</figcaption></figure><blockquote>VOICEOVER: HAN</blockquote><p>Indeed, not a mouse was stirring that night. But one was clicking, as I sat at my laptop and worked through the wee hours.</p><p>As I sat in front of the fireplace, the warmth of the flames soothing my tired eyes, I couldn't help but feel a sense of purpose. I had been working tirelessly on a project that I believed could change the world for the better. I was driven by a deep desire to use my skills and expertise to make a positive impact, to help people make more informed, smarter decisions.</p><p>And possibly (just possibly) put those overpriced arrogant bastards at McKinsey out of a job.</p><p>But it wasn't easy. The hours were long and the work was grueling. I had sacrificed time with friends and family, even skipping out on Christmas celebrations, just to see this project through to the end.</p><p>And there were moments of doubt, when I questioned whether it was all worth it. As I sipped on my cold cocoa and watched the fire die, I couldn't help but feel a twinge of sadness. "Bah, humbug," I muttered to myself, feeling the weight of my solitude.</p><p>So, what is this project? I'll give you a hint: I had previously written about how <a href="https://jina.ai/news/seo-is-dead-long-live-llmo?ref=jina-ai-gmbh.ghost.io">LLMO would kill SEO</a>, but I wanted to take large language models further and apply them to more areas of everyday life. <a href="https://openai.com/blog/chatgpt/?ref=jina-ai-gmbh.ghost.io">ChatGPT</a> and generative AI in general have been causing a lot of concern about putting people out of jobs, but I believe we can use this technology to help people instead. That's why I'm launching <a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io">Rationale</a>, a product that I hope will make a difference in the world.</p><h2 id="what-problem-does-rationale-solve">What problem does Rationale solve?</h2><p>Making decisions is tough.</p><iframe width="560" height="315" src="https://www.youtube.com/embed/cvLIUMcCs6s?controls=0&amp;start=20&amp;end=40 title=" youtube="" video="" player"="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe><p>We're drowning in information that we have to take action on. And then, on top of that, we need to find <em>more</em> information to work out exactly which actions to take.</p><p>And that second level of information? Search engines return pages and pages of bullshit sites that disagree with each other, and some questions just aren't easy to research. For example:</p><blockquote class="kg-blockquote-alt">As the CEO of a 2 year old startup with 50 employees and series A funding, should I give my employees a raise during these difficult financial times?</blockquote><p>Good luck getting something that even matches enough search terms, let alone provides guidance.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-18.png" class="kg-image" alt="" width="797" height="665" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-18.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-18.png 797w" sizes="(min-width: 720px) 720px"><figcaption>Crap. Complete and utter crap. Imagine doing this for every important decision you have to make!</figcaption></figure><p>There needs to be an impartial tool to help you make decisions that returns <em>just the information you need</em>. Rationale does that. You don't need to read through countless articles or fork money over to expensive consultants who'll recommend doing what you were going to do anyway. </p><p>While Rationale won't tell you <em>what</em> to do, it will give pros and cons or a <a href="https://en.wikipedia.org/wiki/SWOT_analysis?ref=jina-ai-gmbh.ghost.io">SWOT analysis</a> about your potential course of action. Simple as that. No endless googling. No frills. No bullshit.</p><h2 id="so-what-is-rationale">So what <em>is</em> Rationale?</h2><p>In short, Rationale is a tool for making better decisions. But to better understand how it works, let's use some familiar examples.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-1.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-1.png 1440w" sizes="(min-width: 720px) 720px"><figcaption>Left to right: Morty, Two-Face, The Ghost of Christmas Yet to Come</figcaption></figure><ul><li>Rationale is <em>kind of like</em> the coin flipped by <a href="https://batman.fandom.com/wiki/Two-Face?ref=jina-ai-gmbh.ghost.io">Two-Face</a> in Batman (or Donald Duck in Flip Decision). The coin tells the flipper what to do next.</li><li>Rationale is <em>kind of like</em> the <a href="https://rickandmorty.fandom.com/wiki/Death_Crystal?ref=jina-ai-gmbh.ghost.io">death crystal</a> in Rick and Morty. When Morty strapped it to his head, he could see different futures based on every potential course of action.</li><li>Rationale is <em>kind of like</em> the <a href="https://en.wikipedia.org/wiki/Ghost_of_Christmas_Yet_to_Come?ref=jina-ai-gmbh.ghost.io">Ghost of Christmas Yet to Come</a> in A Christmas Carol. Ebenezer Scrooge led a mean, cruel, penny-pinching life. It took that ghost to show him where he would end up if he continued down that path, with his "friends" celebrating around his grave, and the death of Tiny Tim. Only by seeing the negative potential future could he change his fate.</li></ul><p>So, Rationale is <em>kind of</em> like the coin, crystal, or ghost, but with a brain (or rather, a large language model and handcrafted prompt). Instead of giving you a simple "yes" or "no" or predicting the future, Rationale allows you to input a decision and then shows you the pros and cons (or other analyses - see below!) of that decision based on your user profile. It's primarily aimed at businesses, but can be used for all kinds of "should I..." decisions.</p><p>We're not only building Rationale, but putting our money where our mouth is by using it internally to help make decisions and plan the future of Jina AI. We believe in its effectiveness and are confident it can make a difference for other businesses as well.</p><h2 id="does-it-really-work">Does it really work?</h2><p>It's important to remember that no system, human or machine, is perfect. But Rationale has a track record of providing logical answers more often than not, especially for real-world business decisions:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.00332 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-2.png" width="604" height="602" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-2.png 604w"></div><div class="kg-gallery-image" style="flex: 1.05061 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-4.png" width="602" height="573" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-4.png 602w"></div><div class="kg-gallery-image" style="flex: 0.96769 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-07-11-44-49.png" width="599" height="619" alt=""></div></div></div></figure><p>It also works for more, <em>ahem</em>, unconventional decisions:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.988468 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-21.png" width="600" height="607" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-21.png 600w"></div><div class="kg-gallery-image" style="flex: 1.01695 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-23.png" width="600" height="590" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-23.png 600w"></div><div class="kg-gallery-image" style="flex: 1.10313 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-22.png" width="599" height="543" alt=""></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/02/rationale-proscons.mp4" poster="https://img.spacergif.org/v1/2314x1556/0a/spacer.png" width="2314" height="1556" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/02/media-thumbnail-ember929.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="going-beyond-pros-and-cons">Going beyond pro's and cons</h2><p>Rationale doesn't just help by giving advantages and disadvantages. It has a bunch of other modes and functionalities to help you make better decisions.</p><h3 id="outcome-analysis-mode">Outcome analysis mode</h3><p>What if you tell your boss you quit? And then what are knock-on effects of that? And then the knock-on effects of <em>that</em>?</p><p>Outcome analysis mode lets you look into your potential multiverse. Like a crystal ball of fracturing timelines, it presents a peek at your potential futures and shows which outcomes are positive, negative, or neutral.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.520305 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/2xokr.png" width="615" height="1182" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/2xokr.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/2xokr.png 615w"></div><div class="kg-gallery-image" style="flex: 0.578704 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/expand_team.png" width="625" height="1080" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/expand_team.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/expand_team.png 625w"></div><div class="kg-gallery-image" style="flex: 0.640657 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/ragequit.png" width="624" height="974" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/ragequit.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/ragequit.png 624w"></div></div></div></figure><p></p><h3 id="swot-mode">SWOT mode</h3><p>A strengths, weaknesses, opportunities and threats analysis is a very common tool in business for making decisions on projects or the organization. It's often used in business and strategic planning, marketing and branding strategy, and problem-solving and decision-making.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.650106 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/pyongyang.png" width="615" height="946" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/pyongyang.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/pyongyang.png 615w"></div><div class="kg-gallery-image" style="flex: 0.595353 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/poach.png" width="615" height="1033" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/poach.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/poach.png 615w"></div><div class="kg-gallery-image" style="flex: 0.548791 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/llm-1.png" width="613" height="1117" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/llm-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/llm-1.png 613w"></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/02/rationale-swot.mp4" poster="https://img.spacergif.org/v1/2314x1556/0a/spacer.png" width="2314" height="1556" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/02/media-thumbnail-ember917.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h3 id="multi-choice-mode">Multi-choice mode</h3><p>Which company department to expand? Which cost savings to make? Heck, what to eat for lunch?</p><p>Some decisions aren't just yes/no or pro/con. That's where multi-choice comes in. Type in your choices and you'll get a report offering suggestions from different perspectives.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.70289 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-48-50.png" width="608" height="865" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-from-2023-01-31-11-48-50.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-48-50.png 608w"></div><div class="kg-gallery-image" style="flex: 0.748775 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-46-30.png" width="611" height="816" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-from-2023-01-31-11-46-30.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-46-30.png 611w"></div><div class="kg-gallery-image" style="flex: 0.695652 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-52-36-1.png" width="608" height="874" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-from-2023-01-31-11-52-36-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-52-36-1.png 608w"></div></div></div></figure><h3></h3><h3 id="custom-profiles">Custom profiles</h3><p>Let's make things personal. Now you can create custom profiles to reflect the real you and better guide your decisions. Want to be a kick-butt boss who takes no prisoners, but also really work on your spiritual wellness? Or maybe just desperately lose a few pounds? The profiles feature has got you covered!</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 2.91866 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-12-00-25.png" width="610" height="209" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-from-2023-01-31-12-00-25.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-12-00-25.png 610w"></div><div class="kg-gallery-image" style="flex: 2.91866 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-57-28-1.png" width="610" height="209" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-from-2023-01-31-11-57-28-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-57-28-1.png 610w"></div><div class="kg-gallery-image" style="flex: 2.91866 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-56-06.png" width="610" height="209" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-from-2023-01-31-11-56-06.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-56-06.png 610w"></div></div></div></figure><h2 id="cant-i-just-use-chatgpt-for-this">Can't I just use ChatGPT for this?</h2><p>While prompt engineering may be the future (or at least <em>a</em> future) of programming, it's not always as straightforward as it sounds. It can take hours of work and collaboration to create a prompt that provides MVP quality results. Even then, getting ChatGPT to remain focused instead of wandering off-prompt can be a headache.</p><p>Alternatively, you could just ask Rationale for a clear and logical answer to your decision-making needs. It's a simpler and more efficient solution:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-10.png" class="kg-image" alt="" width="605" height="594" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-10.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-10.png 605w"></figure><h2 id="eating-our-own-dog-food-using-rationale-at-jina-ai">Eating our own dog food: Using Rationale at Jina AI</h2><p>At Jina AI, we're all about staying on top of our game. That's why we're making it a priority for every team member to become a pro at using Rationale as a hard skill, especially our leaders and senior managers. By putting it to the test in the real world, we can keep making it better and better. It's like our super power for decision-making and strategy.</p><p>How often will we be using it? Well, let's just ask Rationale:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.972669 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-12.png" width="605" height="622" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-12.png 605w"></div><div class="kg-gallery-image" style="flex: 1.04131 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-11.png" width="605" height="581" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-11.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-11.png 605w"></div><div class="kg-gallery-image" style="flex: 1.04506 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-20.png" width="603" height="577" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-20.png 603w"></div></div></div></figure><h2 id="faq">FAQ</h2><h3 id="why-is-it-called-rationale">Why is it called Rationale?</h3><p>Because we didn't think anyone would want to use a product called Death Crystal.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-14.png" class="kg-image" alt="" width="602" height="615" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-14.png 602w"></figure><h3 id="should-i-really-follow-everything-it-says">Should I really follow everything it says?</h3><p>Good question! Here's what Rationale has to say about that:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-15.png" class="kg-image" alt="" width="602" height="634" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-15.png 602w"></figure><h3 id="does-it-always-have-such-a-serious-tone-can-it-cite-sources">Does it always have such a serious tone? Can it cite sources?</h3><p>You can customize the tone of Rationale to fit your style. We offer several presets, including "professional" (which cites sources where possible), "gen Z," "sarcastic," and more. The default tone is "concise," which provides short, straightforward answers for quick decision-making.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-17.png" class="kg-image" alt="" width="880" height="375" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-17.png 880w" sizes="(min-width: 720px) 720px"></figure><h3 id="what-kind-of-ai-algorithms-can-be-used-for-decision-making">What kind of AI algorithms can be used for decision-making?</h3><p>There are several AI algorithms that can be used for decision-making, including machine learning algorithms, deep neural networks, expert systems, decision trees, and rule-based systems. The right choice of algorithm depends on the specific requirements of the task and the characteristics of the data being analyzed. Each approach has its own strengths and limitations, so it's important to carefully consider which one is most suitable for the given problem.</p><h3 id="how-does-rationale-use-cutting-edge-technology-to-provide-top-notch-analysis">How does Rationale use cutting-edge technology to provide top-notch analysis?</h3><p>Rationale is all about making great decisions, and to do that, we use the best technology around. That's why we've built Rationale on top of GPT, a state-of-the-art language model. With GPT under the hood, Rationale is able to analyze and understand written or spoken language with ease.</p><p>But we don't stop there. To really fine-tune our analysis, we use in-context learning to train the model on specific types of data or tasks. And to top it all off, we've developed a unique approach to generating analysis in multiple languages, which allows us to offer a wide range of language processing services. All this adds up to one thing: top-notch analysis that you can trust to help you make informed decisions.</p><h3 id="how-can-gpt-and-large-language-models-make-decision-making-a-breeze">How can GPT and large language models make decision-making a breeze?</h3><p>GPT (or large language models in general) are like super computers for natural language processing. They're able to analyze and understand written or spoken language, thanks to some fancy machine learning techniques (namely, deep learning). Basically, we feed them a ton of text and they learn all about the statistical patterns and relationships within that data. Then, when it's time to make a decision, we can use the model to analyze and understand new text data and make predictions based on what it's learned. So whether you're trying to decide on the best course of action for your business or just trying to choose what to have for dinner, GPT and large language models can help make the process a whole lot easier.</p><h3 id="how-does-in-context-learning-help">How does in-context learning help?</h3><p>In-context learning involves further refining the model's abilities by training it on specific types of data or tasks. For example, if you want to use Rationale to analyze marketing data, you could train the model on a dataset of marketing texts to improve its performance on that specific task.</p><p>By using both GPT and in-context learning, Rationale is able to generate analysis that is accurate, coherent, and tailored to the needs of the user. The unique approach to generating analysis in multiple languages further enhances its capabilities, allowing it to provide a wide range of language processing services.</p><h2 id="use-rationale-for-yourself">Use Rationale for yourself</h2><p>You can sign up for a beta account today at <strong><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io">rationale.jina.ai</a></strong> and get 20 free decisions. After that, we have several affordable plans to choose from. So in 2023, you won't have to risk the Ghost of Christmas Future showing you your terrible mistakes. With Rationale, you can make the right decisions ahead of time and let him have a night off. Try it out and see how it can help you make better, more informed choices.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-16.png" class="kg-image" alt="" width="602" height="561" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-16.png 602w"></figure><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Sign up for Rationale</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fconfused-confident-rationale-can-help-make-better-decisions-ai%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="4b01b9fd-71d6-4187-825e-3d3595f58ec9" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="4b01b9fd-71d6-4187-825e-3d3595f58ec9" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">From Confused to Confident: How Rationale Can Help You Make Better Decisions with AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Need help making decisions? Rationale is the impartial tool you need. No more endless reading or expensive consultants. Get the information you need without the bias.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 06, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><blockquote class="kg-blockquote-alt">'Twas the night before Christmas, <br>And all through the house, <br>Not a creature was stirring, <br>Not even a mouse.</blockquote><blockquote>Scene: Jina AI's CEO, Han Xiao, sitting in front of a dwindling fireplace, typing feverishly into his laptop. His hair is disheveled and his five o'clock shadow is now looking more like eight o'clock. We zoom in on him to hear him tell his story</blockquote><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image.png" class="kg-image" alt="" width="1536" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image.png 1536w" sizes="(min-width: 720px) 720px"><figcaption>Han Xiao, an (AI) artist’s rendition, Midjourney</figcaption></figure><blockquote>VOICEOVER: HAN</blockquote><p>Indeed, not a mouse was stirring that night. But one was clicking, as I sat at my laptop and worked through the wee hours.</p><p>As I sat in front of the fireplace, the warmth of the flames soothing my tired eyes, I couldn't help but feel a sense of purpose. I had been working tirelessly on a project that I believed could change the world for the better. I was driven by a deep desire to use my skills and expertise to make a positive impact, to help people make more informed, smarter decisions.</p><p>And possibly (just possibly) put those overpriced arrogant bastards at McKinsey out of a job.</p><p>But it wasn't easy. The hours were long and the work was grueling. I had sacrificed time with friends and family, even skipping out on Christmas celebrations, just to see this project through to the end.</p><p>And there were moments of doubt, when I questioned whether it was all worth it. As I sipped on my cold cocoa and watched the fire die, I couldn't help but feel a twinge of sadness. "Bah, humbug," I muttered to myself, feeling the weight of my solitude.</p><p>So, what is this project? I'll give you a hint: I had previously written about how <a href="https://jina.ai/news/seo-is-dead-long-live-llmo?ref=jina-ai-gmbh.ghost.io">LLMO would kill SEO</a>, but I wanted to take large language models further and apply them to more areas of everyday life. <a href="https://openai.com/blog/chatgpt/?ref=jina-ai-gmbh.ghost.io">ChatGPT</a> and generative AI in general have been causing a lot of concern about putting people out of jobs, but I believe we can use this technology to help people instead. That's why I'm launching <a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io">Rationale</a>, a product that I hope will make a difference in the world.</p><h2 id="what-problem-does-rationale-solve">What problem does Rationale solve?</h2><p>Making decisions is tough.</p><iframe width="560" height="315" src="https://www.youtube.com/embed/cvLIUMcCs6s?controls=0&amp;start=20&amp;end=40 title=" youtube="" video="" player"="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen=""></iframe><p>We're drowning in information that we have to take action on. And then, on top of that, we need to find <em>more</em> information to work out exactly which actions to take.</p><p>And that second level of information? Search engines return pages and pages of bullshit sites that disagree with each other, and some questions just aren't easy to research. For example:</p><blockquote class="kg-blockquote-alt">As the CEO of a 2 year old startup with 50 employees and series A funding, should I give my employees a raise during these difficult financial times?</blockquote><p>Good luck getting something that even matches enough search terms, let alone provides guidance.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-18.png" class="kg-image" alt="" width="797" height="665" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-18.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-18.png 797w" sizes="(min-width: 720px) 720px"><figcaption>Crap. Complete and utter crap. Imagine doing this for every important decision you have to make!</figcaption></figure><p>There needs to be an impartial tool to help you make decisions that returns <em>just the information you need</em>. Rationale does that. You don't need to read through countless articles or fork money over to expensive consultants who'll recommend doing what you were going to do anyway. </p><p>While Rationale won't tell you <em>what</em> to do, it will give pros and cons or a <a href="https://en.wikipedia.org/wiki/SWOT_analysis?ref=jina-ai-gmbh.ghost.io">SWOT analysis</a> about your potential course of action. Simple as that. No endless googling. No frills. No bullshit.</p><h2 id="so-what-is-rationale">So what <em>is</em> Rationale?</h2><p>In short, Rationale is a tool for making better decisions. But to better understand how it works, let's use some familiar examples.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-1.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-1.png 1440w" sizes="(min-width: 720px) 720px"><figcaption>Left to right: Morty, Two-Face, The Ghost of Christmas Yet to Come</figcaption></figure><ul><li>Rationale is <em>kind of like</em> the coin flipped by <a href="https://batman.fandom.com/wiki/Two-Face?ref=jina-ai-gmbh.ghost.io">Two-Face</a> in Batman (or Donald Duck in Flip Decision). The coin tells the flipper what to do next.</li><li>Rationale is <em>kind of like</em> the <a href="https://rickandmorty.fandom.com/wiki/Death_Crystal?ref=jina-ai-gmbh.ghost.io">death crystal</a> in Rick and Morty. When Morty strapped it to his head, he could see different futures based on every potential course of action.</li><li>Rationale is <em>kind of like</em> the <a href="https://en.wikipedia.org/wiki/Ghost_of_Christmas_Yet_to_Come?ref=jina-ai-gmbh.ghost.io">Ghost of Christmas Yet to Come</a> in A Christmas Carol. Ebenezer Scrooge led a mean, cruel, penny-pinching life. It took that ghost to show him where he would end up if he continued down that path, with his "friends" celebrating around his grave, and the death of Tiny Tim. Only by seeing the negative potential future could he change his fate.</li></ul><p>So, Rationale is <em>kind of</em> like the coin, crystal, or ghost, but with a brain (or rather, a large language model and handcrafted prompt). Instead of giving you a simple "yes" or "no" or predicting the future, Rationale allows you to input a decision and then shows you the pros and cons (or other analyses - see below!) of that decision based on your user profile. It's primarily aimed at businesses, but can be used for all kinds of "should I..." decisions.</p><p>We're not only building Rationale, but putting our money where our mouth is by using it internally to help make decisions and plan the future of Jina AI. We believe in its effectiveness and are confident it can make a difference for other businesses as well.</p><h2 id="does-it-really-work">Does it really work?</h2><p>It's important to remember that no system, human or machine, is perfect. But Rationale has a track record of providing logical answers more often than not, especially for real-world business decisions:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.00332 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-2.png" width="604" height="602" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-2.png 604w"></div><div class="kg-gallery-image" style="flex: 1.05061 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-4.png" width="602" height="573" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-4.png 602w"></div><div class="kg-gallery-image" style="flex: 0.96769 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-07-11-44-49.png" width="599" height="619" alt=""></div></div></div></figure><p>It also works for more, <em>ahem</em>, unconventional decisions:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.988468 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-21.png" width="600" height="607" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-21.png 600w"></div><div class="kg-gallery-image" style="flex: 1.01695 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-23.png" width="600" height="590" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-23.png 600w"></div><div class="kg-gallery-image" style="flex: 1.10313 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-22.png" width="599" height="543" alt=""></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/02/rationale-proscons.mp4" poster="https://img.spacergif.org/v1/2314x1556/0a/spacer.png" width="2314" height="1556" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/02/media-thumbnail-ember929.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="going-beyond-pros-and-cons">Going beyond pro's and cons</h2><p>Rationale doesn't just help by giving advantages and disadvantages. It has a bunch of other modes and functionalities to help you make better decisions.</p><h3 id="outcome-analysis-mode">Outcome analysis mode</h3><p>What if you tell your boss you quit? And then what are knock-on effects of that? And then the knock-on effects of <em>that</em>?</p><p>Outcome analysis mode lets you look into your potential multiverse. Like a crystal ball of fracturing timelines, it presents a peek at your potential futures and shows which outcomes are positive, negative, or neutral.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.520305 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/2xokr.png" width="615" height="1182" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/2xokr.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/2xokr.png 615w"></div><div class="kg-gallery-image" style="flex: 0.578704 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/expand_team.png" width="625" height="1080" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/expand_team.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/expand_team.png 625w"></div><div class="kg-gallery-image" style="flex: 0.640657 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/ragequit.png" width="624" height="974" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/ragequit.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/ragequit.png 624w"></div></div></div></figure><p></p><h3 id="swot-mode">SWOT mode</h3><p>A strengths, weaknesses, opportunities and threats analysis is a very common tool in business for making decisions on projects or the organization. It's often used in business and strategic planning, marketing and branding strategy, and problem-solving and decision-making.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.650106 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/pyongyang.png" width="615" height="946" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/pyongyang.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/pyongyang.png 615w"></div><div class="kg-gallery-image" style="flex: 0.595353 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/poach.png" width="615" height="1033" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/poach.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/poach.png 615w"></div><div class="kg-gallery-image" style="flex: 0.548791 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/llm-1.png" width="613" height="1117" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/llm-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/llm-1.png 613w"></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/02/rationale-swot.mp4" poster="https://img.spacergif.org/v1/2314x1556/0a/spacer.png" width="2314" height="1556" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/02/media-thumbnail-ember917.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h3 id="multi-choice-mode">Multi-choice mode</h3><p>Which company department to expand? Which cost savings to make? Heck, what to eat for lunch?</p><p>Some decisions aren't just yes/no or pro/con. That's where multi-choice comes in. Type in your choices and you'll get a report offering suggestions from different perspectives.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.70289 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-48-50.png" width="608" height="865" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-from-2023-01-31-11-48-50.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-48-50.png 608w"></div><div class="kg-gallery-image" style="flex: 0.748775 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-46-30.png" width="611" height="816" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-from-2023-01-31-11-46-30.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-46-30.png 611w"></div><div class="kg-gallery-image" style="flex: 0.695652 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-52-36-1.png" width="608" height="874" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-from-2023-01-31-11-52-36-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-52-36-1.png 608w"></div></div></div></figure><h3></h3><h3 id="custom-profiles">Custom profiles</h3><p>Let's make things personal. Now you can create custom profiles to reflect the real you and better guide your decisions. Want to be a kick-butt boss who takes no prisoners, but also really work on your spiritual wellness? Or maybe just desperately lose a few pounds? The profiles feature has got you covered!</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 2.91866 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-12-00-25.png" width="610" height="209" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-from-2023-01-31-12-00-25.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-12-00-25.png 610w"></div><div class="kg-gallery-image" style="flex: 2.91866 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-57-28-1.png" width="610" height="209" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-from-2023-01-31-11-57-28-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-57-28-1.png 610w"></div><div class="kg-gallery-image" style="flex: 2.91866 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-56-06.png" width="610" height="209" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-from-2023-01-31-11-56-06.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-from-2023-01-31-11-56-06.png 610w"></div></div></div></figure><h2 id="cant-i-just-use-chatgpt-for-this">Can't I just use ChatGPT for this?</h2><p>While prompt engineering may be the future (or at least <em>a</em> future) of programming, it's not always as straightforward as it sounds. It can take hours of work and collaboration to create a prompt that provides MVP quality results. Even then, getting ChatGPT to remain focused instead of wandering off-prompt can be a headache.</p><p>Alternatively, you could just ask Rationale for a clear and logical answer to your decision-making needs. It's a simpler and more efficient solution:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-10.png" class="kg-image" alt="" width="605" height="594" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-10.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-10.png 605w"></figure><h2 id="eating-our-own-dog-food-using-rationale-at-jina-ai">Eating our own dog food: Using Rationale at Jina AI</h2><p>At Jina AI, we're all about staying on top of our game. That's why we're making it a priority for every team member to become a pro at using Rationale as a hard skill, especially our leaders and senior managers. By putting it to the test in the real world, we can keep making it better and better. It's like our super power for decision-making and strategy.</p><p>How often will we be using it? Well, let's just ask Rationale:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.972669 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-12.png" width="605" height="622" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-12.png 605w"></div><div class="kg-gallery-image" style="flex: 1.04131 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-11.png" width="605" height="581" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-11.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-11.png 605w"></div><div class="kg-gallery-image" style="flex: 1.04506 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-20.png" width="603" height="577" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-20.png 603w"></div></div></div></figure><h2 id="faq">FAQ</h2><h3 id="why-is-it-called-rationale">Why is it called Rationale?</h3><p>Because we didn't think anyone would want to use a product called Death Crystal.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-14.png" class="kg-image" alt="" width="602" height="615" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-14.png 602w"></figure><h3 id="should-i-really-follow-everything-it-says">Should I really follow everything it says?</h3><p>Good question! Here's what Rationale has to say about that:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-15.png" class="kg-image" alt="" width="602" height="634" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-15.png 602w"></figure><h3 id="does-it-always-have-such-a-serious-tone-can-it-cite-sources">Does it always have such a serious tone? Can it cite sources?</h3><p>You can customize the tone of Rationale to fit your style. We offer several presets, including "professional" (which cites sources where possible), "gen Z," "sarcastic," and more. The default tone is "concise," which provides short, straightforward answers for quick decision-making.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-17.png" class="kg-image" alt="" width="880" height="375" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-17.png 880w" sizes="(min-width: 720px) 720px"></figure><h3 id="what-kind-of-ai-algorithms-can-be-used-for-decision-making">What kind of AI algorithms can be used for decision-making?</h3><p>There are several AI algorithms that can be used for decision-making, including machine learning algorithms, deep neural networks, expert systems, decision trees, and rule-based systems. The right choice of algorithm depends on the specific requirements of the task and the characteristics of the data being analyzed. Each approach has its own strengths and limitations, so it's important to carefully consider which one is most suitable for the given problem.</p><h3 id="how-does-rationale-use-cutting-edge-technology-to-provide-top-notch-analysis">How does Rationale use cutting-edge technology to provide top-notch analysis?</h3><p>Rationale is all about making great decisions, and to do that, we use the best technology around. That's why we've built Rationale on top of GPT, a state-of-the-art language model. With GPT under the hood, Rationale is able to analyze and understand written or spoken language with ease.</p><p>But we don't stop there. To really fine-tune our analysis, we use in-context learning to train the model on specific types of data or tasks. And to top it all off, we've developed a unique approach to generating analysis in multiple languages, which allows us to offer a wide range of language processing services. All this adds up to one thing: top-notch analysis that you can trust to help you make informed decisions.</p><h3 id="how-can-gpt-and-large-language-models-make-decision-making-a-breeze">How can GPT and large language models make decision-making a breeze?</h3><p>GPT (or large language models in general) are like super computers for natural language processing. They're able to analyze and understand written or spoken language, thanks to some fancy machine learning techniques (namely, deep learning). Basically, we feed them a ton of text and they learn all about the statistical patterns and relationships within that data. Then, when it's time to make a decision, we can use the model to analyze and understand new text data and make predictions based on what it's learned. So whether you're trying to decide on the best course of action for your business or just trying to choose what to have for dinner, GPT and large language models can help make the process a whole lot easier.</p><h3 id="how-does-in-context-learning-help">How does in-context learning help?</h3><p>In-context learning involves further refining the model's abilities by training it on specific types of data or tasks. For example, if you want to use Rationale to analyze marketing data, you could train the model on a dataset of marketing texts to improve its performance on that specific task.</p><p>By using both GPT and in-context learning, Rationale is able to generate analysis that is accurate, coherent, and tailored to the needs of the user. The unique approach to generating analysis in multiple languages further enhances its capabilities, allowing it to provide a wide range of language processing services.</p><h2 id="use-rationale-for-yourself">Use Rationale for yourself</h2><p>You can sign up for a beta account today at <strong><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io">rationale.jina.ai</a></strong> and get 20 free decisions. After that, we have several affordable plans to choose from. So in 2023, you won't have to risk the Ghost of Christmas Future showing you your terrible mistakes. With Rationale, you can make the right decisions ahead of time and let him have a night off. Try it out and see how it can help you make better, more informed choices.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-16.png" class="kg-image" alt="" width="602" height="561" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-16.png 602w"></figure><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Sign up for Rationale</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fconfused-confident-rationale-can-help-make-better-decisions-ai%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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\ No newline at end of file
diff --git a/news/cross-modal-search-with-imagebind-and-docarray/index.html b/news/cross-modal-search-with-imagebind-and-docarray/index.html
index 1735ce86aed..901ed8e6176 100644
--- a/news/cross-modal-search-with-imagebind-and-docarray/index.html
+++ b/news/cross-modal-search-with-imagebind-and-docarray/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Cross-modal search with ImageBind and DocArray</title><meta charset="utf-8"><meta name="title" content="Cross-modal search with ImageBind and DocArray"><meta name="description" content="Combine ImageBind with DocArray to implement a cross-modal search system"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/cross-modal-search-with-imagebind-and-docarray"><meta property="og:title" content="Cross-modal search with ImageBind and DocArray"><meta property="og:description" content="Combine ImageBind with DocArray to implement a cross-modal search system"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/banner-Cross-modal-search-with-ImageBind-and-DocArray--1-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/cross-modal-search-with-imagebind-and-docarray"><meta property="twitter:title" content="Cross-modal search with ImageBind and DocArray"><meta property="twitter:description" content="Combine ImageBind with DocArray to implement a cross-modal search system"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/banner-Cross-modal-search-with-ImageBind-and-DocArray--1-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Cross-modal search with ImageBind and DocArray</title><meta charset="utf-8"><meta name="title" content="Cross-modal search with ImageBind and DocArray"><meta name="description" content="Combine ImageBind with DocArray to implement a cross-modal search system"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/cross-modal-search-with-imagebind-and-docarray"><meta property="og:title" content="Cross-modal search with ImageBind and DocArray"><meta property="og:description" content="Combine ImageBind with DocArray to implement a cross-modal search system"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/banner-Cross-modal-search-with-ImageBind-and-DocArray--1-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/cross-modal-search-with-imagebind-and-docarray"><meta property="twitter:title" content="Cross-modal search with ImageBind and DocArray"><meta property="twitter:description" content="Combine ImageBind with DocArray to implement a cross-modal search system"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/banner-Cross-modal-search-with-ImageBind-and-DocArray--1-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
       uc.reloadOnOptIn('BJz7qNsdj-7'); // reload page on YouTube opt-in</script><style prerender-ignore>.uc-embedding-container {
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Cross-modal search with ImageBind and DocArray</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Combine ImageBind with DocArray to implement a cross-modal search system</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alaeddine Abdessalem</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 22, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><hr><h2 id="background">Background</h2><p>Meta recently released yet another open-source model, after a series of cool models like LLaMA and SAM.</p><p>This time they embrace further multimodal AI with a focus on embeddings with the new <a href="https://ai.facebook.com/blog/imagebind-six-modalities-binding-ai/?ref=jina-ai-gmbh.ghost.io">ImageBind</a> Model.</p><p>We gave it a try and in this blog post, we will show how you can use this cool model along with DocArray to implement a cross-modal search system!</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/multimodal-1.png" class="kg-image" alt="" width="1384" height="786" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/multimodal-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/multimodal-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/multimodal-1.png 1384w" sizes="(min-width: 720px) 720px"></figure><h2 id="imagebind">ImageBind</h2><p><a href="https://ai.facebook.com/blog/imagebind-six-modalities-binding-ai/?ref=jina-ai-gmbh.ghost.io">ImageBind</a> is a new embedding model from Meta that is capable of learning a joint embedding across six different modalities - images, text, audio, depth, thermal, and IMU data (inertial measurement units, which track motion and position).</p><p>The true power of ImageBind lies in its ability to surpass specialist models that are trained for one specific modality, demonstrating its capability to analyze a multitude of data forms in unison. This holistic approach enables ImageBind to relate objects in an image to their corresponding sounds, 3D shapes, temperatures, and motion patterns, mirroring our human ability to process a complex blend of sensory information.</p><p>Moreover, ImageBind demonstrates that it's feasible to create a shared embedding space across multiple modalities without the need for training on data encompassing every possible combination of these modalities. This is a crucial development given the impracticality of creating datasets that include every potential combination of modalities.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Untitled.png" class="kg-image" alt="" width="1920" height="1080" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/Untitled.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/Untitled.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/05/Untitled.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/Untitled.png 1920w" sizes="(min-width: 720px) 720px"><figcaption>Source: <a href="https://ai.facebook.com/blog/imagebind-six-modalities-binding-ai/?ref=jina-ai-gmbh.ghost.io">https://ai.facebook.com/blog/imagebind-six-modalities-binding-ai/</a></figcaption></figure><p>Representing different modalities in the same embedding space allows for several use cases, like cross-modal generation, embedding-space generation, or cross-modal retrieval. In this blog, we’re interested in the latter use case and we’ll implement it using DocArray.</p><h2 id="docarray">DocArray</h2><p><a href="https://docs.docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray</a> is a library for <strong>representing, sending, and storing multi-modal data</strong>, perfect for <strong>Machine Learning applications</strong>.</p><p>With DocArray you can:</p><ol><li><strong><a href="https://docs.docarray.org/?ref=jina-ai-gmbh.ghost.io#represent">Represent data</a></strong></li><li><strong><a href="https://docs.docarray.org/?ref=jina-ai-gmbh.ghost.io#send">Send data</a></strong></li><li><strong><a href="https://docs.docarray.org/?ref=jina-ai-gmbh.ghost.io#store">Store data</a></strong></li></ol><p>DocArray is also optimized for neural search and supports searching by vector either in-memory or using a variety of vector databases, notably Weaviate, Qdrant, and ElasticSearch.</p><p>As we observed more multimodal AI models, we reshaped DocArray to become more suitable for multimodal AI use cases: multimodal AI search and generation.</p><p>Since <a href="https://jina.ai/news/docarray-v2-update/?ref=jina-ai-gmbh.ghost.io">the new release (v0.30.0)</a>, you can enjoy flexible schemas, more multimodal datatypes, and native support for multimodal neural search.</p><p>Let’s see it in action with ImageBind!</p><h2 id="cross-modal-search-with-docarray">Cross-modal search with DocArray</h2><p>First, we need to install DocArray:</p><pre><code class="language-bash hljs">pip install docarray
-</code></pre><p>Next, we need to install ImageBind. We can do so by cloning the repository:</p><pre><code class="language-bash hljs">git <span class="hljs-built_in">clone</span> https://github.com/facebookresearch/ImageBind
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Cross-modal search with ImageBind and DocArray</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Combine ImageBind with DocArray to implement a cross-modal search system</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alaeddine Abdessalem</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 22, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><hr><h2 id="background">Background</h2><p>Meta recently released yet another open-source model, after a series of cool models like LLaMA and SAM.</p><p>This time they embrace further multimodal AI with a focus on embeddings with the new <a href="https://ai.facebook.com/blog/imagebind-six-modalities-binding-ai/?ref=jina-ai-gmbh.ghost.io">ImageBind</a> Model.</p><p>We gave it a try and in this blog post, we will show how you can use this cool model along with DocArray to implement a cross-modal search system!</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/multimodal-1.png" class="kg-image" alt="" width="1384" height="786" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/multimodal-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/multimodal-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/multimodal-1.png 1384w" sizes="(min-width: 720px) 720px"></figure><h2 id="imagebind">ImageBind</h2><p><a href="https://ai.facebook.com/blog/imagebind-six-modalities-binding-ai/?ref=jina-ai-gmbh.ghost.io">ImageBind</a> is a new embedding model from Meta that is capable of learning a joint embedding across six different modalities - images, text, audio, depth, thermal, and IMU data (inertial measurement units, which track motion and position).</p><p>The true power of ImageBind lies in its ability to surpass specialist models that are trained for one specific modality, demonstrating its capability to analyze a multitude of data forms in unison. This holistic approach enables ImageBind to relate objects in an image to their corresponding sounds, 3D shapes, temperatures, and motion patterns, mirroring our human ability to process a complex blend of sensory information.</p><p>Moreover, ImageBind demonstrates that it's feasible to create a shared embedding space across multiple modalities without the need for training on data encompassing every possible combination of these modalities. This is a crucial development given the impracticality of creating datasets that include every potential combination of modalities.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Untitled.png" class="kg-image" alt="" width="1920" height="1080" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/Untitled.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/Untitled.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/05/Untitled.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/Untitled.png 1920w" sizes="(min-width: 720px) 720px"><figcaption>Source: <a href="https://ai.facebook.com/blog/imagebind-six-modalities-binding-ai/?ref=jina-ai-gmbh.ghost.io">https://ai.facebook.com/blog/imagebind-six-modalities-binding-ai/</a></figcaption></figure><p>Representing different modalities in the same embedding space allows for several use cases, like cross-modal generation, embedding-space generation, or cross-modal retrieval. In this blog, we’re interested in the latter use case and we’ll implement it using DocArray.</p><h2 id="docarray">DocArray</h2><p><a href="https://docs.docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray</a> is a library for <strong>representing, sending, and storing multi-modal data</strong>, perfect for <strong>Machine Learning applications</strong>.</p><p>With DocArray you can:</p><ol><li><strong><a href="https://docs.docarray.org/?ref=jina-ai-gmbh.ghost.io#represent">Represent data</a></strong></li><li><strong><a href="https://docs.docarray.org/?ref=jina-ai-gmbh.ghost.io#send">Send data</a></strong></li><li><strong><a href="https://docs.docarray.org/?ref=jina-ai-gmbh.ghost.io#store">Store data</a></strong></li></ol><p>DocArray is also optimized for neural search and supports searching by vector either in-memory or using a variety of vector databases, notably Weaviate, Qdrant, and ElasticSearch.</p><p>As we observed more multimodal AI models, we reshaped DocArray to become more suitable for multimodal AI use cases: multimodal AI search and generation.</p><p>Since <a href="https://jina.ai/news/docarray-v2-update/?ref=jina-ai-gmbh.ghost.io">the new release (v0.30.0)</a>, you can enjoy flexible schemas, more multimodal datatypes, and native support for multimodal neural search.</p><p>Let’s see it in action with ImageBind!</p><h2 id="cross-modal-search-with-docarray">Cross-modal search with DocArray</h2><p>First, we need to install DocArray:</p><pre><code class="language-bash">pip install docarray
+</code></pre><p>Next, we need to install ImageBind. We can do so by cloning the repository:</p><pre><code class="language-bash">git clone https://github.com/facebookresearch/ImageBind
 pip install -r ImageBind/requirements.txt
-</code></pre><p>Once we install the dependencies, we can load the ImageBind model:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> os
-os.chdir(<span class="hljs-string">'ImageBind'</span>)
+</code></pre><p>Once we install the dependencies, we can load the ImageBind model:</p><pre><code class="language-python">import os
+os.chdir('ImageBind')
 
-<span class="hljs-keyword">import</span> data
-<span class="hljs-keyword">import</span> torch
-<span class="hljs-keyword">from</span> models <span class="hljs-keyword">import</span> imagebind_model
-<span class="hljs-keyword">from</span> models.imagebind_model <span class="hljs-keyword">import</span> ModalityType
+import data
+import torch
+from models import imagebind_model
+from models.imagebind_model import ModalityType
 
-device = <span class="hljs-string">"cuda:0"</span> <span class="hljs-keyword">if</span> torch.cuda.is_available() <span class="hljs-keyword">else</span> <span class="hljs-string">"cpu"</span>
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
-<span class="hljs-comment"># Instantiate model</span>
-model = imagebind_model.imagebind_huge(pretrained=<span class="hljs-literal">True</span>)
-model.<span class="hljs-built_in">eval</span>()
+# Instantiate model
+model = imagebind_model.imagebind_huge(pretrained=True)
+model.eval()
 model.to(device)
-</code></pre><p>We will use pre-defined documents from DocArray for 3 data types:</p><ul><li><a href="https://docs.docarray.org/data_types/image/image/?ref=jina-ai-gmbh.ghost.io">🖼️ Image</a></li><li><a href="https://docs.docarray.org/data_types/text/text/?ref=jina-ai-gmbh.ghost.io">🔤 Text</a></li><li>and <a href="https://docs.docarray.org/data_types/audio/audio/?ref=jina-ai-gmbh.ghost.io">🔊 Audio</a>.</li></ul><p>The predefined documents offer several utilities like data loading, visualization, and built-in embedding.</p><p>Let’s first use these documents to implement an embedding function that uses the loaded ImageBind model:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> typing <span class="hljs-keyword">import</span> <span class="hljs-type">Union</span>
-<span class="hljs-keyword">from</span> docarray.documents <span class="hljs-keyword">import</span> TextDoc, ImageDoc, AudioDoc
+</code></pre><p>We will use pre-defined documents from DocArray for 3 data types:</p><ul><li><a href="https://docs.docarray.org/data_types/image/image/?ref=jina-ai-gmbh.ghost.io">🖼️ Image</a></li><li><a href="https://docs.docarray.org/data_types/text/text/?ref=jina-ai-gmbh.ghost.io">🔤 Text</a></li><li>and <a href="https://docs.docarray.org/data_types/audio/audio/?ref=jina-ai-gmbh.ghost.io">🔊 Audio</a>.</li></ul><p>The predefined documents offer several utilities like data loading, visualization, and built-in embedding.</p><p>Let’s first use these documents to implement an embedding function that uses the loaded ImageBind model:</p><pre><code class="language-python">from typing import Union
+from docarray.documents import TextDoc, ImageDoc, AudioDoc
 
-<span class="hljs-keyword">def</span> <span class="hljs-title function_">embed</span>(<span class="hljs-params">doc: <span class="hljs-type">Union</span>[TextDoc, ImageDoc, AudioDoc]</span>):
-    <span class="hljs-string">"""inplace embedding of document"""</span>
-    <span class="hljs-keyword">with</span> torch.no_grad():
-        <span class="hljs-keyword">if</span> <span class="hljs-built_in">isinstance</span>(doc, TextDoc):
+def embed(doc: Union[TextDoc, ImageDoc, AudioDoc]):
+    """inplace embedding of document"""
+    with torch.no_grad():
+        if isinstance(doc, TextDoc):
             embedding = model({ModalityType.TEXT: data.load_and_transform_text([doc.text], device)})[ModalityType.TEXT]
-        <span class="hljs-keyword">elif</span> <span class="hljs-built_in">isinstance</span>(doc, ImageDoc):
+        elif isinstance(doc, ImageDoc):
             embedding = model({ModalityType.VISION: data.load_and_transform_vision_data([doc.url], device)})[ModalityType.VISION]
-        <span class="hljs-keyword">elif</span> <span class="hljs-built_in">isinstance</span>(doc, AudioDoc):
+        elif isinstance(doc, AudioDoc):
             embedding = model({ModalityType.AUDIO: data.load_and_transform_audio_data([doc.url], device)})[ModalityType.AUDIO]
-        <span class="hljs-keyword">else</span>:
-            <span class="hljs-keyword">raise</span> ValueError(<span class="hljs-string">'one of the modality fields need to be set'</span>)
+        else:
+            raise ValueError('one of the modality fields need to be set')
 
-    doc.embedding = embedding.detach().cpu().numpy()[<span class="hljs-number">0</span>]
+    doc.embedding = embedding.detach().cpu().numpy()[0]
 
-    <span class="hljs-keyword">return</span> doc</code></pre><p>Let’s quickly try out the in-place embedding function:</p><pre><code class="language-python hljs">doc = ImageDoc(url=<span class="hljs-string">'.assets/car_image.jpg'</span>)
+    return doc</code></pre><p>Let’s quickly try out the in-place embedding function:</p><pre><code class="language-python">doc = ImageDoc(url='.assets/car_image.jpg')
 doc = embed(doc)
 doc
-</code></pre><pre><code class="language-bash hljs">📄ImageDoc: e679676 ...
+</code></pre><pre><code class="language-bash">📄ImageDoc: e679676 ...
 ╭─────────────────────────────┬────────────────────────────────────────╮
 │ Attribute                   │ Value                                  │
 ├─────────────────────────────┼────────────────────────────────────────┤
 │ url: ImageUrl               │ .assets/car_image.jpg                  │
 │ embedding: NdArrayEmbedding │ NdArrayEmbedding of shape (1024,)      │
 ╰─────────────────────────────┴────────────────────────────────────────╯
-</code></pre><p>As we can see, the document has an embedding field generated with shape of <code>(1024,)</code>. Now let’s dive into search.</p><h2 id="cross-modal-search">Cross-modal search</h2><h3 id="text-to-image">Text-to-image</h3><p>In this blog, we will use <a href="https://docs.docarray.org/user_guide/storing/index_in_memory/?ref=jina-ai-gmbh.ghost.io">the in-memory vector index</a> to perform neural search using the embeddings. However, feel free to check <a href="https://docs.docarray.org/user_guide/storing/docindex/?ref=jina-ai-gmbh.ghost.io">our documentation</a> to find out about vector database integrations.</p><p>Let’s create an index for image documents and index some documents:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray.index.backends.in_memory <span class="hljs-keyword">import</span> InMemoryExactNNIndex
+</code></pre><p>As we can see, the document has an embedding field generated with shape of <code>(1024,)</code>. Now let’s dive into search.</p><h2 id="cross-modal-search">Cross-modal search</h2><h3 id="text-to-image">Text-to-image</h3><p>In this blog, we will use <a href="https://docs.docarray.org/user_guide/storing/index_in_memory/?ref=jina-ai-gmbh.ghost.io">the in-memory vector index</a> to perform neural search using the embeddings. However, feel free to check <a href="https://docs.docarray.org/user_guide/storing/docindex/?ref=jina-ai-gmbh.ghost.io">our documentation</a> to find out about vector database integrations.</p><p>Let’s create an index for image documents and index some documents:</p><pre><code class="language-python">from docarray.index.backends.in_memory import InMemoryExactNNIndex
 
 image_index = InMemoryExactNNIndex[ImageDoc]()
 image_index.index([
-    embed(doc) <span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span> 
-    [ImageDoc(url=img_path) <span class="hljs-keyword">for</span> img_path <span class="hljs-keyword">in</span> [<span class="hljs-string">".assets/dog_image.jpg"</span>, <span class="hljs-string">".assets/car_image.jpg"</span>, <span class="hljs-string">".assets/bird_image.jpg"</span>]]
+    embed(doc) for doc in 
+    [ImageDoc(url=img_path) for img_path in [".assets/dog_image.jpg", ".assets/car_image.jpg", ".assets/bird_image.jpg"]]
 ])
-</code></pre><p>Now, let's search for bird images using text:</p><pre><code class="language-python hljs"><span class="hljs-keyword">match</span> = image_index.find(embed(TextDoc(text=<span class="hljs-string">'bird'</span>)).embedding, search_field=<span class="hljs-string">'embedding'</span>, limit=<span class="hljs-number">1</span>) \
-                   .documents[<span class="hljs-number">0</span>]
-<span class="hljs-keyword">match</span>.url.display()</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Untitled--1-.png" class="kg-image" alt="" width="640" height="855" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/Untitled--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/Untitled--1-.png 640w"></figure><h3 id="text-to-audio">Text-to-audio</h3><p>Now let's try a different modality: audio. The process is pretty much the same. First, create an index for audio documents:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray.index.backends.in_memory <span class="hljs-keyword">import</span> InMemoryExactNNIndex
+</code></pre><p>Now, let's search for bird images using text:</p><pre><code class="language-python">match = image_index.find(embed(TextDoc(text='bird')).embedding, search_field='embedding', limit=1) \
+                   .documents[0]
+match.url.display()</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Untitled--1-.png" class="kg-image" alt="" width="640" height="855" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/Untitled--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/Untitled--1-.png 640w"></figure><h3 id="text-to-audio">Text-to-audio</h3><p>Now let's try a different modality: audio. The process is pretty much the same. First, create an index for audio documents:</p><pre><code class="language-python">from docarray.index.backends.in_memory import InMemoryExactNNIndex
 
 audio_index = InMemoryExactNNIndex[AudioDoc]()
 audio_index.index([
-    embed(doc) <span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span>
-    [AudioDoc(url=audio_path) <span class="hljs-keyword">for</span> audio_path <span class="hljs-keyword">in</span> [<span class="hljs-string">".assets/dog_audio.wav"</span>, <span class="hljs-string">".assets/car_audio.wav"</span>, <span class="hljs-string">".assets/bird_audio.wav"</span>]]
+    embed(doc) for doc in
+    [AudioDoc(url=audio_path) for audio_path in [".assets/dog_audio.wav", ".assets/car_audio.wav", ".assets/bird_audio.wav"]]
 ])
-</code></pre><p>Now search for bird sounds by using text:</p><pre><code class="language-python hljs"><span class="hljs-keyword">match</span> = audio_index.find(embed(TextDoc(text=<span class="hljs-string">'bird'</span>)).embedding, search_field=<span class="hljs-string">'embedding'</span>, limit=<span class="hljs-number">1</span>) \
-                   .documents[<span class="hljs-number">0</span>]
-<span class="hljs-keyword">match</span>.url.display()
-<span class="hljs-comment"># Displays the bird sound</span>
-</code></pre><div class="kg-card kg-audio-card"><img loading="lazy" src="" alt="audio-thumbnail" class="kg-audio-thumbnail kg-audio-hide"><div class="kg-audio-thumbnail placeholder"><svg width="24" height="24" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.5 15.33a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0ZM15 13.83a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.486 6.81A2.25 2.25 0 0 1 17.25 9v5.579a.75.75 0 0 1-1.5 0v-5.58a.75.75 0 0 0-.932-.727.755.755 0 0 1-.059.013l-4.465.744a.75.75 0 0 0-.544.72v6.33a.75.75 0 0 1-1.5 0v-6.33a2.25 2.25 0 0 1 1.763-2.194l4.473-.746Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3 1.5a.75.75 0 0 0-.75.75v19.5a.75.75 0 0 0 .75.75h18a.75.75 0 0 0 .75-.75V5.133a.75.75 0 0 0-.225-.535l-.002-.002-3-2.883A.75.75 0 0 0 18 1.5H3ZM1.409.659A2.25 2.25 0 0 1 3 0h15a2.25 2.25 0 0 1 1.568.637l.003.002 3 2.883a2.25 2.25 0 0 1 .679 1.61V21.75A2.25 2.25 0 0 1 21 24H3a2.25 2.25 0 0 1-2.25-2.25V2.25c0-.597.237-1.169.659-1.591Z"></path></svg></div><div class="kg-audio-player-container" style="--buffered-width:100%;"><audio src="https://jina-ai-gmbh.ghost.io/content/media/2023/05/bird_audio.wav" preload="metadata"></audio><div class="kg-audio-title">Bird audio</div><div class="kg-audio-player"><button class="kg-audio-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-audio-pause-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-audio-current-time">0:00</span><div class="kg-audio-time">/<span class="kg-audio-duration">0:05</span></div><input type="range" class="kg-audio-seek-slider" max="5" value="0"><button class="kg-audio-playback-rate">1×</button><button class="kg-audio-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-audio-mute-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-audio-volume-slider" max="100" value="100"></div></div></div><h3 id="image-to-audio">Image-to-audio</h3><p>What’s cool with ImageBind is that you can do image-to-audio search as well. Let’s use the same index and perform one more search query, with an image this time!</p><pre><code class="language-python hljs"><span class="hljs-comment"># using the same audio_index, find by image:</span>
-<span class="hljs-keyword">match</span> = audio_index.find(embed(ImageDoc(url=<span class="hljs-string">'.assets/car_image.jpg'</span>)).embedding, search_field=<span class="hljs-string">'embedding'</span>, limit=<span class="hljs-number">1</span>) \
-									 .documents[<span class="hljs-number">0</span>]
-<span class="hljs-keyword">match</span>.url.display()
-<span class="hljs-comment"># Displays the card sound</span></code></pre><div class="kg-card kg-audio-card"><img loading="lazy" src="" alt="audio-thumbnail" class="kg-audio-thumbnail kg-audio-hide"><div class="kg-audio-thumbnail placeholder"><svg width="24" height="24" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.5 15.33a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0ZM15 13.83a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.486 6.81A2.25 2.25 0 0 1 17.25 9v5.579a.75.75 0 0 1-1.5 0v-5.58a.75.75 0 0 0-.932-.727.755.755 0 0 1-.059.013l-4.465.744a.75.75 0 0 0-.544.72v6.33a.75.75 0 0 1-1.5 0v-6.33a2.25 2.25 0 0 1 1.763-2.194l4.473-.746Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3 1.5a.75.75 0 0 0-.75.75v19.5a.75.75 0 0 0 .75.75h18a.75.75 0 0 0 .75-.75V5.133a.75.75 0 0 0-.225-.535l-.002-.002-3-2.883A.75.75 0 0 0 18 1.5H3ZM1.409.659A2.25 2.25 0 0 1 3 0h15a2.25 2.25 0 0 1 1.568.637l.003.002 3 2.883a2.25 2.25 0 0 1 .679 1.61V21.75A2.25 2.25 0 0 1 21 24H3a2.25 2.25 0 0 1-2.25-2.25V2.25c0-.597.237-1.169.659-1.591Z"></path></svg></div><div class="kg-audio-player-container" style="--buffered-width:100%;"><audio src="https://jina-ai-gmbh.ghost.io/content/media/2023/05/car_audio.wav" preload="metadata"></audio><div class="kg-audio-title">Car audio</div><div class="kg-audio-player"><button class="kg-audio-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-audio-pause-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-audio-current-time">0:00</span><div class="kg-audio-time">/<span class="kg-audio-duration">0:05</span></div><input type="range" class="kg-audio-seek-slider" max="5" value="0"><button class="kg-audio-playback-rate">1×</button><button class="kg-audio-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-audio-mute-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-audio-volume-slider" max="100" value="100"></div></div></div><h2 id="conclusion">Conclusion</h2><p>Cross-modal search, made possible with ImageBind and DocArray, is transforming the way we handle and interpret multimodal data. With ImageBind's ability to generate shared embedding spaces across multiple modalities and DocArray's clear and easy API to represent, send, and store this multimodal data, we have demonstrated how to implement a cross-modal search system.</p><p>These tools enable you to explore a wide range of use cases and applications. The cross-modal search capabilities we’ve showcased here are just the beginning, and we’re excited to see what you can build and the exciting applications around it.</p><p>Check out <a href="https://docs.docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray’s documentation</a>, <a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io">GitHub repo</a>, and <a href="https://discord.gg/WaMp6PVPgR?ref=jina-ai-gmbh.ghost.io">Discord</a> to find out how to implement multi-modal search systems.</p><p>Furthermore, you can check the ImageBind <a href="https://arxiv.org/abs/2305.05665?ref=jina-ai-gmbh.ghost.io">paper</a> and <a href="https://github.com/facebookresearch/ImageBind?ref=jina-ai-gmbh.ghost.io">GitHub repo</a> for more details about the model.</p><p>Happy searching!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fcross-modal-search-with-imagebind-and-docarray%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.385%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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\ No newline at end of file
+</code></pre><p>Now search for bird sounds by using text:</p><pre><code class="language-python">match = audio_index.find(embed(TextDoc(text='bird')).embedding, search_field='embedding', limit=1) \
+                   .documents[0]
+match.url.display()
+# Displays the bird sound
+</code></pre><div class="kg-card kg-audio-card"><img loading="lazy" src="" alt="audio-thumbnail" class="kg-audio-thumbnail kg-audio-hide"><div class="kg-audio-thumbnail placeholder"><svg width="24" height="24" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.5 15.33a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0ZM15 13.83a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.486 6.81A2.25 2.25 0 0 1 17.25 9v5.579a.75.75 0 0 1-1.5 0v-5.58a.75.75 0 0 0-.932-.727.755.755 0 0 1-.059.013l-4.465.744a.75.75 0 0 0-.544.72v6.33a.75.75 0 0 1-1.5 0v-6.33a2.25 2.25 0 0 1 1.763-2.194l4.473-.746Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3 1.5a.75.75 0 0 0-.75.75v19.5a.75.75 0 0 0 .75.75h18a.75.75 0 0 0 .75-.75V5.133a.75.75 0 0 0-.225-.535l-.002-.002-3-2.883A.75.75 0 0 0 18 1.5H3ZM1.409.659A2.25 2.25 0 0 1 3 0h15a2.25 2.25 0 0 1 1.568.637l.003.002 3 2.883a2.25 2.25 0 0 1 .679 1.61V21.75A2.25 2.25 0 0 1 21 24H3a2.25 2.25 0 0 1-2.25-2.25V2.25c0-.597.237-1.169.659-1.591Z"></path></svg></div><div class="kg-audio-player-container"><audio src="https://jina-ai-gmbh.ghost.io/content/media/2023/05/bird_audio.wav" preload="metadata"></audio><div class="kg-audio-title">Bird audio</div><div class="kg-audio-player"><button class="kg-audio-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-audio-pause-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-audio-current-time">0:00</span><div class="kg-audio-time">/<span class="kg-audio-duration">0:05</span></div><input type="range" class="kg-audio-seek-slider" max="100" value="0"><button class="kg-audio-playback-rate">1×</button><button class="kg-audio-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-audio-mute-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-audio-volume-slider" max="100" value="100"></div></div></div><h3 id="image-to-audio">Image-to-audio</h3><p>What’s cool with ImageBind is that you can do image-to-audio search as well. Let’s use the same index and perform one more search query, with an image this time!</p><pre><code class="language-python"># using the same audio_index, find by image:
+match = audio_index.find(embed(ImageDoc(url='.assets/car_image.jpg')).embedding, search_field='embedding', limit=1) \
+									 .documents[0]
+match.url.display()
+# Displays the card sound</code></pre><div class="kg-card kg-audio-card"><img loading="lazy" src="" alt="audio-thumbnail" class="kg-audio-thumbnail kg-audio-hide"><div class="kg-audio-thumbnail placeholder"><svg width="24" height="24" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.5 15.33a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0ZM15 13.83a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.486 6.81A2.25 2.25 0 0 1 17.25 9v5.579a.75.75 0 0 1-1.5 0v-5.58a.75.75 0 0 0-.932-.727.755.755 0 0 1-.059.013l-4.465.744a.75.75 0 0 0-.544.72v6.33a.75.75 0 0 1-1.5 0v-6.33a2.25 2.25 0 0 1 1.763-2.194l4.473-.746Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3 1.5a.75.75 0 0 0-.75.75v19.5a.75.75 0 0 0 .75.75h18a.75.75 0 0 0 .75-.75V5.133a.75.75 0 0 0-.225-.535l-.002-.002-3-2.883A.75.75 0 0 0 18 1.5H3ZM1.409.659A2.25 2.25 0 0 1 3 0h15a2.25 2.25 0 0 1 1.568.637l.003.002 3 2.883a2.25 2.25 0 0 1 .679 1.61V21.75A2.25 2.25 0 0 1 21 24H3a2.25 2.25 0 0 1-2.25-2.25V2.25c0-.597.237-1.169.659-1.591Z"></path></svg></div><div class="kg-audio-player-container"><audio src="https://jina-ai-gmbh.ghost.io/content/media/2023/05/car_audio.wav" preload="metadata"></audio><div class="kg-audio-title">Car audio</div><div class="kg-audio-player"><button class="kg-audio-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-audio-pause-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-audio-current-time">0:00</span><div class="kg-audio-time">/<span class="kg-audio-duration">0:05</span></div><input type="range" class="kg-audio-seek-slider" max="100" value="0"><button class="kg-audio-playback-rate">1×</button><button class="kg-audio-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-audio-mute-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-audio-volume-slider" max="100" value="100"></div></div></div><h2 id="conclusion">Conclusion</h2><p>Cross-modal search, made possible with ImageBind and DocArray, is transforming the way we handle and interpret multimodal data. With ImageBind's ability to generate shared embedding spaces across multiple modalities and DocArray's clear and easy API to represent, send, and store this multimodal data, we have demonstrated how to implement a cross-modal search system.</p><p>These tools enable you to explore a wide range of use cases and applications. The cross-modal search capabilities we’ve showcased here are just the beginning, and we’re excited to see what you can build and the exciting applications around it.</p><p>Check out <a href="https://docs.docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray’s documentation</a>, <a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io">GitHub repo</a>, and <a href="https://discord.gg/WaMp6PVPgR?ref=jina-ai-gmbh.ghost.io">Discord</a> to find out how to implement multi-modal search systems.</p><p>Furthermore, you can check the ImageBind <a href="https://arxiv.org/abs/2305.05665?ref=jina-ai-gmbh.ghost.io">paper</a> and <a href="https://github.com/facebookresearch/ImageBind?ref=jina-ai-gmbh.ghost.io">GitHub repo</a> for more details about the model.</p><p>Happy searching!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fcross-modal-search-with-imagebind-and-docarray%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Dancing Bears on Cocaine: Why Generative AI is Nothing to Panic About</title><meta charset="utf-8"><meta name="title" content="Dancing Bears on Cocaine: Why Generative AI is Nothing to Panic About"><meta name="description" content="The appeal of the dancing bears was in how remarkable it was to see a bear dance and perform tricks and act like a person. The appeal of Generative AI is much the same. But lately, Generative AI has gone from dancing bear to cocaine bear. What's really going on beneath the hype?"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/dancing-bears-or-why-generative-ai-is-nothing-to-panic-about"><meta property="og:title" content="Dancing Bears on Cocaine: Why Generative AI is Nothing to Panic About"><meta property="og:description" content="The appeal of the dancing bears was in how remarkable it was to see a bear dance and perform tricks and act like a person. The appeal of Generative AI is much the same. But lately, Generative AI has gone from dancing bear to cocaine bear. What's really going on beneath the hype?"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Dancing-cocaine-bear-fixed-cropped-2-1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/dancing-bears-or-why-generative-ai-is-nothing-to-panic-about"><meta property="twitter:title" content="Dancing Bears on Cocaine: Why Generative AI is Nothing to Panic About"><meta property="twitter:description" content="The appeal of the dancing bears was in how remarkable it was to see a bear dance and perform tricks and act like a person. The appeal of Generative AI is much the same. But lately, Generative AI has gone from dancing bear to cocaine bear. What's really going on beneath the hype?"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Dancing-cocaine-bear-fixed-cropped-2-1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Dancing Bears on Cocaine: Why Generative AI is Nothing to Panic About</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The appeal of the dancing bears was in how remarkable it was to see a bear dance and perform tricks and act like a person. The appeal of Generative AI is much the same. But lately, Generative AI has gone from dancing bear to cocaine bear. What's really going on beneath the hype?</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 02, 2023 • 15 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><blockquote><strong>"The marvel is not that the bear dances well, but that the bear dances at all."</strong><br> — Traditionally attributed as an “old Russian proverb” but probably of more recent English origin.</blockquote><p>Long before <a href="https://youtu.be/DuWEEKeJLMI?ref=jina-ai-gmbh.ghost.io"><em>Cocaine Bear</em></a>, a film fictionalizing <a href="https://variety.com/2023/film/news/cocaine-bear-true-story-1235533218/?ref=jina-ai-gmbh.ghost.io">an incident in the 1980s</a> where a wild bear died after consuming a large quantity of cocaine abandoned by a smuggler, “dancing bears” were a widespread kind of entertainment. In many parts of Europe, in the 17th through 19th centuries, itinerant fairs would put on dancing bear shows for the public. </p><p>Drugs were not generally involved, as far as I know. Trainers would kidnap bear cubs, raise them to be tame, and teach them to perform tricks of various kinds. There was even an “academy” for “learned bears” (учёные медведи) in Smorgon (Сморгонь, now a city in Belarus) until the Russian Empire banned performing bears in 1870.</p><p>Historical association with eastern Europe is probably why the traditional saying about dancing bears is usually credited as an “old Russian proverb”, even though it doesn’t exist in Russian. Its origin is most likely English, adapted from a <a href="https://www.bartleby.com/100/249.60.html?ref=jina-ai-gmbh.ghost.io">misogynist quote attributed to Samuel Johnson</a>.</p><p>I asked <a href="https://openai.com/blog/chatgpt?ref=jina-ai-gmbh.ghost.io">ChatGPT</a> about dancing bears:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-01-at-13.38.12.png" class="kg-image" alt="" width="1446" height="606" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-01-at-13.38.12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-01-at-13.38.12.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-01-at-13.38.12.png 1446w" sizes="(min-width: 720px) 720px"></figure><p>ChatGPT has an impressive fluency in language. This is a remarkable development that attracts a lot of attention, but like the way dancing bears were trained to perform, large Generative AI models are trained to speak, construct pictures, and make music.</p><blockquote>The appeal of the dancing bears was in how remarkable it was to see a bear — a large, antagonistic, dangerous animal — dance and perform tricks and act like a person.<br><br>The appeal of Generative AI is much the same.</blockquote><p>OpenAI released GPT-2 in early 2019, and DALL-E in January 2021. Both attracted a lot of attention in the AI community, for the same reasons the dancing bears did: They represented a perceptibly large leap in the quality of AI text and image generation. However, these models attracted relatively little public interest in the midst of the Covid pandemic.</p><p>What a difference a couple of years makes!</p><blockquote>With GPT-3, ChatGPT, Stable Diffusion, and MidJourney, AI has moved from being dancing bear to a bear cranked up on cocaine.</blockquote><p>These models are shocking not just to AI researchers but to the larger public, and OpenAI's decision to make these models accessible to everyone has created an enormous buzz. The Internet is now full of discussions of artificial consciousness and the risk of an AI apocalypse, both from <a href="https://www.thestreet.com/technology/elon-musk-warns-about-ai-danger?ref=jina-ai-gmbh.ghost.io">people who regularly say ridiculous things</a> and from <a href="https://futurism.com/fired-google-engineer-ai-sentience?ref=jina-ai-gmbh.ghost.io">people who should know better</a>.</p><p>But generative AI is still a dancing bear. Like any dancing bear, its performance is so remarkable that it hardly seems fair to critique its quality.</p><p>For example, ChatGPT often makes mistakes:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-03-at-14.05.33.png" class="kg-image" alt="" width="1454" height="874" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-03-at-14.05.33.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-03-at-14.05.33.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-03-at-14.05.33.png 1454w" sizes="(min-width: 720px) 720px"><figcaption>ChatGPT confidently getting it wrong when asked for specific information</figcaption></figure><p>Conversations like this show that ChatGPT generally gives superficially plausible answers. Often, the most plausible answer is in fact correct, but far from always. Most people who know anything about Nietzsche will know that he said “God is Dead” and maybe that he wrote “Thus Spoke Zarathustra” (<em>Also Sprach Zarathustra</em>). It is entirely <em>plausible</em> that the two facts go together, but in fact, the full quote is only found in "The Gay Science" (<em>Die Fröhliche Wissenschaft</em>).</p><p>When confronted with a mistake, ChatGPT changes its mind easily. Unfortunately, it does so <em>even when it’s right</em>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-09-at-15.50.28.png" class="kg-image" alt="" width="1456" height="812" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-09-at-15.50.28.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-09-at-15.50.28.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-09-at-15.50.28.png 1456w" sizes="(min-width: 720px) 720px"><figcaption>ChatGPT giving a correct answer, then accepting my “correction” to the wrong answer, and adding more information to make it more plausible.</figcaption></figure><p>Asking ChatGPT to do any kind of quantitative reasoning shows that it doesn’t really do much reasoning at all:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-01-at-16.53.58.png" class="kg-image" alt="" width="1450" height="416" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-01-at-16.53.58.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-01-at-16.53.58.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-01-at-16.53.58.png 1450w" sizes="(min-width: 720px) 720px"><figcaption>The correct answer is 3 days, because it takes 1 chicken 1.5 days to lay 1 egg, so 5 chickens need 3 days to lay 10.</figcaption></figure><p>Worse still, generative AI sometimes acts like it's doing drugs, although it's a lot more like LSD than cocaine. In the current jargon, it often "hallucinates"<em>,</em> or more accurately, <a href="https://www.webmd.com/mental-health/what-to-know-about-confabulation?ref=jina-ai-gmbh.ghost.io"><em>confabulates</em> </a>in the absence of adequate information. Asking about somewhat obscure topics often brings this behavior out:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Untitled--2-.png" class="kg-image" alt="" width="789" height="240" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Untitled--2-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Untitled--2-.png 789w" sizes="(min-width: 720px) 720px"><figcaption>ChatGPT confabulating a flatly wrong answer, even though the right answer is in Wikipedia and therefore almost certainly in its training data.</figcaption></figure><p>V. N. Voloshinov did write a book called "Marxism and the Philosophy of Language" (Марксизм и философия языка), so this answer is plausible, but "Marxism and the Problems of Linguistics" (Марксизм и вопросы языкознания) was the work of Joseph Stalin.</p><p>The most consistent way to get ChatGPT to confabulate is to ask it to translate nonsense texts from some less widely used language:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-13-at-13.01.59.png" class="kg-image" alt="" width="1262" height="778" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-13-at-13.01.59.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-13-at-13.01.59.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-13-at-13.01.59.png 1262w" sizes="(min-width: 720px) 720px"></figure><p>This all seems plausible, if you know nothing of the Twi language and didn't look closely at the text to translate. But ChatGPT is confidently asserting that it knows languages that it clearly doesn't know!</p><p>Confabulation is a real problem for AI applications. There is right now a rush to market AI-chat driven Internet search products. So far, it's been a disaster for both <a href="https://www.reuters.com/technology/google-ai-chatbot-bard-offers-inaccurate-information-company-ad-2023-02-08/?ref=jina-ai-gmbh.ghost.io">Google</a> and <a href="https://www.nytimes.com/2023/02/16/technology/bing-chatbot-microsoft-chatgpt.html?ref=jina-ai-gmbh.ghost.io">Microsoft</a>. </p><blockquote>I don’t need a computer to get things wrong. I’m perfectly capable of doing that on my own. These failures call into question what large language models are actually good for. Clearly they are not suited to act as information retrieval systems.</blockquote><h2 id="ai-confabulation-as-art">AI Confabulation as Art</h2><p>Confabulation affects other kinds of large neural network models as well, not just the ones that talk.</p><p>Stable Diffusion, MidJourney, DALL-E and other AI art models produce excellent work, when seen in terms of the purely technical aspects of style and image composition. However, AI-made images are typically marred by odd flaws. For example, the images below were generated by <a href="http://lexica.art/?ref=jina-ai-gmbh.ghost.io">Lexica.art</a> in response to a request (called a ‘prompt’ in the lingo of AI art) for “<em>a statuesque beautiful woman with natural red hair in a revealing cocktail dress, smiling, looking at the camera, and holding up a wine glass</em>”.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.666667 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/ed68d59a-ee1e-4fe6-ba8e-0bfb2d83e18d.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/ed68d59a-ee1e-4fe6-ba8e-0bfb2d83e18d.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/ed68d59a-ee1e-4fe6-ba8e-0bfb2d83e18d.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/ed68d59a-ee1e-4fe6-ba8e-0bfb2d83e18d.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/ed68d59a-ee1e-4fe6-ba8e-0bfb2d83e18d.jpeg 2048w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.666667 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/67151bc0-832a-4e93-862b-d5ec7ad2bafb.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/67151bc0-832a-4e93-862b-d5ec7ad2bafb.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/67151bc0-832a-4e93-862b-d5ec7ad2bafb.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/67151bc0-832a-4e93-862b-d5ec7ad2bafb.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/67151bc0-832a-4e93-862b-d5ec7ad2bafb.jpeg 2048w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>“<em>A statuesque beautiful woman with natural red hair in a revealing cocktail dress, smiling, looking at the camera, and holding up a wine glass</em>”, from Lexica.art</figcaption></figure><p>Count the number of hands in the left image, the number of elbows in the right image, and the number of fingers in both. Even humans with very little artistic skill know how many fingers there are on a hand, and are even more likely to know hands usually connect to arms.</p><p>Another example: Using as a source (a 'seed image' in the jargon) <a href="https://en.wikipedia.org/wiki/Boris_Johnson?ref=jina-ai-gmbh.ghost.io#/media/File:Boris_Johnson_official_portrait_(cropped).jpg">the official portrait of Boris Johnson</a>, I asked Lexica.art to make it “art nouveau, in the style of Alphonse Mucha.” This was the result:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-01-at-17.38.43.png" class="kg-image" alt="" width="2000" height="740" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-01-at-17.38.43.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-01-at-17.38.43.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/Screenshot-2023-02-01-at-17.38.43.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-01-at-17.38.43.png 2346w" sizes="(min-width: 720px) 720px"><figcaption>Boris Johnson as <em>"art nouveau, in the style of Alphonse Mucha"</em>, from Lexica.art</figcaption></figure><p>Mucha’s human models were mostly women, as are many artists’ models, and as a result, this software rendered the former Prime Minister as a woman half of the time. No human artist, if asked to create a picture of Boris Johnson in any style, would instead depict a woman who looks nothing like him.</p><p>These large models have “learned” to do things that are neither specifically in their training data nor in the instructions given to them. This is confabulation, but in a different medium.</p><p>And in much the same way that ChatGPT fails at quantitative analysis, asking AI art generators for anything that requires counting above three is at best hit and miss. Below is an example of asking for “six apples”:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-03-at-12.58.32.png" class="kg-image" alt="" width="2000" height="748" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-03-at-12.58.32.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-03-at-12.58.32.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/Screenshot-2023-02-03-at-12.58.32.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/02/Screenshot-2023-02-03-at-12.58.32.png 2400w" sizes="(min-width: 720px) 720px"><figcaption><em>“Six apples”</em> from Lexica.art</figcaption></figure><blockquote>These large neural network models are some of the most massive and computationally demanding software in the world, and they cannot count to six!</blockquote><p>Furthermore, these models cannot write even the simplest text. The images below come from MidJourney, prompted with “a stop sign, with the word 'STOP' printed on it in all capital letters”.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Untitled--7-.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Untitled--7-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Untitled--7-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Untitled--7-.png 1024w" sizes="(min-width: 720px) 720px"></figure><p>These AI models were not trained to understand written text. They can produce single letters when prompted, and they produce text-like features in many images, but rarely legible, correct text.</p><p>AI music is a less well-developed application of Generative AI technologies, but <a href="https://google-research.github.io/seanet/musiclm/examples/?ref=jina-ai-gmbh.ghost.io">recent very impressive results from Google</a> suggest similar qualities.</p><p>We should not minimize the remarkable aspects of Generative AI, but its fundamental shortcomings are not little flaws that might go away in the next release. These problems are intrinsic to their underlying architecture and manner of functioning.</p><h2 id="human-bias-and-the-theory-of-bullshit">Human Bias and the Theory of Bullshit</h2><p>Large neural network models, trained with incredibly large datasets, excel at things like apparent linguistic fluency and technical artistic skill. They speak clearly, credibly, even confidently and produce balanced, aesthetically sound images, full of rich detail, depicting their objects with clarity and, in some cases, shocking realism.</p><blockquote>Generative AI manipulates entrenched human biases, and when evaluating it, we need to keep those biases clearly in mind.</blockquote><p>Fluency in language creates an appearance of intelligence and depth of thought. This particular bias is well-known and people should guard against it much more aggressively than they do.</p><p>For example, it is a truism among English-speakers that people who speak with British “Received Pronunciation” are presumed to be more intelligent than other people. This prejudice is very robust across the English-speaking world, as is its converse: Someone speaking a social or regional variant, or having a recognizable "accent", is perceived as ignorant or unintelligent, despite decades of debunking by sociolinguists.</p><p>What appears so impressive about ChatGPT is a reflection of that prejudice. We equate normative linguistic behavior with intelligence, reflection and depth, even in the complete absence of those things. &nbsp;Much has been made of AI models getting moderately good scores on <a href="https://davidrozado.substack.com/p/what-is-the-iq-of-chatgpt?ref=jina-ai-gmbh.ghost.io">standardized IQ-style tests</a> like the <a href="https://twitter.com/teddynpc/status/1598767389390573569?ref=jina-ai-gmbh.ghost.io">SAT</a>, and on university examinations in <a href="https://www.reuters.com/legal/transactional/chatgpt-passes-law-school-exams-despite-mediocre-performance-2023-01-25/?ref=jina-ai-gmbh.ghost.io">law</a>, <a href="https://www.medpagetoday.com/special-reports/exclusives/102705?ref=jina-ai-gmbh.ghost.io">medicine</a>, and <a href="https://www.bloomberg.com/news/articles/2023-02-04/chatgpt-passed-a-wharton-mba-exam-are-professors-worried?ref=jina-ai-gmbh.ghost.io">business</a>. We should be questioning the usefulness and validity of these tests instead of thinking that ChatGPT can <a href="https://www.theregister.com/2023/01/30/ai_in_brief/?ref=jina-ai-gmbh.ghost.io">practice law</a>, or <a href="https://doi.org/10.1101/2023.01.23.23284735?ref=jina-ai-gmbh.ghost.io">medicine</a>, or run a business.</p><blockquote>Large language models engage in speech without regard for any relationship between what they say and any external or objective truth.</blockquote><p>"Confabulation" is a more accurate word than "hallucination" for what happens when large language models get something wrong. AI models are not misinformed about the world and telling you things they “think” are true. Nor are they lying, because lying requires an awareness of what is true and what is false and an intent to mislead you. Confabulation in humans is seen as a sign of brain damage.</p><p>We can also look at AI confabulation through the lens of pragmatics and speech act theory. Since the ground-breaking work of <a href="https://en.wikipedia.org/wiki/Harry_Frankfurt?ref=jina-ai-gmbh.ghost.io">Harry G. Frankfurt</a> in the 1980s, we have a technical term for the kind of language ChatGPT produces: <em>bullshit</em>.</p><blockquote>What bullshit essentially misrepresents is neither the state of affairs to which it refers nor the beliefs of the speaker concerning that state of affairs. Those are what lies misrepresent, by virtue of being false. Since bullshit need not be false, it differs from lies in its misrepresentational intent. The bullshitter may not deceive us, or even intend to do so, either about the facts or about what he takes the facts to be. What he does necessarily attempt to deceive us about is his enterprise. His only indispensably distinctive characteristic is that in a certain way he misrepresents what he is up to. [...]<br><br>[The bullshitter] is neither on the side of the true nor on the side of the false. [...] He does not care whether the things he says describe reality correctly. He just picks them out, or makes them up, to suit his purpose.<br><br><em><strong><strong><strong><strong><strong>On Bullshit</strong></strong></strong></strong></strong></em>, 2005 (1986)</blockquote><p>That is what large language models do: They create speech designed to closely approximate coherent, reasonable, human answers to the requests given to it. Their "purpose" is to optimize the values of variables in a complex algebraic equation constructed by their training. The result may be an accurate representation of the external world, or not, but that is entirely irrelevant to how they work.</p><p>AI art is “bullshit” in a similar way. Just like the way that humans are prejudiced to perceive fluent language as indicative of awareness, intelligence and depth, we are prejudiced to think that technically well-made images reflect artistic talent.</p><p>This prejudice is just as faulty.</p><p>There are countless important, meaningful, critically lauded, publicly loved, and expensively sold works of art that don't match up with preconceptions of what art is “supposed to look like.” Consider Jean-Michel Basquiat’s <em>Untitled (1982)</em> (see below), a work rich with symbolism and meaning that sold at auction in 2017 for US $110 million. It is the work of a largely self-trained “street artist” (the preferred euphemism for someone who makes graffiti) who rarely if ever created traditional representational art using “proper” technique.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/34366630840_d407b05465_w.jpg" class="kg-image" alt="" width="377" height="400"><figcaption>Jean-Michel Basquiat’s <em>Untitled (1982)</em>, currently in the personal collection of Yusaku Maezawa. (Source: <a href="https://www.flickr.com/photos/rocor/34366630840?ref=jina-ai-gmbh.ghost.io">Rob Corder on Flickr</a>)</figcaption></figure><p>The value of an artwork is not to be found in the technical skills with which it is executed. Next to Basquiat, we could name any number of indisputably meaningful and important works of art that do not employ traditional techniques, from <a href="https://en.wikipedia.org/wiki/Guernica_(Picasso)?ref=jina-ai-gmbh.ghost.io">Picasso's <em>Guernica</em></a> to <a href="https://en.wikipedia.org/wiki/Fountain_(Duchamp)?ref=jina-ai-gmbh.ghost.io">Duchamp's <em>Fountain</em></a>.</p><blockquote>AI art is the flip side of that coin: Just as the works of Basquiat, Picasso, and Duchamp can be great art without using traditional technical skills, computers can now create images with great technical skill, but that have no particular artistic merit.</blockquote><p>The creativity of Generative AI is really only constrained randomness. Humans have a strong aversion to perceiving randomness as such. We are inclined to find meaning and perceive creativity in anything that even slightly resembles meaningful or creative activity.</p><p>Art is intended to provoke. It's made by artists with something to say. Generative AI creates images from descriptions, or even random inputs, but AI models have nothing to say. They can demonstrate considerable technical skill and can even create attractive images, but do so without any consideration of what they are representing, nor what they say about the objects they depict. The visual flaws so common to it, like extra and disconnected body parts, reflect its indifference to its artistic subjects.</p><p>There is no need to perform any pernicious gatekeeping here about what is and isn’t art. We don’t have to say that AI art isn’t really art. AI output is motivated by an intent just as much as abstract art, or even “found” art is. But that intent does not come from the AI.</p><p>Bullshit has a purpose. People routinely bullshit in order to misrepresent their personal expertise in some subject, or to impress someone, or to win an election to a political office. Speech acts are still goal-oriented acts, even when they are bullshit. What is the goal of AI bullshit?</p><p>The answer is the same as why the dancing bear dances: There is a trainer who seeks to profit.</p><h2 id="coming-down-from-the-hype-a-modest-future-for-generative-ai">Coming Down from the Hype: A Modest Future for Generative AI</h2><p>To say that AI output is bullshit is not to say AI engineering is bullshit. It represents real progress in machine learning and embodies a great deal of time and money spent on genuinely important research. Generative AI has real applications, although it is as yet unclear how important or valuable those applications are.</p><p>The last few months have been quite a high for the AI sector, but we have to start asking questions, like "what is it actually good for?" and "how do I use it to do something productive?" What happens when we take the cocaine away from the bear and it starts to come down?</p><blockquote>We can outline a few obvious markets for it, but honestly it is not yet clear that this impressive new technology has any genuinely revolutionary applications.</blockquote><p>There is probably some honest money to be made in using Generative AI as a writing assistant for very mundane tasks, particularly as an aid for non-fluent writers. Microsoft has expressed some interest in <a href="https://www.theverge.com/2023/1/9/23546144/microsoft-openai-word-powerpoint-outlook-gpt-integration-rumor?ref=jina-ai-gmbh.ghost.io">integrating this kind of AI into its Office suite</a>.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-03-at-15.48.21.png" class="kg-image" alt="" width="1452" height="1274" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-03-at-15.48.21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-03-at-15.48.21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-03-at-15.48.21.png 1452w" sizes="(min-width: 720px) 720px"></figure><p>The most predictable uses for generative AI are in line with developments that have been underway in natural language processing for decades.</p><p>We might realistically envision a future in which we can confidently “query” unstructured, man-made texts, extracting computer-accessible, actionable information from them without human intervention. This potentially represents a very large advance in natural language understanding technology, one with significant value for many industries that have to process natural language texts. It could be a paradigm-changing technology for digital document management and potentially for customer service. But as important as those fields are, both already make heavy use of automation, and we should not expect world-shaking changes to come from them.</p><p>As for AI art, having a “smart” brush, powered by an AI model, has some clear value for graphic designers or anyone else who has to handle computer images. For example, I took the official portrait of Boris Johnson (below) and erased his famously unkempt hair, then made DALL-E 2 fill it in.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.827434 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Boris_Johnson_official_portrait_-cropped--1.jpg" width="1122" height="1356" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Boris_Johnson_official_portrait_-cropped--1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Boris_Johnson_official_portrait_-cropped--1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Boris_Johnson_official_portrait_-cropped--1.jpg 1122w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-07-104509.png" width="975" height="975" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-07-104509.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-07-104509.png 975w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/DALL-E-2023-02-07-10.39.33---Middle-aged-English-businessman-with-straw-blonde-hair-with-a-neat--professional--expensive-cut..png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/DALL-E-2023-02-07-10.39.33---Middle-aged-English-businessman-with-straw-blonde-hair-with-a-neat--professional--expensive-cut..png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/DALL-E-2023-02-07-10.39.33---Middle-aged-English-businessman-with-straw-blonde-hair-with-a-neat--professional--expensive-cut..png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/DALL-E-2023-02-07-10.39.33---Middle-aged-English-businessman-with-straw-blonde-hair-with-a-neat--professional--expensive-cut..png 1024w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: <i>Boris Johnson’s official portrait</i>; Center: <i>The same photo, cropped, with the hair erased manually</i>; Right: Alternate hair, filled in by DALL-E 2.</figcaption></figure><p>One can readily imagine all sort of touch-ups and changes to images might be easier with this kind of technology, and there are doubtless people working at integrating Generative AI models into graphic design and photo processing tools.</p><p>Purely generative AI art products like MidJourney have a large and devoted paying user base, which indicates that many people are having a lot of fun with it. Many users treat prompt construction as a kind of game and enjoy seeing what the AI produces as a result. It is akin to pulling the lever on a slot machine: The anticipation of not knowing what you'll get and the dopamine hit of seeing something new come out of it.</p><p>Even sending random strings to AI art generators can be a fun pastime:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/generativejina_queezes_quarropt_alizathly_darripring_cif_4f1724ba-fa13-4a6f-a16e-ffb79185780b.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/generativejina_queezes_quarropt_alizathly_darripring_cif_4f1724ba-fa13-4a6f-a16e-ffb79185780b.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/generativejina_queezes_quarropt_alizathly_darripring_cif_4f1724ba-fa13-4a6f-a16e-ffb79185780b.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/generativejina_queezes_quarropt_alizathly_darripring_cif_4f1724ba-fa13-4a6f-a16e-ffb79185780b.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.666667 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Untitled--11-.png" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Untitled--11-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Untitled--11-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/Untitled--11-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Untitled--11-.png 2048w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: MidJourney, “queezes quarropt alizathly darripring cif”; Right: Lexica.art, “coolts avesslational perchery quident belusen”</figcaption></figure><p>Making fun software for people is a perfectly legitimate use of AI, one with quite reasonable profit potential, and certainly preferable to many other possible uses. But it's far from revolutionary.</p><p>Generative AI’s value as inspiration — as a source of materials around which human creativity can crystallize — is impossible to assess or measure, but we already see some examples of applications along those lines.</p><p>One example is <a href="https://rationale.jina.ai/decisions?ref=jina-ai-gmbh.ghost.io">Rationale</a>, a GPT-3 powered decision-support tool. You can ask it to provide various kinds of analysis of potential decisions. Even if it doesn’t tell you anything you don’t already know, people often think more clearly when the alternatives are laid out for them, in print. Every now and then, it might even come up with a consideration you hadn’t thought of.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-07-at-14.23.26.png" class="kg-image" alt="" width="986" height="1170" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-07-at-14.23.26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-07-at-14.23.26.png 986w" sizes="(min-width: 720px) 720px"><figcaption>Example analysis from <a href="https://rationale.jina.ai/decisions?ref=jina-ai-gmbh.ghost.io">Rationale</a>.</figcaption></figure><p>These kinds of uses are the ones where Generative AI can most likely really add value. However, to access that value, we will need to learn how to deploy large AI models within information processing workflows. There is not very much precedent for this because AI models do not work like traditional software modules. <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI</a> is building frameworks for exactly that kind of integration, and we expect to continue to make progress for the foreseeable future.</p><p>There may be some truly revolutionary application for this technology, but if so, it has not yet manifested itself. Right now, Generative AI has a lot of hype, as does AI in general, and few money-making applications. It's not all hype, but we shouldn't forget that it’s mostly hype.</p><h2 id="ai-hype-snow-and-ai-winter">AI Hype Snow and AI Winter</h2><p>For most drugs – including alcohol – there is a period after a session of moderate to heavy use when the user may feel uncomfortable, unhappy, or ill. Like any drug, AI hype causes comedowns and hangovers. This field has a cyclical history of breakthroughs, overpromising, and then disappointment and disinvestment. After snorting a lot of "hype snow", we experience what AI veterans call “AI Winter.” </p><p>The realization that <a href="https://www.theverge.com/2021/7/5/22563751/tesla-elon-musk-full-self-driving-admission-autopilot-crash?ref=jina-ai-gmbh.ghost.io">AI-powered self-driving cars are not right around the corner</a> has brought back talk of another "AI Winter". It is entirely possible, even likely, that the current set of impressive-seeming AI models will prove less useful than the hype would have you believe, and will not be immediately followed by significant improvements.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/AI_WINTER_meme2.png" class="kg-image" alt="" width="950" height="534" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/AI_WINTER_meme2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/AI_WINTER_meme2.png 950w" sizes="(min-width: 720px) 720px"><figcaption>Of course there’s a Game of Thrones meme for that!</figcaption></figure><p>It is not clear which businesses Generative AI might revolutionize and which ones might only experience incremental changes or none at all. It is important to have realistic expectations.</p><p>For now, it’s okay to enjoy the dancing bear performing for us, even speculate what use we might put a trained bear to in our homes and businesses. But don't snort too much of the hype. In the end, it’s still a dancing bear. It's quite an impressive accomplishment, as long as you don't focus on how well or how poorly it actually does things.</p><p>Those of us in the emerging 'AI sector', including <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI</a>, are doing the hard work of making this technology genuinely productive. The proof of its value will be in productivity-enhancing tools and profitable businesses, rather than impressive-appearing demos. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/artificial-general-intelligence-is-cursed-and-science-fiction-isnt-helping" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Artificial General Intelligence is Cursed, And Science Fiction isn't Helping</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">AI is cursed by intellectual hubris, moving goalposts, bad incentives, and science fiction. Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The appeal of the dancing bears was in how remarkable it was to see a bear dance and perform tricks and act like a person. The appeal of Generative AI is much the same. But lately, Generative AI has gone from dancing bear to cocaine bear. What's really going on beneath the hype?</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 02, 2023 • 15 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><blockquote><strong>"The marvel is not that the bear dances well, but that the bear dances at all."</strong><br> — Traditionally attributed as an “old Russian proverb” but probably of more recent English origin.</blockquote><p>Long before <a href="https://youtu.be/DuWEEKeJLMI?ref=jina-ai-gmbh.ghost.io"><em>Cocaine Bear</em></a>, a film fictionalizing <a href="https://variety.com/2023/film/news/cocaine-bear-true-story-1235533218/?ref=jina-ai-gmbh.ghost.io">an incident in the 1980s</a> where a wild bear died after consuming a large quantity of cocaine abandoned by a smuggler, “dancing bears” were a widespread kind of entertainment. In many parts of Europe, in the 17th through 19th centuries, itinerant fairs would put on dancing bear shows for the public. </p><p>Drugs were not generally involved, as far as I know. Trainers would kidnap bear cubs, raise them to be tame, and teach them to perform tricks of various kinds. There was even an “academy” for “learned bears” (учёные медведи) in Smorgon (Сморгонь, now a city in Belarus) until the Russian Empire banned performing bears in 1870.</p><p>Historical association with eastern Europe is probably why the traditional saying about dancing bears is usually credited as an “old Russian proverb”, even though it doesn’t exist in Russian. Its origin is most likely English, adapted from a <a href="https://www.bartleby.com/100/249.60.html?ref=jina-ai-gmbh.ghost.io">misogynist quote attributed to Samuel Johnson</a>.</p><p>I asked <a href="https://openai.com/blog/chatgpt?ref=jina-ai-gmbh.ghost.io">ChatGPT</a> about dancing bears:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-01-at-13.38.12.png" class="kg-image" alt="" width="1446" height="606" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-01-at-13.38.12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-01-at-13.38.12.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-01-at-13.38.12.png 1446w" sizes="(min-width: 720px) 720px"></figure><p>ChatGPT has an impressive fluency in language. This is a remarkable development that attracts a lot of attention, but like the way dancing bears were trained to perform, large Generative AI models are trained to speak, construct pictures, and make music.</p><blockquote>The appeal of the dancing bears was in how remarkable it was to see a bear — a large, antagonistic, dangerous animal — dance and perform tricks and act like a person.<br><br>The appeal of Generative AI is much the same.</blockquote><p>OpenAI released GPT-2 in early 2019, and DALL-E in January 2021. Both attracted a lot of attention in the AI community, for the same reasons the dancing bears did: They represented a perceptibly large leap in the quality of AI text and image generation. However, these models attracted relatively little public interest in the midst of the Covid pandemic.</p><p>What a difference a couple of years makes!</p><blockquote>With GPT-3, ChatGPT, Stable Diffusion, and MidJourney, AI has moved from being dancing bear to a bear cranked up on cocaine.</blockquote><p>These models are shocking not just to AI researchers but to the larger public, and OpenAI's decision to make these models accessible to everyone has created an enormous buzz. The Internet is now full of discussions of artificial consciousness and the risk of an AI apocalypse, both from <a href="https://www.thestreet.com/technology/elon-musk-warns-about-ai-danger?ref=jina-ai-gmbh.ghost.io">people who regularly say ridiculous things</a> and from <a href="https://futurism.com/fired-google-engineer-ai-sentience?ref=jina-ai-gmbh.ghost.io">people who should know better</a>.</p><p>But generative AI is still a dancing bear. Like any dancing bear, its performance is so remarkable that it hardly seems fair to critique its quality.</p><p>For example, ChatGPT often makes mistakes:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-03-at-14.05.33.png" class="kg-image" alt="" width="1454" height="874" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-03-at-14.05.33.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-03-at-14.05.33.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-03-at-14.05.33.png 1454w" sizes="(min-width: 720px) 720px"><figcaption>ChatGPT confidently getting it wrong when asked for specific information</figcaption></figure><p>Conversations like this show that ChatGPT generally gives superficially plausible answers. Often, the most plausible answer is in fact correct, but far from always. Most people who know anything about Nietzsche will know that he said “God is Dead” and maybe that he wrote “Thus Spoke Zarathustra” (<em>Also Sprach Zarathustra</em>). It is entirely <em>plausible</em> that the two facts go together, but in fact, the full quote is only found in "The Gay Science" (<em>Die Fröhliche Wissenschaft</em>).</p><p>When confronted with a mistake, ChatGPT changes its mind easily. Unfortunately, it does so <em>even when it’s right</em>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-09-at-15.50.28.png" class="kg-image" alt="" width="1456" height="812" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-09-at-15.50.28.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-09-at-15.50.28.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-09-at-15.50.28.png 1456w" sizes="(min-width: 720px) 720px"><figcaption>ChatGPT giving a correct answer, then accepting my “correction” to the wrong answer, and adding more information to make it more plausible.</figcaption></figure><p>Asking ChatGPT to do any kind of quantitative reasoning shows that it doesn’t really do much reasoning at all:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-01-at-16.53.58.png" class="kg-image" alt="" width="1450" height="416" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-01-at-16.53.58.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-01-at-16.53.58.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-01-at-16.53.58.png 1450w" sizes="(min-width: 720px) 720px"><figcaption>The correct answer is 3 days, because it takes 1 chicken 1.5 days to lay 1 egg, so 5 chickens need 3 days to lay 10.</figcaption></figure><p>Worse still, generative AI sometimes acts like it's doing drugs, although it's a lot more like LSD than cocaine. In the current jargon, it often "hallucinates"<em>,</em> or more accurately, <a href="https://www.webmd.com/mental-health/what-to-know-about-confabulation?ref=jina-ai-gmbh.ghost.io"><em>confabulates</em> </a>in the absence of adequate information. Asking about somewhat obscure topics often brings this behavior out:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Untitled--2-.png" class="kg-image" alt="" width="789" height="240" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Untitled--2-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Untitled--2-.png 789w" sizes="(min-width: 720px) 720px"><figcaption>ChatGPT confabulating a flatly wrong answer, even though the right answer is in Wikipedia and therefore almost certainly in its training data.</figcaption></figure><p>V. N. Voloshinov did write a book called "Marxism and the Philosophy of Language" (Марксизм и философия языка), so this answer is plausible, but "Marxism and the Problems of Linguistics" (Марксизм и вопросы языкознания) was the work of Joseph Stalin.</p><p>The most consistent way to get ChatGPT to confabulate is to ask it to translate nonsense texts from some less widely used language:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-13-at-13.01.59.png" class="kg-image" alt="" width="1262" height="778" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-13-at-13.01.59.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-13-at-13.01.59.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-13-at-13.01.59.png 1262w" sizes="(min-width: 720px) 720px"></figure><p>This all seems plausible, if you know nothing of the Twi language and didn't look closely at the text to translate. But ChatGPT is confidently asserting that it knows languages that it clearly doesn't know!</p><p>Confabulation is a real problem for AI applications. There is right now a rush to market AI-chat driven Internet search products. So far, it's been a disaster for both <a href="https://www.reuters.com/technology/google-ai-chatbot-bard-offers-inaccurate-information-company-ad-2023-02-08/?ref=jina-ai-gmbh.ghost.io">Google</a> and <a href="https://www.nytimes.com/2023/02/16/technology/bing-chatbot-microsoft-chatgpt.html?ref=jina-ai-gmbh.ghost.io">Microsoft</a>. </p><blockquote>I don’t need a computer to get things wrong. I’m perfectly capable of doing that on my own. These failures call into question what large language models are actually good for. Clearly they are not suited to act as information retrieval systems.</blockquote><h2 id="ai-confabulation-as-art">AI Confabulation as Art</h2><p>Confabulation affects other kinds of large neural network models as well, not just the ones that talk.</p><p>Stable Diffusion, MidJourney, DALL-E and other AI art models produce excellent work, when seen in terms of the purely technical aspects of style and image composition. However, AI-made images are typically marred by odd flaws. For example, the images below were generated by <a href="http://lexica.art/?ref=jina-ai-gmbh.ghost.io">Lexica.art</a> in response to a request (called a ‘prompt’ in the lingo of AI art) for “<em>a statuesque beautiful woman with natural red hair in a revealing cocktail dress, smiling, looking at the camera, and holding up a wine glass</em>”.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/ed68d59a-ee1e-4fe6-ba8e-0bfb2d83e18d.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/ed68d59a-ee1e-4fe6-ba8e-0bfb2d83e18d.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/ed68d59a-ee1e-4fe6-ba8e-0bfb2d83e18d.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/ed68d59a-ee1e-4fe6-ba8e-0bfb2d83e18d.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/ed68d59a-ee1e-4fe6-ba8e-0bfb2d83e18d.jpeg 2048w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/67151bc0-832a-4e93-862b-d5ec7ad2bafb.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/67151bc0-832a-4e93-862b-d5ec7ad2bafb.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/67151bc0-832a-4e93-862b-d5ec7ad2bafb.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/67151bc0-832a-4e93-862b-d5ec7ad2bafb.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/67151bc0-832a-4e93-862b-d5ec7ad2bafb.jpeg 2048w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>“<em>A statuesque beautiful woman with natural red hair in a revealing cocktail dress, smiling, looking at the camera, and holding up a wine glass</em>”, from Lexica.art</figcaption></figure><p>Count the number of hands in the left image, the number of elbows in the right image, and the number of fingers in both. Even humans with very little artistic skill know how many fingers there are on a hand, and are even more likely to know hands usually connect to arms.</p><p>Another example: Using as a source (a 'seed image' in the jargon) <a href="https://en.wikipedia.org/wiki/Boris_Johnson?ref=jina-ai-gmbh.ghost.io#/media/File:Boris_Johnson_official_portrait_(cropped).jpg">the official portrait of Boris Johnson</a>, I asked Lexica.art to make it “art nouveau, in the style of Alphonse Mucha.” This was the result:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-01-at-17.38.43.png" class="kg-image" alt="" width="2000" height="740" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-01-at-17.38.43.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-01-at-17.38.43.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/Screenshot-2023-02-01-at-17.38.43.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-01-at-17.38.43.png 2346w" sizes="(min-width: 720px) 720px"><figcaption>Boris Johnson as <em>"art nouveau, in the style of Alphonse Mucha"</em>, from Lexica.art</figcaption></figure><p>Mucha’s human models were mostly women, as are many artists’ models, and as a result, this software rendered the former Prime Minister as a woman half of the time. No human artist, if asked to create a picture of Boris Johnson in any style, would instead depict a woman who looks nothing like him.</p><p>These large models have “learned” to do things that are neither specifically in their training data nor in the instructions given to them. This is confabulation, but in a different medium.</p><p>And in much the same way that ChatGPT fails at quantitative analysis, asking AI art generators for anything that requires counting above three is at best hit and miss. Below is an example of asking for “six apples”:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-03-at-12.58.32.png" class="kg-image" alt="" width="2000" height="748" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-03-at-12.58.32.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-03-at-12.58.32.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/Screenshot-2023-02-03-at-12.58.32.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/02/Screenshot-2023-02-03-at-12.58.32.png 2400w" sizes="(min-width: 720px) 720px"><figcaption><em>“Six apples”</em> from Lexica.art</figcaption></figure><blockquote>These large neural network models are some of the most massive and computationally demanding software in the world, and they cannot count to six!</blockquote><p>Furthermore, these models cannot write even the simplest text. The images below come from MidJourney, prompted with “a stop sign, with the word 'STOP' printed on it in all capital letters”.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Untitled--7-.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Untitled--7-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Untitled--7-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Untitled--7-.png 1024w" sizes="(min-width: 720px) 720px"></figure><p>These AI models were not trained to understand written text. They can produce single letters when prompted, and they produce text-like features in many images, but rarely legible, correct text.</p><p>AI music is a less well-developed application of Generative AI technologies, but <a href="https://google-research.github.io/seanet/musiclm/examples/?ref=jina-ai-gmbh.ghost.io">recent very impressive results from Google</a> suggest similar qualities.</p><p>We should not minimize the remarkable aspects of Generative AI, but its fundamental shortcomings are not little flaws that might go away in the next release. These problems are intrinsic to their underlying architecture and manner of functioning.</p><h2 id="human-bias-and-the-theory-of-bullshit">Human Bias and the Theory of Bullshit</h2><p>Large neural network models, trained with incredibly large datasets, excel at things like apparent linguistic fluency and technical artistic skill. They speak clearly, credibly, even confidently and produce balanced, aesthetically sound images, full of rich detail, depicting their objects with clarity and, in some cases, shocking realism.</p><blockquote>Generative AI manipulates entrenched human biases, and when evaluating it, we need to keep those biases clearly in mind.</blockquote><p>Fluency in language creates an appearance of intelligence and depth of thought. This particular bias is well-known and people should guard against it much more aggressively than they do.</p><p>For example, it is a truism among English-speakers that people who speak with British “Received Pronunciation” are presumed to be more intelligent than other people. This prejudice is very robust across the English-speaking world, as is its converse: Someone speaking a social or regional variant, or having a recognizable "accent", is perceived as ignorant or unintelligent, despite decades of debunking by sociolinguists.</p><p>What appears so impressive about ChatGPT is a reflection of that prejudice. We equate normative linguistic behavior with intelligence, reflection and depth, even in the complete absence of those things. &nbsp;Much has been made of AI models getting moderately good scores on <a href="https://davidrozado.substack.com/p/what-is-the-iq-of-chatgpt?ref=jina-ai-gmbh.ghost.io">standardized IQ-style tests</a> like the <a href="https://twitter.com/teddynpc/status/1598767389390573569?ref=jina-ai-gmbh.ghost.io">SAT</a>, and on university examinations in <a href="https://www.reuters.com/legal/transactional/chatgpt-passes-law-school-exams-despite-mediocre-performance-2023-01-25/?ref=jina-ai-gmbh.ghost.io">law</a>, <a href="https://www.medpagetoday.com/special-reports/exclusives/102705?ref=jina-ai-gmbh.ghost.io">medicine</a>, and <a href="https://www.bloomberg.com/news/articles/2023-02-04/chatgpt-passed-a-wharton-mba-exam-are-professors-worried?ref=jina-ai-gmbh.ghost.io">business</a>. We should be questioning the usefulness and validity of these tests instead of thinking that ChatGPT can <a href="https://www.theregister.com/2023/01/30/ai_in_brief/?ref=jina-ai-gmbh.ghost.io">practice law</a>, or <a href="https://doi.org/10.1101/2023.01.23.23284735?ref=jina-ai-gmbh.ghost.io">medicine</a>, or run a business.</p><blockquote>Large language models engage in speech without regard for any relationship between what they say and any external or objective truth.</blockquote><p>"Confabulation" is a more accurate word than "hallucination" for what happens when large language models get something wrong. AI models are not misinformed about the world and telling you things they “think” are true. Nor are they lying, because lying requires an awareness of what is true and what is false and an intent to mislead you. Confabulation in humans is seen as a sign of brain damage.</p><p>We can also look at AI confabulation through the lens of pragmatics and speech act theory. Since the ground-breaking work of <a href="https://en.wikipedia.org/wiki/Harry_Frankfurt?ref=jina-ai-gmbh.ghost.io">Harry G. Frankfurt</a> in the 1980s, we have a technical term for the kind of language ChatGPT produces: <em>bullshit</em>.</p><blockquote>What bullshit essentially misrepresents is neither the state of affairs to which it refers nor the beliefs of the speaker concerning that state of affairs. Those are what lies misrepresent, by virtue of being false. Since bullshit need not be false, it differs from lies in its misrepresentational intent. The bullshitter may not deceive us, or even intend to do so, either about the facts or about what he takes the facts to be. What he does necessarily attempt to deceive us about is his enterprise. His only indispensably distinctive characteristic is that in a certain way he misrepresents what he is up to. [...]<br><br>[The bullshitter] is neither on the side of the true nor on the side of the false. [...] He does not care whether the things he says describe reality correctly. He just picks them out, or makes them up, to suit his purpose.<br><br><em><strong><strong><strong><strong><strong>On Bullshit</strong></strong></strong></strong></strong></em>, 2005 (1986)</blockquote><p>That is what large language models do: They create speech designed to closely approximate coherent, reasonable, human answers to the requests given to it. Their "purpose" is to optimize the values of variables in a complex algebraic equation constructed by their training. The result may be an accurate representation of the external world, or not, but that is entirely irrelevant to how they work.</p><p>AI art is “bullshit” in a similar way. Just like the way that humans are prejudiced to perceive fluent language as indicative of awareness, intelligence and depth, we are prejudiced to think that technically well-made images reflect artistic talent.</p><p>This prejudice is just as faulty.</p><p>There are countless important, meaningful, critically lauded, publicly loved, and expensively sold works of art that don't match up with preconceptions of what art is “supposed to look like.” Consider Jean-Michel Basquiat’s <em>Untitled (1982)</em> (see below), a work rich with symbolism and meaning that sold at auction in 2017 for US $110 million. It is the work of a largely self-trained “street artist” (the preferred euphemism for someone who makes graffiti) who rarely if ever created traditional representational art using “proper” technique.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/34366630840_d407b05465_w.jpg" class="kg-image" alt="" width="377" height="400"><figcaption>Jean-Michel Basquiat’s <em>Untitled (1982)</em>, currently in the personal collection of Yusaku Maezawa. (Source: <a href="https://www.flickr.com/photos/rocor/34366630840?ref=jina-ai-gmbh.ghost.io">Rob Corder on Flickr</a>)</figcaption></figure><p>The value of an artwork is not to be found in the technical skills with which it is executed. Next to Basquiat, we could name any number of indisputably meaningful and important works of art that do not employ traditional techniques, from <a href="https://en.wikipedia.org/wiki/Guernica_(Picasso)?ref=jina-ai-gmbh.ghost.io">Picasso's <em>Guernica</em></a> to <a href="https://en.wikipedia.org/wiki/Fountain_(Duchamp)?ref=jina-ai-gmbh.ghost.io">Duchamp's <em>Fountain</em></a>.</p><blockquote>AI art is the flip side of that coin: Just as the works of Basquiat, Picasso, and Duchamp can be great art without using traditional technical skills, computers can now create images with great technical skill, but that have no particular artistic merit.</blockquote><p>The creativity of Generative AI is really only constrained randomness. Humans have a strong aversion to perceiving randomness as such. We are inclined to find meaning and perceive creativity in anything that even slightly resembles meaningful or creative activity.</p><p>Art is intended to provoke. It's made by artists with something to say. Generative AI creates images from descriptions, or even random inputs, but AI models have nothing to say. They can demonstrate considerable technical skill and can even create attractive images, but do so without any consideration of what they are representing, nor what they say about the objects they depict. The visual flaws so common to it, like extra and disconnected body parts, reflect its indifference to its artistic subjects.</p><p>There is no need to perform any pernicious gatekeeping here about what is and isn’t art. We don’t have to say that AI art isn’t really art. AI output is motivated by an intent just as much as abstract art, or even “found” art is. But that intent does not come from the AI.</p><p>Bullshit has a purpose. People routinely bullshit in order to misrepresent their personal expertise in some subject, or to impress someone, or to win an election to a political office. Speech acts are still goal-oriented acts, even when they are bullshit. What is the goal of AI bullshit?</p><p>The answer is the same as why the dancing bear dances: There is a trainer who seeks to profit.</p><h2 id="coming-down-from-the-hype-a-modest-future-for-generative-ai">Coming Down from the Hype: A Modest Future for Generative AI</h2><p>To say that AI output is bullshit is not to say AI engineering is bullshit. It represents real progress in machine learning and embodies a great deal of time and money spent on genuinely important research. Generative AI has real applications, although it is as yet unclear how important or valuable those applications are.</p><p>The last few months have been quite a high for the AI sector, but we have to start asking questions, like "what is it actually good for?" and "how do I use it to do something productive?" What happens when we take the cocaine away from the bear and it starts to come down?</p><blockquote>We can outline a few obvious markets for it, but honestly it is not yet clear that this impressive new technology has any genuinely revolutionary applications.</blockquote><p>There is probably some honest money to be made in using Generative AI as a writing assistant for very mundane tasks, particularly as an aid for non-fluent writers. Microsoft has expressed some interest in <a href="https://www.theverge.com/2023/1/9/23546144/microsoft-openai-word-powerpoint-outlook-gpt-integration-rumor?ref=jina-ai-gmbh.ghost.io">integrating this kind of AI into its Office suite</a>.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-03-at-15.48.21.png" class="kg-image" alt="" width="1452" height="1274" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-03-at-15.48.21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Screenshot-2023-02-03-at-15.48.21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-03-at-15.48.21.png 1452w" sizes="(min-width: 720px) 720px"></figure><p>The most predictable uses for generative AI are in line with developments that have been underway in natural language processing for decades.</p><p>We might realistically envision a future in which we can confidently “query” unstructured, man-made texts, extracting computer-accessible, actionable information from them without human intervention. This potentially represents a very large advance in natural language understanding technology, one with significant value for many industries that have to process natural language texts. It could be a paradigm-changing technology for digital document management and potentially for customer service. But as important as those fields are, both already make heavy use of automation, and we should not expect world-shaking changes to come from them.</p><p>As for AI art, having a “smart” brush, powered by an AI model, has some clear value for graphic designers or anyone else who has to handle computer images. For example, I took the official portrait of Boris Johnson (below) and erased his famously unkempt hair, then made DALL-E 2 fill it in.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Boris_Johnson_official_portrait_-cropped--1.jpg" width="1122" height="1356" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Boris_Johnson_official_portrait_-cropped--1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Boris_Johnson_official_portrait_-cropped--1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Boris_Johnson_official_portrait_-cropped--1.jpg 1122w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-07-104509.png" width="975" height="975" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-07-104509.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-07-104509.png 975w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/DALL-E-2023-02-07-10.39.33---Middle-aged-English-businessman-with-straw-blonde-hair-with-a-neat--professional--expensive-cut..png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/DALL-E-2023-02-07-10.39.33---Middle-aged-English-businessman-with-straw-blonde-hair-with-a-neat--professional--expensive-cut..png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/DALL-E-2023-02-07-10.39.33---Middle-aged-English-businessman-with-straw-blonde-hair-with-a-neat--professional--expensive-cut..png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/DALL-E-2023-02-07-10.39.33---Middle-aged-English-businessman-with-straw-blonde-hair-with-a-neat--professional--expensive-cut..png 1024w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: <i>Boris Johnson’s official portrait</i>; Center: <i>The same photo, cropped, with the hair erased manually</i>; Right: Alternate hair, filled in by DALL-E 2.</figcaption></figure><p>One can readily imagine all sort of touch-ups and changes to images might be easier with this kind of technology, and there are doubtless people working at integrating Generative AI models into graphic design and photo processing tools.</p><p>Purely generative AI art products like MidJourney have a large and devoted paying user base, which indicates that many people are having a lot of fun with it. Many users treat prompt construction as a kind of game and enjoy seeing what the AI produces as a result. It is akin to pulling the lever on a slot machine: The anticipation of not knowing what you'll get and the dopamine hit of seeing something new come out of it.</p><p>Even sending random strings to AI art generators can be a fun pastime:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/generativejina_queezes_quarropt_alizathly_darripring_cif_4f1724ba-fa13-4a6f-a16e-ffb79185780b.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/generativejina_queezes_quarropt_alizathly_darripring_cif_4f1724ba-fa13-4a6f-a16e-ffb79185780b.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/generativejina_queezes_quarropt_alizathly_darripring_cif_4f1724ba-fa13-4a6f-a16e-ffb79185780b.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/generativejina_queezes_quarropt_alizathly_darripring_cif_4f1724ba-fa13-4a6f-a16e-ffb79185780b.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Untitled--11-.png" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Untitled--11-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/Untitled--11-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/Untitled--11-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Untitled--11-.png 2048w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: MidJourney, “queezes quarropt alizathly darripring cif”; Right: Lexica.art, “coolts avesslational perchery quident belusen”</figcaption></figure><p>Making fun software for people is a perfectly legitimate use of AI, one with quite reasonable profit potential, and certainly preferable to many other possible uses. But it's far from revolutionary.</p><p>Generative AI’s value as inspiration — as a source of materials around which human creativity can crystallize — is impossible to assess or measure, but we already see some examples of applications along those lines.</p><p>One example is <a href="https://rationale.jina.ai/decisions?ref=jina-ai-gmbh.ghost.io">Rationale</a>, a GPT-3 powered decision-support tool. You can ask it to provide various kinds of analysis of potential decisions. Even if it doesn’t tell you anything you don’t already know, people often think more clearly when the alternatives are laid out for them, in print. Every now and then, it might even come up with a consideration you hadn’t thought of.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-07-at-14.23.26.png" class="kg-image" alt="" width="986" height="1170" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/Screenshot-2023-02-07-at-14.23.26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/Screenshot-2023-02-07-at-14.23.26.png 986w" sizes="(min-width: 720px) 720px"><figcaption>Example analysis from <a href="https://rationale.jina.ai/decisions?ref=jina-ai-gmbh.ghost.io">Rationale</a>.</figcaption></figure><p>These kinds of uses are the ones where Generative AI can most likely really add value. However, to access that value, we will need to learn how to deploy large AI models within information processing workflows. There is not very much precedent for this because AI models do not work like traditional software modules. <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI</a> is building frameworks for exactly that kind of integration, and we expect to continue to make progress for the foreseeable future.</p><p>There may be some truly revolutionary application for this technology, but if so, it has not yet manifested itself. Right now, Generative AI has a lot of hype, as does AI in general, and few money-making applications. It's not all hype, but we shouldn't forget that it’s mostly hype.</p><h2 id="ai-hype-snow-and-ai-winter">AI Hype Snow and AI Winter</h2><p>For most drugs – including alcohol – there is a period after a session of moderate to heavy use when the user may feel uncomfortable, unhappy, or ill. Like any drug, AI hype causes comedowns and hangovers. This field has a cyclical history of breakthroughs, overpromising, and then disappointment and disinvestment. After snorting a lot of "hype snow", we experience what AI veterans call “AI Winter.” </p><p>The realization that <a href="https://www.theverge.com/2021/7/5/22563751/tesla-elon-musk-full-self-driving-admission-autopilot-crash?ref=jina-ai-gmbh.ghost.io">AI-powered self-driving cars are not right around the corner</a> has brought back talk of another "AI Winter". It is entirely possible, even likely, that the current set of impressive-seeming AI models will prove less useful than the hype would have you believe, and will not be immediately followed by significant improvements.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/AI_WINTER_meme2.png" class="kg-image" alt="" width="950" height="534" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/AI_WINTER_meme2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/AI_WINTER_meme2.png 950w" sizes="(min-width: 720px) 720px"><figcaption>Of course there’s a Game of Thrones meme for that!</figcaption></figure><p>It is not clear which businesses Generative AI might revolutionize and which ones might only experience incremental changes or none at all. It is important to have realistic expectations.</p><p>For now, it’s okay to enjoy the dancing bear performing for us, even speculate what use we might put a trained bear to in our homes and businesses. But don't snort too much of the hype. In the end, it’s still a dancing bear. It's quite an impressive accomplishment, as long as you don't focus on how well or how poorly it actually does things.</p><p>Those of us in the emerging 'AI sector', including <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI</a>, are doing the hard work of making this technology genuinely productive. The proof of its value will be in productivity-enhancing tools and profitable businesses, rather than impressive-appearing demos. 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\ No newline at end of file
diff --git a/news/datatalksclub-spotlight-x-jina-ai/index.html b/news/datatalksclub-spotlight-x-jina-ai/index.html
index 5e1c7a8983a..44731dbed1a 100644
--- a/news/datatalksclub-spotlight-x-jina-ai/index.html
+++ b/news/datatalksclub-spotlight-x-jina-ai/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DataTalksClub Open Source Spotlight  x Jina AI</title><meta charset="utf-8"><meta name="title" content="DataTalksClub Open Source Spotlight  x Jina AI"><meta name="description" content="Jina AI NLP Engineer, Isabelle Mohr demonstrates the capabilities of Jina NOW in this datatalks.club open source spotlight! "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/datatalksclub-spotlight-x-jina-ai"><meta property="og:title" content="DataTalksClub Open Source Spotlight  x Jina AI"><meta property="og:description" content="Jina AI NLP Engineer, Isabelle Mohr demonstrates the capabilities of Jina NOW in this datatalks.club open source spotlight! "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina--1-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/datatalksclub-spotlight-x-jina-ai"><meta property="twitter:title" content="DataTalksClub Open Source Spotlight  x Jina AI"><meta property="twitter:description" content="Jina AI NLP Engineer, Isabelle Mohr demonstrates the capabilities of Jina NOW in this datatalks.club open source spotlight! "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina--1-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DataTalksClub Open Source Spotlight  x Jina AI</title><meta charset="utf-8"><meta name="title" content="DataTalksClub Open Source Spotlight  x Jina AI"><meta name="description" content="Jina AI NLP Engineer, Isabelle Mohr demonstrates the capabilities of Jina NOW in this datatalks.club open source spotlight! "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/datatalksclub-spotlight-x-jina-ai"><meta property="og:title" content="DataTalksClub Open Source Spotlight  x Jina AI"><meta property="og:description" content="Jina AI NLP Engineer, Isabelle Mohr demonstrates the capabilities of Jina NOW in this datatalks.club open source spotlight! "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina--1-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/datatalksclub-spotlight-x-jina-ai"><meta property="twitter:title" content="DataTalksClub Open Source Spotlight  x Jina AI"><meta property="twitter:description" content="Jina AI NLP Engineer, Isabelle Mohr demonstrates the capabilities of Jina NOW in this datatalks.club open source spotlight! "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina--1-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><script src="https://jina-ai-gmbh.ghost.io/public/cards.min.js" async=""></script><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DataTalksClub Open Source Spotlight  x Jina AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI NLP Engineer, Isabelle Mohr demonstrates the capabilities of Jina NOW in this datatalks.club open source spotlight! </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 28, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><br>We are pleased to announce our collaboration with datatalks.club, where Jina AI NLP Engineer, <a href="https://www.linkedin.com/in/isabelle-mohr-a8ba5516b/?ref=jina-ai-gmbh.ghost.io">Isabelle Mohr</a> will be demonstrating the capabilities of Jina NOW!</p><figure class="kg-card kg-embed-card"><iframe width="200" height="113" src="https://www.youtube.com/embed/za34VHC84ok?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen="" title="Open-Source Spotlight - Jina NOW - Isabelle Mohr"></iframe></figure><p>In this video, Isabelle showcases some key features of Jina NOW, providing users with a better understanding of the platform and how DocArray can be used to handle large-scale datasets. She also walks through the app deployment process and showcases some results of our neural search application.</p><p>Additionally, she touches on hybrid search and explains how Jina NOW can be used in combination with other search engines to achieve even better results. We also provide links to our GitHub repository and documentation, as well as information on how to contribute to the project.</p><p>Finally, viewers get a glimpse of our future projects – so don’t miss out!</p><p>As an experienced developer and NLP Engineer, <a href="https://www.linkedin.com/in/isabelle-mohr-a8ba5516b/?ref=jina-ai-gmbh.ghost.io">Isabelle</a> is an invaluable member of the Jina AI team, making significant contributions to the neural search ecosystem. She recently graduated with a Master's degree in Computational Linguistics and has a strong passion for Machine Learning.</p><p>This video is a part of the Open Source Spotlight series and has been posted on the datatalks.club YouTube channel.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdatatalksclub-spotlight-x-jina-ai%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DataTalksClub Open Source Spotlight  x Jina AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI NLP Engineer, Isabelle Mohr demonstrates the capabilities of Jina NOW in this datatalks.club open source spotlight! </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 28, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><br>We are pleased to announce our collaboration with datatalks.club, where Jina AI NLP Engineer, <a href="https://www.linkedin.com/in/isabelle-mohr-a8ba5516b/?ref=jina-ai-gmbh.ghost.io">Isabelle Mohr</a> will be demonstrating the capabilities of Jina NOW!</p><figure class="kg-card kg-embed-card"><iframe width="200" height="113" src="https://www.youtube.com/embed/za34VHC84ok?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen="" title="Open-Source Spotlight - Jina NOW - Isabelle Mohr"></iframe></figure><p>In this video, Isabelle showcases some key features of Jina NOW, providing users with a better understanding of the platform and how DocArray can be used to handle large-scale datasets. She also walks through the app deployment process and showcases some results of our neural search application.</p><p>Additionally, she touches on hybrid search and explains how Jina NOW can be used in combination with other search engines to achieve even better results. We also provide links to our GitHub repository and documentation, as well as information on how to contribute to the project.</p><p>Finally, viewers get a glimpse of our future projects – so don’t miss out!</p><p>As an experienced developer and NLP Engineer, <a href="https://www.linkedin.com/in/isabelle-mohr-a8ba5516b/?ref=jina-ai-gmbh.ghost.io">Isabelle</a> is an invaluable member of the Jina AI team, making significant contributions to the neural search ecosystem. She recently graduated with a Master's degree in Computational Linguistics and has a strong passion for Machine Learning.</p><p>This video is a part of the Open Source Spotlight series and has been posted on the datatalks.club YouTube channel.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdatatalksclub-spotlight-x-jina-ai%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.385%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>How to Deploy a Deep Learning Model with Jina (and design a kitten along the way)</title><meta charset="utf-8"><meta name="title" content="How to Deploy a Deep Learning Model with Jina (and design a kitten along the way)"><meta name="description" content="How to build and deploy an Executor that uses Stable Diffusion to generate images."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/deploy-deep-learning-model"><meta property="og:title" content="How to Deploy a Deep Learning Model with Jina (and design a kitten along the way)"><meta property="og:description" content="How to build and deploy an Executor that uses Stable Diffusion to generate images."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Cover--1-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/deploy-deep-learning-model"><meta property="twitter:title" content="How to Deploy a Deep Learning Model with Jina (and design a kitten along the way)"><meta property="twitter:description" content="How to build and deploy an Executor that uses Stable Diffusion to generate images."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Cover--1-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How to Deploy a Deep Learning Model with Jina (and design a kitten along the way)</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">How to build and deploy an Executor that uses Stable Diffusion to generate images.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G, Alaeddine Abdessalem</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 06, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Since the start of Jina, we've supported building <a href="https://docs.jina.ai/concepts/flow/?ref=jina-ai-gmbh.ghost.io">Flows</a> - namely pipelines of microservices. Now we're breaking those microservices out of the Flow and letting you deploy them stand-alone in the form of an <a href="https://docs.jina.ai/concepts/executor/?ref=jina-ai-gmbh.ghost.io">Executor</a> and <a href="https://docs.jina.ai/concepts/executor/serve/?ref=jina-ai-gmbh.ghost.io#serve-directly">Deployment.</a></p><p>In this post we’re going to do just that, building and deploying an Executor that uses <a href="https://github.com/Stability-AI/stablediffusion?ref=jina-ai-gmbh.ghost.io">Stable Diffusion</a> to generate images.</p><p>Jina is ideal for this use case because it offers:</p><ul><li>Efficient networking and serialization with <a href="https://grpc.io/?ref=jina-ai-gmbh.ghost.io">gRPC</a> and <a href="https://protobuf.dev/?ref=jina-ai-gmbh.ghost.io">protobuf</a></li><li>Expressive/multimodal data types with <a href="https://docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray</a></li><li>Array-first concept - Batching input for model inference is key to increasing throughput</li><li>Cloud-native features to easily ship ML models in production</li></ul><p>Plus, keep your eyes peeled and your ears open for an upcoming version of <a href="https://docs.jina.ai/concepts/jcloud/?ref=jina-ai-gmbh.ghost.io">JCloud</a>, which will let you run your model Deployments on Jina’s cloud infrastructure for free.</p><h2 id="some-backstory-the-road-to-a-cute-kitten">Some backstory: the road to a cute kitten</h2><p>Some time ago the Jina folks got together for drinks (hey, it was a Friday. Or at least some day that ended with a ‘y’). We were talking about having a cute mascot like <a href="https://en.wikipedia.org/wiki/GitHub?ref=jina-ai-gmbh.ghost.io#Mascot">Octocat</a> or The <a href="https://en.wikipedia.org/wiki/Michelin_Man?ref=jina-ai-gmbh.ghost.io">Michelin Man</a> and after a few beers we really got to brainstorming.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-14.png" class="kg-image" alt="" width="700" height="474" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-14.png 700w"><figcaption>The Michelin Man: If you ask me, it all went downhill after 1898</figcaption></figure><p>Anyhow, the end result of that <s>boozing</s> brainstorming was “rainbow unicorn butterfly kitten.” Now, how could we actually create such a divine creature? Maybe we could sketch out our dreams:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--12-.png" class="kg-image" alt="" width="612" height="612" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Untitled--12-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--12-.png 612w"><figcaption>We’re not just good at engineering - we’re pretty artistic too</figcaption></figure><p>In the end we decided to go with AI-powered image generation (what with genetic modification being unavailable, and gluing animals together into a Frankenkitty typically being frowned upon in polite society).</p><p>And what better way to generate Jina’s new mascot than with Jina itself? With that in mind, we got to work on an Executor and Deployment for image generation. So in this post we’ll walk through building a model into an Executor, deploying it, scaling it, and sharing it with the world.</p><p>There may also be kitten pics.</p><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Having trouble getting things working? Check our <a href="https://github.com/jina-ai/jina/?ref=jina-ai-gmbh.ghost.io">README</a> for a more concise (possibly more up-to-date) tutorial.</div></div><h2 id="building-our-executor">Building our Executor</h2><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">You'll need a GPU to run and deploy this Executor locally. Alternatively you can adapt your code to use <a href="https://cloud.jina.ai/executor/15jzcmam?ref=jina-ai-gmbh.ghost.io">Executor Hub sandboxed version</a>, hosted on Jina AI Cloud.</div></div><p>When you deploy a service in Jina, it's always done in the form of an Executor. An Executor is a Python class that transforms and processes <a href="https://docarray.jina.ai/fundamentals/document?ref=jina-ai-gmbh.ghost.io">Document</a>s, and can go way beyond image generation, for example, <a href="https://cloud.jina.ai/executor/29r2b26t?random=4496&amp;ref=jina-ai-gmbh.ghost.io">encoding text/images into vectors</a>, <a href="https://cloud.jina.ai/executor/2i315eae?random=9647&amp;ref=jina-ai-gmbh.ghost.io">OCR</a>, <a href="https://cloud.jina.ai/executor/14llgoaz?ref=jina-ai-gmbh.ghost.io">extracting tables from PDFs</a>, or <a href="https://cloud.jina.ai/executors?ref=jina-ai-gmbh.ghost.io">lots more</a>.</p><p>If you're just interested in <em>using</em> this Executor, rather than building it from scratch, you can jump straight to the <a href="https://www.notion.so/How-to-Deploy-a-Deep-Learning-Model-with-Jina-and-design-a-kitten-along-the-way-c29e347c893a4a5f933404f211c686c3?ref=jina-ai-gmbh.ghost.io">Executor Hub</a> section.</p><p>In this tutorial we'll focus on just the Executor- and Deployment-specific coding. We won't dive into the Stable Diffusion model's complexities, since that's simply a specific use case and we want this tutorial to be adaptable to <em>any</em> microservice or model.</p><p>This is roughly how we want our Executor to look. The user passes in a prompt, which the Executor uses to generate an image, then it passes that image back to the user:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Bare-Executor.png" class="kg-image" alt="" width="1600" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Bare-Executor.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Bare-Executor.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Bare-Executor.png 1600w" sizes="(min-width: 720px) 720px"></figure><h2 id="prerequisites">Prerequisites</h2><p>You'll need to install Hugging Face Diffusers</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/huggingface/diffusers?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - huggingface/diffusers: 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch</div><div class="kg-bookmark-description">🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch - GitHub - huggingface/diffusers: 🤗 Diffusers: State-of-the-art diffusion models for image and audio generat…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">huggingface</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/565fa924cf91ced165a4cb7194974cc660ce13c01b808ebbc4e4bf113d62e00d/huggingface/diffusers" alt=""></div></a></figure><pre><code class="hljs language-css">pip install diffusers<span class="hljs-selector-attr">[torch]</span></code></pre><p>Now, let's take a look at the Executor code as a whole, and then go through it section by section:</p><p>We'll start by creating <code>text_to_image.py</code>:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
-<span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests
-<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">How to build and deploy an Executor that uses Stable Diffusion to generate images.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G, Alaeddine Abdessalem</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 06, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Since the start of Jina, we've supported building <a href="https://docs.jina.ai/concepts/flow/?ref=jina-ai-gmbh.ghost.io">Flows</a> - namely pipelines of microservices. Now we're breaking those microservices out of the Flow and letting you deploy them stand-alone in the form of an <a href="https://docs.jina.ai/concepts/executor/?ref=jina-ai-gmbh.ghost.io">Executor</a> and <a href="https://docs.jina.ai/concepts/executor/serve/?ref=jina-ai-gmbh.ghost.io#serve-directly">Deployment.</a></p><p>In this post we’re going to do just that, building and deploying an Executor that uses <a href="https://github.com/Stability-AI/stablediffusion?ref=jina-ai-gmbh.ghost.io">Stable Diffusion</a> to generate images.</p><p>Jina is ideal for this use case because it offers:</p><ul><li>Efficient networking and serialization with <a href="https://grpc.io/?ref=jina-ai-gmbh.ghost.io">gRPC</a> and <a href="https://protobuf.dev/?ref=jina-ai-gmbh.ghost.io">protobuf</a></li><li>Expressive/multimodal data types with <a href="https://docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray</a></li><li>Array-first concept - Batching input for model inference is key to increasing throughput</li><li>Cloud-native features to easily ship ML models in production</li></ul><p>Plus, keep your eyes peeled and your ears open for an upcoming version of <a href="https://docs.jina.ai/concepts/jcloud/?ref=jina-ai-gmbh.ghost.io">JCloud</a>, which will let you run your model Deployments on Jina’s cloud infrastructure for free.</p><h2 id="some-backstory-the-road-to-a-cute-kitten">Some backstory: the road to a cute kitten</h2><p>Some time ago the Jina folks got together for drinks (hey, it was a Friday. Or at least some day that ended with a ‘y’). We were talking about having a cute mascot like <a href="https://en.wikipedia.org/wiki/GitHub?ref=jina-ai-gmbh.ghost.io#Mascot">Octocat</a> or The <a href="https://en.wikipedia.org/wiki/Michelin_Man?ref=jina-ai-gmbh.ghost.io">Michelin Man</a> and after a few beers we really got to brainstorming.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-14.png" class="kg-image" alt="" width="700" height="474" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-14.png 700w"><figcaption>The Michelin Man: If you ask me, it all went downhill after 1898</figcaption></figure><p>Anyhow, the end result of that <s>boozing</s> brainstorming was “rainbow unicorn butterfly kitten.” Now, how could we actually create such a divine creature? Maybe we could sketch out our dreams:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--12-.png" class="kg-image" alt="" width="612" height="612" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Untitled--12-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--12-.png 612w"><figcaption>We’re not just good at engineering - we’re pretty artistic too</figcaption></figure><p>In the end we decided to go with AI-powered image generation (what with genetic modification being unavailable, and gluing animals together into a Frankenkitty typically being frowned upon in polite society).</p><p>And what better way to generate Jina’s new mascot than with Jina itself? With that in mind, we got to work on an Executor and Deployment for image generation. So in this post we’ll walk through building a model into an Executor, deploying it, scaling it, and sharing it with the world.</p><p>There may also be kitten pics.</p><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Having trouble getting things working? Check our <a href="https://github.com/jina-ai/jina/?ref=jina-ai-gmbh.ghost.io">README</a> for a more concise (possibly more up-to-date) tutorial.</div></div><h2 id="building-our-executor">Building our Executor</h2><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">You'll need a GPU to run and deploy this Executor locally. Alternatively you can adapt your code to use <a href="https://cloud.jina.ai/executor/15jzcmam?ref=jina-ai-gmbh.ghost.io">Executor Hub sandboxed version</a>, hosted on Jina AI Cloud.</div></div><p>When you deploy a service in Jina, it's always done in the form of an Executor. An Executor is a Python class that transforms and processes <a href="https://docarray.jina.ai/fundamentals/document?ref=jina-ai-gmbh.ghost.io">Document</a>s, and can go way beyond image generation, for example, <a href="https://cloud.jina.ai/executor/29r2b26t?random=4496&amp;ref=jina-ai-gmbh.ghost.io">encoding text/images into vectors</a>, <a href="https://cloud.jina.ai/executor/2i315eae?random=9647&amp;ref=jina-ai-gmbh.ghost.io">OCR</a>, <a href="https://cloud.jina.ai/executor/14llgoaz?ref=jina-ai-gmbh.ghost.io">extracting tables from PDFs</a>, or <a href="https://cloud.jina.ai/executors?ref=jina-ai-gmbh.ghost.io">lots more</a>.</p><p>If you're just interested in <em>using</em> this Executor, rather than building it from scratch, you can jump straight to the <a href="https://www.notion.so/How-to-Deploy-a-Deep-Learning-Model-with-Jina-and-design-a-kitten-along-the-way-c29e347c893a4a5f933404f211c686c3?ref=jina-ai-gmbh.ghost.io">Executor Hub</a> section.</p><p>In this tutorial we'll focus on just the Executor- and Deployment-specific coding. We won't dive into the Stable Diffusion model's complexities, since that's simply a specific use case and we want this tutorial to be adaptable to <em>any</em> microservice or model.</p><p>This is roughly how we want our Executor to look. The user passes in a prompt, which the Executor uses to generate an image, then it passes that image back to the user:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Bare-Executor.png" class="kg-image" alt="" width="1600" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Bare-Executor.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Bare-Executor.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Bare-Executor.png 1600w" sizes="(min-width: 720px) 720px"></figure><h2 id="prerequisites">Prerequisites</h2><p>You'll need to install Hugging Face Diffusers</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/huggingface/diffusers?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - huggingface/diffusers: 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch</div><div class="kg-bookmark-description">🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch - GitHub - huggingface/diffusers: 🤗 Diffusers: State-of-the-art diffusion models for image and audio generat…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">huggingface</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/565fa924cf91ced165a4cb7194974cc660ce13c01b808ebbc4e4bf113d62e00d/huggingface/diffusers" alt=""></div></a></figure><pre><code>pip install diffusers[torch]</code></pre><p>Now, let's take a look at the Executor code as a whole, and then go through it section by section:</p><p>We'll start by creating <code>text_to_image.py</code>:</p><pre><code class="language-python">from docarray import DocumentArray
+from jina import Executor, requests
+import numpy as np
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">TextToImage</span>(<span class="hljs-title class_ inherited__">Executor</span>):
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">__init__</span>(<span class="hljs-params">self, **kwargs</span>):
-        <span class="hljs-built_in">super</span>().__init__(**kwargs)
-        <span class="hljs-keyword">import</span> torch
-        <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> StableDiffusionPipeline
+class TextToImage(Executor):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        import torch
+        from diffusers import StableDiffusionPipeline
 
         self.pipe = StableDiffusionPipeline.from_pretrained(
-            <span class="hljs-string">"CompVis/stable-diffusion-v1-4"</span>, torch_dtype=torch.float16
-        ).to(<span class="hljs-string">"cuda"</span>)
+            "CompVis/stable-diffusion-v1-4", torch_dtype=torch.float16
+        ).to("cuda")
 
-<span class="hljs-meta">    @requests</span>
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">generate_image</span>(<span class="hljs-params">self, docs: DocumentArray, **kwargs</span>):
-    	<span class="hljs-comment"># image here is in PIL format</span>
+    @requests
+    def generate_image(self, docs: DocumentArray, **kwargs):
+    	# image here is in PIL format
         images = self.pipe(docs.texts).images
         
-        <span class="hljs-keyword">for</span> i, doc <span class="hljs-keyword">in</span> <span class="hljs-built_in">enumerate</span>(docs):
-            doc.tensor = np.array(images[i])</code></pre><h3 id="imports">Imports</h3><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray</code></pre><p><a href="https://docs.docarray.org/fundamentals/document/?ref=jina-ai-gmbh.ghost.io">Documents</a> and <a href="https://docs.docarray.org/fundamentals/documentarray/?ref=jina-ai-gmbh.ghost.io">DocumentArrays</a> (from the <a href="https://docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray</a> package) are Jina's native IO format.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests</code></pre><p>Jina's <a href="https://docs.jina.ai/fundamentals/executor/?ref=jina-ai-gmbh.ghost.io">Executor</a> class and <a href="https://docs.jina.ai/concepts/executor/add-endpoints/?ref=jina-ai-gmbh.ghost.io">requests</a> decorator - we'll jump into these in the next section.</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np</code></pre><p>In our case, <a href="https://numpy.org/?ref=jina-ai-gmbh.ghost.io">NumPy</a> is specific to this Executor only. We won't really cover it in this article, since we want to keep this as a general overview. (And there’s plenty of information about NumPy out there already).</p><h3 id="executor-class">Executor class</h3><pre><code class="language-python hljs"><span class="hljs-keyword">class</span> <span class="hljs-title class_">TextToImage</span>(<span class="hljs-title class_ inherited__">Executor</span>):
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">__init__</span>(<span class="hljs-params">self, **kwargs</span>):
-        <span class="hljs-built_in">super</span>().__init__(**kwargs)
-        <span class="hljs-keyword">import</span> torch
-        <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> StableDiffusionPipeline
+        for i, doc in enumerate(docs):
+            doc.tensor = np.array(images[i])</code></pre><h3 id="imports">Imports</h3><pre><code class="language-python">from docarray import DocumentArray</code></pre><p><a href="https://docs.docarray.org/fundamentals/document/?ref=jina-ai-gmbh.ghost.io">Documents</a> and <a href="https://docs.docarray.org/fundamentals/documentarray/?ref=jina-ai-gmbh.ghost.io">DocumentArrays</a> (from the <a href="https://docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray</a> package) are Jina's native IO format.</p><pre><code class="language-python">from jina import Executor, requests</code></pre><p>Jina's <a href="https://docs.jina.ai/fundamentals/executor/?ref=jina-ai-gmbh.ghost.io">Executor</a> class and <a href="https://docs.jina.ai/concepts/executor/add-endpoints/?ref=jina-ai-gmbh.ghost.io">requests</a> decorator - we'll jump into these in the next section.</p><pre><code class="language-python">import numpy as np</code></pre><p>In our case, <a href="https://numpy.org/?ref=jina-ai-gmbh.ghost.io">NumPy</a> is specific to this Executor only. We won't really cover it in this article, since we want to keep this as a general overview. (And there’s plenty of information about NumPy out there already).</p><h3 id="executor-class">Executor class</h3><pre><code class="language-python">class TextToImage(Executor):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        import torch
+        from diffusers import StableDiffusionPipeline
 
         self.pipe = StableDiffusionPipeline.from_pretrained(
-            <span class="hljs-string">"CompVis/stable-diffusion-v1-4"</span>, torch_dtype=torch.float16
-        ).to(<span class="hljs-string">"cuda"</span>)</code></pre><p>All Executors are created from Jina's Executor class. <a href="https://docs.jina.ai/concepts/executor/create/?ref=jina-ai-gmbh.ghost.io#constructor">User-definable parameters</a> are arguments defined in the <code>__init__()</code> method.</p><h3 id="requests-decorator">Requests decorator</h3><pre><code class="language-python hljs"><span class="hljs-meta">@requests</span>
-<span class="hljs-keyword">def</span> <span class="hljs-title function_">generate_image</span>(<span class="hljs-params">self, docs: DocumentArray, **kwargs</span>):
-    <span class="hljs-comment"># image here is in PIL format</span>
+            "CompVis/stable-diffusion-v1-4", torch_dtype=torch.float16
+        ).to("cuda")</code></pre><p>All Executors are created from Jina's Executor class. <a href="https://docs.jina.ai/concepts/executor/create/?ref=jina-ai-gmbh.ghost.io#constructor">User-definable parameters</a> are arguments defined in the <code>__init__()</code> method.</p><h3 id="requests-decorator">Requests decorator</h3><pre><code class="language-python">@requests
+def generate_image(self, docs: DocumentArray, **kwargs):
+    # image here is in PIL format
     images = self.pipe(docs.texts).images
 
-    <span class="hljs-keyword">for</span> i, doc <span class="hljs-keyword">in</span> <span class="hljs-built_in">enumerate</span>(docs):
-        doc.tensor = np.array(images[i])</code></pre><p>Any Executor methods decorated with <code>@requests</code> can be called via an <a href="https://docs.jina.ai/concepts/executor/add-endpoints/?ref=jina-ai-gmbh.ghost.io">endpoint</a> when the Executor is run or deployed. Since we're using a bare <code>@requests</code> (rather than say <code>@requests(on='/foo')</code>), the <code>generate_image()</code> method will be called as the default fallback handler for <em>any</em> endpoint.</p><h2 id="deploying-our-microservice">Deploying our microservice</h2><p>So, now that we've got our Executor, what's the next step? Deployment of course! With a Deployment you can run and scale up your Executor, adding sharding, replicas and dynamic batching. It's also easy to then deploy with <a href="https://kubernetes.io/?ref=jina-ai-gmbh.ghost.io">Kubernetes</a> or <a href="https://docs.docker.com/compose/?ref=jina-ai-gmbh.ghost.io">Docker Compose</a>, which we’ll cover later in this post.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Deployment.png" class="kg-image" alt="" width="1600" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Deployment.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Deployment.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Deployment.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>We can deploy our Executor through the Python API or YAML/CLI. We'll keep it simple for now, and add scaling, replicas and more in a later section.</p><h3 id="deploy-via-python-api">Deploy via Python API</h3><p>In the file <code>deployment.py</code>:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment
-<span class="hljs-keyword">from</span> text_to_image <span class="hljs-keyword">import</span> TextToImage
+    for i, doc in enumerate(docs):
+        doc.tensor = np.array(images[i])</code></pre><p>Any Executor methods decorated with <code>@requests</code> can be called via an <a href="https://docs.jina.ai/concepts/executor/add-endpoints/?ref=jina-ai-gmbh.ghost.io">endpoint</a> when the Executor is run or deployed. Since we're using a bare <code>@requests</code> (rather than say <code>@requests(on='/foo')</code>), the <code>generate_image()</code> method will be called as the default fallback handler for <em>any</em> endpoint.</p><h2 id="deploying-our-microservice">Deploying our microservice</h2><p>So, now that we've got our Executor, what's the next step? Deployment of course! With a Deployment you can run and scale up your Executor, adding sharding, replicas and dynamic batching. It's also easy to then deploy with <a href="https://kubernetes.io/?ref=jina-ai-gmbh.ghost.io">Kubernetes</a> or <a href="https://docs.docker.com/compose/?ref=jina-ai-gmbh.ghost.io">Docker Compose</a>, which we’ll cover later in this post.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Deployment.png" class="kg-image" alt="" width="1600" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Deployment.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Deployment.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Deployment.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>We can deploy our Executor through the Python API or YAML/CLI. We'll keep it simple for now, and add scaling, replicas and more in a later section.</p><h3 id="deploy-via-python-api">Deploy via Python API</h3><p>In the file <code>deployment.py</code>:</p><pre><code class="language-python">from jina import Deployment
+from text_to_image import TextToImage
 
-<span class="hljs-keyword">with</span> Deployment(uses=TextToImage, timeout_ready=-<span class="hljs-number">1</span>, install_requirements=<span class="hljs-literal">True</span>) <span class="hljs-keyword">as</span> dep:
-    dep.block()</code></pre><p>And then run with <code>python deployment.py</code></p><h3 id="deploy-via-yaml">Deploy via YAML</h3><p>In <code>deployment.yaml</code>:</p><pre><code class="language-yaml hljs"><span class="hljs-attr">jtype:</span> <span class="hljs-string">Deployment</span>
-<span class="hljs-attr">with:</span>
-  <span class="hljs-attr">port:</span> <span class="hljs-number">12345</span>
-  <span class="hljs-attr">uses:</span> <span class="hljs-string">TextToImage</span>
-  <span class="hljs-attr">py_modules:</span>
-    <span class="hljs-bullet">-</span> <span class="hljs-string">text_to_image.py</span> <span class="hljs-comment"># name of the module containing Executor</span>
-  <span class="hljs-attr">timeout_ready:</span> <span class="hljs-number">-1</span>
-	<span class="hljs-attr">install_requirements:</span> <span class="hljs-literal">True</span></code></pre><p>And run the YAML Deployment with the CLI: <code>jina deployment --uses deployment.yml</code></p><p>However you run your Deployment, you'll see this output:</p><pre><code class="hljs language-vbnet">──────────────────────────────────────── 🎉 Deployment <span class="hljs-built_in">is</span> ready <span class="hljs-keyword">to</span> serve! ─────────────────────────────────────────
+with Deployment(uses=TextToImage, timeout_ready=-1, install_requirements=True) as dep:
+    dep.block()</code></pre><p>And then run with <code>python deployment.py</code></p><h3 id="deploy-via-yaml">Deploy via YAML</h3><p>In <code>deployment.yaml</code>:</p><pre><code class="language-yaml">jtype: Deployment
+with:
+  port: 12345
+  uses: TextToImage
+  py_modules:
+    - text_to_image.py # name of the module containing Executor
+  timeout_ready: -1
+	install_requirements: True</code></pre><p>And run the YAML Deployment with the CLI: <code>jina deployment --uses deployment.yml</code></p><p>However you run your Deployment, you'll see this output:</p><pre><code>──────────────────────────────────────── 🎉 Deployment is ready to serve! ─────────────────────────────────────────
 ╭────────────── 🔗 Endpoint ───────────────╮
 │  ⛓      Protocol                   GRPC │
-│  🏠        Local          <span class="hljs-number">0.0</span>.<span class="hljs-number">0.0</span>:<span class="hljs-number">12345</span>  │
-│  🔒      <span class="hljs-keyword">Private</span>      <span class="hljs-number">172.28</span>.<span class="hljs-number">0.12</span>:<span class="hljs-number">12345</span>  │
-│  🌍       <span class="hljs-keyword">Public</span>    <span class="hljs-number">35.230</span>.<span class="hljs-number">97.208</span>:<span class="hljs-number">12345</span>  │
-╰──────────────────────────────────────────╯</code></pre><h2 id="communicating-with-our-microservice">Communicating with our microservice</h2><p>We can use <a href="https://docs.jina.ai/concepts/client/?ref=jina-ai-gmbh.ghost.io">Jina Client</a> to make requests to our service via gRPC. As before, we deal with Documents as our basic IO format:</p><p>In <code>client.py</code>:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document
-<span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Client
+│  🏠        Local          0.0.0.0:12345  │
+│  🔒      Private      172.28.0.12:12345  │
+│  🌍       Public    35.230.97.208:12345  │
+╰──────────────────────────────────────────╯</code></pre><h2 id="communicating-with-our-microservice">Communicating with our microservice</h2><p>We can use <a href="https://docs.jina.ai/concepts/client/?ref=jina-ai-gmbh.ghost.io">Jina Client</a> to make requests to our service via gRPC. As before, we deal with Documents as our basic IO format:</p><p>In <code>client.py</code>:</p><pre><code class="language-python">from docarray import Document
+from jina import Client
 
-image_text = Document(text=<span class="hljs-string">'rainbow unicorn butterfly kitten'</span>)
+image_text = Document(text='rainbow unicorn butterfly kitten')
 
-client = Client(port=<span class="hljs-number">12345</span>)  <span class="hljs-comment"># use port from output above</span>
-response = client.post(on=<span class="hljs-string">'/'</span>, inputs=[image_text])
+client = Client(port=12345)  # use port from output above
+response = client.post(on='/', inputs=[image_text])
 
-response[<span class="hljs-number">0</span>].display()</code></pre><p>Running <code>python client.py</code> will give us the kitty of our dreams:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/rainbow_kitten.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/rainbow_kitten.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/rainbow_kitten.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/rainbow_kitten.png 1024w" sizes="(min-width: 720px) 720px"><figcaption>Her favorite command is <code>cat</code></figcaption></figure><h2 id="scaling-up-our-microservice">Scaling up our microservice</h2><p>Jina comes with scalability features out of the box like <a href="https://docs.jina.ai/concepts/flow/scale-out/?ref=jina-ai-gmbh.ghost.io#replicate-executors">replicas</a>, <a href="https://docs.jina.ai/concepts/flow/scale-out/?ref=jina-ai-gmbh.ghost.io#customize-polling-behaviors">shards</a> and <a href="https://docs.jina.ai/concepts/executor/dynamic-batching/?ref=jina-ai-gmbh.ghost.io">dynamic batching</a>. This lets you easily increase your application's throughput.</p><p>Let's deploy our Deployment and scale it with replicas and dynamic batching. We'll:</p><ul><li>Create two replicas, with <a href="https://docs.jina.ai/concepts/flow/scale-out/?ref=jina-ai-gmbh.ghost.io#replicate-on-multiple-gpus">a GPU assigned for each</a>.</li><li>Enable dynamic batching to process incoming parallel requests to the same model.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Replicas.png" class="kg-image" alt="" width="1600" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Replicas.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Replicas.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Replicas.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>Here's the Deployment's original (non-scaled) <code>deployment.yml</code>:</p><pre><code class="language-yaml hljs"><span class="hljs-attr">jtype:</span> <span class="hljs-string">Deployment</span>
-<span class="hljs-attr">with:</span>
-  <span class="hljs-attr">timeout_ready:</span> <span class="hljs-number">-1</span>
-  <span class="hljs-attr">uses:</span> <span class="hljs-string">jinaai://jina-ai/TextToImage</span>
-  <span class="hljs-attr">install_requirements:</span> <span class="hljs-literal">true</span></code></pre><p>Now let's scale it up:</p><pre><code class="language-yaml hljs"><span class="hljs-attr">jtype:</span> <span class="hljs-string">Deployment</span>
-<span class="hljs-attr">with:</span>
-  <span class="hljs-attr">timeout_ready:</span> <span class="hljs-number">-1</span>
-  <span class="hljs-attr">uses:</span> <span class="hljs-string">jinaai://jina-ai/TextToImage</span>
-  <span class="hljs-attr">install_requirements:</span> <span class="hljs-literal">true</span>
-  <span class="hljs-attr">env:</span>
-   <span class="hljs-attr">CUDA_VISIBLE_DEVICES:</span> <span class="hljs-string">RR</span>
-  <span class="hljs-attr">replicas:</span> <span class="hljs-number">2</span>
-  <span class="hljs-attr">uses_dynamic_batching:</span> <span class="hljs-comment"># configure dynamic batching</span>
-    <span class="hljs-string">/default:</span>
-      <span class="hljs-attr">preferred_batch_size:</span> <span class="hljs-number">10</span>
-      <span class="hljs-attr">timeout:</span> <span class="hljs-number">200</span></code></pre><p>As you can see, we've added GPU support (via <code>CUDA_VISIBLE_DEVICES</code>), two replicas (each assigned a GPU) and <a href="https://docs.jina.ai/concepts/executor/dynamic-batching/?ref=jina-ai-gmbh.ghost.io">dynamic batching</a>, which allows requests to be accumulated and batched together before being sent to the Executor.</p><p>Assuming your machine has two GPUs, using the scaled Deployment YAML will give better throughput compared to the normal deployment.</p><p>Thanks to the YAML syntax, you can inject deployment configurations regardless of Executor code. Of course, all of this is possible via the <a href="https://docs.jina.ai/concepts/executor/serve/?ref=jina-ai-gmbh.ghost.io#serve-directly">Python API</a> too.</p><h2 id="kubernetes-docker-compose-and-opentelemetry">Kubernetes, Docker Compose and OpenTelemetry</h2><p>Using <a href="https://docs.jina.ai/cloud-nativeness/k8s/?ref=jina-ai-gmbh.ghost.io">Kubernetes</a> with Jina is easy:</p><pre><code class="hljs language-bash">jina <span class="hljs-built_in">export</span> kubernetes deployment.yml ./my-k8s
-kubectl apply -R -f my-k8s</code></pre><p>And so is <a href="https://docs.jina.ai/cloud-nativeness/docker-compose/?ref=jina-ai-gmbh.ghost.io">Docker Compose</a>:</p><pre><code class="hljs language-bash">jina <span class="hljs-built_in">export</span> docker-compose deployment.yml docker-compose.yml
-docker-compose up</code></pre><p>Likewise, tracing and monitoring with <a href="https://opentelemetry.io/?ref=jina-ai-gmbh.ghost.io">OpenTelemetry</a> is straightforward:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
-<span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests
+response[0].display()</code></pre><p>Running <code>python client.py</code> will give us the kitty of our dreams:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/rainbow_kitten.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/rainbow_kitten.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/rainbow_kitten.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/rainbow_kitten.png 1024w" sizes="(min-width: 720px) 720px"><figcaption>Her favorite command is <code>cat</code></figcaption></figure><h2 id="scaling-up-our-microservice">Scaling up our microservice</h2><p>Jina comes with scalability features out of the box like <a href="https://docs.jina.ai/concepts/flow/scale-out/?ref=jina-ai-gmbh.ghost.io#replicate-executors">replicas</a>, <a href="https://docs.jina.ai/concepts/flow/scale-out/?ref=jina-ai-gmbh.ghost.io#customize-polling-behaviors">shards</a> and <a href="https://docs.jina.ai/concepts/executor/dynamic-batching/?ref=jina-ai-gmbh.ghost.io">dynamic batching</a>. This lets you easily increase your application's throughput.</p><p>Let's deploy our Deployment and scale it with replicas and dynamic batching. We'll:</p><ul><li>Create two replicas, with <a href="https://docs.jina.ai/concepts/flow/scale-out/?ref=jina-ai-gmbh.ghost.io#replicate-on-multiple-gpus">a GPU assigned for each</a>.</li><li>Enable dynamic batching to process incoming parallel requests to the same model.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Replicas.png" class="kg-image" alt="" width="1600" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Replicas.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Replicas.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Replicas.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>Here's the Deployment's original (non-scaled) <code>deployment.yml</code>:</p><pre><code class="language-yaml">jtype: Deployment
+with:
+  timeout_ready: -1
+  uses: jinaai://jina-ai/TextToImage
+  install_requirements: true</code></pre><p>Now let's scale it up:</p><pre><code class="language-yaml">jtype: Deployment
+with:
+  timeout_ready: -1
+  uses: jinaai://jina-ai/TextToImage
+  install_requirements: true
+  env:
+   CUDA_VISIBLE_DEVICES: RR
+  replicas: 2
+  uses_dynamic_batching: # configure dynamic batching
+    /default:
+      preferred_batch_size: 10
+      timeout: 200</code></pre><p>As you can see, we've added GPU support (via <code>CUDA_VISIBLE_DEVICES</code>), two replicas (each assigned a GPU) and <a href="https://docs.jina.ai/concepts/executor/dynamic-batching/?ref=jina-ai-gmbh.ghost.io">dynamic batching</a>, which allows requests to be accumulated and batched together before being sent to the Executor.</p><p>Assuming your machine has two GPUs, using the scaled Deployment YAML will give better throughput compared to the normal deployment.</p><p>Thanks to the YAML syntax, you can inject deployment configurations regardless of Executor code. Of course, all of this is possible via the <a href="https://docs.jina.ai/concepts/executor/serve/?ref=jina-ai-gmbh.ghost.io#serve-directly">Python API</a> too.</p><h2 id="kubernetes-docker-compose-and-opentelemetry">Kubernetes, Docker Compose and OpenTelemetry</h2><p>Using <a href="https://docs.jina.ai/cloud-nativeness/k8s/?ref=jina-ai-gmbh.ghost.io">Kubernetes</a> with Jina is easy:</p><pre><code>jina export kubernetes deployment.yml ./my-k8s
+kubectl apply -R -f my-k8s</code></pre><p>And so is <a href="https://docs.jina.ai/cloud-nativeness/docker-compose/?ref=jina-ai-gmbh.ghost.io">Docker Compose</a>:</p><pre><code>jina export docker-compose deployment.yml docker-compose.yml
+docker-compose up</code></pre><p>Likewise, tracing and monitoring with <a href="https://opentelemetry.io/?ref=jina-ai-gmbh.ghost.io">OpenTelemetry</a> is straightforward:</p><pre><code class="language-python">from docarray import DocumentArray
+from jina import Executor, requests
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">Encoder</span>(<span class="hljs-title class_ inherited__">Executor</span>):
-<span class="hljs-meta">    @requests</span>
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">encode</span>(<span class="hljs-params">self, docs: DocumentArray, **kwargs</span>):
-        <span class="hljs-keyword">with</span> self.tracer.start_as_current_span(
-            <span class="hljs-string">'encode'</span>, context=tracing_context
-        ) <span class="hljs-keyword">as</span> span:
-            <span class="hljs-keyword">with</span> self.monitor(
-                <span class="hljs-string">'preprocessing_seconds'</span>, <span class="hljs-string">'Time preprocessing the requests'</span>
+class Encoder(Executor):
+    @requests
+    def encode(self, docs: DocumentArray, **kwargs):
+        with self.tracer.start_as_current_span(
+            'encode', context=tracing_context
+        ) as span:
+            with self.monitor(
+                'preprocessing_seconds', 'Time preprocessing the requests'
             ):
                 docs.tensors = preprocessing(docs)
-            <span class="hljs-keyword">with</span> self.monitor(
-                <span class="hljs-string">'model_inference_seconds'</span>, <span class="hljs-string">'Time doing inference the requests'</span>
+            with self.monitor(
+                'model_inference_seconds', 'Time doing inference the requests'
             ):
-                docs.embedding = model_inference(docs.tensors)</code></pre><p>You can integrate <a href="https://www.jaegertracing.io/?ref=jina-ai-gmbh.ghost.io">Jaeger</a> or any other distributed tracing tool to collect and visualize request-level and application-level service operation attributes. This helps you analyze the request-response lifecycle, application behavior and performance.</p><p>To use Grafana, <a href="https://github.com/jina-ai/example-grafana-prometheus/blob/main/grafana-dashboards/flow-histogram-metrics.json?ref=jina-ai-gmbh.ghost.io">download this JSON</a> and import it into Grafana:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--13-.png" class="kg-image" alt="" width="2000" height="1046" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Untitled--13-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Untitled--13-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/03/Untitled--13-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/03/Untitled--13-.png 2400w" sizes="(min-width: 720px) 720px"></figure><h2 id="share-your-executor">Share your Executor</h2><p>Use <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Executor Hub</a> to share your Executors or use public/private Executors, with little need to worry about dependencies.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Hub.png" class="kg-image" alt="" width="1600" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Hub.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Hub.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Hub.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>To create a Hub-ready Executor:</p><pre><code class="hljs language-cpp">jina hub <span class="hljs-keyword">new</span></code></pre><p>To push it to Executor Hub:</p><pre><code class="hljs language-perl">jina hub <span class="hljs-keyword">push</span> .</code></pre><p>You can use a Hub Executor in your Deployment via Python:</p><pre><code class="language-python hljs">Deployment(uses=<span class="hljs-string">'jinaai://jina-ai/TextToImage'</span>, install_requirements=<span class="hljs-literal">True</span>)  <span class="hljs-comment"># download and run locally</span>
-Deployment(uses=<span class="hljs-string">'jinaai+docker://jina-ai/TextToImage'</span>)  <span class="hljs-comment"># run in Docker container</span>
-Deployment(uses=<span class="hljs-string">'jinaai+sandbox://jina-ai/TextToImage'</span>)  <span class="hljs-comment"># run in hosted sandbox</span></code></pre><p>Or YAML:</p><pre><code class="language-yaml hljs"><span class="hljs-attr">uses:</span> <span class="hljs-string">jinaai://jina-ai/TextToImage</span>  <span class="hljs-comment"># download and run locally</span>
-<span class="hljs-attr">install_requirements:</span> <span class="hljs-literal">true</span>
+                docs.embedding = model_inference(docs.tensors)</code></pre><p>You can integrate <a href="https://www.jaegertracing.io/?ref=jina-ai-gmbh.ghost.io">Jaeger</a> or any other distributed tracing tool to collect and visualize request-level and application-level service operation attributes. This helps you analyze the request-response lifecycle, application behavior and performance.</p><p>To use Grafana, <a href="https://github.com/jina-ai/example-grafana-prometheus/blob/main/grafana-dashboards/flow-histogram-metrics.json?ref=jina-ai-gmbh.ghost.io">download this JSON</a> and import it into Grafana:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--13-.png" class="kg-image" alt="" width="2000" height="1046" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Untitled--13-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Untitled--13-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/03/Untitled--13-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/03/Untitled--13-.png 2400w" sizes="(min-width: 720px) 720px"></figure><h2 id="share-your-executor">Share your Executor</h2><p>Use <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Executor Hub</a> to share your Executors or use public/private Executors, with little need to worry about dependencies.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Hub.png" class="kg-image" alt="" width="1600" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Hub.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Hub.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Hub.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>To create a Hub-ready Executor:</p><pre><code>jina hub new</code></pre><p>To push it to Executor Hub:</p><pre><code>jina hub push .</code></pre><p>You can use a Hub Executor in your Deployment via Python:</p><pre><code class="language-python">Deployment(uses='jinaai://jina-ai/TextToImage', install_requirements=True)  # download and run locally
+Deployment(uses='jinaai+docker://jina-ai/TextToImage')  # run in Docker container
+Deployment(uses='jinaai+sandbox://jina-ai/TextToImage')  # run in hosted sandbox</code></pre><p>Or YAML:</p><pre><code class="language-yaml">uses: jinaai://jina-ai/TextToImage  # download and run locally
+install_requirements: true
 
-<span class="hljs-attr">uses:</span> <span class="hljs-string">jinaai+docker://jina-ai/TextToImage</span>  <span class="hljs-comment"># run in Docker container</span>
-<span class="hljs-attr">uses:</span> <span class="hljs-string">jinaai+sandbox://jina-ai/TextToImage</span>  <span class="hljs-comment"># run in hosted sandbox</span></code></pre><p>Executor Hub manages everything on the backend:</p><ul><li>Automated builds on the cloud</li><li>Store, deploy, and deliver Executors cost-efficiently;</li><li>Automatically resolve version conflicts and dependencies;</li><li>Instant delivery of any Executor via <a href="https://docs.jina.ai/concepts/executor/hub/sandbox/?ref=jina-ai-gmbh.ghost.io">Sandbox</a> without pulling anything to local.</li></ul><h2 id="build-your-microservice-into-a-pipeline">Build your microservice into a pipeline</h2><p>Sometimes you want to chain microservices together into a pipeline. That's where a <a href="https://docs.jina.ai/concepts/flow/?ref=jina-ai-gmbh.ghost.io">Flow</a> comes in. We'll cover building a Flow in more depth in a future post, but for now you can check our <a href="https://github.com/jina-ai/jina/blob/master/README.md?ref=jina-ai-gmbh.ghost.io">README</a>.</p><h2 id="wrapping-it-up">Wrapping it up</h2><p>Just like an Executor and Deployment wraps a microservice or model, we too have to wrap up this article. To summarize what we've covered:</p><ul><li>With Jina you can wrap models into Executors.</li><li>These can then be deployed directly (via a Deployment) or as part of a pipeline (via a Flow).</li><li>Integrating with Kubernetes, Docker Compose and OpenTelemetry is a breeze.</li><li>You can find and share everything easily on <a href="https://cloud.jina.ai/executors?ref=jina-ai-gmbh.ghost.io">Executor Hub</a>.</li></ul><p>If you want to dig deeper, check our docs for more info on <a href="https://docs.jina.ai/concepts/executor/?ref=jina-ai-gmbh.ghost.io">Executors</a> and <a href="https://docs.jina.ai/concepts/executor/serve/?ref=jina-ai-gmbh.ghost.io">Deployments</a>, or look into pipelines with <a href="https://docs.jina.ai/concepts/flow/?ref=jina-ai-gmbh.ghost.io">Jina Flows</a>. You can also get in touch on our <a href="https://jina.ai/slack?ref=jina-ai-gmbh.ghost.io">Slack community</a>.</p><p>Keep your eyes on this blog for upcoming posts which will dive into serving multimodal models and LLMs with Jina, the capabilities of generative AI, and lots more.</p><h2 id="bonus-kitties">Bonus kitties</h2><p>Like all image generation, it took us quite a while to generate our one perfect kitty of loveliness. Here are some of the runners up:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--11-.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Untitled--11-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Untitled--11-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--11-.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--10-.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Untitled--10-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Untitled--10-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--10-.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--9-.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Untitled--9-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Untitled--9-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--9-.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdeploy-deep-learning-model%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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+uses: jinaai+docker://jina-ai/TextToImage  # run in Docker container
+uses: jinaai+sandbox://jina-ai/TextToImage  # run in hosted sandbox</code></pre><p>Executor Hub manages everything on the backend:</p><ul><li>Automated builds on the cloud</li><li>Store, deploy, and deliver Executors cost-efficiently;</li><li>Automatically resolve version conflicts and dependencies;</li><li>Instant delivery of any Executor via <a href="https://docs.jina.ai/concepts/executor/hub/sandbox/?ref=jina-ai-gmbh.ghost.io">Sandbox</a> without pulling anything to local.</li></ul><h2 id="build-your-microservice-into-a-pipeline">Build your microservice into a pipeline</h2><p>Sometimes you want to chain microservices together into a pipeline. That's where a <a href="https://docs.jina.ai/concepts/flow/?ref=jina-ai-gmbh.ghost.io">Flow</a> comes in. We'll cover building a Flow in more depth in a future post, but for now you can check our <a href="https://github.com/jina-ai/jina/blob/master/README.md?ref=jina-ai-gmbh.ghost.io">README</a>.</p><h2 id="wrapping-it-up">Wrapping it up</h2><p>Just like an Executor and Deployment wraps a microservice or model, we too have to wrap up this article. To summarize what we've covered:</p><ul><li>With Jina you can wrap models into Executors.</li><li>These can then be deployed directly (via a Deployment) or as part of a pipeline (via a Flow).</li><li>Integrating with Kubernetes, Docker Compose and OpenTelemetry is a breeze.</li><li>You can find and share everything easily on <a href="https://cloud.jina.ai/executors?ref=jina-ai-gmbh.ghost.io">Executor Hub</a>.</li></ul><p>If you want to dig deeper, check our docs for more info on <a href="https://docs.jina.ai/concepts/executor/?ref=jina-ai-gmbh.ghost.io">Executors</a> and <a href="https://docs.jina.ai/concepts/executor/serve/?ref=jina-ai-gmbh.ghost.io">Deployments</a>, or look into pipelines with <a href="https://docs.jina.ai/concepts/flow/?ref=jina-ai-gmbh.ghost.io">Jina Flows</a>. You can also get in touch on our <a href="https://jina.ai/slack?ref=jina-ai-gmbh.ghost.io">Slack community</a>.</p><p>Keep your eyes on this blog for upcoming posts which will dive into serving multimodal models and LLMs with Jina, the capabilities of generative AI, and lots more.</p><h2 id="bonus-kitties">Bonus kitties</h2><p>Like all image generation, it took us quite a while to generate our one perfect kitty of loveliness. Here are some of the runners up:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--11-.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Untitled--11-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Untitled--11-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--11-.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--10-.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Untitled--10-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Untitled--10-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--10-.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--9-.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Untitled--9-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/Untitled--9-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Untitled--9-.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdeploy-deep-learning-model%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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diff --git a/news/dify-ai-integrates-jina-embeddings-for-rag/index.html b/news/dify-ai-integrates-jina-embeddings-for-rag/index.html
index 0134fa4177c..3a5d44ab6d8 100644
--- a/news/dify-ai-integrates-jina-embeddings-for-rag/index.html
+++ b/news/dify-ai-integrates-jina-embeddings-for-rag/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Dify.AI integrates Jina Embeddings for RAG</title><meta charset="utf-8"><meta name="title" content="Dify.AI integrates Jina Embeddings for RAG"><meta name="description" content="Dify.AI, a leading open-source platform specialized in creating generative AI applications, is now leveraging Jina Embeddings v2! "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/dify-ai-integrates-jina-embeddings-for-rag"><meta property="og:title" content="Dify.AI integrates Jina Embeddings for RAG"><meta property="og:description" content="Dify.AI, a leading open-source platform specialized in creating generative AI applications, is now leveraging Jina Embeddings v2! "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Difyco.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/dify-ai-integrates-jina-embeddings-for-rag"><meta property="twitter:title" content="Dify.AI integrates Jina Embeddings for RAG"><meta property="twitter:description" content="Dify.AI, a leading open-source platform specialized in creating generative AI applications, is now leveraging Jina Embeddings v2! "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Difyco.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Dify.AI integrates Jina Embeddings for RAG</title><meta charset="utf-8"><meta name="title" content="Dify.AI integrates Jina Embeddings for RAG"><meta name="description" content="Dify.AI, a leading open-source platform specialized in creating generative AI applications, is now leveraging Jina Embeddings v2! "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/dify-ai-integrates-jina-embeddings-for-rag"><meta property="og:title" content="Dify.AI integrates Jina Embeddings for RAG"><meta property="og:description" content="Dify.AI, a leading open-source platform specialized in creating generative AI applications, is now leveraging Jina Embeddings v2! "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Difyco.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/dify-ai-integrates-jina-embeddings-for-rag"><meta property="twitter:title" content="Dify.AI integrates Jina Embeddings for RAG"><meta property="twitter:description" content="Dify.AI, a leading open-source platform specialized in creating generative AI applications, is now leveraging Jina Embeddings v2! "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Difyco.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Dify.AI integrates Jina Embeddings for RAG</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Dify.AI, a leading open-source platform specialized in creating generative AI applications, is now leveraging Jina Embeddings v2! </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 06, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Online LLM application development platform <a href="https://dify.ai/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Dify.AI</a> has integrated the <a href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Jina Embeddings v2 API</a> in its innovative AI toolkit for instant access when building and hosting LLM applications. All you need to do is add your Jina Embeddings API key via their intuitive web interface to get the full power of Jina AI’s industry-leading embedding models in your RAG (retrieval-augmented generation) applications.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://dify.ai/blog/integrating-jina-embeddings-v2-dify-enhancing-rag-applications?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Dify.AI x Jina AI：Dify now Integrates Jina Embedding Model - Dify Blog</div><div class="kg-bookmark-description">The next-gen development platform - Easily build and operate generative AI applications. Create Assistants API and GPTs based on any LLMs.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://framerusercontent.com/images/KWDRAMQLGjoMFBAjNjoCFMP7XI.png" alt=""><span class="kg-bookmark-author">Dify Blog</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://framerusercontent.com/images/2OftM3MmDVHkLcxaNn58ZNWaE.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Embedding API</div><div class="kg-bookmark-description">Top-performing, 8192-token length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/banner-embedding-api.png" alt=""></div></a></figure><h2 id="integrating-embeddings-in-rag">Integrating Embeddings in RAG</h2><p>Current AI architectures today have no direct way to integrate outside information sources. The model itself encodes information from its training data with varying levels of accuracy, and it is impractical to retrain the model every time there is new, potentially useful data that could be incorporated into it.</p><p>For example, I asked <a href="https://chat.jina.ai/chat?ref=jina-ai-gmbh.ghost.io">JinaChat</a> a question about current events:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot-2023-12-01-at-11.48.59.png" class="kg-image" alt="Screenshot 2023-12-01 at 11.48.59.png" width="1408" height="1654" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Screenshot-2023-12-01-at-11.48.59.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/Screenshot-2023-12-01-at-11.48.59.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot-2023-12-01-at-11.48.59.png 1408w" sizes="(min-width: 720px) 720px"></figure><p>The only way to ensure that an LLM has the information needed to answer a factual question is to provide it in the prompt:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot-2023-12-01-at-11.53.33.png" class="kg-image" alt="Screenshot 2023-12-01 at 11.53.33.png" width="1316" height="1186" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Screenshot-2023-12-01-at-11.53.33.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/Screenshot-2023-12-01-at-11.53.33.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot-2023-12-01-at-11.53.33.png 1316w" sizes="(min-width: 720px) 720px"></figure><p>Naturally, an LLM that only answers questions correctly if you include the answer in your question isn’t very useful. This has led to a body of techniques called <strong>Retrieval-Augmented Generation</strong> or <strong>RAG</strong>. RAG is a framework installed around an LLM that searches external information sources for materials that might contain the information needed to answer a user’s request and then presents them, with the user’s prompt, to the LLM.</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/image-2.png" class="kg-image" alt="" width="2000" height="938" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/image-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/12/image-2.png 2400w" sizes="(min-width: 1200px) 1200px"></figure><p>This strategy has the added benefit that LLMs hallucinate much less when they are expected to handle a given text rather than recall things they might partially remember from training.</p><h2 id="leveraging-jina-embeddings-superior-performance">Leveraging Jina Embeddings Superior Performance</h2><p><a href="http://dify.ai/?ref=jina-ai-gmbh.ghost.io">Dify.AI</a> has integrated Jina Embeddings v2 to enhance retrieval quality for RAG prompting. Jina AI’s models provide <a href="https://blog.llamaindex.ai/boosting-rag-picking-the-best-embedding-reranker-models-42d079022e83?ref=jina-ai-gmbh.ghost.io">state-of-the-art accuracy in RAG applications</a>, and <a href="https://jina.ai/news/jina-embeddings-2-the-best-solution-for-embedding-long-documents/?ref=jina-ai-gmbh.ghost.io">with an input window of 8,192 tokens</a>, they can support much larger and more complex questions than most competing models at a much lower price.</p><p>You can now use Jina Embeddings in your LLM projects via <a href="http://dify.ai/?ref=jina-ai-gmbh.ghost.io">Dify.AI</a>’s intuitive application builder, as shown in the video below or in the <a href="https://dify.ai/blog/integrating-jina-embeddings-v2-dify-enhancing-rag-applications?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">post on Dify.AI's blog</a>:</p><figure class="kg-card kg-video-card kg-width-regular" data-kg-thumbnail="https://jina-ai-gmbh.ghost.io/content/media/2023/12/ssstwitter.com_1701878449396_thumb.jpg" data-kg-custom-thumbnail="">
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Dify.AI integrates Jina Embeddings for RAG</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Dify.AI, a leading open-source platform specialized in creating generative AI applications, is now leveraging Jina Embeddings v2! </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 06, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Online LLM application development platform <a href="https://dify.ai/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Dify.AI</a> has integrated the <a href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Jina Embeddings v2 API</a> in its innovative AI toolkit for instant access when building and hosting LLM applications. All you need to do is add your Jina Embeddings API key via their intuitive web interface to get the full power of Jina AI’s industry-leading embedding models in your RAG (retrieval-augmented generation) applications.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://dify.ai/blog/integrating-jina-embeddings-v2-dify-enhancing-rag-applications?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Dify.AI x Jina AI：Dify now Integrates Jina Embedding Model - Dify Blog</div><div class="kg-bookmark-description">The next-gen development platform - Easily build and operate generative AI applications. Create Assistants API and GPTs based on any LLMs.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://framerusercontent.com/images/KWDRAMQLGjoMFBAjNjoCFMP7XI.png" alt=""><span class="kg-bookmark-author">Dify Blog</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://framerusercontent.com/images/2OftM3MmDVHkLcxaNn58ZNWaE.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Embedding API</div><div class="kg-bookmark-description">Top-performing, 8192-token length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/banner-embedding-api.png" alt=""></div></a></figure><h2 id="integrating-embeddings-in-rag">Integrating Embeddings in RAG</h2><p>Current AI architectures today have no direct way to integrate outside information sources. The model itself encodes information from its training data with varying levels of accuracy, and it is impractical to retrain the model every time there is new, potentially useful data that could be incorporated into it.</p><p>For example, I asked <a href="https://chat.jina.ai/chat?ref=jina-ai-gmbh.ghost.io">JinaChat</a> a question about current events:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot-2023-12-01-at-11.48.59.png" class="kg-image" alt="Screenshot 2023-12-01 at 11.48.59.png" width="1408" height="1654" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Screenshot-2023-12-01-at-11.48.59.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/Screenshot-2023-12-01-at-11.48.59.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot-2023-12-01-at-11.48.59.png 1408w" sizes="(min-width: 720px) 720px"></figure><p>The only way to ensure that an LLM has the information needed to answer a factual question is to provide it in the prompt:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot-2023-12-01-at-11.53.33.png" class="kg-image" alt="Screenshot 2023-12-01 at 11.53.33.png" width="1316" height="1186" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Screenshot-2023-12-01-at-11.53.33.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/Screenshot-2023-12-01-at-11.53.33.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot-2023-12-01-at-11.53.33.png 1316w" sizes="(min-width: 720px) 720px"></figure><p>Naturally, an LLM that only answers questions correctly if you include the answer in your question isn’t very useful. This has led to a body of techniques called <strong>Retrieval-Augmented Generation</strong> or <strong>RAG</strong>. RAG is a framework installed around an LLM that searches external information sources for materials that might contain the information needed to answer a user’s request and then presents them, with the user’s prompt, to the LLM.</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/image-2.png" class="kg-image" alt="" width="2000" height="938" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/12/image-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/12/image-2.png 2400w" sizes="(min-width: 1200px) 1200px"></figure><p>This strategy has the added benefit that LLMs hallucinate much less when they are expected to handle a given text rather than recall things they might partially remember from training.</p><h2 id="leveraging-jina-embeddings-superior-performance">Leveraging Jina Embeddings Superior Performance</h2><p><a href="http://dify.ai/?ref=jina-ai-gmbh.ghost.io">Dify.AI</a> has integrated Jina Embeddings v2 to enhance retrieval quality for RAG prompting. Jina AI’s models provide <a href="https://blog.llamaindex.ai/boosting-rag-picking-the-best-embedding-reranker-models-42d079022e83?ref=jina-ai-gmbh.ghost.io">state-of-the-art accuracy in RAG applications</a>, and <a href="https://jina.ai/news/jina-embeddings-2-the-best-solution-for-embedding-long-documents/?ref=jina-ai-gmbh.ghost.io">with an input window of 8,192 tokens</a>, they can support much larger and more complex questions than most competing models at a much lower price.</p><p>You can now use Jina Embeddings in your LLM projects via <a href="http://dify.ai/?ref=jina-ai-gmbh.ghost.io">Dify.AI</a>’s intuitive application builder, as shown in the video below or in the <a href="https://dify.ai/blog/integrating-jina-embeddings-v2-dify-enhancing-rag-applications?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">post on Dify.AI's blog</a>:</p><figure class="kg-card kg-video-card kg-width-regular" data-kg-thumbnail="https://jina-ai-gmbh.ghost.io/content/media/2023/12/ssstwitter.com_1701878449396_thumb.jpg" data-kg-custom-thumbnail="">
             <div class="kg-video-container">
                 <video src="https://jina-ai-gmbh.ghost.io/content/media/2023/12/ssstwitter.com_1701878449396.mp4" poster="https://img.spacergif.org/v1/1244x720/0a/spacer.png" width="1244" height="720" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/media/2023/12/ssstwitter.com_1701878449396_thumb.jpg') 50% 50% / cover no-repeat;"></video>
                 <div class="kg-video-overlay">
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 01, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>At the EMNLP2023 BoF (birds of a feather) session, we're set to explore the frontiers of embeddings. While recent developments like <code>jina-embeddings-v2</code> <a href="https://blog.llamaindex.ai/boosting-rag-picking-the-best-embedding-reranker-models-42d079022e83?ref=jina-ai-gmbh.ghost.io">have made significant strides</a>, they also open the door to new questions and challenges in the field. This 1.5-hour session is a platform to tackle these emerging issues in embeddings. You can register via the Google Form below:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://forms.gle/z5E5BFvQqFf3fpW68?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">EMNLP 2023/BoF 6: Embeddings</div><div class="kg-bookmark-description">What: A BoF (Birds of a Feather) in-person session on Embeddings, co-organized by EMNLP PC and Jina AI. When &amp; Where: Saturday, December 9th, from 11:00 AM to 12:30 PM Singapore time at ‘Aquarius 1’ room. Highlights: multimodal embeddings, long context embeddings, multi- and bilingual embeddings,…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ssl.gstatic.com/docs/forms/device_home/android_192.png" alt=""><span class="kg-bookmark-author">Google Docs</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://lh5.googleusercontent.com/osAO-g4ajeOU2CCB6rhbi9UfHIsCU8_oa8HaZjsx0e6UuWoulCngSugztdf3Yoe2a5FQVSymImg=w1200-h630-p" alt=""></div></a></figure><h2 id="event-details">Event Details</h2><p><strong>Date &amp; Time:</strong> December 9th, 11:00 AM - 12:30 PM Singapore time, at 'Aquarius 1' room.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">📆</div><div class="kg-callout-text">Add Embeddings BoF at EMNLP to your calendar now [<a href="https://www.google.com/calendar/render?action=TEMPLATE&amp;text=Embeddings%3A+Birds+of+a+Feather+6&amp;dates=20231209T040000%2F20231209T053000&amp;ctz=UTC&amp;details=Birds+of+a+Feather+6&amp;location=&amp;sprop=&amp;sprop=name%3A&amp;ref=jina-ai-gmbh.ghost.io" target="_blank">Google</a>][<a href="https://outlook.office365.com/owa/?path=%2Fcalendar%2Faction%2Fcompose&amp;rru=addevent&amp;subject=Embeddings%3A+Birds+of+a+Feather+6&amp;startdt=2023-12-09T05%3A00%3A00+01%3A00&amp;enddt=2023-12-09T06%3A30%3A00+01%3A00&amp;body=Birds+of+a+Feather+6&amp;location=true&amp;ref=jina-ai-gmbh.ghost.io" target="_blank">Office365</a>][<a href="about:blank">Outlook</a>][<a href="about:blank">iCal</a>]</div></div><p><strong>Format:</strong> In-person, with an interactive and collaborative approach.<br><strong>Registration: </strong><a href="https://forms.gle/z5E5BFvQqFf3fpW68?ref=jina-ai-gmbh.ghost.io">Google Form</a></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/image-1.png" class="kg-image" alt="" width="1288" height="962" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/image-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/image-1.png 1288w" sizes="(min-width: 720px) 720px"></figure><h2 id="themes-and-highlights">Themes and Highlights</h2><p>This BoF session features a set of thought-provoking presentations, panel discussions, and lightning talks, reflecting the ongoing evolution in the field:</p><h4 id="multimodal-embeddings">Multimodal Embeddings:</h4><ul><li>"How can multimodal embeddings be advanced to handle the context and nuance in diverse data types?"</li><li>"What are the challenges in scaling multimodal embeddings for complex applications like personalized AI assistants?"</li><li>"In what ways can vector databases be integrated with multimodal embeddings to enhance their contextual understanding?"</li></ul><h4 id="long-context-embeddings">Long Context Embeddings:</h4><ul><li>"How can long context embeddings be optimized to reduce hallucination in LLMs?"</li><li>"What are the computational and practical challenges in scaling embeddings to handle longer contexts efficiently?"</li><li>"Beyond the 8K limit, what novel approaches can push the boundaries of context length in embeddings?"</li></ul><h4 id="multiand-bilingual-embeddings">Multi- and Bilingual Embeddings:</h4><ul><li>"What are the key hurdles in achieving high accuracy and cultural sensitivity in multi- and bilingual embeddings?"</li><li>"How can embeddings tackle the challenge of representing less popular factual knowledge accurately?"</li><li>"In the development of bilingual embeddings, how can we address the lack of in-house NLP expertise and high development costs?"</li></ul><h4 id="embeddings-for-low-resource-languages">Embeddings for Low-Resource Languages:</h4><ul><li>"What innovative strategies can be adopted to significantly boost support for low-resource languages in embeddings?"</li><li>"How can we incentivize the development of embeddings for less popular languages amidst high costs and complexity?"</li><li>"What role can transfer learning and fine-tuning play in enhancing embeddings for low-resource languages?"</li></ul><h4 id="rag-retrieval-augmented-generation-applications">RAG (Retrieval Augmented Generation) Applications:</h4><ul><li>"How can RAG applications overcome the limitations of vector databases in understanding complex, nuanced meanings?"</li><li>"What are the potentials and challenges of using RAG in AI assistants for deep personalization and context understanding?"</li><li>"Considering the current state of RAG, what are the ethical considerations and potential risks in its widespread adoption?"</li></ul><p>For more information, visit <a 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 01, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>At the EMNLP2023 BoF (birds of a feather) session, we're set to explore the frontiers of embeddings. While recent developments like <code>jina-embeddings-v2</code> <a href="https://blog.llamaindex.ai/boosting-rag-picking-the-best-embedding-reranker-models-42d079022e83?ref=jina-ai-gmbh.ghost.io">have made significant strides</a>, they also open the door to new questions and challenges in the field. This 1.5-hour session is a platform to tackle these emerging issues in embeddings. You can register via the Google Form below:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://forms.gle/z5E5BFvQqFf3fpW68?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">EMNLP 2023/BoF 6: Embeddings</div><div class="kg-bookmark-description">What: A BoF (Birds of a Feather) in-person session on Embeddings, co-organized by EMNLP PC and Jina AI. When &amp; Where: Saturday, December 9th, from 11:00 AM to 12:30 PM Singapore time at ‘Aquarius 1’ room. Highlights: multimodal embeddings, long context embeddings, multi- and bilingual embeddings,…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ssl.gstatic.com/docs/forms/device_home/android_192.png" alt=""><span class="kg-bookmark-author">Google Docs</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://lh5.googleusercontent.com/osAO-g4ajeOU2CCB6rhbi9UfHIsCU8_oa8HaZjsx0e6UuWoulCngSugztdf3Yoe2a5FQVSymImg=w1200-h630-p" alt=""></div></a></figure><h2 id="event-details">Event Details</h2><p><strong>Date &amp; Time:</strong> December 9th, 11:00 AM - 12:30 PM Singapore time, at 'Aquarius 1' room.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">📆</div><div class="kg-callout-text">Add Embeddings BoF at EMNLP to your calendar now [<a href="https://www.google.com/calendar/render?action=TEMPLATE&amp;text=Embeddings%3A+Birds+of+a+Feather+6&amp;dates=20231209T040000%2F20231209T053000&amp;ctz=UTC&amp;details=Birds+of+a+Feather+6&amp;location=&amp;sprop=&amp;sprop=name%3A&amp;ref=jina-ai-gmbh.ghost.io" target="_blank">Google</a>][<a href="https://outlook.office365.com/owa/?path=%2Fcalendar%2Faction%2Fcompose&amp;rru=addevent&amp;subject=Embeddings%3A+Birds+of+a+Feather+6&amp;startdt=2023-12-09T05%3A00%3A00+01%3A00&amp;enddt=2023-12-09T06%3A30%3A00+01%3A00&amp;body=Birds+of+a+Feather+6&amp;location=true&amp;ref=jina-ai-gmbh.ghost.io" target="_blank">Office365</a>][<a href="about:blank">Outlook</a>][<a href="about:blank">iCal</a>]</div></div><p><strong>Format:</strong> In-person, with an interactive and collaborative approach.<br><strong>Registration: </strong><a href="https://forms.gle/z5E5BFvQqFf3fpW68?ref=jina-ai-gmbh.ghost.io">Google Form</a></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/image-1.png" class="kg-image" alt="" width="1288" height="962" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/image-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/image-1.png 1288w" sizes="(min-width: 720px) 720px"></figure><h2 id="themes-and-highlights">Themes and Highlights</h2><p>This BoF session features a set of thought-provoking presentations, panel discussions, and lightning talks, reflecting the ongoing evolution in the field:</p><h4 id="multimodal-embeddings">Multimodal Embeddings:</h4><ul><li>"How can multimodal embeddings be advanced to handle the context and nuance in diverse data types?"</li><li>"What are the challenges in scaling multimodal embeddings for complex applications like personalized AI assistants?"</li><li>"In what ways can vector databases be integrated with multimodal embeddings to enhance their contextual understanding?"</li></ul><h4 id="long-context-embeddings">Long Context Embeddings:</h4><ul><li>"How can long context embeddings be optimized to reduce hallucination in LLMs?"</li><li>"What are the computational and practical challenges in scaling embeddings to handle longer contexts efficiently?"</li><li>"Beyond the 8K limit, what novel approaches can push the boundaries of context length in embeddings?"</li></ul><h4 id="multiand-bilingual-embeddings">Multi- and Bilingual Embeddings:</h4><ul><li>"What are the key hurdles in achieving high accuracy and cultural sensitivity in multi- and bilingual embeddings?"</li><li>"How can embeddings tackle the challenge of representing less popular factual knowledge accurately?"</li><li>"In the development of bilingual embeddings, how can we address the lack of in-house NLP expertise and high development costs?"</li></ul><h4 id="embeddings-for-low-resource-languages">Embeddings for Low-Resource Languages:</h4><ul><li>"What innovative strategies can be adopted to significantly boost support for low-resource languages in embeddings?"</li><li>"How can we incentivize the development of embeddings for less popular languages amidst high costs and complexity?"</li><li>"What role can transfer learning and fine-tuning play in enhancing embeddings for low-resource languages?"</li></ul><h4 id="rag-retrieval-augmented-generation-applications">RAG (Retrieval Augmented Generation) Applications:</h4><ul><li>"How can RAG applications overcome the limitations of vector databases in understanding complex, nuanced meanings?"</li><li>"What are the potentials and challenges of using RAG in AI assistants for deep personalization and context understanding?"</li><li>"Considering the current state of RAG, what are the ethical considerations and potential risks in its widespread adoption?"</li></ul><p>For more information, visit <a href="https://2023.emnlp.org/program/bof/?ref=jina-ai-gmbh.ghost.io">EMNLP2023 Program</a>. </p><p>We are looking forward to seeing you in person in Singapore next week!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-ap-virtual-ticket-giveaway-for-pycon-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina AI Virtual Ticket Giveaway for PyCon 2023 Online</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina AI's giving away PyCon US Online passes. Deadline April 10.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/avatar.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jocelyn Matthews</div><div class="q-item__label q-item__label--caption text-caption">April 03, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/virtual-ticket-promo.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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diff --git a/news/distilled-ai-using-large-models-to-teach-smaller-ones/index.html b/news/distilled-ai-using-large-models-to-teach-smaller-ones/index.html
index e6044c34db6..d404f847188 100644
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+++ b/news/distilled-ai-using-large-models-to-teach-smaller-ones/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Distilled AI: Using Large Models to Teach Smaller Ones</title><meta charset="utf-8"><meta name="title" content="Distilled AI: Using Large Models to Teach Smaller Ones"><meta name="description" content="Better AI with smaller models and cheaper data costs! But only if you use AI to train AI."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/distilled-ai-using-large-models-to-teach-smaller-ones"><meta property="og:title" content="Distilled AI: Using Large Models to Teach Smaller Ones"><meta property="og:description" content="Better AI with smaller models and cheaper data costs! But only if you use AI to train AI."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/373440831_1747441042382077_2749157957406765240_n.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/distilled-ai-using-large-models-to-teach-smaller-ones"><meta property="twitter:title" content="Distilled AI: Using Large Models to Teach Smaller Ones"><meta property="twitter:description" content="Better AI with smaller models and cheaper data costs! But only if you use AI to train AI."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/373440831_1747441042382077_2749157957406765240_n.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Distilled AI: Using Large Models to Teach Smaller Ones</title><meta charset="utf-8"><meta name="title" content="Distilled AI: Using Large Models to Teach Smaller Ones"><meta name="description" content="Better AI with smaller models and cheaper data costs! But only if you use AI to train AI."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/distilled-ai-using-large-models-to-teach-smaller-ones"><meta property="og:title" content="Distilled AI: Using Large Models to Teach Smaller Ones"><meta property="og:description" content="Better AI with smaller models and cheaper data costs! But only if you use AI to train AI."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/373440831_1747441042382077_2749157957406765240_n.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/distilled-ai-using-large-models-to-teach-smaller-ones"><meta property="twitter:title" content="Distilled AI: Using Large Models to Teach Smaller Ones"><meta property="twitter:description" content="Better AI with smaller models and cheaper data costs! But only if you use AI to train AI."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/373440831_1747441042382077_2749157957406765240_n.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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But only if you use AI to train AI.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 105px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/MWI_6577--1-.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/PXL_20221116_122857628.PORTRAIT.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 75px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alaeddine Abdessalem, Sebastian Weisshaar, Sami Jaghouar, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 07, 2023 • 11 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>A lot of public attention has gone into generative large language models and AI art because they produce striking results, even in the eyes of people who don’t know anything about AI. However, one area has garnered a lot of research and commercial interest without attracting as much attention from the general public: Using AI models to write computer code. </p><p>In this article, we'll show how we fine-tuned a one-billion-parameter AI model – <a href="https://github.com/bigcode-project/starcoder?ref=jina-ai-gmbh.ghost.io">StarCoder 1B</a>, a relatively small model – to improve its Python programming skills, raising its score on the <a href="https://paperswithcode.com/sota/code-generation-on-humaneval?ref=jina-ai-gmbh.ghost.io">HumanEval benchmark</a> from 15.2% to 27.0%. We did this by distilling the knowledge present in <a href="https://platform.openai.com/docs/models/gpt-3-5?ref=jina-ai-gmbh.ghost.io">GPT 3.5</a>, a 180-billion-parameter large language model that itself scores 48.1% on the same benchmark, into the much smaller model. Our method was to prompt GPT 3.5 into creating a roughly 120-thousand item Python programming dataset, which we then used to fine-tune the StarCoder model.</p><h2 id="ai-models-that-write-code">AI models that write code &nbsp;</h2><p>A number of AI models have had some success actually writing code directly in response to problem descriptions. <a href="https://github.com/features/copilot?ref=jina-ai-gmbh.ghost.io">GitHub Copilot</a> is available commercially, and the GPT series from OpenAI will write code for you if you ask it to, but <a href="https://paperswithcode.com/sota/code-generation-on-humaneval?ref=jina-ai-gmbh.ghost.io">there are also dozens of other models</a> that have at least some coding ability.</p><p>This technology has the potential to be very disruptive to the software development industry.</p><p>One major barrier to implementing AI coding is one that holds up a lot of AI work: The kinds of very large AI models that produce high-quality results are very expensive to train and run. Members of the GPT family of closed-access models are not only expensive but also remotely hosted with unclear security. Ideally, we would like to have smaller but more specialized models that can give comparable performance to the large models but run on less expensive hardware that users can keep under their own control.</p><p>This article is a step in that direction, demonstrating that it is feasible, and a way to do it inexpensively.</p><h2 id="more-data-vs-better-data-scaling-factors-in-ai">More data vs. better data: Scaling factors in AI</h2><p>All else being equal, we know that the performance of an AI model depends on <a href="https://doi.org/10.48550/arXiv.2001.08361?ref=jina-ai-gmbh.ghost.io">three scaling factors</a>:</p><ul><li><strong>Training time</strong>. Models trained for more cycles perform better than identical models trained for fewer on the same data.</li><li><strong>Data size</strong>. Models trained with more data perform better than identical models trained with less, given the same training time.</li><li><strong>Number of parameters</strong>, i.e., the size of the model. A model with more weights (or more neurons, which is the same thing) performs better than one with fewer, given the same training data and training time.</li></ul><p>To build a model with a smaller size but comparable performance to a larger one, we should, logically, use more data and more training cycles. But all else is not always equal. Data quality is a more difficult factor to quantify than training time, data size, or model size, but it makes a significant difference to performance. Intuitively, the model should learn better to solve a particular kind of problem if it learns from the most instructive examples. The problem with improving data quality is that it can be difficult or expensive to curate enough high-quality data to make a difference.</p><h2 id="using-ai-models-as-both-teacher-and-student">Using AI models as both teacher and student</h2><p>One solution is to use AI models to create training data. This has the benefit of being much cheaper than commissioning humans to create enough data or paying them to curate existing data, picking out just the most relevant examples.</p><p>At first glance, this seems counter-intuitive. If the model is already good enough to create high-quality training data to learn to solve a problem, then surely it can’t use this knowledge to improve its own performance. And this is true. But when the goal is to train a smaller, less capable AI to improve its performance, and we use a much more capable AI to create the training data, it makes just as much sense as a child learning to read from a teacher who is already literate.</p><p>This is especially relevant to our goal of creating a smaller model with performance comparable to larger ones. We know that a smaller model will need more examples and more training time to reach the same result as a larger one, if it can reach it at all. What a 100 billion parameter model can learn from a thousand examples of sufficient quality might take a million equally high-quality examples for a 1 billion parameter model. The cost of human construction or curation of a million items of training data is a lot more than a thousand, no matter what the problem is.</p><p>To address this problem, we took inspiration from the recent paper <em>Textbooks Are All You Need</em> (<a href="https://doi.org/10.48550/arXiv.2306.11644?ref=jina-ai-gmbh.ghost.io">Gunasekar et al. 2023</a>), which introduces the phi-1 family of models, which write Python code after being trained on a mixture of human and synthetic data. While they started with completely untrained models, we took an existing open access model — the one billion parameter <a href="https://github.com/bigcode-project/starcoder?ref=jina-ai-gmbh.ghost.io">StarCoder 1B</a> model (<a href="https://doi.org/10.48550/arXiv.2305.06161?ref=jina-ai-gmbh.ghost.io">Li et al. 2023</a>) that has already been trained to write code in 86 languages – and then fine-tuned it exclusively with Python code examples created by ChatGPT 3.5.</p><h2 id="creating-the-data">Creating the data</h2><p>We constructed roughly 120,000 training exercises using ChatGPT 3.5.</p><p>We were aware that one major issue in using model-synthesized data is ensuring sufficient diversity. To address this problem, we first decided on 60 broad topic labels in Python programming. For example:</p><ul><li>Python Basic Operators</li><li>Control Structures in Python</li><li>Functions in Python</li><li>Python Lambda Functions</li></ul><p>The <a href="https://github.com/jina-ai/textbook/blob/main/textbook/dataset_gen/tree/topics.csv?ref=jina-ai-gmbh.ghost.io">complete list of topics</a> is documented in <a href="https://github.com/jina-ai/textbook?ref=jina-ai-gmbh.ghost.io">the project’s GitHub repository</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/textbook?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/textbook: distill chatGPT coding ability into small model (1b)</div><div class="kg-bookmark-description">distill chatGPT coding ability into small model (1b) - GitHub - jina-ai/textbook: distill chatGPT coding ability into small model (1b)</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/36f220c7a33fa0a997544fab3950924bee95917428dc2662e8451c586124ce68/jina-ai/textbook" alt=""></div></a></figure><p>We decided that we would use only 42 of them in this experiment (the ones marked with a <code>1</code> in the <code>Mixing</code> column). For each of those 42 topics, we queried GPT 4 to give us 10 sub-topics using the prompt below:</p><pre><code class="language-Text">For a Python textbook give me 10 subtopics of {topic}, formatted as a Python list. 
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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But only if you use AI to train AI.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 105px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 151.086%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/MWI_6577--1-.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 132.812%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/PXL_20221116_122857628.PORTRAIT.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 75px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alaeddine Abdessalem, Sebastian Weisshaar, Sami Jaghouar, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 07, 2023 • 11 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>A lot of public attention has gone into generative large language models and AI art because they produce striking results, even in the eyes of people who don’t know anything about AI. However, one area has garnered a lot of research and commercial interest without attracting as much attention from the general public: Using AI models to write computer code. </p><p>In this article, we'll show how we fine-tuned a one-billion-parameter AI model – <a href="https://github.com/bigcode-project/starcoder?ref=jina-ai-gmbh.ghost.io">StarCoder 1B</a>, a relatively small model – to improve its Python programming skills, raising its score on the <a href="https://paperswithcode.com/sota/code-generation-on-humaneval?ref=jina-ai-gmbh.ghost.io">HumanEval benchmark</a> from 15.2% to 27.0%. We did this by distilling the knowledge present in <a href="https://platform.openai.com/docs/models/gpt-3-5?ref=jina-ai-gmbh.ghost.io">GPT 3.5</a>, a 180-billion-parameter large language model that itself scores 48.1% on the same benchmark, into the much smaller model. Our method was to prompt GPT 3.5 into creating a roughly 120-thousand item Python programming dataset, which we then used to fine-tune the StarCoder model.</p><h2 id="ai-models-that-write-code">AI models that write code &nbsp;</h2><p>A number of AI models have had some success actually writing code directly in response to problem descriptions. <a href="https://github.com/features/copilot?ref=jina-ai-gmbh.ghost.io">GitHub Copilot</a> is available commercially, and the GPT series from OpenAI will write code for you if you ask it to, but <a href="https://paperswithcode.com/sota/code-generation-on-humaneval?ref=jina-ai-gmbh.ghost.io">there are also dozens of other models</a> that have at least some coding ability.</p><p>This technology has the potential to be very disruptive to the software development industry.</p><p>One major barrier to implementing AI coding is one that holds up a lot of AI work: The kinds of very large AI models that produce high-quality results are very expensive to train and run. Members of the GPT family of closed-access models are not only expensive but also remotely hosted with unclear security. Ideally, we would like to have smaller but more specialized models that can give comparable performance to the large models but run on less expensive hardware that users can keep under their own control.</p><p>This article is a step in that direction, demonstrating that it is feasible, and a way to do it inexpensively.</p><h2 id="more-data-vs-better-data-scaling-factors-in-ai">More data vs. better data: Scaling factors in AI</h2><p>All else being equal, we know that the performance of an AI model depends on <a href="https://doi.org/10.48550/arXiv.2001.08361?ref=jina-ai-gmbh.ghost.io">three scaling factors</a>:</p><ul><li><strong>Training time</strong>. Models trained for more cycles perform better than identical models trained for fewer on the same data.</li><li><strong>Data size</strong>. Models trained with more data perform better than identical models trained with less, given the same training time.</li><li><strong>Number of parameters</strong>, i.e., the size of the model. A model with more weights (or more neurons, which is the same thing) performs better than one with fewer, given the same training data and training time.</li></ul><p>To build a model with a smaller size but comparable performance to a larger one, we should, logically, use more data and more training cycles. But all else is not always equal. Data quality is a more difficult factor to quantify than training time, data size, or model size, but it makes a significant difference to performance. Intuitively, the model should learn better to solve a particular kind of problem if it learns from the most instructive examples. The problem with improving data quality is that it can be difficult or expensive to curate enough high-quality data to make a difference.</p><h2 id="using-ai-models-as-both-teacher-and-student">Using AI models as both teacher and student</h2><p>One solution is to use AI models to create training data. This has the benefit of being much cheaper than commissioning humans to create enough data or paying them to curate existing data, picking out just the most relevant examples.</p><p>At first glance, this seems counter-intuitive. If the model is already good enough to create high-quality training data to learn to solve a problem, then surely it can’t use this knowledge to improve its own performance. And this is true. But when the goal is to train a smaller, less capable AI to improve its performance, and we use a much more capable AI to create the training data, it makes just as much sense as a child learning to read from a teacher who is already literate.</p><p>This is especially relevant to our goal of creating a smaller model with performance comparable to larger ones. We know that a smaller model will need more examples and more training time to reach the same result as a larger one, if it can reach it at all. What a 100 billion parameter model can learn from a thousand examples of sufficient quality might take a million equally high-quality examples for a 1 billion parameter model. The cost of human construction or curation of a million items of training data is a lot more than a thousand, no matter what the problem is.</p><p>To address this problem, we took inspiration from the recent paper <em>Textbooks Are All You Need</em> (<a href="https://doi.org/10.48550/arXiv.2306.11644?ref=jina-ai-gmbh.ghost.io">Gunasekar et al. 2023</a>), which introduces the phi-1 family of models, which write Python code after being trained on a mixture of human and synthetic data. While they started with completely untrained models, we took an existing open access model — the one billion parameter <a href="https://github.com/bigcode-project/starcoder?ref=jina-ai-gmbh.ghost.io">StarCoder 1B</a> model (<a href="https://doi.org/10.48550/arXiv.2305.06161?ref=jina-ai-gmbh.ghost.io">Li et al. 2023</a>) that has already been trained to write code in 86 languages – and then fine-tuned it exclusively with Python code examples created by ChatGPT 3.5.</p><h2 id="creating-the-data">Creating the data</h2><p>We constructed roughly 120,000 training exercises using ChatGPT 3.5.</p><p>We were aware that one major issue in using model-synthesized data is ensuring sufficient diversity. To address this problem, we first decided on 60 broad topic labels in Python programming. For example:</p><ul><li>Python Basic Operators</li><li>Control Structures in Python</li><li>Functions in Python</li><li>Python Lambda Functions</li></ul><p>The <a href="https://github.com/jina-ai/textbook/blob/main/textbook/dataset_gen/tree/topics.csv?ref=jina-ai-gmbh.ghost.io">complete list of topics</a> is documented in <a href="https://github.com/jina-ai/textbook?ref=jina-ai-gmbh.ghost.io">the project’s GitHub repository</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/textbook?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/textbook: distill chatGPT coding ability into small model (1b)</div><div class="kg-bookmark-description">distill chatGPT coding ability into small model (1b) - GitHub - jina-ai/textbook: distill chatGPT coding ability into small model (1b)</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/36f220c7a33fa0a997544fab3950924bee95917428dc2662e8451c586124ce68/jina-ai/textbook" alt=""></div></a></figure><p>We decided that we would use only 42 of them in this experiment (the ones marked with a <code>1</code> in the <code>Mixing</code> column). For each of those 42 topics, we queried GPT 4 to give us 10 sub-topics using the prompt below:</p><pre><code class="language-Text">For a Python textbook give me 10 subtopics of {topic}, formatted as a Python list. 
 Just provide the titles and give no explanation.
 Format the result as Python list.
 </code></pre><p>We then repeated this procedure to get five very fine-grained topics for each of the 420 subtopics. This yields approximately 2000 topics.</p><p>We furthermore manually constructed a list of 40 professions. For example:</p><ul><li>Economist</li><li>Engineer</li><li>Social Worker</li><li>Game Developer</li></ul><p>The <a href="https://github.com/jina-ai/textbook/blob/main/textbook/dataset_gen/tree/professions.json?ref=jina-ai-gmbh.ghost.io">complete list of professions</a> is also documented in <a href="https://github.com/jina-ai/textbook?ref=jina-ai-gmbh.ghost.io">the project’s GitHub repository</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/textbook?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/textbook: distill chatGPT coding ability into small model (1b)</div><div class="kg-bookmark-description">distill chatGPT coding ability into small model (1b) - GitHub - jina-ai/textbook: distill chatGPT coding ability into small model (1b)</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/36f220c7a33fa0a997544fab3950924bee95917428dc2662e8451c586124ce68/jina-ai/textbook" alt=""></div></a></figure><p>To generate code exercises, we selected two topics randomly from the list of 2000 and one profession from the list of 40 and then prompted ChatGPT 3.5 with the following:</p><pre><code class="language-Python">Create a code completion exercise on the intersection of {topic 1} and {topic 2}.
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Do You Truly Need a Dedicated Vector Store?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. Navigating enterprise mazes &amp; startup vibes. Where's search headed next?</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 01, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the rapidly shifting landscape of technology, it's all too easy to be ensnared by the latest buzzwords and narratives. One such prevailing discourse is the perceived necessity for a dedicated "vector store" or "vector database" in the modern AI stack. This notion is propelled by the increasing application of deep neural networks to search, leading many to believe that managing a vast number of dense vectors demands a specialized store. But is this narrative grounded in reality?</p><p>Drawing from the insights of the paper "<strong>Vector Search with OpenAI Embeddings: Lucene Is All You Need</strong>" by Jimmy Lin etc., and enriched by the collective wisdom of the tech community, let's dissect this debate.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2308.14963?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Vector Search with OpenAI Embeddings: Lucene Is All You Need</div><div class="kg-bookmark-description">We provide a reproducible, end-to-end demonstration of vector search withOpenAI embeddings using Lucene on the popular MS MARCO passage ranking testcollection. The main goal of our work is to challenge the prevailing narrativethat a dedicated vector store is necessary to take advantage of recent…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Jimmy Lin</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><h2 id="lucenes-role-in-modern-vector-search">Lucene's Role in Modern Vector Search</h2><p>Lucene, renowned for its inverted index-based search, has long been a cornerstone in the search realm. Critics argue its limitations, particularly in contextual search with fuzzy logic like min edit distance. Yet, Lucene is far from stagnant. As described in the paper, the advent of hierarchical navigable small-world network (HNSW) indexes showcases Lucene's adaptability, proving its prowess in vector search capabilities on par with any dedicated vector store.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image.png" class="kg-image" alt="" width="1112" height="546" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image.png 1112w" sizes="(min-width: 720px) 720px"><figcaption>A standard bi-encoder architecture used in Jimmy's paper, where encoders generate dense vector representations (embeddings) from queries and documents (passages). Retrieval is framed as k-nearest neighbor search in vector space.</figcaption></figure><p>It's not just Lucene making waves. Vector indices are now industry staples. Giants like ElasticSearch, Postgresql, and Redis are embracing this trend. Google's recent endorsement of pgvector for their AlloyDB offering underscores the mainstream shift towards vector search.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.google.com/blog/products/databases/helping-developers-build-gen-ai-apps-with-google-cloud-databases?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Helping developers build Gen AI apps with Google Cloud PostgreSQL databases | Google Cloud Blog</div><div class="kg-bookmark-description">Announcing a series of new features and capabilities to help developers build enterprise generative AI apps with Google Cloud PostgreSQL databases.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ssl.gstatic.com/cloud/images/icons/favicon.ico" alt=""><span class="kg-bookmark-author">Google Cloud</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://storage.googleapis.com/gweb-cloudblog-publish/images/AlloyDB_AI_for_building_gen_AI_apps_Blog.max-2600x2600.jpg" alt=""></div></a></figure><h2 id="enterprise-search-challenges-navigating-the-vector-store-maze">Enterprise Search Challenges: Navigating the Vector Store Maze</h2><p>Modern enterprise architectures are intricate tapestries of legacy systems, cutting-edge solutions, and a myriad of tools aimed at solving specific problems. The introduction of a dedicated vector store would not just be a simple addition; it would be a paradigm shift. Historically, enterprises have shown a tendency to lean on tried-and-tested solutions, especially when significant investments have been made. Lucene-based platforms, with their proven track record, offer a sense of reliability. The challenge for enterprises is not just about technology but also about change management, training, and integration. The real question is: Is the potential performance gain worth the upheaval?</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/mermaid-diagram-2023-09-01-125304.svg" class="kg-image" alt="" width="170" height="150"><figcaption>Navigating the Vector Store Decision: A Strategic Framework for Enterprises</figcaption></figure><h2 id="startup-innovations-beyond-the-vector-store-hype">Startup Innovations: Beyond the Vector Store Hype</h2><p>The startup ecosystem thrives on disruption and innovation. The vision of a dedicated vector store is alluring, promising unparalleled performance and capabilities. But in the world of startups, vision needs to be backed by tangible benefits. The reality is that while vector stores offer a new approach, tools like Lucene have been refining their capabilities for years. For startups, the challenge is to prove that their solutions offer not just incremental improvements but transformative changes. In a data-driven world, the onus is on these startups to showcase empirical evidence of their superiority, not just in lab conditions but in real-world scenarios.</p><h2 id="achieving-the-ideal-performance-meets-practicality-in-search-solutions">Achieving the Ideal: Performance Meets Practicality in Search Solutions</h2><p>Performance is the holy grail in the world of search. But it's essential to understand that performance doesn't exist in a vacuum. It's intertwined with factors like cost, scalability, and ease of integration. While specialized vector databases might offer a performance edge in specific scenarios, solutions like Lucene bring a balance of performance, reliability, and familiarity. The challenge is to discern when to chase the bleeding edge of performance and when to opt for a more pragmatic, holistic solution. In a world inundated with options, the true art lies in making choices that deliver consistent value over time.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/benchmark-vector-search-databases-with-one-million-data/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Benchmark Vector Search Databases with One Million Data</div><div class="kg-bookmark-description">In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here’s a comprehensive benchmark to help guide you.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">DocArray 0.18.2 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--33-.png" alt=""></div></a></figure><h2 id="the-future-of-vector-search-lucene-vs-dedicated-stores">The Future of Vector Search: Lucene vs. Dedicated Stores</h2><p>The debate surrounding dedicated vector stores versus <a href="https://jina.ai/news/hype-and-hybrids-multimodal-search-means-more-than-keywords-and-vectors-2/?ref=jina-ai-gmbh.ghost.io">hybrid</a> Lucene <a href="https://jina.ai/news/hype-and-hybrids-multimodal-search-means-more-than-keywords-and-vectors-2/?ref=jina-ai-gmbh.ghost.io">solutions</a> is alive and well. However, a clear sentiment is emerging from the tech community: the inclination towards optimizing what we have rather than chasing the next shiny object. As we push the envelope in search capabilities, it's paramount to remember that often, the optimal solution is already within our grasp.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Insights</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdo-you-truly-need-a-dedicated-vector-store%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/artificial-general-intelligence-is-cursed-and-science-fiction-isnt-helping" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Artificial General Intelligence is Cursed, And Science Fiction isn't Helping</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">AI is cursed by intellectual hubris, moving goalposts, bad incentives, and science fiction. Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/fine-tuning-gpt-3-5-turbo-a-costly-mirage" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 25, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.044%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_modern_geometric_abstract_pattern_featuring_pu_24e4060e-dc76-4186-afb7-94d18d266b41.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/the-boundless-horizon-of-ai-its-not-just-about-the-size" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Beyond Sheer Scale: Navigating AI Alignment Odyssey</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">AI’s march forward isn't just about bigger models, but ensuring they harmonize with human values. Journey with us through the challenges, revelations, and aspirations at the forefront of AI safety and ethics.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">August 24, 2023 • 8 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.044%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_retrowave_sabattier_filter_sanriocore_in_the_sty_7881ce67-ea8f-417f-a204-bd101a3f58c0.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Do You Truly Need a Dedicated Vector Store?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. Navigating enterprise mazes &amp; startup vibes. Where's search headed next?</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 01, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the rapidly shifting landscape of technology, it's all too easy to be ensnared by the latest buzzwords and narratives. One such prevailing discourse is the perceived necessity for a dedicated "vector store" or "vector database" in the modern AI stack. This notion is propelled by the increasing application of deep neural networks to search, leading many to believe that managing a vast number of dense vectors demands a specialized store. But is this narrative grounded in reality?</p><p>Drawing from the insights of the paper "<strong>Vector Search with OpenAI Embeddings: Lucene Is All You Need</strong>" by Jimmy Lin etc., and enriched by the collective wisdom of the tech community, let's dissect this debate.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2308.14963?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Vector Search with OpenAI Embeddings: Lucene Is All You Need</div><div class="kg-bookmark-description">We provide a reproducible, end-to-end demonstration of vector search withOpenAI embeddings using Lucene on the popular MS MARCO passage ranking testcollection. The main goal of our work is to challenge the prevailing narrativethat a dedicated vector store is necessary to take advantage of recent…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Jimmy Lin</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><h2 id="lucenes-role-in-modern-vector-search">Lucene's Role in Modern Vector Search</h2><p>Lucene, renowned for its inverted index-based search, has long been a cornerstone in the search realm. Critics argue its limitations, particularly in contextual search with fuzzy logic like min edit distance. Yet, Lucene is far from stagnant. As described in the paper, the advent of hierarchical navigable small-world network (HNSW) indexes showcases Lucene's adaptability, proving its prowess in vector search capabilities on par with any dedicated vector store.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image.png" class="kg-image" alt="" width="1112" height="546" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image.png 1112w" sizes="(min-width: 720px) 720px"><figcaption>A standard bi-encoder architecture used in Jimmy's paper, where encoders generate dense vector representations (embeddings) from queries and documents (passages). Retrieval is framed as k-nearest neighbor search in vector space.</figcaption></figure><p>It's not just Lucene making waves. Vector indices are now industry staples. Giants like ElasticSearch, Postgresql, and Redis are embracing this trend. Google's recent endorsement of pgvector for their AlloyDB offering underscores the mainstream shift towards vector search.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.google.com/blog/products/databases/helping-developers-build-gen-ai-apps-with-google-cloud-databases?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Helping developers build Gen AI apps with Google Cloud PostgreSQL databases | Google Cloud Blog</div><div class="kg-bookmark-description">Announcing a series of new features and capabilities to help developers build enterprise generative AI apps with Google Cloud PostgreSQL databases.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ssl.gstatic.com/cloud/images/icons/favicon.ico" alt=""><span class="kg-bookmark-author">Google Cloud</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://storage.googleapis.com/gweb-cloudblog-publish/images/AlloyDB_AI_for_building_gen_AI_apps_Blog.max-2600x2600.jpg" alt=""></div></a></figure><h2 id="enterprise-search-challenges-navigating-the-vector-store-maze">Enterprise Search Challenges: Navigating the Vector Store Maze</h2><p>Modern enterprise architectures are intricate tapestries of legacy systems, cutting-edge solutions, and a myriad of tools aimed at solving specific problems. The introduction of a dedicated vector store would not just be a simple addition; it would be a paradigm shift. Historically, enterprises have shown a tendency to lean on tried-and-tested solutions, especially when significant investments have been made. Lucene-based platforms, with their proven track record, offer a sense of reliability. The challenge for enterprises is not just about technology but also about change management, training, and integration. The real question is: Is the potential performance gain worth the upheaval?</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/mermaid-diagram-2023-09-01-125304.svg" class="kg-image" alt="" width="170" height="150"><figcaption>Navigating the Vector Store Decision: A Strategic Framework for Enterprises</figcaption></figure><h2 id="startup-innovations-beyond-the-vector-store-hype">Startup Innovations: Beyond the Vector Store Hype</h2><p>The startup ecosystem thrives on disruption and innovation. The vision of a dedicated vector store is alluring, promising unparalleled performance and capabilities. But in the world of startups, vision needs to be backed by tangible benefits. The reality is that while vector stores offer a new approach, tools like Lucene have been refining their capabilities for years. For startups, the challenge is to prove that their solutions offer not just incremental improvements but transformative changes. In a data-driven world, the onus is on these startups to showcase empirical evidence of their superiority, not just in lab conditions but in real-world scenarios.</p><h2 id="achieving-the-ideal-performance-meets-practicality-in-search-solutions">Achieving the Ideal: Performance Meets Practicality in Search Solutions</h2><p>Performance is the holy grail in the world of search. But it's essential to understand that performance doesn't exist in a vacuum. It's intertwined with factors like cost, scalability, and ease of integration. While specialized vector databases might offer a performance edge in specific scenarios, solutions like Lucene bring a balance of performance, reliability, and familiarity. The challenge is to discern when to chase the bleeding edge of performance and when to opt for a more pragmatic, holistic solution. In a world inundated with options, the true art lies in making choices that deliver consistent value over time.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/benchmark-vector-search-databases-with-one-million-data/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Benchmark Vector Search Databases with One Million Data</div><div class="kg-bookmark-description">In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here’s a comprehensive benchmark to help guide you.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">DocArray 0.18.2 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--33-.png" alt=""></div></a></figure><h2 id="the-future-of-vector-search-lucene-vs-dedicated-stores">The Future of Vector Search: Lucene vs. Dedicated Stores</h2><p>The debate surrounding dedicated vector stores versus <a href="https://jina.ai/news/hype-and-hybrids-multimodal-search-means-more-than-keywords-and-vectors-2/?ref=jina-ai-gmbh.ghost.io">hybrid</a> Lucene <a href="https://jina.ai/news/hype-and-hybrids-multimodal-search-means-more-than-keywords-and-vectors-2/?ref=jina-ai-gmbh.ghost.io">solutions</a> is alive and well. However, a clear sentiment is emerging from the tech community: the inclination towards optimizing what we have rather than chasing the next shiny object. As we push the envelope in search capabilities, it's paramount to remember that often, the optimal solution is already within our grasp.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Insights</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdo-you-truly-need-a-dedicated-vector-store%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/fine-tuning-gpt-3-5-turbo-a-costly-mirage" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 25, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.044%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_modern_geometric_abstract_pattern_featuring_pu_24e4060e-dc76-4186-afb7-94d18d266b41.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/the-boundless-horizon-of-ai-its-not-just-about-the-size" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Beyond Sheer Scale: Navigating AI Alignment Odyssey</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">AI’s march forward isn't just about bigger models, but ensuring they harmonize with human values. Journey with us through the challenges, revelations, and aspirations at the forefront of AI safety and ethics.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">August 24, 2023 • 8 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.044%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_retrowave_sabattier_filter_sanriocore_in_the_sty_7881ce67-ea8f-417f-a204-bd101a3f58c0.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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diff --git a/news/do-you-want-to-play-a-game-lets-build-semantle-with-docarray-and-gpt/index.html b/news/do-you-want-to-play-a-game-lets-build-semantle-with-docarray-and-gpt/index.html
index e1378b78d11..529c9fac81d 100644
--- a/news/do-you-want-to-play-a-game-lets-build-semantle-with-docarray-and-gpt/index.html
+++ b/news/do-you-want-to-play-a-game-lets-build-semantle-with-docarray-and-gpt/index.html
@@ -1,6 +1,6 @@
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Let's build Semantle with DocArray and GPT</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Exploring DocArray v2 by building a word game using GPT</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 17, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="se-what-now">Se-what now?</h2><p><a href="https://semantle.com/?ref=jina-ai-gmbh.ghost.io">Semantle</a> is a game similar to <a href="https://www.nytimes.com/games/wordle?ref=jina-ai-gmbh.ghost.io">Wordle</a>, but rather than guessing based on the word's <em>letters</em>, you guess based on the word's <em>semantics</em>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/image-2.png" class="kg-image" alt="" width="1278" height="965" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/image-2.png 1278w" sizes="(min-width: 720px) 720px"><figcaption>This is just the junior version. As you can see I'm quite the expert when it comes to competing with 12 year olds</figcaption></figure><p>We'll build our own simple version using <a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io">DocArray v2</a> and <a href="https://openai.com/?ref=jina-ai-gmbh.ghost.io">OpenAI</a>’s large language models, based on the top <a href="https://github.com/first20hours/google-10000-english?ref=jina-ai-gmbh.ghost.io">10,000 most common words in English</a>.</p><h2 id="play-with-it-yourself">Play with it yourself</h2><p>To test it out yourself, you can install the version from the [repo]. It's a little bit enhanced, but all the relevant stuff is covered in this tutorial.</p><pre><code class="hljs language-bash">git <span class="hljs-built_in">clone</span> https://github.com/alexcg1/semantle-docarray
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Exploring DocArray v2 by building a word game using GPT</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 17, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="se-what-now">Se-what now?</h2><p><a href="https://semantle.com/?ref=jina-ai-gmbh.ghost.io">Semantle</a> is a game similar to <a href="https://www.nytimes.com/games/wordle?ref=jina-ai-gmbh.ghost.io">Wordle</a>, but rather than guessing based on the word's <em>letters</em>, you guess based on the word's <em>semantics</em>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/image-2.png" class="kg-image" alt="" width="1278" height="965" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/image-2.png 1278w" sizes="(min-width: 720px) 720px"><figcaption>This is just the junior version. As you can see I'm quite the expert when it comes to competing with 12 year olds</figcaption></figure><p>We'll build our own simple version using <a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io">DocArray v2</a> and <a href="https://openai.com/?ref=jina-ai-gmbh.ghost.io">OpenAI</a>’s large language models, based on the top <a href="https://github.com/first20hours/google-10000-english?ref=jina-ai-gmbh.ghost.io">10,000 most common words in English</a>.</p><h2 id="play-with-it-yourself">Play with it yourself</h2><p>To test it out yourself, you can install the version from the [repo]. It's a little bit enhanced, but all the relevant stuff is covered in this tutorial.</p><pre><code>git clone https://github.com/alexcg1/semantle-docarray
 
-</code></pre><h2 id="understanding-the-game">Understanding the game</h2><p>In our implementation of Semantle:</p><ul><li>A loop is started where the user has to guess the word.</li><li>As soon as the guess matches the target word, the loop ends and the game displays the guess and hint counts to the user.</li><li>If the user asks for a hint, we use GPT-4 to generate a hint from the target word.</li><li>If the user doesn't get it right and doesn't ask for a hint, we fall back to <code>else</code>, where:</li><li>The guess counter increments.</li><li>The distance is calculated and presented to the user.</li></ul><p>Keep reading to see how we build it all up!</p><h2 id="getting-started">Getting started</h2><h3 id="install-requirements">Install requirements</h3><p>To build our game, we'll need a few dependencies:</p><ul><li><code>docarray</code> - our data structure, ideal for representing <a href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io">multimodal documents</a> and embeddings.</li><li><code>openai</code> - we'll use their models to generate embeddings for the target word, guess words, and hints.</li></ul><pre><code class="language-bash hljs">pip install docarray openai
+</code></pre><h2 id="understanding-the-game">Understanding the game</h2><p>In our implementation of Semantle:</p><ul><li>A loop is started where the user has to guess the word.</li><li>As soon as the guess matches the target word, the loop ends and the game displays the guess and hint counts to the user.</li><li>If the user asks for a hint, we use GPT-4 to generate a hint from the target word.</li><li>If the user doesn't get it right and doesn't ask for a hint, we fall back to <code>else</code>, where:</li><li>The guess counter increments.</li><li>The distance is calculated and presented to the user.</li></ul><p>Keep reading to see how we build it all up!</p><h2 id="getting-started">Getting started</h2><h3 id="install-requirements">Install requirements</h3><p>To build our game, we'll need a few dependencies:</p><ul><li><code>docarray</code> - our data structure, ideal for representing <a href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io">multimodal documents</a> and embeddings.</li><li><code>openai</code> - we'll use their models to generate embeddings for the target word, guess words, and hints.</li></ul><pre><code class="language-bash">pip install docarray openai
 
-</code></pre><h3 id="get-the-list-of-words">Get the list of words</h3><pre><code class="language-bash hljs">wget https://raw.githubusercontent.com/first20hours/google-10000-english/master/google-10000-english.txt
+</code></pre><h3 id="get-the-list-of-words">Get the list of words</h3><pre><code class="language-bash">wget https://raw.githubusercontent.com/first20hours/google-10000-english/master/google-10000-english.txt
 
-</code></pre><p>Alternatively, for an easier version you can use a list of just fruits:</p><pre><code class="language-bash hljs">wget https://raw.githubusercontent.com/alexcg1/semantle-docarray/main/wordlists/fruits.txt
+</code></pre><p>Alternatively, for an easier version you can use a list of just fruits:</p><pre><code class="language-bash">wget https://raw.githubusercontent.com/alexcg1/semantle-docarray/main/wordlists/fruits.txt
 
-</code></pre><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Why not use a random word generator API? Because English has a <em>lot</em> of words. Most of which very few people would know. I want to keep this example accessible. (C'mon, who's going to guess "<a href="https://www.allwords.com/word-pseudoantidisestablishmentarianism.html?ref=jina-ai-gmbh.ghost.io">pseudoantidisestablishmentarianism</a>"?)</div></div><h3 id="set-openai-api-key">Set OpenAI API key</h3><p>You'll need an <a href="https://platform.openai.com/account/api-keys?ref=jina-ai-gmbh.ghost.io">OpenAI API key</a> to use the models. You use this command from the CLI:</p><pre><code class="language-bash hljs"><span class="hljs-built_in">export</span> OPENAI_API_KEY=&lt;your_key_here&gt;
+</code></pre><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Why not use a random word generator API? Because English has a <em>lot</em> of words. Most of which very few people would know. I want to keep this example accessible. (C'mon, who's going to guess "<a href="https://www.allwords.com/word-pseudoantidisestablishmentarianism.html?ref=jina-ai-gmbh.ghost.io">pseudoantidisestablishmentarianism</a>"?)</div></div><h3 id="set-openai-api-key">Set OpenAI API key</h3><p>You'll need an <a href="https://platform.openai.com/account/api-keys?ref=jina-ai-gmbh.ghost.io">OpenAI API key</a> to use the models. You use this command from the CLI:</p><pre><code class="language-bash">export OPENAI_API_KEY=&lt;your_key_here&gt;
 
-</code></pre><h2 id="let%E2%80%99s-write-some-code">Let’s write some code</h2><h3 id="defining-our-data-structure">Defining our data structure</h3><p>Since we’re just working with text and embeddings, we’ll define a data structure with just a text field and an embedding field by subclassing from <code><a href="https://docs.docarray.org/user_guide/representing/first_step/?ref=jina-ai-gmbh.ghost.io">BaseDoc</a></code>. Let’s call that data structure <code>WordDoc</code>. Not that kind of <a href="https://learn.microsoft.com/en-us/openspecs/office_standards/ms-docx/728a7abc-7f55-40dc-90a7-1276ff53c8b2?ref=jina-ai-gmbh.ghost.io">Word doc</a>. Don't worry. No Clippy here).</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/7nbpMQwEGC8AAAAC/clippy-microsoft.gif" class="kg-image" alt="" width="200" height="176"><figcaption>Just kidding. Clippy is always there. Watching. Waiting to come back from the dungeon dimensions where Bill Gates banished him so long ago</figcaption></figure><p>We'll create a file called <code>app.py</code>:</p><pre><code class="language-python hljs">
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Doclist, BaseDoc
+</code></pre><h2 id="let%E2%80%99s-write-some-code">Let’s write some code</h2><h3 id="defining-our-data-structure">Defining our data structure</h3><p>Since we’re just working with text and embeddings, we’ll define a data structure with just a text field and an embedding field by subclassing from <code><a href="https://docs.docarray.org/user_guide/representing/first_step/?ref=jina-ai-gmbh.ghost.io">BaseDoc</a></code>. Let’s call that data structure <code>WordDoc</code>. Not that kind of <a href="https://learn.microsoft.com/en-us/openspecs/office_standards/ms-docx/728a7abc-7f55-40dc-90a7-1276ff53c8b2?ref=jina-ai-gmbh.ghost.io">Word doc</a>. Don't worry. No Clippy here).</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/7nbpMQwEGC8AAAAC/clippy-microsoft.gif" class="kg-image" alt="" width="200" height="176"><figcaption>Just kidding. Clippy is always there. Watching. Waiting to come back from the dungeon dimensions where Bill Gates banished him so long ago</figcaption></figure><p>We'll create a file called <code>app.py</code>:</p><pre><code class="language-python">
+from docarray import Doclist, BaseDoc
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">WordDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    text: <span class="hljs-built_in">str</span> = <span class="hljs-string">''</span>
-    embedding: NdArray[<span class="hljs-number">1536</span>] | <span class="hljs-literal">None</span>
+class WordDoc(BaseDoc):
+    text: str = ''
+    embedding: NdArray[1536] | None
 
-</code></pre><p>Here we've defined our <code>.embedding</code> attribute as an <code>NdArray</code> with a length of 1,536, which is the length of the <a href="https://developers.google.com/machine-learning/crash-course/embeddings/video-lecture?ref=jina-ai-gmbh.ghost.io">embeddings</a> we'll get later from OpenAI. We didn't need to define the <code>.text</code> attribute, since that's already provided by <code>TextDoc</code>.</p><p>That means we have two useful attributes to work with:</p><ul><li><code>text</code>: the string of the word.</li><li><code>embedding</code>: the <code>NdArray</code> of the vector embedding of the word.</li></ul><h3 id="choosing-our-target-word">Choosing our target word</h3><p>We'll randomly choose one of those words from our list and encode it into a <code>WordDoc</code>:</p><pre><code class="language-python hljs">word_list = <span class="hljs-string">'google-10000-english.txt'</span> <span class="hljs-comment"># or fruits.txt</span>
+</code></pre><p>Here we've defined our <code>.embedding</code> attribute as an <code>NdArray</code> with a length of 1,536, which is the length of the <a href="https://developers.google.com/machine-learning/crash-course/embeddings/video-lecture?ref=jina-ai-gmbh.ghost.io">embeddings</a> we'll get later from OpenAI. We didn't need to define the <code>.text</code> attribute, since that's already provided by <code>TextDoc</code>.</p><p>That means we have two useful attributes to work with:</p><ul><li><code>text</code>: the string of the word.</li><li><code>embedding</code>: the <code>NdArray</code> of the vector embedding of the word.</li></ul><h3 id="choosing-our-target-word">Choosing our target word</h3><p>We'll randomly choose one of those words from our list and encode it into a <code>WordDoc</code>:</p><pre><code class="language-python">word_list = 'google-10000-english.txt' # or fruits.txt
 
-<span class="hljs-keyword">def</span> <span class="hljs-title function_">wordlist_to_doclist</span>(<span class="hljs-params">filename: <span class="hljs-built_in">str</span></span>):
+def wordlist_to_doclist(filename: str):
     docs = DocList[TextDoc]()
-    <span class="hljs-keyword">with</span> <span class="hljs-built_in">open</span>(filename, <span class="hljs-string">'r'</span>) <span class="hljs-keyword">as</span> file:
-        <span class="hljs-keyword">for</span> line <span class="hljs-keyword">in</span> file:
+    with open(filename, 'r') as file:
+        for line in file:
             doc = TextDoc(text=line.lower().strip())
             docs.append(doc)
 
-    <span class="hljs-keyword">return</span> docs
+    return docs
 
 all_words = wordlist_to_doclist(word_list)
 target_word = random.choice(all_words)
 
-</code></pre><h3 id="getting-the-embedding-for-our-target-word">Getting the embedding for our target word</h3><p>We need to generate an embedding for our target word so that we can give the user a score for their guess based on how near or far it is from our target word.</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> openai
+</code></pre><h3 id="getting-the-embedding-for-our-target-word">Getting the embedding for our target word</h3><p>We need to generate an embedding for our target word so that we can give the user a score for their guess based on how near or far it is from our target word.</p><pre><code class="language-python">import openai
 
-openai.api_key = os.environ[<span class="hljs-string">'OPENAI_API_KEY'</span>]
+openai.api_key = os.environ['OPENAI_API_KEY']
 
-<span class="hljs-keyword">def</span> <span class="hljs-title function_">gpt_encode</span>(<span class="hljs-params">doc: WordDoc, model_name: <span class="hljs-built_in">str</span>=<span class="hljs-string">'text-embedding-ada-002'</span></span>):
-    response = openai.Embedding.create(<span class="hljs-built_in">input</span>=doc.text, model=model_name)
-    doc.embedding = response[<span class="hljs-string">'data'</span>][<span class="hljs-number">0</span>][<span class="hljs-string">'embedding'</span>]
+def gpt_encode(doc: WordDoc, model_name: str='text-embedding-ada-002'):
+    response = openai.Embedding.create(input=doc.text, model=model_name)
+    doc.embedding = response['data'][0]['embedding']
 
-    <span class="hljs-keyword">return</span> doc
+    return doc
 
 gpt_encode(target_word)
 
-</code></pre><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">We use the <a href="https://openai.com/blog/new-and-improved-embedding-model?ref=jina-ai-gmbh.ghost.io"><code>ada-002</code> model</a> here since we're just generating the embedding for a simple string. Using GPT-4 would be like using a nuclear bomb to crack a nut.</div></div><h3 id="getting-a-users-guess">Getting a user's guess</h3><p>A user has a (currently) infinite number of guesses:</p><pre><code class="language-python hljs">guess = WordDoc(text=<span class="hljs-string">''</span>)
+</code></pre><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">We use the <a href="https://openai.com/blog/new-and-improved-embedding-model?ref=jina-ai-gmbh.ghost.io"><code>ada-002</code> model</a> here since we're just generating the embedding for a simple string. Using GPT-4 would be like using a nuclear bomb to crack a nut.</div></div><h3 id="getting-a-users-guess">Getting a user's guess</h3><p>A user has a (currently) infinite number of guesses:</p><pre><code class="language-python">guess = WordDoc(text='')
 
-guess_counter = <span class="hljs-number">0</span>
-hint_counter = <span class="hljs-number">0</span>
+guess_counter = 0
+hint_counter = 0
 
-<span class="hljs-keyword">while</span> guess.text != target_word.text:
-    guess = WordDoc(text=<span class="hljs-built_in">input</span>(<span class="hljs-string">'What is your guess? '</span>))
+while guess.text != target_word.text:
+    guess = WordDoc(text=input('What is your guess? '))
 
-</code></pre><h3 id="responding-to-a-wrong-guess">Responding to a wrong guess</h3><p>If the user's input doesn't match the target word, we'll encode the input into vectors using our function from above:</p><pre><code class="language-python hljs">gpt_encode(guess)
+</code></pre><h3 id="responding-to-a-wrong-guess">Responding to a wrong guess</h3><p>If the user's input doesn't match the target word, we'll encode the input into vectors using our function from above:</p><pre><code class="language-python">gpt_encode(guess)
 
-</code></pre><p>Then we work out the distance of the vectors of both the guess and the target word:</p><pre><code class="language-python hljs">distance = cosine(target_word.embedding, guess.embedding)
+</code></pre><p>Then we work out the distance of the vectors of both the guess and the target word:</p><pre><code class="language-python">distance = cosine(target_word.embedding, guess.embedding)
 
-<span class="hljs-keyword">if</span> guess.text != target_word.text:
-    <span class="hljs-built_in">print</span>(<span class="hljs-string">f'Try again. Your distance is <span class="hljs-subst">{<span class="hljs-built_in">round</span>(distance, <span class="hljs-number">2</span>)}</span>.'</span>)
+if guess.text != target_word.text:
+    print(f'Try again. Your distance is {round(distance, 2)}.')
 
-</code></pre><blockquote>The score corresponds to the distance between the guess and the target, so an exact match is 0, while the most distant match could be up to 1.</blockquote><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Then the <code>while</code> loop checks if the guess matches the target. If not, the user gets another guess.</div></div><h3 id="responding-to-a-hint-request">Responding to a <code>/hint</code> request</h3><p>We can re-arrange the above into an <code>if</code> block:</p><pre><code class="language-python hljs"><span class="hljs-keyword">while</span> guess.text != target_word.text:
-    guess = WordDoc(text=<span class="hljs-built_in">input</span>(<span class="hljs-string">'What is your guess? '</span>))
+</code></pre><blockquote>The score corresponds to the distance between the guess and the target, so an exact match is 0, while the most distant match could be up to 1.</blockquote><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Then the <code>while</code> loop checks if the guess matches the target. If not, the user gets another guess.</div></div><h3 id="responding-to-a-hint-request">Responding to a <code>/hint</code> request</h3><p>We can re-arrange the above into an <code>if</code> block:</p><pre><code class="language-python">while guess.text != target_word.text:
+    guess = WordDoc(text=input('What is your guess? '))
 
-    <span class="hljs-keyword">if</span> guess.text.lower() == <span class="hljs-string">'/hint'</span>:
-        hint_counter += <span class="hljs-number">1</span>
-        <span class="hljs-comment">#  give hint</span>
-    <span class="hljs-keyword">else</span>:
-        <span class="hljs-comment">#  check if guess is right or wrong</span>
+    if guess.text.lower() == '/hint':
+        hint_counter += 1
+        #  give hint
+    else:
+        #  check if guess is right or wrong
 
-</code></pre><p>For the hint, we once again use OpenAI, but this time with GPT. This is because generating a hint for a word is way more complex than just generating an embedding, and requires decent prompting:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> openai
+</code></pre><p>For the hint, we once again use OpenAI, but this time with GPT. This is because generating a hint for a word is way more complex than just generating an embedding, and requires decent prompting:</p><pre><code class="language-python">import openai
 
-<span class="hljs-keyword">def</span> <span class="hljs-title function_">get_hint</span>(<span class="hljs-params">doc, model_name=<span class="hljs-string">'text-davinci-003'</span></span>):
+def get_hint(doc, model_name='text-davinci-003'):
     response = openai.Completion.create(
         model=model_name,
-        prompt=<span class="hljs-string">f'Create a crossword clue for the word "<span class="hljs-subst">{doc.text}</span>". You will give a brief dictionary definition of the word, but not say the word itself.'</span>,
-        max_tokens=<span class="hljs-number">100</span>,
-        temperature=<span class="hljs-number">0.7</span>,
+        prompt=f'Create a crossword clue for the word "{doc.text}". You will give a brief dictionary definition of the word, but not say the word itself.',
+        max_tokens=100,
+        temperature=0.7,
     )
 
-    hint = response.choices[<span class="hljs-number">0</span>].text.strip()
+    hint = response.choices[0].text.strip()
 
-    <span class="hljs-keyword">return</span> hint
+    return hint
 
-</code></pre><h3 id="responding-to-a-correct-guess">Responding to a correct guess</h3><p>This is handled by the <code>while</code> loop itself. As soon as the text of the guess is equal to that of the target word, the loop ends and the user is given their score.</p><pre><code class="language-python hljs"><span class="hljs-keyword">while</span> guess.text != target_word.text:
-    guess = WordDoc(text=<span class="hljs-built_in">input</span>(<span class="hljs-string">'What is your guess? '</span>))
+</code></pre><h3 id="responding-to-a-correct-guess">Responding to a correct guess</h3><p>This is handled by the <code>while</code> loop itself. As soon as the text of the guess is equal to that of the target word, the loop ends and the user is given their score.</p><pre><code class="language-python">while guess.text != target_word.text:
+    guess = WordDoc(text=input('What is your guess? '))
 
-    <span class="hljs-keyword">if</span> guess.text.lower() == <span class="hljs-string">'/hint'</span>:
-        hint_counter +=<span class="hljs-number">1</span>
-        <span class="hljs-built_in">print</span>(get_hint(target_word))
-    <span class="hljs-keyword">else</span>:
-        guess_counter += <span class="hljs-number">1</span>
+    if guess.text.lower() == '/hint':
+        hint_counter +=1
+        print(get_hint(target_word))
+    else:
+        guess_counter += 1
         gpt_encode(guess)
 
         distance = cosine(target_word.embedding, guess.embedding)
 
-        <span class="hljs-keyword">if</span> guess.text != target_word.text:
-            <span class="hljs-built_in">print</span>(
-                <span class="hljs-string">f'Try again. Your distance is <span class="hljs-subst">{<span class="hljs-built_in">round</span>(distance, <span class="hljs-number">2</span>)}</span>.'</span>
+        if guess.text != target_word.text:
+            print(
+                f'Try again. Your distance is {round(distance, 2)}.'
             )
 
-<span class="hljs-built_in">print</span>(
-    <span class="hljs-string">f'Congratulations! You guessed in <span class="hljs-subst">{guess_counter}</span> turn(s) and <span class="hljs-subst">{hint_counter}</span> hint(s).'</span>
+print(
+    f'Congratulations! You guessed in {guess_counter} turn(s) and {hint_counter} hint(s).'
 )
-</code></pre><h2 id="next-steps">Next steps</h2><p>DocArray is way more than a toy just for making games. You can use it to build search engines, chatbots, image generation APIs, music search (ala Shazam) and much more.</p><p>How would you improve the game? Or what (actually useful) thing would you build with DocArray? Join our Discord community and let us know, or make your first contribution today!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://discord.gg/WaMp6PVPgR?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Join the DocArray Discord</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdo-you-want-to-play-a-game-lets-build-semantle-with-docarray-and-gpt%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
+</code></pre><h2 id="next-steps">Next steps</h2><p>DocArray is way more than a toy just for making games. You can use it to build search engines, chatbots, image generation APIs, music search (ala Shazam) and much more.</p><p>How would you improve the game? Or what (actually useful) thing would you build with DocArray? Join our Discord community and let us know, or make your first contribution today!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://discord.gg/WaMp6PVPgR?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Join the DocArray Discord</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdo-you-want-to-play-a-game-lets-build-semantle-with-docarray-and-gpt%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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 💡DocArray is the common data layer used in all Jina AI products.Release 💫 Release v0.17.0 · jina-ai/docarrayRelease Note (0.17.0) Release time: 2022-09-23 16:18:19 This release contains 8 new features, 2 performance improvem"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/Blue-Pink-Gradient-Fashion-Banner--30---15-in-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-17-update"><meta property="twitter:title" content="DocArray 0.17 Update"><meta property="twitter:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer the multi-modal data with a Pythonic API.
 
-💡DocArray is the common data layer used in all Jina AI products.Release 💫 Release v0.17.0 · jina-ai/docarrayRelease Note (0.17.0) Release time: 2022-09-23 16:18:19 This release contains 8 new features, 2 performance improvem"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/Blue-Pink-Gradient-Fashion-Banner--30---15-in-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="226819d1-0b95-4a2d-8465-481fadf80ed4" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="226819d1-0b95-4a2d-8465-481fadf80ed4" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.17 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer the multi-modal data with a Pythonic API.
 
-💡DocArray is the common data layer used in all Jina AI products.Release 💫 Release v0.17.0 · jina-ai/docarrayRelease Note (0.17.0) Release time: 2022-09-23 16:18:19 This release contains 8 new features, 2 performance improvem</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 24, 2022 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer the multi-modal data with a Pythonic API.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">DocArray is the common data layer used in all Jina AI products.</div></div><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/docarray/releases/tag/v0.17.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.17.0 · jina-ai/docarray</div><div class="kg-bookmark-description">Release Note (0.17.0) Release time: 2022-09-23 16:18:19 This release contains 8 new features, 2 performance improvements, 7 bug fixes, and 2 documentation improvements.🆕 FeaturesAllow passing p...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/fc6397ec7b8459eb79616ddc6ad211095b198c80fdff9c839902069e71c75cd5/jina-ai/docarray/releases/tag/v0.17.0" alt=""></div></a><figcaption>Full release note with links to pull requests</figcaption></figure><h2 id="release-note-0170">Release Note (<code>0.17.0</code>)</h2><blockquote>Release time: 2022-09-23 16:18:19</blockquote><p>This release contains 8 new features, 2 performance improvements, 7 bug fixes, and 2 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="allow-passing-parameters-to-loadurito-methods-540">Allow passing parameters to <code>load_uri_to_*</code> methods (#540)</h3><p>The <code>load_uri_to_*</code> methods (<code>load_uri_to_blob</code>, <code>load_uri_to_text</code>, etc.) now accept <code>kwargs</code> so that you can pass a timeout parameter to the underlying request methods.</p><p>For example:</p><pre><code class="language-python hljs">doc = Document(uri=<span class="hljs-string">'uri_path'</span>)
-doc.load_uri_to_blob(timeout=<span class="hljs-number">2</span>)
-</code></pre><h3 id="allow-multiple-documentarrays-per-redis-server-540">Allow multiple DocumentArrays per Redis server (#540)</h3><p>You can now store multiple DocumentArrays in a single Redis instance, as long as each DocumentArray has a different <code>index_name</code>:</p><pre><code class="language-python hljs">da1 = DocumentArray(storage=<span class="hljs-string">'redis'</span>, config={<span class="hljs-string">'host'</span>: <span class="hljs-string">'localhost'</span>, <span class="hljs-string">'port'</span>: <span class="hljs-number">6379</span>, <span class="hljs-string">'n_dim'</span>: <span class="hljs-number">128</span>, <span class="hljs-string">'index_name'</span>: <span class="hljs-string">'da1'</span>})
-da2 = DocumentArray(storage=<span class="hljs-string">'redis'</span>, config={<span class="hljs-string">'host'</span>: <span class="hljs-string">'localhost'</span>, <span class="hljs-string">'port'</span>: <span class="hljs-number">6379</span>, <span class="hljs-string">'n_dim'</span>: <span class="hljs-number">256</span>, <span class="hljs-string">'index_name'</span>: <span class="hljs-string">'da2'</span>})
-da3 = DocumentArray(storage=<span class="hljs-string">'redis'</span>, config={<span class="hljs-string">'host'</span>: <span class="hljs-string">'localhost'</span>, <span class="hljs-string">'port'</span>: <span class="hljs-number">6379</span>, <span class="hljs-string">'n_dim'</span>: <span class="hljs-number">512</span>, <span class="hljs-string">'index_name'</span>: <span class="hljs-string">'da3'</span>})
-</code></pre><h3 id="login-required-for-documentarray-push-and-pull-541">Login required for DocumentArray push and pull (#541)</h3><p>Logging in to Jina Cloud is now required before pushing/pulling DocumentArrays to/from Jina Cloud. You can log in either by creating a token in <code>hub.jina.ai</code> and setting it as an environment variable (<code>JINA_AUTH_TOKEN=my_token</code>) or using the CLI command <code>jina auth login</code>.</p><h3 id="push-metadata-along-with-documentarray-and-add-cloudlist-and-clouddelete-methods-490">Push metadata along with DocumentArray and add <code>cloud_list</code> and <code>cloud_delete</code> methods (#490)</h3><p><code>DocumentArray.push</code> will extract metadata about the DocumentArray and send it to Jina Cloud. Although this is transparent to users, it will help with visualization of DocumentArrays in Jina Cloud.</p><p>It is also possible to list and delete DocumentArrays in Jina Cloud using the following methods:</p><ul><li><code>DocumentArray.cloud_list()</code>: will list all DocumentArray objects owned by the authenticated user</li><li><code>DocumentArray.cloud_delete(da_name)</code>: will delete the DocumentArray by name if it is owned by the authenticated user</li></ul><h3 id="full-text-search-support-in-redis-backend-535">Full text search support in Redis backend (#535)</h3><p>Full text search is supported either on the <code>Document.text</code> field or on Document tags as long as you enable indexing text or specify tag fields to be indexed.</p><p>For example:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document, DocumentArray
+💡DocArray is the common data layer used in all Jina AI products.Release 💫 Release v0.17.0 · jina-ai/docarrayRelease Note (0.17.0) Release time: 2022-09-23 16:18:19 This release contains 8 new features, 2 performance improvem</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 24, 2022 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer the multi-modal data with a Pythonic API.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">DocArray is the common data layer used in all Jina AI products.</div></div><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/docarray/releases/tag/v0.17.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.17.0 · jina-ai/docarray</div><div class="kg-bookmark-description">Release Note (0.17.0) Release time: 2022-09-23 16:18:19 This release contains 8 new features, 2 performance improvements, 7 bug fixes, and 2 documentation improvements.🆕 FeaturesAllow passing p...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/fc6397ec7b8459eb79616ddc6ad211095b198c80fdff9c839902069e71c75cd5/jina-ai/docarray/releases/tag/v0.17.0" alt=""></div></a><figcaption>Full release note with links to pull requests</figcaption></figure><h2 id="release-note-0170">Release Note (<code>0.17.0</code>)</h2><blockquote>Release time: 2022-09-23 16:18:19</blockquote><p>This release contains 8 new features, 2 performance improvements, 7 bug fixes, and 2 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="allow-passing-parameters-to-loadurito-methods-540">Allow passing parameters to <code>load_uri_to_*</code> methods (#540)</h3><p>The <code>load_uri_to_*</code> methods (<code>load_uri_to_blob</code>, <code>load_uri_to_text</code>, etc.) now accept <code>kwargs</code> so that you can pass a timeout parameter to the underlying request methods.</p><p>For example:</p><pre><code class="language-python">doc = Document(uri='uri_path')
+doc.load_uri_to_blob(timeout=2)
+</code></pre><h3 id="allow-multiple-documentarrays-per-redis-server-540">Allow multiple DocumentArrays per Redis server (#540)</h3><p>You can now store multiple DocumentArrays in a single Redis instance, as long as each DocumentArray has a different <code>index_name</code>:</p><pre><code class="language-python">da1 = DocumentArray(storage='redis', config={'host': 'localhost', 'port': 6379, 'n_dim': 128, 'index_name': 'da1'})
+da2 = DocumentArray(storage='redis', config={'host': 'localhost', 'port': 6379, 'n_dim': 256, 'index_name': 'da2'})
+da3 = DocumentArray(storage='redis', config={'host': 'localhost', 'port': 6379, 'n_dim': 512, 'index_name': 'da3'})
+</code></pre><h3 id="login-required-for-documentarray-push-and-pull-541">Login required for DocumentArray push and pull (#541)</h3><p>Logging in to Jina Cloud is now required before pushing/pulling DocumentArrays to/from Jina Cloud. You can log in either by creating a token in <code>hub.jina.ai</code> and setting it as an environment variable (<code>JINA_AUTH_TOKEN=my_token</code>) or using the CLI command <code>jina auth login</code>.</p><h3 id="push-metadata-along-with-documentarray-and-add-cloudlist-and-clouddelete-methods-490">Push metadata along with DocumentArray and add <code>cloud_list</code> and <code>cloud_delete</code> methods (#490)</h3><p><code>DocumentArray.push</code> will extract metadata about the DocumentArray and send it to Jina Cloud. Although this is transparent to users, it will help with visualization of DocumentArrays in Jina Cloud.</p><p>It is also possible to list and delete DocumentArrays in Jina Cloud using the following methods:</p><ul><li><code>DocumentArray.cloud_list()</code>: will list all DocumentArray objects owned by the authenticated user</li><li><code>DocumentArray.cloud_delete(da_name)</code>: will delete the DocumentArray by name if it is owned by the authenticated user</li></ul><h3 id="full-text-search-support-in-redis-backend-535">Full text search support in Redis backend (#535)</h3><p>Full text search is supported either on the <code>Document.text</code> field or on Document tags as long as you enable indexing text or specify tag fields to be indexed.</p><p>For example:</p><pre><code class="language-python">from docarray import Document, DocumentArray
 
 da = DocumentArray(
-    storage=<span class="hljs-string">'redis'</span>, config={<span class="hljs-string">'n_dim'</span>: <span class="hljs-number">2</span>, <span class="hljs-string">'index_text'</span>: <span class="hljs-literal">True</span>}
+    storage='redis', config={'n_dim': 2, 'index_text': True}
 )
 da.extend([
-    Document(text=<span class="hljs-string">'Redis allows you to search by text query,'</span>),
-    Document(text=<span class="hljs-string">'by vector similarity'</span>),
-    Document(text=<span class="hljs-string">'Or by filter conditions'</span>),
-]) <span class="hljs-comment"># add documents with text field</span>
+    Document(text='Redis allows you to search by text query,'),
+    Document(text='by vector similarity'),
+    Document(text='Or by filter conditions'),
+]) # add documents with text field
 
-da.find(<span class="hljs-string">'my text query'</span>).texts
-</code></pre><p>Result:</p><pre><code class="language-text hljs language-plaintext">['Redis allows you to search by text query,']
-</code></pre><h3 id="add-logical-operators-and-and-or-in-redis-509">Add logical operators <code>$and</code> and <code>$or</code> in Redis (#509)</h3><p>The Redis backend now supports <code>$and</code> and <code>$or</code> logical operators. For example:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
+da.find('my text query').texts
+</code></pre><p>Result:</p><pre><code class="language-text">['Redis allows you to search by text query,']
+</code></pre><h3 id="add-logical-operators-and-and-or-in-redis-509">Add logical operators <code>$and</code> and <code>$or</code> in Redis (#509)</h3><p>The Redis backend now supports <code>$and</code> and <code>$or</code> logical operators. For example:</p><pre><code class="language-python">from docarray import DocumentArray
 
-da = DocumentArray(storage=<span class="hljs-string">'redis'</span>, config={<span class="hljs-string">'n_dim'</span>: <span class="hljs-number">128</span>, <span class="hljs-string">'columns'</span>: {<span class="hljs-string">'col1'</span>: <span class="hljs-string">'str'</span>, <span class="hljs-string">'col2'</span>: <span class="hljs-string">'int'</span>}})
+da = DocumentArray(storage='redis', config={'n_dim': 128, 'columns': {'col1': 'str', 'col2': 'int'}})
 
 redis_filter = {
-    <span class="hljs-string">"$or"</span>: {
-        <span class="hljs-string">"col1"</span>: {<span class="hljs-string">"$eq"</span>: <span class="hljs-string">"value"</span>},
-        <span class="hljs-string">"col2"</span>: {<span class="hljs-string">"$lt"</span>: <span class="hljs-number">100</span>}
+    "$or": {
+        "col1": {"$eq": "value"},
+        "col2": {"$lt": 100}
     }
 }
 
-<span class="hljs-comment"># retrieve documents using filter</span>
+# retrieve documents using filter
 da.find(redis_filter)
-</code></pre><h3 id="columns-in-backend-configuration-should-be-a-dictionary-not-a-list-of-tuples-526">Columns in backend configuration should be a dictionary, not a list of tuples (#526)</h3><p>The <code>columns</code> configuration parameter for storage backends has been changed from a list of tuples to a dictionary in the following format: <code>{'column_name': 'column_type'}</code>. This helps with YAML compatibility.</p><p>For example:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
-da = DocumentArray(storage=<span class="hljs-string">'annlite'</span>, config={<span class="hljs-string">'n_dim'</span>: <span class="hljs-number">128</span>, <span class="hljs-string">'columns'</span>: {<span class="hljs-string">'col1'</span>: <span class="hljs-string">'str'</span>, <span class="hljs-string">'col2'</span>: <span class="hljs-string">'float'</span>}})
-</code></pre><h3 id="allow-displaying-image-documents-using-either-tensor-or-uri-518">Allow displaying image documents using either tensor or URI (#518)</h3><p>It is now possible to choose which field to use when displaying an image document:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document
+</code></pre><h3 id="columns-in-backend-configuration-should-be-a-dictionary-not-a-list-of-tuples-526">Columns in backend configuration should be a dictionary, not a list of tuples (#526)</h3><p>The <code>columns</code> configuration parameter for storage backends has been changed from a list of tuples to a dictionary in the following format: <code>{'column_name': 'column_type'}</code>. This helps with YAML compatibility.</p><p>For example:</p><pre><code class="language-python">from docarray import DocumentArray
+da = DocumentArray(storage='annlite', config={'n_dim': 128, 'columns': {'col1': 'str', 'col2': 'float'}})
+</code></pre><h3 id="allow-displaying-image-documents-using-either-tensor-or-uri-518">Allow displaying image documents using either tensor or URI (#518)</h3><p>It is now possible to choose which field to use when displaying an image document:</p><pre><code class="language-python">from docarray import Document
 
-d = Document(uri=os.path.join(cur_dir, <span class="hljs-string">'toydata/test.png'</span>))
+d = Document(uri=os.path.join(cur_dir, 'toydata/test.png'))
 d.display()
-d.display(from_=<span class="hljs-string">'uri'</span>)
-</code></pre><p>or</p><pre><code class="language-python hljs">d.load_uri_to_image_tensor()
-d.display(from_=<span class="hljs-string">'tensor'</span>)
+d.display(from_='uri')
+</code></pre><p>or</p><pre><code class="language-python">d.load_uri_to_image_tensor()
+d.display(from_='tensor')
 </code></pre><h2 id="backwards-incompatible-api-changes">Backwards incompatible API changes</h2><h3 id="increased-minimum-versions-for-dependencies">Increased minimum versions for dependencies:</h3><table>
 <thead>
 <tr>
@@ -76,14 +76,14 @@
 <td><code>0.3.12</code></td>
 </tr>
 </tbody>
-</table><p>Other API Changes:</p><ul><li>The <code>columns</code> configuration parameter for storage backends has been changed from a list of tuples to a dictionary in the following format: <code>{'column_name': 'column_type'}</code>.</li></ul><h2 id="%F0%9F%9A%80-performance">🚀 Performance</h2><h3 id="optimize-find-with-an-exists-condition-519">Optimize find with an <code>exists</code> condition (#519)</h3><p>We got rid of unnecessary and costly computation when computing <code>DocumentArray.find</code> with an <code>exists</code> filter. When running the following code:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray, Document
-da = DocumentArray(Document(text=<span class="hljs-string">'text'</span>) <span class="hljs-keyword">for</span> _ <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(num)) + \
-     DocumentArray(Document(blob=<span class="hljs-string">b'blob'</span>) <span class="hljs-keyword">for</span> _ <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(num))
+</table><p>Other API Changes:</p><ul><li>The <code>columns</code> configuration parameter for storage backends has been changed from a list of tuples to a dictionary in the following format: <code>{'column_name': 'column_type'}</code>.</li></ul><h2 id="%F0%9F%9A%80-performance">🚀 Performance</h2><h3 id="optimize-find-with-an-exists-condition-519">Optimize find with an <code>exists</code> condition (#519)</h3><p>We got rid of unnecessary and costly computation when computing <code>DocumentArray.find</code> with an <code>exists</code> filter. When running the following code:</p><pre><code class="language-python">from docarray import DocumentArray, Document
+da = DocumentArray(Document(text='text') for _ in range(num)) + \
+     DocumentArray(Document(blob=b'blob') for _ in range(num))
 
 
-da.find(query={<span class="hljs-string">'text'</span>: {<span class="hljs-string">'$exists'</span>: <span class="hljs-literal">True</span>}})
-</code></pre><p>you should expect a 200-300% speed increase in <code>find</code> latency.</p><p>This optimization only affects performing <code>DocumentArray.find</code> or <code>DocumentArray.match</code> when an <code>exists</code> condition is used and an <code>in-memory</code> document store is used.</p><h3 id="change-default-journal-mode-to-wal-in-sqlite-backend-506">Change default journal mode to WAL in SQLite backend (#506):</h3><p>The default journal mode in the SQLite backend is now WAL. This should improve performance when using the SQLite backend.</p><p>According to the <a href="https://sqlite.org/wal.html?ref=jina-ai-gmbh.ghost.io">SQLite docs</a>, WAL is significantly faster, provides more concurrency, and is more robust.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="keep-default-values-for-vector-similarity-parameters-in-redis-backend-559">Keep default values for vector similarity parameters in Redis backend (#559)</h3><p>DocumentArray's Redis backend previously initialized schemas in the Redis database with default values of vector similarity search parameters. Those default values came from DocArray, not Redis.</p><p>This altered the database's default behavior, although the user didn't explicitly specify that. We've changed the implementation to avoid altering default values of the database. Default values now depend on the Redis database version.</p><h3 id="adapt-to-annlite-changes-543">Adapt to AnnLite changes (#543)</h3><p>AnnLite introduced a breaking change in <code>0.3.12</code>. Therefore, we have adapted our implementation to the latest version of AnnLite and increased the minimum required version to <code>0.3.12</code>.</p><h3 id="keep-out-of-mask-docs-in-delete-by-mask-534">Keep out of mask docs in delete by mask (#534)</h3><p>DocumentArray's delete by mask operation used to present an unexpected behavior. The following code erases the last Document, even though it is not covered by the mask:</p><pre><code class="language-python hljs">da = DocumentArray.empty(<span class="hljs-number">3</span>)
-mask = [<span class="hljs-literal">True</span>, <span class="hljs-literal">False</span>]
-<span class="hljs-keyword">del</span> da[mask]
-<span class="hljs-built_in">print</span>(<span class="hljs-built_in">len</span>(da))  <span class="hljs-comment"># prints 1</span>
-</code></pre><p>We have fixed this behavior, and DocumentArray will now correctly keep documents that are not present in the mask.</p><h3 id="fix-finetuner-link-for-totally-looks-like-532">Fix Finetuner link for Totally Looks Like (#532)</h3><p>We've fixed an incorrect link in the documentation.</p><h3 id="fix-annlite-type-map-533">Fix AnnLite type map (#533)</h3><p>DocArray type mapping used the wrong types in AnnLite. We've now replaced the types specified in the document store implementation with the correct ones.</p><h3 id="create-strawberry-types-with-kwargs-527">Create Strawberry types with kwargs (#527)</h3><p>Strawberry introduced a breaking change in <code>0.128.0</code>, making it necessary to pass parameters as key arguments. We've adapted our code base to this change.</p><h3 id="make-device-more-generic-515">Make device more generic (#515)</h3><p>Some parts of in-memory distance computation used to restrict tensor device conversion to <code>cuda</code>. We've changed the implementation to make device conversion more generic.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><h3 id="add-benchmark-reference-to-feature-summary-510">Add benchmark reference to feature summary (#510)</h3><p>We've added a "One Million Benchmark" section to the "Feature Summary" page.</p><h3 id="update-pushpull-setup-instructions-516">Update push/pull setup instructions (#516)</h3><p>We've updated the pip setup instruction required to use DocumentArray push/pull.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release: Joan Fontanals(@github_user)<br>Leon Wolf(@fogx)<br>samsja(@samsja)<br>AlaeddineAbdessalem(@alaeddine-13)<br>Halo Master(@linkerlin)<br>Han Xiao(@hanxiao)<br>Wang Bo(@bwanglzu)<br>Anne Yang(@AnneYang720)<br>Joan Fontanals(@JoanFM)</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-17-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
+da.find(query={'text': {'$exists': True}})
+</code></pre><p>you should expect a 200-300% speed increase in <code>find</code> latency.</p><p>This optimization only affects performing <code>DocumentArray.find</code> or <code>DocumentArray.match</code> when an <code>exists</code> condition is used and an <code>in-memory</code> document store is used.</p><h3 id="change-default-journal-mode-to-wal-in-sqlite-backend-506">Change default journal mode to WAL in SQLite backend (#506):</h3><p>The default journal mode in the SQLite backend is now WAL. This should improve performance when using the SQLite backend.</p><p>According to the <a href="https://sqlite.org/wal.html?ref=jina-ai-gmbh.ghost.io">SQLite docs</a>, WAL is significantly faster, provides more concurrency, and is more robust.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="keep-default-values-for-vector-similarity-parameters-in-redis-backend-559">Keep default values for vector similarity parameters in Redis backend (#559)</h3><p>DocumentArray's Redis backend previously initialized schemas in the Redis database with default values of vector similarity search parameters. Those default values came from DocArray, not Redis.</p><p>This altered the database's default behavior, although the user didn't explicitly specify that. We've changed the implementation to avoid altering default values of the database. Default values now depend on the Redis database version.</p><h3 id="adapt-to-annlite-changes-543">Adapt to AnnLite changes (#543)</h3><p>AnnLite introduced a breaking change in <code>0.3.12</code>. Therefore, we have adapted our implementation to the latest version of AnnLite and increased the minimum required version to <code>0.3.12</code>.</p><h3 id="keep-out-of-mask-docs-in-delete-by-mask-534">Keep out of mask docs in delete by mask (#534)</h3><p>DocumentArray's delete by mask operation used to present an unexpected behavior. The following code erases the last Document, even though it is not covered by the mask:</p><pre><code class="language-python">da = DocumentArray.empty(3)
+mask = [True, False]
+del da[mask]
+print(len(da))  # prints 1
+</code></pre><p>We have fixed this behavior, and DocumentArray will now correctly keep documents that are not present in the mask.</p><h3 id="fix-finetuner-link-for-totally-looks-like-532">Fix Finetuner link for Totally Looks Like (#532)</h3><p>We've fixed an incorrect link in the documentation.</p><h3 id="fix-annlite-type-map-533">Fix AnnLite type map (#533)</h3><p>DocArray type mapping used the wrong types in AnnLite. We've now replaced the types specified in the document store implementation with the correct ones.</p><h3 id="create-strawberry-types-with-kwargs-527">Create Strawberry types with kwargs (#527)</h3><p>Strawberry introduced a breaking change in <code>0.128.0</code>, making it necessary to pass parameters as key arguments. We've adapted our code base to this change.</p><h3 id="make-device-more-generic-515">Make device more generic (#515)</h3><p>Some parts of in-memory distance computation used to restrict tensor device conversion to <code>cuda</code>. We've changed the implementation to make device conversion more generic.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><h3 id="add-benchmark-reference-to-feature-summary-510">Add benchmark reference to feature summary (#510)</h3><p>We've added a "One Million Benchmark" section to the "Feature Summary" page.</p><h3 id="update-pushpull-setup-instructions-516">Update push/pull setup instructions (#516)</h3><p>We've updated the pip setup instruction required to use DocumentArray push/pull.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release: Joan Fontanals(@github_user)<br>Leon Wolf(@fogx)<br>samsja(@samsja)<br>AlaeddineAbdessalem(@alaeddine-13)<br>Halo Master(@linkerlin)<br>Han Xiao(@hanxiao)<br>Wang Bo(@bwanglzu)<br>Anne Yang(@AnneYang720)<br>Joan Fontanals(@JoanFM)</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-17-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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diff --git a/news/docarray-0-18-update/index.html b/news/docarray-0-18-update/index.html
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@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.18 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.18 Update"><meta name="description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. This release contains 7 new features, 6 bug fixes, and 8 documentation improvements. It also contains breaking changes."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-18-update"><meta property="og:title" content="DocArray 0.18 Update"><meta property="og:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. This release contains 7 new features, 6 bug fixes, and 8 documentation improvements. It also contains breaking changes."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--8--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-18-update"><meta property="twitter:title" content="DocArray 0.18 Update"><meta property="twitter:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. This release contains 7 new features, 6 bug fixes, and 8 documentation improvements. It also contains breaking changes."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--8--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.18 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.18 Update"><meta name="description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. This release contains 7 new features, 6 bug fixes, and 8 documentation improvements. It also contains breaking changes."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-18-update"><meta property="og:title" content="DocArray 0.18 Update"><meta property="og:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. This release contains 7 new features, 6 bug fixes, and 8 documentation improvements. It also contains breaking changes."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--8--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-18-update"><meta property="twitter:title" content="DocArray 0.18 Update"><meta property="twitter:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. This release contains 7 new features, 6 bug fixes, and 8 documentation improvements. It also contains breaking changes."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--8--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.18 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. This release contains 7 new features, 6 bug fixes, and 8 documentation improvements. It also contains breaking changes.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 20, 2022 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multi-modal data with a Pythonic API.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/docarray?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store</div><div class="kg-bookmark-description">🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store - GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Se...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/438303578/57aae8cb-5b20-4e35-a46c-9a742af1470c" alt=""></div></a></figure><p>This release contains 7 new features, 6 bug fixes, and 8 documentation improvements. It also contains breaking changes.</p><h2 id="%F0%9F%92%A5-backwards-incompatible-api-changes">💥 Backwards incompatible API changes</h2><h3 id="increased-minimum-versions-for-dependencies">Increased minimum versions for dependencies:</h3><table>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f01c444f-b162-466a-a563-e3fea45d8a42" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f01c444f-b162-466a-a563-e3fea45d8a42" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.18 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. This release contains 7 new features, 6 bug fixes, and 8 documentation improvements. It also contains breaking changes.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 20, 2022 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multi-modal data with a Pythonic API.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/docarray?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store</div><div class="kg-bookmark-description">🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store - GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Se...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/438303578/57aae8cb-5b20-4e35-a46c-9a742af1470c" alt=""></div></a></figure><p>This release contains 7 new features, 6 bug fixes, and 8 documentation improvements. It also contains breaking changes.</p><h2 id="%F0%9F%92%A5-backwards-incompatible-api-changes">💥 Backwards incompatible API changes</h2><h3 id="increased-minimum-versions-for-dependencies">Increased minimum versions for dependencies:</h3><table>
 <thead>
 <tr>
 <th>Package</th>
@@ -24,83 +24,83 @@
 <td><code>0.8.0</code></td>
 </tr>
 </tbody>
-</table><p>The Qdrant backend in DocArray now requires Qdrant database v0.8.0 or higher.</p><h3 id="other-api-changes">Other API Changes:</h3><ul><li>The return type of <code>DocumentArray.evaluate()</code> changed from a single score float to a dict mapping score names to score values.</li><li>Fully persisting data in <code>DocumentArray</code> using a storage backend now has to be ensured by using the context manager. Therefore, you need to wrap your write operations to a <code>DocumentArray</code> in a context manager like so:</li></ul><pre><code class="language-python hljs">my_da = DocumentArray(storage=<span class="hljs-string">'my_storage'</span>, config=...)
-<span class="hljs-keyword">with</span> my_da:
-    ...  <span class="hljs-comment"># write operations</span>
-</code></pre><p>Alternatively, you can call the <code>sync()</code> method when you finish write operations:</p><pre><code class="language-python hljs">my_da = DocumentArray(storage=<span class="hljs-string">'my_storage'</span>, config=...)
-<span class="hljs-meta">... </span> <span class="hljs-comment"># write operations</span>
+</table><p>The Qdrant backend in DocArray now requires Qdrant database v0.8.0 or higher.</p><h3 id="other-api-changes">Other API Changes:</h3><ul><li>The return type of <code>DocumentArray.evaluate()</code> changed from a single score float to a dict mapping score names to score values.</li><li>Fully persisting data in <code>DocumentArray</code> using a storage backend now has to be ensured by using the context manager. Therefore, you need to wrap your write operations to a <code>DocumentArray</code> in a context manager like so:</li></ul><pre><code class="language-python">my_da = DocumentArray(storage='my_storage', config=...)
+with my_da:
+    ...  # write operations
+</code></pre><p>Alternatively, you can call the <code>sync()</code> method when you finish write operations:</p><pre><code class="language-python">my_da = DocumentArray(storage='my_storage', config=...)
+...  # write operations
 my_da.sync()
-</code></pre><h3 id="future-api-changes">Future API Changes:</h3><ul><li>The MongoDB-like query language syntax for filtering in the Redis backend will be deprecated soon.</li><li>The <code>metric</code> and <code>metric_name</code> parameters in the <code>DocumentArray.evaluate()</code> method were renamed and accept a list type rather than a single value (as mentioned above). The old naming and type will be deprecated soon.</li></ul><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="support-geospatial-filters-in-redis-backend-579">Support geospatial filters in Redis backend (#579)</h3><p>The Redis Document Store can now accept geospatial filter queries in the <code>DocumentArray.find()</code> method:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document, DocumentArray
+</code></pre><h3 id="future-api-changes">Future API Changes:</h3><ul><li>The MongoDB-like query language syntax for filtering in the Redis backend will be deprecated soon.</li><li>The <code>metric</code> and <code>metric_name</code> parameters in the <code>DocumentArray.evaluate()</code> method were renamed and accept a list type rather than a single value (as mentioned above). The old naming and type will be deprecated soon.</li></ul><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="support-geospatial-filters-in-redis-backend-579">Support geospatial filters in Redis backend (#579)</h3><p>The Redis Document Store can now accept geospatial filter queries in the <code>DocumentArray.find()</code> method:</p><pre><code class="language-python">from docarray import Document, DocumentArray
 
-n_dim = <span class="hljs-number">3</span>
+n_dim = 3
 da = DocumentArray(
-    storage=<span class="hljs-string">'redis'</span>,
+    storage='redis',
     config={
-        <span class="hljs-string">'n_dim'</span>: n_dim,
-        <span class="hljs-string">'columns'</span>: {<span class="hljs-string">'location'</span>: <span class="hljs-string">'geo'</span>},
+        'n_dim': n_dim,
+        'columns': {'location': 'geo'},
     },
 )
-<span class="hljs-keyword">with</span> da:
+with da:
     da.extend(
         [
-            Document(<span class="hljs-built_in">id</span>=<span class="hljs-string">f'r<span class="hljs-subst">{i}</span>'</span>, tags={<span class="hljs-string">'location'</span>: <span class="hljs-string">f"<span class="hljs-subst">{-<span class="hljs-number">98.17</span>+i}</span>,<span class="hljs-subst">{<span class="hljs-number">38.71</span>+i}</span>"</span>})
-            <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">10</span>)
+            Document(id=f'r{i}', tags={'location': f"{-98.17+i},{38.71+i}"})
+            for i in range(10)
         ]
     )
-max_distance = <span class="hljs-number">300</span>
-<span class="hljs-built_in">filter</span> = <span class="hljs-string">f'@location:[-98.71 38.71 <span class="hljs-subst">{max_distance}</span> km] '</span>
-results = da.find(<span class="hljs-built_in">filter</span>=<span class="hljs-built_in">filter</span>, limit=<span class="hljs-number">10</span>)
-<span class="hljs-built_in">print</span>(
-    <span class="hljs-string">f'Locations within: <span class="hljs-subst">{max_distance}</span> km'</span>,
-    [(doc.<span class="hljs-built_in">id</span>, doc.tags[<span class="hljs-string">'location'</span>]) <span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span> results],
+max_distance = 300
+filter = f'@location:[-98.71 38.71 {max_distance} km] '
+results = da.find(filter=filter, limit=10)
+print(
+    f'Locations within: {max_distance} km',
+    [(doc.id, doc.tags['location']) for doc in results],
 )
-</code></pre><p>Results:</p><pre><code class="language-text hljs language-plaintext">Locations within: 300 km [('r0', '-98.17,38.71'), ('r1', '-97.17,39.71')]
-</code></pre><h3 id="support-multiple-metrics-in-evaluate-643">Support multiple metrics in evaluate (#643)</h3><p><code>DocumentArray.evaluate()</code> now supports computing evaluations for multiple metrics at once. The <code>metric</code> parameter is renamed to <code>metrics</code>, and <code>metric_name</code> is renamed to <code>metric_names</code>.</p><p>The <code>evaluate()</code> method expects a list for <code>metrics</code> and <code>metric_names</code> rather than a single value. For instance, instead of doing:</p><pre><code class="language-python hljs">da2.evaluate(
-    ground_truth=da1, metric=<span class="hljs-string">'precision_at_k'</span>, metric_name=<span class="hljs-string">'precision@k'</span>, k=<span class="hljs-number">5</span>
-)  <span class="hljs-comment"># returns average_evaluation</span>
-</code></pre><p>use:</p><pre><code class="language-python hljs">da2.evaluate(
-    ground_truth=da1, metrics=[<span class="hljs-string">'precision_at_k'</span>], metric_names=[<span class="hljs-string">'precision@k'</span>], k=<span class="hljs-number">10</span>
-)  <span class="hljs-comment"># returns {'precision@k': prec_at_k_average_evaluation}</span>
-</code></pre><p>The first usage will raise a deprecation warning and will be deprecated soon.</p><p>The return type is also changed: <code>evaluate()</code> will now return a dict mapping metric names to their average evaluation scores instead of a single score value.</p><p>For more info, check the <a href="https://docarray.jina.ai/fundamentals/documentarray/evaluation/?ref=jina-ai-gmbh.ghost.io">Evaluate Matches</a> section in the documentation.</p><h3 id="show-server-error-messages-in-push">Show server error messages in push</h3><p>When using <code>DocumentArray.push()</code>, error messages returned by the server will show up in the stack trace. For instance, pushing a <code>DocumentArray</code> with a name reserved by another user will return the following error:</p><pre><code class="language-text hljs language-plaintext">requests.exceptions.HTTPError: 403 Client Error: OperationNotAllowedError: Current user is not allowed to edit this artifact. Permission denied. for url: https://api.hubble.jina.ai/v2/rpc/artifact.upload
-</code></pre><h3 id="add-warnings-when-using-mongodb-like-filter-ql-syntax-in-redis-and-support-native-filter-ql-645">Add warnings when using MongoDB-like filter QL syntax in Redis and support native filter QL (#645)</h3><p>MongoDB-like filter QL is no longer supported in the Redis backend, and this release adds support for the native <a href="https://redis.io/docs/stack/search/reference/query_syntax/?ref=jina-ai-gmbh.ghost.io">Redis QL syntax</a>. Using MongoDB-like filter QL will raise a deprecation warning and will be deprecated soon.</p><p>Therefore, instead of using:</p><pre><code class="language-python hljs">redis_da.find(<span class="hljs-built_in">filter</span>={<span class="hljs-string">'field'</span>: {<span class="hljs-string">'@eq'</span>: <span class="hljs-string">'value'</span>}})
-</code></pre><p>use this syntax instead:</p><pre><code class="language-python hljs">redis_da.find(<span class="hljs-built_in">filter</span>=<span class="hljs-string">'@field:value'</span>)
-</code></pre><p>For more information, check the <a href="https://docarray.jina.ai/advanced/document-store/redis/?ref=jina-ai-gmbh.ghost.io">Redis Document Store</a> documentation.</p><h3 id="add-support-for-labeled-datasets-to-the-evaluate-function-617">Add support for labeled datasets to the evaluate function (#617)</h3><p>As of this release, <code>DocumentArray.evaluate()</code> supports labeled datasets. Labels can be added using a <code>tag</code> field in each Document of your DocumentArray:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document, DocumentArray
+</code></pre><p>Results:</p><pre><code class="language-text">Locations within: 300 km [('r0', '-98.17,38.71'), ('r1', '-97.17,39.71')]
+</code></pre><h3 id="support-multiple-metrics-in-evaluate-643">Support multiple metrics in evaluate (#643)</h3><p><code>DocumentArray.evaluate()</code> now supports computing evaluations for multiple metrics at once. The <code>metric</code> parameter is renamed to <code>metrics</code>, and <code>metric_name</code> is renamed to <code>metric_names</code>.</p><p>The <code>evaluate()</code> method expects a list for <code>metrics</code> and <code>metric_names</code> rather than a single value. For instance, instead of doing:</p><pre><code class="language-python">da2.evaluate(
+    ground_truth=da1, metric='precision_at_k', metric_name='precision@k', k=5
+)  # returns average_evaluation
+</code></pre><p>use:</p><pre><code class="language-python">da2.evaluate(
+    ground_truth=da1, metrics=['precision_at_k'], metric_names=['precision@k'], k=10
+)  # returns {'precision@k': prec_at_k_average_evaluation}
+</code></pre><p>The first usage will raise a deprecation warning and will be deprecated soon.</p><p>The return type is also changed: <code>evaluate()</code> will now return a dict mapping metric names to their average evaluation scores instead of a single score value.</p><p>For more info, check the <a href="https://docarray.jina.ai/fundamentals/documentarray/evaluation/?ref=jina-ai-gmbh.ghost.io">Evaluate Matches</a> section in the documentation.</p><h3 id="show-server-error-messages-in-push">Show server error messages in push</h3><p>When using <code>DocumentArray.push()</code>, error messages returned by the server will show up in the stack trace. For instance, pushing a <code>DocumentArray</code> with a name reserved by another user will return the following error:</p><pre><code class="language-text">requests.exceptions.HTTPError: 403 Client Error: OperationNotAllowedError: Current user is not allowed to edit this artifact. Permission denied. for url: https://api.hubble.jina.ai/v2/rpc/artifact.upload
+</code></pre><h3 id="add-warnings-when-using-mongodb-like-filter-ql-syntax-in-redis-and-support-native-filter-ql-645">Add warnings when using MongoDB-like filter QL syntax in Redis and support native filter QL (#645)</h3><p>MongoDB-like filter QL is no longer supported in the Redis backend, and this release adds support for the native <a href="https://redis.io/docs/stack/search/reference/query_syntax/?ref=jina-ai-gmbh.ghost.io">Redis QL syntax</a>. Using MongoDB-like filter QL will raise a deprecation warning and will be deprecated soon.</p><p>Therefore, instead of using:</p><pre><code class="language-python">redis_da.find(filter={'field': {'@eq': 'value'}})
+</code></pre><p>use this syntax instead:</p><pre><code class="language-python">redis_da.find(filter='@field:value')
+</code></pre><p>For more information, check the <a href="https://docarray.jina.ai/advanced/document-store/redis/?ref=jina-ai-gmbh.ghost.io">Redis Document Store</a> documentation.</p><h3 id="add-support-for-labeled-datasets-to-the-evaluate-function-617">Add support for labeled datasets to the evaluate function (#617)</h3><p>As of this release, <code>DocumentArray.evaluate()</code> supports labeled datasets. Labels can be added using a <code>tag</code> field in each Document of your DocumentArray:</p><pre><code class="language-python">import numpy as np
+from docarray import Document, DocumentArray
 
-example_da = DocumentArray([Document(tags={<span class="hljs-string">'label'</span>: (i % <span class="hljs-number">2</span>)}) <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">10</span>)])
-example_da.embeddings = np.random.random([<span class="hljs-number">10</span>, <span class="hljs-number">3</span>])
-example_da.<span class="hljs-keyword">match</span>(example_da)
-<span class="hljs-built_in">print</span>(example_da.evaluate(metric=<span class="hljs-string">'precision_at_k'</span>))
-</code></pre><p>The results of the evaluation will be stored in the <code>evaluations</code> field of each Document.</p><p>You can specify the label field name using the <code>label_tag</code> attribute:</p><pre><code class="language-python hljs">example_da = DocumentArray(
-    [Document(tags={<span class="hljs-string">'my_custom_label'</span>: (i % <span class="hljs-number">2</span>)}) <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">10</span>)]
+example_da = DocumentArray([Document(tags={'label': (i % 2)}) for i in range(10)])
+example_da.embeddings = np.random.random([10, 3])
+example_da.match(example_da)
+print(example_da.evaluate(metric='precision_at_k'))
+</code></pre><p>The results of the evaluation will be stored in the <code>evaluations</code> field of each Document.</p><p>You can specify the label field name using the <code>label_tag</code> attribute:</p><pre><code class="language-python">example_da = DocumentArray(
+    [Document(tags={'my_custom_label': (i % 2)}) for i in range(10)]
 )
-example_da.embeddings = np.random.random([<span class="hljs-number">10</span>, <span class="hljs-number">3</span>])
-example_da.<span class="hljs-keyword">match</span>(example_da)
-<span class="hljs-built_in">print</span>(example_da.evaluate(metric=<span class="hljs-string">'precision_at_k'</span>, label_tag=<span class="hljs-string">'my_custom_label'</span>))
-</code></pre><h3 id="allow-progress-bar-while-batching-628">Allow progress bar while batching (#628)</h3><p>You can see the progress of batching documents using <code>DocumentArray.batch()</code> with the <code>show_progress</code> parameter:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> time
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document, DocumentArray
+example_da.embeddings = np.random.random([10, 3])
+example_da.match(example_da)
+print(example_da.evaluate(metric='precision_at_k', label_tag='my_custom_label'))
+</code></pre><h3 id="allow-progress-bar-while-batching-628">Allow progress bar while batching (#628)</h3><p>You can see the progress of batching documents using <code>DocumentArray.batch()</code> with the <code>show_progress</code> parameter:</p><pre><code class="language-python">import time
+from docarray import Document, DocumentArray
 
-da = DocumentArray.empty(<span class="hljs-number">100000</span>)
-<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">1</span>, <span class="hljs-number">100000</span>):
-    da.append(Document(text=<span class="hljs-built_in">str</span>(i)))
+da = DocumentArray.empty(100000)
+for i in range(1, 100000):
+    da.append(Document(text=str(i)))
 
-<span class="hljs-built_in">print</span>(<span class="hljs-string">'append finished'</span>)
+print('append finished')
 
-<span class="hljs-keyword">for</span> batch <span class="hljs-keyword">in</span> da.batch(<span class="hljs-number">500</span>, show_progress=<span class="hljs-literal">True</span>):
-    time.sleep(<span class="hljs-number">0.1</span>)
-</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://user-images.githubusercontent.com/15269265/196729199-8769ecb6-c3b1-45a3-87d2-09502bebb256.gif" class="kg-image" alt="my gif"></figure><h3 id="add-the-ncomponents-pca-parameter-to-annlite-configurations-606">Add the <code>n_components</code> PCA parameter to AnnLite configurations (#606)</h3><p>The parameter <code>n_components</code> is added to <a href="https://github.com/jina-ai/annlite?ref=jina-ai-gmbh.ghost.io">AnnLite</a>'s configuration in DocArray. Use this parameter when you want to use PCA in your AnnLite backend.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="support-qdrant-080">Support Qdrant 0.8.0</h3><p>DocArray adds support for Qdrant versions greater than or equal to v0.8.0 and drops support for previous versions. Therefore, make sure to use version 0.8.0 or higher for both <code>qdrant-client</code> and the Qdrant database.</p><h3 id="sync-documentarray-using-sync-method-and-context-manager-625">Sync DocumentArray using sync() method and context manager (#625)</h3><p>Fully persisting (syncing) data in a DocumentArray to a database is now ensured using either the context manager or the <code>sync()</code> method. Make sure to wrap write operations to a <code>DocumentArray</code> in a context manager like so:</p><pre><code class="language-python hljs">my_da = DocumentArray(storage=<span class="hljs-string">'my_storage'</span>, config=...)
-<span class="hljs-keyword">with</span> my_da:
-    ...  <span class="hljs-comment"># write operations</span>
-</code></pre><p>or use the <code>sync()</code> method:</p><pre><code class="language-python hljs">my_da = DocumentArray(storage=<span class="hljs-string">'my_storage'</span>, config=...)
-<span class="hljs-meta">... </span> <span class="hljs-comment"># write operations</span>
+for batch in da.batch(500, show_progress=True):
+    time.sleep(0.1)
+</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://user-images.githubusercontent.com/15269265/196729199-8769ecb6-c3b1-45a3-87d2-09502bebb256.gif" class="kg-image" alt="my gif"></figure><h3 id="add-the-ncomponents-pca-parameter-to-annlite-configurations-606">Add the <code>n_components</code> PCA parameter to AnnLite configurations (#606)</h3><p>The parameter <code>n_components</code> is added to <a href="https://github.com/jina-ai/annlite?ref=jina-ai-gmbh.ghost.io">AnnLite</a>'s configuration in DocArray. Use this parameter when you want to use PCA in your AnnLite backend.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="support-qdrant-080">Support Qdrant 0.8.0</h3><p>DocArray adds support for Qdrant versions greater than or equal to v0.8.0 and drops support for previous versions. Therefore, make sure to use version 0.8.0 or higher for both <code>qdrant-client</code> and the Qdrant database.</p><h3 id="sync-documentarray-using-sync-method-and-context-manager-625">Sync DocumentArray using sync() method and context manager (#625)</h3><p>Fully persisting (syncing) data in a DocumentArray to a database is now ensured using either the context manager or the <code>sync()</code> method. Make sure to wrap write operations to a <code>DocumentArray</code> in a context manager like so:</p><pre><code class="language-python">my_da = DocumentArray(storage='my_storage', config=...)
+with my_da:
+    ...  # write operations
+</code></pre><p>or use the <code>sync()</code> method:</p><pre><code class="language-python">my_da = DocumentArray(storage='my_storage', config=...)
+...  # write operations
 my_da.sync()
-</code></pre><h3 id="close-the-file-handler-properly-in-loaduritoaudiotensor-609">Close the file handler properly in <code>load_uri_to_audio_tensor</code> (#609)</h3><p>Method <code>load_uri_to_audio_tensor</code> used to open a file handler without properly closing the file. This release fixes this bug and makes sure the file is opened with a context manager and is closed properly.</p><h3 id="fix-add-not-performing-deep-copy-582">Fix add not performing deep copy (#582)</h3><p>Concatenation operations in DocumentArray used to operate on objects in-place, without making a copy. This resulted in the following unexpected behavior:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
+</code></pre><h3 id="close-the-file-handler-properly-in-loaduritoaudiotensor-609">Close the file handler properly in <code>load_uri_to_audio_tensor</code> (#609)</h3><p>Method <code>load_uri_to_audio_tensor</code> used to open a file handler without properly closing the file. This release fixes this bug and makes sure the file is opened with a context manager and is closed properly.</p><h3 id="fix-add-not-performing-deep-copy-582">Fix add not performing deep copy (#582)</h3><p>Concatenation operations in DocumentArray used to operate on objects in-place, without making a copy. This resulted in the following unexpected behavior:</p><pre><code class="language-python">from docarray import DocumentArray
 
-da1 = DocumentArray.empty(<span class="hljs-number">3</span>)
-da2 = DocumentArray.empty(<span class="hljs-number">4</span>)
-da3 = DocumentArray.empty(<span class="hljs-number">5</span>)
-<span class="hljs-built_in">print</span>(da1 + da2 + da3)
+da1 = DocumentArray.empty(3)
+da2 = DocumentArray.empty(4)
+da3 = DocumentArray.empty(5)
+print(da1 + da2 + da3)
 
 da1 += da2
-<span class="hljs-built_in">print</span>(<span class="hljs-string">'length ='</span>, <span class="hljs-built_in">len</span>(da1))  <span class="hljs-comment"># expected length = 7 but prints length = 16</span>
-</code></pre><p>This release fixes the bug. Concatenation will operate on new copied objects each time rather than concatenating in-place.</p><h3 id="fix-loading-from-a-database-with-subindices-581">Fix loading from a database with subindices (#581)</h3><p>Prior to this release, reloading a DocumentArray configured with subindices from a database used to produce a <code>unique ID existing</code> error (the actual error message depends on the backend). This happened because <code>DocumentArray</code> attempted to index initial documents twice in the sub-index, although they had already been indexed.</p><p>This release fixes the issue.</p><h3 id="remove-check-of-default-value-in-nonemptyfields-565">Remove check of default value in _non_empty_fields (#565)</h3><p>Serializing a Document used to ignore scores with value <code>0.0</code>. For instance, the string representation of a Document might ignore the scores with value 0 and consider them as an empty field. This release fixes the issue.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Highlight the importance of using the context manager when it comes to fully persisting data in a database. Read more in <a href="https://docarray.jina.ai/advanced/document-store/?ref=jina-ai-gmbh.ghost.io#persistence-mutations-and-context-manager">Persistence, mutations and context manager</a>. (#613)</li><li>Fix a mention of the <code>convert_uri_to_datauri()</code> method in the documentation. (#608)</li><li>Fix the documentation build stage so that the API reference section appears correctly for Document Stores. Now you can find the API reference for Document Stores in <a href="https://docarray.jina.ai/api/?ref=jina-ai-gmbh.ghost.io#docarray-array-document-stores">this section</a>. (#594)</li><li>Fix the docstring of the <code>set_image_normalization()</code> method so that it mentions proper usage and aligns with PyTorch<br>conventions. (#585)</li><li>Clarify that the Query Language syntax of filter queries in DocArray depends on the Document Store used with the<br>DocumentArray instance. (#586)</li><li>Introduce a few improvements to the README example, so that the user takes into consideration the dataset size and<br>requirements. (#577)</li><li>Fix an example of plotting embeddings in the README. (#576)</li><li>Introduce a few grammatical improvements to the <a href="https://docarray.jina.ai/get-started/what-is/?ref=jina-ai-gmbh.ghost.io">What is DocArray</a> section. (#566)</li></ul><h2></h2><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><p>Jie Fu (@jemmyshin)<br>Wang Bo (@bwanglzu)<br>Jonathan Rowley (@jonathan-rowley)<br>Alex Cureton-Griffiths (@alexcg1)<br>Han Xiao (@hanxiao)<br>AlaeddineAbdessalem (@alaeddine-13)<br>Michael Günther (@guenthermi)<br>samsja (@samsja)<br>Johannes Messner (@JohannesMessner)<br>dong xiang (@dongxiang123)<br>Jackmin801 (@Jackmin801)<br>Joan Fontanals (@JoanFM)</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-18-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
+print('length =', len(da1))  # expected length = 7 but prints length = 16
+</code></pre><p>This release fixes the bug. Concatenation will operate on new copied objects each time rather than concatenating in-place.</p><h3 id="fix-loading-from-a-database-with-subindices-581">Fix loading from a database with subindices (#581)</h3><p>Prior to this release, reloading a DocumentArray configured with subindices from a database used to produce a <code>unique ID existing</code> error (the actual error message depends on the backend). This happened because <code>DocumentArray</code> attempted to index initial documents twice in the sub-index, although they had already been indexed.</p><p>This release fixes the issue.</p><h3 id="remove-check-of-default-value-in-nonemptyfields-565">Remove check of default value in _non_empty_fields (#565)</h3><p>Serializing a Document used to ignore scores with value <code>0.0</code>. For instance, the string representation of a Document might ignore the scores with value 0 and consider them as an empty field. This release fixes the issue.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Highlight the importance of using the context manager when it comes to fully persisting data in a database. Read more in <a href="https://docarray.jina.ai/advanced/document-store/?ref=jina-ai-gmbh.ghost.io#persistence-mutations-and-context-manager">Persistence, mutations and context manager</a>. (#613)</li><li>Fix a mention of the <code>convert_uri_to_datauri()</code> method in the documentation. (#608)</li><li>Fix the documentation build stage so that the API reference section appears correctly for Document Stores. Now you can find the API reference for Document Stores in <a href="https://docarray.jina.ai/api/?ref=jina-ai-gmbh.ghost.io#docarray-array-document-stores">this section</a>. (#594)</li><li>Fix the docstring of the <code>set_image_normalization()</code> method so that it mentions proper usage and aligns with PyTorch<br>conventions. (#585)</li><li>Clarify that the Query Language syntax of filter queries in DocArray depends on the Document Store used with the<br>DocumentArray instance. (#586)</li><li>Introduce a few improvements to the README example, so that the user takes into consideration the dataset size and<br>requirements. (#577)</li><li>Fix an example of plotting embeddings in the README. (#576)</li><li>Introduce a few grammatical improvements to the <a href="https://docarray.jina.ai/get-started/what-is/?ref=jina-ai-gmbh.ghost.io">What is DocArray</a> section. (#566)</li></ul><h2></h2><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><p>Jie Fu (@jemmyshin)<br>Wang Bo (@bwanglzu)<br>Jonathan Rowley (@jonathan-rowley)<br>Alex Cureton-Griffiths (@alexcg1)<br>Han Xiao (@hanxiao)<br>AlaeddineAbdessalem (@alaeddine-13)<br>Michael Günther (@guenthermi)<br>samsja (@samsja)<br>Johannes Messner (@JohannesMessner)<br>dong xiang (@dongxiang123)<br>Jackmin801 (@Jackmin801)<br>Joan Fontanals (@JoanFM)</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-18-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.19.1 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.19.1 Update"><meta name="description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-19-1-update"><meta property="og:title" content="DocArray 0.19.1 Update"><meta property="og:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--7-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-19-1-update"><meta property="twitter:title" content="DocArray 0.19.1 Update"><meta property="twitter:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--7-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.19.1 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.19.1 Update"><meta name="description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-19-1-update"><meta property="og:title" content="DocArray 0.19.1 Update"><meta property="og:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--7-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-19-1-update"><meta property="twitter:title" content="DocArray 0.19.1 Update"><meta property="twitter:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--7-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.19.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 24, 2022 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer the multi-modal data with a Pythonic API.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">DocArray is the common data layer used in all Jina AI products.</div></div><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.19.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v0.19.1 · docarray/docarray</div><div class="kg-bookmark-description">Release note 0.19.1This release contains 1 hot fix.🐞 Hot FixSupport for new Jina AI Cloud namespace format.This release introduces namespaces when pushing/pulling DocumentArrays to/from Jina AI...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/7abb6ed70398b5d050f404efbdbf3f952bf6f24807a66679fdfb822ddc799904/docarray/docarray/releases/tag/v0.19.1" alt=""></div></a></figure><h1 id="release-note-0191"><strong>Release Note (<code>0.19.1</code>)</strong></h1><p>This release contains 1 hot fix.</p><h2 id="%F0%9F%94%A5-hot-fix">🔥 Hot Fix</h2><h3 id="support-for-new-jina-ai-cloud-namespace-format">Support for new Jina AI Cloud namespace format.</h3><p>This release introduces namespaces when pushing/pulling DocumentArrays to/from Jina AI Cloud:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="d6cf86bc-9eb5-47fc-a7c4-8a71338ba30a" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="d6cf86bc-9eb5-47fc-a7c4-8a71338ba30a" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.19.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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 DocumentArray.pull(<span class="hljs-string">'&lt;username&gt;/&lt;da-name&gt;'</span>)
 DocumentArray.push(<span class="hljs-string">'&lt;username&gt;/&lt;da-name&gt;'</span>)</code></pre><p>You should now use a namespace when accessing an artifact. This release fixes a bug related to this namespace in DocArray.</p><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><ul><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>delgermurun (<a href="https://github.com/delgermurun?ref=jina-ai-gmbh.ghost.io">@delgermurun</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-19-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.19 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.19 Update"><meta name="description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-19-update"><meta property="og:title" content="DocArray 0.19 Update"><meta property="og:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--3-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-19-update"><meta property="twitter:title" content="DocArray 0.19 Update"><meta property="twitter:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--3-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.19 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 15, 2022 • 17 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer the multi-modal data with a Pythonic API.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">DocArray is the common data layer used in all Jina AI products.</div></div><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.19.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.19.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.19.0) Release time: 2022-11-15 15:22:16 This release contains 2 breaking changes, 11 new features, 1 performance improvement, 7 bug fixes and 7 documentation improvements.💥 Break...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/6ac968034923c2fbaf4ac5e8877415e7f3511a89b64d3e94d7c897d150d7dd14/docarray/docarray/releases/tag/v0.19.0" alt=""></div></a><figcaption>Full release note with links to pull requests</figcaption></figure><h1 id="release-note-0190">Release Note (<code>0.19.0</code>)</h1><p>This release contains 2 breaking changes, 11 new features, 1 performance improvement, 7 bug fixes and 7 documentation improvements.</p><h2 id="%F0%9F%92%A5-breaking-changes">💥 Breaking changes</h2><ul><li>DocumentArray now supports Qdrant versions above 0.10.1, and drops support for previous versions (<a href="https://github.com/docarray/docarray/pull/726?ref=jina-ai-gmbh.ghost.io">#726</a>)</li><li>DocumentArray now supports Weaviate versions above 0.16.0 and client 3.9.0, and drops support for previous versions (<a href="https://github.com/docarray/docarray/pull/736?ref=jina-ai-gmbh.ghost.io">#736</a>)</li></ul><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="add-flag-to-disable-list-like-structure-and-behavior-730-766-768-762">Add flag to disable list-like structure and behavior (<a href="https://github.com/docarray/docarray/pull/730?ref=jina-ai-gmbh.ghost.io">#730</a>, <a href="https://github.com/docarray/docarray/pull/766?ref=jina-ai-gmbh.ghost.io">#766</a>, <a href="https://github.com/docarray/docarray/pull/768?ref=jina-ai-gmbh.ghost.io">#768</a>, <a href="https://github.com/docarray/docarray/pull/762?ref=jina-ai-gmbh.ghost.io">#762</a>)</h3><p>Sometimes, you do not need to use a <code>DocumentArray</code> as a list and access by offset. Since this capability involves keeping in the store a mapping of <code>Offset2ID</code> it comes with overhead.</p><p>Now, when using a <code>DocumentArray</code> with external storage, you can disable this behavior. This improves performance when accessing Documents by ID while disallowing some <code>list-like</code> behavior.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.19 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 15, 2022 • 17 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer the multi-modal data with a Pythonic API.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">DocArray is the common data layer used in all Jina AI products.</div></div><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.19.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.19.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.19.0) Release time: 2022-11-15 15:22:16 This release contains 2 breaking changes, 11 new features, 1 performance improvement, 7 bug fixes and 7 documentation improvements.💥 Break...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/6ac968034923c2fbaf4ac5e8877415e7f3511a89b64d3e94d7c897d150d7dd14/docarray/docarray/releases/tag/v0.19.0" alt=""></div></a><figcaption>Full release note with links to pull requests</figcaption></figure><h1 id="release-note-0190">Release Note (<code>0.19.0</code>)</h1><p>This release contains 2 breaking changes, 11 new features, 1 performance improvement, 7 bug fixes and 7 documentation improvements.</p><h2 id="%F0%9F%92%A5-breaking-changes">💥 Breaking changes</h2><ul><li>DocumentArray now supports Qdrant versions above 0.10.1, and drops support for previous versions (<a href="https://github.com/docarray/docarray/pull/726?ref=jina-ai-gmbh.ghost.io">#726</a>)</li><li>DocumentArray now supports Weaviate versions above 0.16.0 and client 3.9.0, and drops support for previous versions (<a href="https://github.com/docarray/docarray/pull/736?ref=jina-ai-gmbh.ghost.io">#736</a>)</li></ul><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="add-flag-to-disable-list-like-structure-and-behavior-730-766-768-762">Add flag to disable list-like structure and behavior (<a href="https://github.com/docarray/docarray/pull/730?ref=jina-ai-gmbh.ghost.io">#730</a>, <a href="https://github.com/docarray/docarray/pull/766?ref=jina-ai-gmbh.ghost.io">#766</a>, <a href="https://github.com/docarray/docarray/pull/768?ref=jina-ai-gmbh.ghost.io">#768</a>, <a href="https://github.com/docarray/docarray/pull/762?ref=jina-ai-gmbh.ghost.io">#762</a>)</h3><p>Sometimes, you do not need to use a <code>DocumentArray</code> as a list and access by offset. Since this capability involves keeping in the store a mapping of <code>Offset2ID</code> it comes with overhead.</p><p>Now, when using a <code>DocumentArray</code> with external storage, you can disable this behavior. This improves performance when accessing Documents by ID while disallowing some <code>list-like</code> behavior.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
 
 da = DocumentArray(storage=<span class="hljs-string">'qdrant'</span>, config={<span class="hljs-string">'n_dim'</span>: <span class="hljs-number">10</span>, <span class="hljs-string">'list_like'</span>: <span class="hljs-literal">False</span>})</code></pre><h3 id="support-find-by-text-and-filter-for-elasticsearch-and-redis-backends-740">Support find by text and filter for ElasticSearch and Redis backends (<a href="https://github.com/docarray/docarray/pull/740?ref=jina-ai-gmbh.ghost.io">#740</a>)</h3><p>For ElasticSearch and Redis document stores we now support <code>find</code> by text while applying filtering.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray, Document
 
@@ -137,4 +137,4 @@
 
 Document(A(img = []))</code></pre><h3 id="propagate-context-enter-and-exit-to-subindices-737">Propagate context enter and exit to subindices (<a href="https://github.com/docarray/docarray/pull/737?ref=jina-ai-gmbh.ghost.io">#737</a>)</h3><p>When using <code>DocumentArray</code> as a context manager, <code>subindices</code> are now handled as context managers as well.<br>This makes handling <code>subindices</code> more robust.</p><h3 id="correct-type-hint-for-tags-in-documentdata-735">Correct type hint for tags in DocumentData (<a href="https://github.com/docarray/docarray/pull/735?ref=jina-ai-gmbh.ghost.io">#735</a> )</h3><p>Change the type hint for tags in <code>docarray.document.data.DocumentData</code> from <code>tags: Optional[Dict[str, 'StructValueType']]</code> to <code>tags: Optional[Dict[str, Any]]</code>.<br>This stops the IDE complaining when passing nested dictionaries inside <code>tags</code>.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><h3 id="add-new-benchmark-page-with-sift1m-dataset-691">Add new benchmark page with SIFT1M dataset (<a href="https://github.com/docarray/docarray/pull/691?ref=jina-ai-gmbh.ghost.io">#691</a>)</h3><p>Change the benchmark section of docs to use <code>SIFT1M</code> dataset. Also add <code>QPS-Recall</code> graphs to compare how different <code>DocumentStores</code> work in DocArray.</p><p>Mouse over the graph below to start interacting:</p><div>                        <script type="text/javascript">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>
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-<h3 id="other-documentation-improvements">Other documentation improvements</h3><ul><li>Add Colab notebook for interactive 3D data visualization (<a href="https://github.com/docarray/docarray/pull/749?ref=jina-ai-gmbh.ghost.io">#749</a>)</li><li>Fix Finetuner links in README (<a href="https://github.com/docarray/docarray/pull/706?ref=jina-ai-gmbh.ghost.io">#706</a>)</li><li>Use URL instead of session state in version selector (<a href="https://github.com/docarray/docarray/pull/693?ref=jina-ai-gmbh.ghost.io">#693</a>)</li><li>Replace <code>plot</code> with <code>display</code> (<a href="https://github.com/docarray/docarray/pull/689?ref=jina-ai-gmbh.ghost.io">#689</a>)</li><li>Add versioned documentation (<a href="https://github.com/docarray/docarray/pull/664?ref=jina-ai-gmbh.ghost.io">#664</a>)</li><li>Complement and rewrite evaluation docs (<a href="https://github.com/docarray/docarray/pull/662?ref=jina-ai-gmbh.ghost.io">#662</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Adrien (<a href="https://github.com/adrienlachaize?ref=jina-ai-gmbh.ghost.io">@adrienlachaize</a>)</li><li>anna-charlotte (<a href="https://github.com/anna-charlotte?ref=jina-ai-gmbh.ghost.io">@anna-charlotte</a>)</li><li>Nan Wang (<a href="https://github.com/nan-wang?ref=jina-ai-gmbh.ghost.io">@nan-wang</a>)</li><li>Bob van Luijt (<a href="https://github.com/bobvanluijt?ref=jina-ai-gmbh.ghost.io">@bobvanluijt</a>)</li><li>Dirk Kulawiak (<a href="https://github.com/dirkkul?ref=jina-ai-gmbh.ghost.io">@dirkkul</a>)</li><li>Jackmin801 (<a href="https://github.com/Jackmin801?ref=jina-ai-gmbh.ghost.io">@Jackmin801</a>)</li><li>Nicholas Dunham (<a href="https://github.com/NicholasDunham?ref=jina-ai-gmbh.ghost.io">@NicholasDunham</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>dong xiang (<a href="https://github.com/dongxiang123?ref=jina-ai-gmbh.ghost.io">@dongxiang123</a>)</li><li>Anne Yang (<a href="https://github.com/AnneYang720?ref=jina-ai-gmbh.ghost.io">@AnneYang720</a>)</li><li>Marco Luca Sbodio (<a href="https://github.com/marcosbodio?ref=jina-ai-gmbh.ghost.io">@marcosbodio</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>Han Xiao (<a href="https://github.com/hanxiao?ref=jina-ai-gmbh.ghost.io">@hanxiao</a>)</li><li>Marco Luca Sbodio (<a href="https://github.com/marcosbodio?ref=jina-ai-gmbh.ghost.io">@marcosbodio</a>])</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-19-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<h3 id="other-documentation-improvements">Other documentation improvements</h3><ul><li>Add Colab notebook for interactive 3D data visualization (<a href="https://github.com/docarray/docarray/pull/749?ref=jina-ai-gmbh.ghost.io">#749</a>)</li><li>Fix Finetuner links in README (<a href="https://github.com/docarray/docarray/pull/706?ref=jina-ai-gmbh.ghost.io">#706</a>)</li><li>Use URL instead of session state in version selector (<a href="https://github.com/docarray/docarray/pull/693?ref=jina-ai-gmbh.ghost.io">#693</a>)</li><li>Replace <code>plot</code> with <code>display</code> (<a href="https://github.com/docarray/docarray/pull/689?ref=jina-ai-gmbh.ghost.io">#689</a>)</li><li>Add versioned documentation (<a href="https://github.com/docarray/docarray/pull/664?ref=jina-ai-gmbh.ghost.io">#664</a>)</li><li>Complement and rewrite evaluation docs (<a href="https://github.com/docarray/docarray/pull/662?ref=jina-ai-gmbh.ghost.io">#662</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Adrien (<a href="https://github.com/adrienlachaize?ref=jina-ai-gmbh.ghost.io">@adrienlachaize</a>)</li><li>anna-charlotte (<a href="https://github.com/anna-charlotte?ref=jina-ai-gmbh.ghost.io">@anna-charlotte</a>)</li><li>Nan Wang (<a href="https://github.com/nan-wang?ref=jina-ai-gmbh.ghost.io">@nan-wang</a>)</li><li>Bob van Luijt (<a href="https://github.com/bobvanluijt?ref=jina-ai-gmbh.ghost.io">@bobvanluijt</a>)</li><li>Dirk Kulawiak (<a href="https://github.com/dirkkul?ref=jina-ai-gmbh.ghost.io">@dirkkul</a>)</li><li>Jackmin801 (<a href="https://github.com/Jackmin801?ref=jina-ai-gmbh.ghost.io">@Jackmin801</a>)</li><li>Nicholas Dunham (<a href="https://github.com/NicholasDunham?ref=jina-ai-gmbh.ghost.io">@NicholasDunham</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>dong xiang (<a href="https://github.com/dongxiang123?ref=jina-ai-gmbh.ghost.io">@dongxiang123</a>)</li><li>Anne Yang (<a href="https://github.com/AnneYang720?ref=jina-ai-gmbh.ghost.io">@AnneYang720</a>)</li><li>Marco Luca Sbodio (<a href="https://github.com/marcosbodio?ref=jina-ai-gmbh.ghost.io">@marcosbodio</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>Han Xiao (<a href="https://github.com/hanxiao?ref=jina-ai-gmbh.ghost.io">@hanxiao</a>)</li><li>Marco Luca Sbodio (<a href="https://github.com/marcosbodio?ref=jina-ai-gmbh.ghost.io">@marcosbodio</a>])</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-19-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.20.1 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.20.1 Update"><meta name="description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-20-1-update"><meta property="og:title" content="DocArray 0.20.1 Update"><meta property="og:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--10-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-20-1-update"><meta property="twitter:title" content="DocArray 0.20.1 Update"><meta property="twitter:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--10-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.20.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 12, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multi-modal data with a Pythonic API.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">DocArray was released under the open-source <a href="https://github.com/docarray/docarray/blob/main/LICENSE?ref=jina-ai-gmbh.ghost.io">Apache License 2.0</a> in January 2022. It is currently a sandbox project under <a href="https://lfaidata.foundation/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">LF AI &amp; Data Foundation</a>.<br><br>DocArray is the common data layer used in all Jina AI products.</div></div><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.20.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v0.20.1 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.20.1) Release time: 2022-12-12 09:32:37 🐞 Bug FixesMake Milvus DocumentArray thread safe and suitable for pytest (#904)This bug was causing connectivity issues when using multip...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/36e29e41dbe1b58335e41849417657860b6d1843e76863e08e8d9387ad2c3282/docarray/docarray/releases/tag/v0.20.1" alt=""></div></a></figure><h1 id="release-note-0201">Release Note (0.20.1)</h1><p>This release contains 2 bug fixes and 1 documentation improvement.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="make-milvus-documentarray-thread-safe-and-suitable-for-pytest-904">Make Milvus DocumentArray thread safe and suitable for pytest (<a href="https://github.com/docarray/docarray/pull/904?ref=jina-ai-gmbh.ghost.io">#904</a>)</h3><p>This bug was causing connectivity issues when using <em>multiple DocumentArrays in different threads to connect to the same Milvus instance</em>, e.g. in pytest.</p><p>This would produce an error like the following:</p><pre><code class="hljs language-yaml"><span class="hljs-string">E1207</span> <span class="hljs-number">14</span><span class="hljs-string">:59:51.357528591</span>    <span class="hljs-number">2279 </span><span class="hljs-string">fork_posix.cc:76]</span>           <span class="hljs-string">Other</span> <span class="hljs-string">threads</span> <span class="hljs-string">are</span> <span class="hljs-string">currently</span> <span class="hljs-string">calling</span> <span class="hljs-string">into</span> <span class="hljs-string">gRPC,</span> <span class="hljs-string">skipping</span> <span class="hljs-string">fork()</span> <span class="hljs-string">handlers</span>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.20.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 12, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multi-modal data with a Pythonic API.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">DocArray was released under the open-source <a href="https://github.com/docarray/docarray/blob/main/LICENSE?ref=jina-ai-gmbh.ghost.io">Apache License 2.0</a> in January 2022. It is currently a sandbox project under <a href="https://lfaidata.foundation/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">LF AI &amp; Data Foundation</a>.<br><br>DocArray is the common data layer used in all Jina AI products.</div></div><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.20.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v0.20.1 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.20.1) Release time: 2022-12-12 09:32:37 🐞 Bug FixesMake Milvus DocumentArray thread safe and suitable for pytest (#904)This bug was causing connectivity issues when using multip...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/36e29e41dbe1b58335e41849417657860b6d1843e76863e08e8d9387ad2c3282/docarray/docarray/releases/tag/v0.20.1" alt=""></div></a></figure><h1 id="release-note-0201">Release Note (0.20.1)</h1><p>This release contains 2 bug fixes and 1 documentation improvement.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="make-milvus-documentarray-thread-safe-and-suitable-for-pytest-904">Make Milvus DocumentArray thread safe and suitable for pytest (<a href="https://github.com/docarray/docarray/pull/904?ref=jina-ai-gmbh.ghost.io">#904</a>)</h3><p>This bug was causing connectivity issues when using <em>multiple DocumentArrays in different threads to connect to the same Milvus instance</em>, e.g. in pytest.</p><p>This would produce an error like the following:</p><pre><code class="hljs language-yaml"><span class="hljs-string">E1207</span> <span class="hljs-number">14</span><span class="hljs-string">:59:51.357528591</span>    <span class="hljs-number">2279 </span><span class="hljs-string">fork_posix.cc:76]</span>           <span class="hljs-string">Other</span> <span class="hljs-string">threads</span> <span class="hljs-string">are</span> <span class="hljs-string">currently</span> <span class="hljs-string">calling</span> <span class="hljs-string">into</span> <span class="hljs-string">gRPC,</span> <span class="hljs-string">skipping</span> <span class="hljs-string">fork()</span> <span class="hljs-string">handlers</span>
 <span class="hljs-string">E1207</span> <span class="hljs-number">14</span><span class="hljs-string">:59:51.367985469</span>    <span class="hljs-number">2279 </span><span class="hljs-string">fork_posix.cc:76]</span>           <span class="hljs-string">Other</span> <span class="hljs-string">threads</span> <span class="hljs-string">are</span> <span class="hljs-string">currently</span> <span class="hljs-string">calling</span> <span class="hljs-string">into</span> <span class="hljs-string">gRPC,</span> <span class="hljs-string">skipping</span> <span class="hljs-string">fork()</span> <span class="hljs-string">handlers</span>
 <span class="hljs-string">E1207</span> <span class="hljs-number">14</span><span class="hljs-string">:59:51.457061884</span>    <span class="hljs-number">3934 </span><span class="hljs-string">ev_epoll1_linux.cc:824]</span>     <span class="hljs-attr">assertion failed:</span> <span class="hljs-string">gpr_atm_no_barrier_load(&amp;g_active_poller)</span> <span class="hljs-type">!=</span> <span class="hljs-string">(gpr_atm)worker</span>
 <span class="hljs-attr">Fatal Python error:</span> <span class="hljs-string">Aborted</span></code></pre><p>This fix <em>creates a separate gRPC connection for each MilvusDocumentArray instance</em>, circumventing the issue.</p><h3 id="restore-backwards-compatibility-for-deserialization-903">Restore backwards compatibility for (de)serialization (<a href="https://github.com/docarray/docarray/pull/903?ref=jina-ai-gmbh.ghost.io">#903</a>)</h3><p><em>DocArray v0.20.0 broke (de)serialization backwards compatibility with earlier versions</em> of the library, making it impossible to load DocumentArrays from v0.19.1 or earlier from disk:</p><pre><code class="language-python hljs"><span class="hljs-comment"># DocArray &lt;= 0.19.1</span>
diff --git a/news/docarray-0-20-update/index.html b/news/docarray-0-20-update/index.html
index 45e2f38e29f..334d69ad48e 100644
--- a/news/docarray-0-20-update/index.html
+++ b/news/docarray-0-20-update/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.20 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.20 Update"><meta name="description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-20-update"><meta property="og:title" content="DocArray 0.20 Update"><meta property="og:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--9-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-20-update"><meta property="twitter:title" content="DocArray 0.20 Update"><meta property="twitter:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--9-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.20 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.20 Update"><meta name="description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-20-update"><meta property="og:title" content="DocArray 0.20 Update"><meta property="og:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--9-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-20-update"><meta property="twitter:title" content="DocArray 0.20 Update"><meta property="twitter:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--9-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 07, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multi-modal data with a Pythonic API.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">DocArray was released under the open-source <a href="https://github.com/docarray/docarray/blob/main/LICENSE?ref=jina-ai-gmbh.ghost.io">Apache License 2.0</a> in January 2022. It is currently a sandbox project under <a href="https://lfaidata.foundation/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">LF AI &amp; Data Foundation</a>.<br><br>DocArray is the common data layer used in all Jina AI products.</div></div><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.20.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.20.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.20.0) Release time: 2022-12-07 12:15:30 This release contains 7 new features, 3 bug fixes and 7 documentation improvements.🆕 FeaturesMilvus document store (#587)This release su...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/f3d9815441f39fd02bccd7a1cbe547f7c1a368690b81ff5c1a2e276be0f6ed45/docarray/docarray/releases/tag/v0.20.0" alt=""></div></a></figure><h1 id="release-note-0200">Release Note (<code>0.20.0</code>)</h1><p>This release contains 8 new features, 3 bug fixes and 7 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="milvus-document-store-587">Milvus document store (<a href="https://github.com/docarray/docarray/pull/587?ref=jina-ai-gmbh.ghost.io">#587</a>)</h3><p>This release supports the <a href="https://github.com/milvus-io/milvus?ref=jina-ai-gmbh.ghost.io">Milvus</a> vector database as a document store.</p><pre><code class="language-python hljs">da = DocumentArray(storage=<span class="hljs-string">'milvus'</span>, config={<span class="hljs-string">'n_dim'</span>: <span class="hljs-number">3</span>))</code></pre><h3 id="rootid-for-document-stores-808">Root_id for document stores (<a href="https://github.com/docarray/docarray/pull/808?ref=jina-ai-gmbh.ghost.io">#808</a>)</h3><p>When working with a vector database you can now retrieve the root document even if you search at a nested level with sub-indices (for example at chunk level).</p><pre><code class="language-python hljs">top_level_matches = da.find(query=np.random.rand(<span class="hljs-number">512</span>), on=<span class="hljs-string">'@.[image]'</span>, return_root=<span class="hljs-literal">True</span>)</code></pre><p>To allow this we now store the <code>root_id</code> in the chunks' tags. You can enable this by passing <code>root_id=True</code> in your document store configuration.</p><h3 id="filtering-based-on-text-keywords-for-qdrant-849">Filtering based on text keywords for Qdrant (<a href="https://github.com/docarray/docarray/pull/849?ref=jina-ai-gmbh.ghost.io">#849</a>)</h3><p>You can now filter based on text keywords for the Qdrant document store.</p><pre><code class="language-python hljs"><span class="hljs-built_in">filter</span> = {
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.20 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 07, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multi-modal data with a Pythonic API.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">DocArray was released under the open-source <a href="https://github.com/docarray/docarray/blob/main/LICENSE?ref=jina-ai-gmbh.ghost.io">Apache License 2.0</a> in January 2022. It is currently a sandbox project under <a href="https://lfaidata.foundation/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">LF AI &amp; Data Foundation</a>.<br><br>DocArray is the common data layer used in all Jina AI products.</div></div><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.20.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.20.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.20.0) Release time: 2022-12-07 12:15:30 This release contains 7 new features, 3 bug fixes and 7 documentation improvements.🆕 FeaturesMilvus document store (#587)This release su...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/f3d9815441f39fd02bccd7a1cbe547f7c1a368690b81ff5c1a2e276be0f6ed45/docarray/docarray/releases/tag/v0.20.0" alt=""></div></a></figure><h1 id="release-note-0200">Release Note (<code>0.20.0</code>)</h1><p>This release contains 8 new features, 3 bug fixes and 7 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="milvus-document-store-587">Milvus document store (<a href="https://github.com/docarray/docarray/pull/587?ref=jina-ai-gmbh.ghost.io">#587</a>)</h3><p>This release supports the <a href="https://github.com/milvus-io/milvus?ref=jina-ai-gmbh.ghost.io">Milvus</a> vector database as a document store.</p><pre><code class="language-python hljs">da = DocumentArray(storage=<span class="hljs-string">'milvus'</span>, config={<span class="hljs-string">'n_dim'</span>: <span class="hljs-number">3</span>))</code></pre><h3 id="rootid-for-document-stores-808">Root_id for document stores (<a href="https://github.com/docarray/docarray/pull/808?ref=jina-ai-gmbh.ghost.io">#808</a>)</h3><p>When working with a vector database you can now retrieve the root document even if you search at a nested level with sub-indices (for example at chunk level).</p><pre><code class="language-python hljs">top_level_matches = da.find(query=np.random.rand(<span class="hljs-number">512</span>), on=<span class="hljs-string">'@.[image]'</span>, return_root=<span class="hljs-literal">True</span>)</code></pre><p>To allow this we now store the <code>root_id</code> in the chunks' tags. You can enable this by passing <code>root_id=True</code> in your document store configuration.</p><h3 id="filtering-based-on-text-keywords-for-qdrant-849">Filtering based on text keywords for Qdrant (<a href="https://github.com/docarray/docarray/pull/849?ref=jina-ai-gmbh.ghost.io">#849</a>)</h3><p>You can now filter based on text keywords for the Qdrant document store.</p><pre><code class="language-python hljs"><span class="hljs-built_in">filter</span> = {
     <span class="hljs-string">'must'</span>: [
         {<span class="hljs-string">"key"</span>: <span class="hljs-string">"info"</span>, <span class="hljs-string">"match"</span>: {<span class="hljs-string">"text"</span>: <span class="hljs-string">"shoes"</span>}}
     ]
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.21 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.21 Update"><meta name="description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-21-update"><meta property="og:title" content="DocArray 0.21 Update"><meta property="og:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/docarray-new-banner.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-21-update"><meta property="twitter:title" content="DocArray 0.21 Update"><meta property="twitter:description" content="DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/docarray-new-banner.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 17, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">DocArray was released under the open-source <a href="https://github.com/docarray/docarray/blob/main/LICENSE?ref=jina-ai-gmbh.ghost.io">Apache License 2.0</a> in January 2022. It is currently a sandbox project under <a href="https://lfaidata.foundation/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">LF AI &amp; Data Foundation</a>.<br><br>DocArray is the common data layer used in all Jina AI products.</div></div><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.21.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.21.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.21.0) Release time: 2023-01-17 09:10:50 This release contains 3 new features, 7 bug fixes and 5 documentation improvements.🆕 FeaturesOpenSearch Document Store (#853)This versio...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/c2bd78b1d8a1f919f26457f43cf70c572f18ed22e51bca429fdbfaa4aec77b06/docarray/docarray/releases/tag/v0.21.0" alt=""></div></a></figure><h2 id="release-note-0210">Release Note (<code>0.21.0</code>)</h2><p>This release contains 3 new features, 7 bug fixes and 5 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="opensearch-document-store-853">OpenSearch Document Store (<a href="https://github.com/docarray/docarray/pull/853?ref=jina-ai-gmbh.ghost.io">#853</a>)</h3><p>This version of DocArray adds a <strong>new Document Store</strong>: <a href="https://opensearch.org/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">OpenSearch</a>!</p><p>You can use the OpenSearch Document Store to index your Documents and perform <strong>ANN search</strong> on them:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document, DocumentArray
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.21 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 17, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">DocArray was released under the open-source <a href="https://github.com/docarray/docarray/blob/main/LICENSE?ref=jina-ai-gmbh.ghost.io">Apache License 2.0</a> in January 2022. It is currently a sandbox project under <a href="https://lfaidata.foundation/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">LF AI &amp; Data Foundation</a>.<br><br>DocArray is the common data layer used in all Jina AI products.</div></div><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.21.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.21.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.21.0) Release time: 2023-01-17 09:10:50 This release contains 3 new features, 7 bug fixes and 5 documentation improvements.🆕 FeaturesOpenSearch Document Store (#853)This versio...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/c2bd78b1d8a1f919f26457f43cf70c572f18ed22e51bca429fdbfaa4aec77b06/docarray/docarray/releases/tag/v0.21.0" alt=""></div></a></figure><h2 id="release-note-0210">Release Note (<code>0.21.0</code>)</h2><p>This release contains 3 new features, 7 bug fixes and 5 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="opensearch-document-store-853">OpenSearch Document Store (<a href="https://github.com/docarray/docarray/pull/853?ref=jina-ai-gmbh.ghost.io">#853</a>)</h3><p>This version of DocArray adds a <strong>new Document Store</strong>: <a href="https://opensearch.org/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">OpenSearch</a>!</p><p>You can use the OpenSearch Document Store to index your Documents and perform <strong>ANN search</strong> on them:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document, DocumentArray
 <span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
 
 <span class="hljs-comment"># Connect to OpenSearch instance</span>
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.31.1 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.31.1 Update"><meta name="description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-31-1-update"><meta property="og:title" content="DocArray 0.31.1 Update"><meta property="og:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/docarray-new-banner--3--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-31-1-update"><meta property="twitter:title" content="DocArray 0.31.1 Update"><meta property="twitter:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/docarray-new-banner--3--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.31.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 11, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0311">Release Note (<code>0.31.1</code>)</h2><p>This patch release fixes a bug that was introduced in the latest minor release (<code>0.31.0</code>).</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.31.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v0.31.1 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.31.1)This patch release fixes a small bug that was introduced in the latest minor release (0.31.0).🐞 Bug Fixes Calling json or dict on a Optional nested DocList does not throw an…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/0c44a7c752f431f7a9505a1101f4909b313db687bb5aa01e135dd80b412a0ddd/docarray/docarray/releases/tag/v0.31.1" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><ul><li>Calling <code>json</code> or <code>dict</code> on an Optional nested DocList no longer throws an error if the value is set to <code>None</code> (<a href="https://github.com/docarray/docarray/pull/1512?ref=jina-ai-gmbh.ghost.io">#1512</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-31-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.31.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 11, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0311">Release Note (<code>0.31.1</code>)</h2><p>This patch release fixes a bug that was introduced in the latest minor release (<code>0.31.0</code>).</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.31.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v0.31.1 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.31.1)This patch release fixes a small bug that was introduced in the latest minor release (0.31.0).🐞 Bug Fixes Calling json or dict on a Optional nested DocList does not throw an…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/0c44a7c752f431f7a9505a1101f4909b313db687bb5aa01e135dd80b412a0ddd/docarray/docarray/releases/tag/v0.31.1" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><ul><li>Calling <code>json</code> or <code>dict</code> on an Optional nested DocList no longer throws an error if the value is set to <code>None</code> (<a href="https://github.com/docarray/docarray/pull/1512?ref=jina-ai-gmbh.ghost.io">#1512</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-31-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.31 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.31 Update"><meta name="description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-31-update"><meta property="og:title" content="DocArray 0.31 Update"><meta property="og:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/docarray-new-banner--3-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-31-update"><meta property="twitter:title" content="DocArray 0.31 Update"><meta property="twitter:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/docarray-new-banner--3-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.31 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 08, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>This release contains 2 breaking changes, 4 new features, 11 bug fixes, and several documentation improvements.</p><h1 id="release-note-v0310">Release Note (<code>v0.31.0</code>)</h1><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.31.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.31.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (v0.31.0)This release contains 4 new features, 11 bug fixes, and several documentation improvements.💥 Breaking changesReturn type of DocVec Optional Tensor (#1472)Optional tensor f…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/0ef3df9d7445019529de97003bb2eae0eeef2687d9b2e3687ae4879fd162182e/docarray/docarray/releases/tag/v0.31.0" alt=""></div></a></figure><h2 id="%F0%9F%92%A5-breaking-changes">💥 Breaking changes</h2><h3 id="return-type-of-docvec-optional-tensor-1472">Return type of <code>DocVec</code> Optional Tensor (<a href="https://github.com/docarray/docarray/pull/1472?ref=jina-ai-gmbh.ghost.io">#1472</a>)</h3><p>Optional tensor fields in a <code>DocVec</code> will return <code>None</code> instead of a list of <code>Nan</code> if the column does not hold any tensor.</p><p>This code snippet shows the breaking change:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> typing <span class="hljs-keyword">import</span> <span class="hljs-type">Optional</span>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 08, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>This release contains 2 breaking changes, 4 new features, 11 bug fixes, and several documentation improvements.</p><h1 id="release-note-v0310">Release Note (<code>v0.31.0</code>)</h1><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.31.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.31.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (v0.31.0)This release contains 4 new features, 11 bug fixes, and several documentation improvements.💥 Breaking changesReturn type of DocVec Optional Tensor (#1472)Optional tensor f…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/0ef3df9d7445019529de97003bb2eae0eeef2687d9b2e3687ae4879fd162182e/docarray/docarray/releases/tag/v0.31.0" alt=""></div></a></figure><h2 id="%F0%9F%92%A5-breaking-changes">💥 Breaking changes</h2><h3 id="return-type-of-docvec-optional-tensor-1472">Return type of <code>DocVec</code> Optional Tensor (<a href="https://github.com/docarray/docarray/pull/1472?ref=jina-ai-gmbh.ghost.io">#1472</a>)</h3><p>Optional tensor fields in a <code>DocVec</code> will return <code>None</code> instead of a list of <code>Nan</code> if the column does not hold any tensor.</p><p>This code snippet shows the breaking change:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> typing <span class="hljs-keyword">import</span> <span class="hljs-type">Optional</span>
 
 <span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocVec
 <span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> NdArray
@@ -48,4 +48,4 @@
 doc_index = InMemoryExactNNIndex[MyDoc]()
 doc_index.index(docs)
 
-<span class="hljs-built_in">print</span>(doc_index.find(<span class="hljs-number">3</span>*np.ones(<span class="hljs-number">512</span>), search_field=<span class="hljs-string">'tensor'</span>, top_k=<span class="hljs-number">3</span>))</code></pre><pre><code class="language-python hljs">FindResult(documents=&lt;DocList[MyDoc] (length=<span class="hljs-number">10</span>)&gt;, scores=array([<span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>]))</code></pre><h3 id="doclist-inherits-from-python-list-1457"><code>DocList</code> inherits from Python <code>list</code> (<a href="https://github.com/docarray/docarray/pull/1457?ref=jina-ai-gmbh.ghost.io">#1457</a>)</h3><p><code>DocList</code> is now a subclass of Python's <code>list</code>. This means that you can now use all the methods that are available to Python lists on <code>DocList</code> objects. For example, you can now use <code>len</code> on <code>DocList</code> objects and tools like Pydantic or FastAPI will be able to work with it more easily.</p><h3 id="add-len-to-docindex-1454">Add <code>len</code> to <code>DocIndex</code> (<a href="https://github.com/docarray/docarray/pull/1454?ref=jina-ai-gmbh.ghost.io">#1454</a>)</h3><p>You can now perform <code>len(vector_index)</code> which is equivalent to <code>vector_index.num_docs()</code>.</p><h3 id="other-minor-features">Other minor features</h3><ul><li>Add a <code>to_json</code> alias to <code>BaseDoc</code> (<a href="https://github.com/docarray/docarray/pull/1494?ref=jina-ai-gmbh.ghost.io">#1494</a>)</li></ul><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="point-to-older-versions-when-importing-document-or-documentarray-1422">Point to older versions when importing <code>Document</code> or <code>Documentarray</code> (<a href="https://github.com/docarray/docarray/pull/1422?ref=jina-ai-gmbh.ghost.io">#1422</a>)</h3><p>Trying to load <code>Document</code> or <code>DocumentArray</code> from DocArray would previously raise an error, saying that you needed to downgrade your version of DocArray if you wanted to use these two objects. This behavior has been fixed.</p><h3 id="fix-anydocfromprotobuf-1437">Fix <code>AnyDoc.from_protobuf</code> (<a href="https://github.com/docarray/docarray/pull/1437?ref=jina-ai-gmbh.ghost.io">#1437</a>)</h3><p><code>AnyDoc</code> can now read any <code>BaseDoc</code> protobuf file. The same applies to <code>DocList</code>.</p><h3 id="other-bug-fixes">Other bug fixes</h3><ul><li>Fix <code>extend</code> to <code>DocList</code> (<a href="https://github.com/docarray/docarray/pull/1493?ref=jina-ai-gmbh.ghost.io">#1493</a>)</li><li>Fix bug when calling <code>dict()</code> on <code>BaseDoc</code> (<a href="https://github.com/docarray/docarray/pull/1481?ref=jina-ai-gmbh.ghost.io">#1481</a>)</li><li>Fix bug when calling <code>json()</code> on <code>BaseDoc</code> (<a href="https://github.com/docarray/docarray/pull/1481?ref=jina-ai-gmbh.ghost.io">#1481</a>)</li><li>Support Pandas 2.0 by using <code>pd.concat()</code> instead of <code>df.append()</code> in <code>to_dataframe()</code> to avoid warning (<a href="https://github.com/docarray/docarray/pull/1478?ref=jina-ai-gmbh.ghost.io">#1478</a>)</li><li>Add logs to Elasticsearch index (<a href="https://github.com/docarray/docarray/pull/1427?ref=jina-ai-gmbh.ghost.io">#1427</a>)</li><li>Fix a bug in Document Index where Torch tensors that required grad were not able to be converted to <code>ndarray</code> (<a href="https://github.com/docarray/docarray/pull/1429?ref=jina-ai-gmbh.ghost.io">#1429</a>)</li><li>Fix a bug with HNSW (<a href="https://github.com/docarray/docarray/pull/1426?ref=jina-ai-gmbh.ghost.io">#1426</a>)</li><li>Hubble Binary format version bump (<a href="https://github.com/docarray/docarray/pull/1414?ref=jina-ai-gmbh.ghost.io">#1414</a>)</li><li>Save index during creation for <code>hnswlib</code> (<a href="https://github.com/docarray/docarray/pull/1424?ref=jina-ai-gmbh.ghost.io">#1424</a>)</li></ul><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Fix FastAPI docs (<a href="https://github.com/docarray/docarray/pull/1453?ref=jina-ai-gmbh.ghost.io">#1453</a>)</li><li>Index predefined Documents (<a href="https://github.com/docarray/docarray/pull/1434?ref=jina-ai-gmbh.ghost.io">#1434</a>)</li><li>Clean up data types section (<a href="https://github.com/docarray/docarray/pull/1412?ref=jina-ai-gmbh.ghost.io">#1412</a>)</li><li>Remove duplicate API reference section (<a href="https://github.com/docarray/docarray/pull/1408?ref=jina-ai-gmbh.ghost.io">#1408</a>)</li><li><code>Docindex</code> URLs (<a href="https://github.com/docarray/docarray/pull/1433?ref=jina-ai-gmbh.ghost.io">#1433</a>)</li><li>Fix Install commands hint (<a href="https://github.com/docarray/docarray/pull/1421?ref=jina-ai-gmbh.ghost.io">#1421</a>)</li><li>Add Google Analytics (<a href="https://github.com/docarray/docarray/pull/1432?ref=jina-ai-gmbh.ghost.io">#1432</a>)</li><li>Add install instructions for <code>hnswlib</code> and <code>elastic</code> document indexes (<a href="https://github.com/docarray/docarray/pull/1431?ref=jina-ai-gmbh.ghost.io">#1431</a>)</li><li>Various fixes (<a href="https://github.com/docarray/docarray/pull/1436?ref=jina-ai-gmbh.ghost.io">#1436</a>, <a href="https://github.com/docarray/docarray/pull/1417?ref=jina-ai-gmbh.ghost.io">#1417</a>, <a href="https://github.com/docarray/docarray/pull/1423?ref=jina-ai-gmbh.ghost.io">#1423</a>, <a href="https://github.com/docarray/docarray/pull/1418?ref=jina-ai-gmbh.ghost.io">#1418</a>, <a href="https://github.com/docarray/docarray/pull/1411?ref=jina-ai-gmbh.ghost.io">#1411</a>, <a href="https://github.com/docarray/docarray/pull/1419?ref=jina-ai-gmbh.ghost.io">#1419</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li><li>Anne Yang (<a href="https://github.com/AnneYang720?ref=jina-ai-gmbh.ghost.io">@AnneYang720</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li><li>カレン (<a href="https://github.com/RStar2022?ref=jina-ai-gmbh.ghost.io">@RStar2022</a>)</li><li>Aman Agarwal (<a href="https://github.com/agaraman0?ref=jina-ai-gmbh.ghost.io">@agaraman0</a>)</li><li>Yanlong Wang (<a href="https://github.com/nomagick?ref=jina-ai-gmbh.ghost.io">@nomagick</a>)</li><li>Charlotte Gerhaher (<a href="https://github.com/anna-charlotte?ref=jina-ai-gmbh.ghost.io">@anna-charlotte</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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+<span class="hljs-built_in">print</span>(doc_index.find(<span class="hljs-number">3</span>*np.ones(<span class="hljs-number">512</span>), search_field=<span class="hljs-string">'tensor'</span>, top_k=<span class="hljs-number">3</span>))</code></pre><pre><code class="language-python hljs">FindResult(documents=&lt;DocList[MyDoc] (length=<span class="hljs-number">10</span>)&gt;, scores=array([<span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.</span>]))</code></pre><h3 id="doclist-inherits-from-python-list-1457"><code>DocList</code> inherits from Python <code>list</code> (<a href="https://github.com/docarray/docarray/pull/1457?ref=jina-ai-gmbh.ghost.io">#1457</a>)</h3><p><code>DocList</code> is now a subclass of Python's <code>list</code>. This means that you can now use all the methods that are available to Python lists on <code>DocList</code> objects. For example, you can now use <code>len</code> on <code>DocList</code> objects and tools like Pydantic or FastAPI will be able to work with it more easily.</p><h3 id="add-len-to-docindex-1454">Add <code>len</code> to <code>DocIndex</code> (<a href="https://github.com/docarray/docarray/pull/1454?ref=jina-ai-gmbh.ghost.io">#1454</a>)</h3><p>You can now perform <code>len(vector_index)</code> which is equivalent to <code>vector_index.num_docs()</code>.</p><h3 id="other-minor-features">Other minor features</h3><ul><li>Add a <code>to_json</code> alias to <code>BaseDoc</code> (<a href="https://github.com/docarray/docarray/pull/1494?ref=jina-ai-gmbh.ghost.io">#1494</a>)</li></ul><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="point-to-older-versions-when-importing-document-or-documentarray-1422">Point to older versions when importing <code>Document</code> or <code>Documentarray</code> (<a href="https://github.com/docarray/docarray/pull/1422?ref=jina-ai-gmbh.ghost.io">#1422</a>)</h3><p>Trying to load <code>Document</code> or <code>DocumentArray</code> from DocArray would previously raise an error, saying that you needed to downgrade your version of DocArray if you wanted to use these two objects. This behavior has been fixed.</p><h3 id="fix-anydocfromprotobuf-1437">Fix <code>AnyDoc.from_protobuf</code> (<a href="https://github.com/docarray/docarray/pull/1437?ref=jina-ai-gmbh.ghost.io">#1437</a>)</h3><p><code>AnyDoc</code> can now read any <code>BaseDoc</code> protobuf file. The same applies to <code>DocList</code>.</p><h3 id="other-bug-fixes">Other bug fixes</h3><ul><li>Fix <code>extend</code> to <code>DocList</code> (<a href="https://github.com/docarray/docarray/pull/1493?ref=jina-ai-gmbh.ghost.io">#1493</a>)</li><li>Fix bug when calling <code>dict()</code> on <code>BaseDoc</code> (<a href="https://github.com/docarray/docarray/pull/1481?ref=jina-ai-gmbh.ghost.io">#1481</a>)</li><li>Fix bug when calling <code>json()</code> on <code>BaseDoc</code> (<a href="https://github.com/docarray/docarray/pull/1481?ref=jina-ai-gmbh.ghost.io">#1481</a>)</li><li>Support Pandas 2.0 by using <code>pd.concat()</code> instead of <code>df.append()</code> in <code>to_dataframe()</code> to avoid warning (<a href="https://github.com/docarray/docarray/pull/1478?ref=jina-ai-gmbh.ghost.io">#1478</a>)</li><li>Add logs to Elasticsearch index (<a href="https://github.com/docarray/docarray/pull/1427?ref=jina-ai-gmbh.ghost.io">#1427</a>)</li><li>Fix a bug in Document Index where Torch tensors that required grad were not able to be converted to <code>ndarray</code> (<a href="https://github.com/docarray/docarray/pull/1429?ref=jina-ai-gmbh.ghost.io">#1429</a>)</li><li>Fix a bug with HNSW (<a href="https://github.com/docarray/docarray/pull/1426?ref=jina-ai-gmbh.ghost.io">#1426</a>)</li><li>Hubble Binary format version bump (<a href="https://github.com/docarray/docarray/pull/1414?ref=jina-ai-gmbh.ghost.io">#1414</a>)</li><li>Save index during creation for <code>hnswlib</code> (<a href="https://github.com/docarray/docarray/pull/1424?ref=jina-ai-gmbh.ghost.io">#1424</a>)</li></ul><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Fix FastAPI docs (<a href="https://github.com/docarray/docarray/pull/1453?ref=jina-ai-gmbh.ghost.io">#1453</a>)</li><li>Index predefined Documents (<a href="https://github.com/docarray/docarray/pull/1434?ref=jina-ai-gmbh.ghost.io">#1434</a>)</li><li>Clean up data types section (<a href="https://github.com/docarray/docarray/pull/1412?ref=jina-ai-gmbh.ghost.io">#1412</a>)</li><li>Remove duplicate API reference section (<a href="https://github.com/docarray/docarray/pull/1408?ref=jina-ai-gmbh.ghost.io">#1408</a>)</li><li><code>Docindex</code> URLs (<a href="https://github.com/docarray/docarray/pull/1433?ref=jina-ai-gmbh.ghost.io">#1433</a>)</li><li>Fix Install commands hint (<a href="https://github.com/docarray/docarray/pull/1421?ref=jina-ai-gmbh.ghost.io">#1421</a>)</li><li>Add Google Analytics (<a href="https://github.com/docarray/docarray/pull/1432?ref=jina-ai-gmbh.ghost.io">#1432</a>)</li><li>Add install instructions for <code>hnswlib</code> and <code>elastic</code> document indexes (<a href="https://github.com/docarray/docarray/pull/1431?ref=jina-ai-gmbh.ghost.io">#1431</a>)</li><li>Various fixes (<a href="https://github.com/docarray/docarray/pull/1436?ref=jina-ai-gmbh.ghost.io">#1436</a>, <a href="https://github.com/docarray/docarray/pull/1417?ref=jina-ai-gmbh.ghost.io">#1417</a>, <a href="https://github.com/docarray/docarray/pull/1423?ref=jina-ai-gmbh.ghost.io">#1423</a>, <a href="https://github.com/docarray/docarray/pull/1418?ref=jina-ai-gmbh.ghost.io">#1418</a>, <a href="https://github.com/docarray/docarray/pull/1411?ref=jina-ai-gmbh.ghost.io">#1411</a>, <a href="https://github.com/docarray/docarray/pull/1419?ref=jina-ai-gmbh.ghost.io">#1419</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li><li>Anne Yang (<a href="https://github.com/AnneYang720?ref=jina-ai-gmbh.ghost.io">@AnneYang720</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li><li>カレン (<a href="https://github.com/RStar2022?ref=jina-ai-gmbh.ghost.io">@RStar2022</a>)</li><li>Aman Agarwal (<a href="https://github.com/agaraman0?ref=jina-ai-gmbh.ghost.io">@agaraman0</a>)</li><li>Yanlong Wang (<a href="https://github.com/nomagick?ref=jina-ai-gmbh.ghost.io">@nomagick</a>)</li><li>Charlotte Gerhaher (<a href="https://github.com/anna-charlotte?ref=jina-ai-gmbh.ghost.io">@anna-charlotte</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.32 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.32 Update"><meta name="description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-32-update"><meta property="og:title" content="DocArray 0.32 Update"><meta property="og:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/docarray-new-banner--4-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-32-update"><meta property="twitter:title" content="DocArray 0.32 Update"><meta property="twitter:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/docarray-new-banner--4-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 17, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h1 id="release-note-v0320">Release Note (<code>v0.32.0</code>)</h1><p>This release contains 4 new features, 5 bug fixes and 4 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.32.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.32.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (v0.32.0)This release contains 4 new features, 0 performance improvements, 5 bug fixes and 4 documentation improvements.🆕 FeaturesSubindex for document index (#1428)The subindex fe…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/0f59428c51fd4cbae7cc13ac0b3445b69fbc880bd396830684b5c7d395e8290e/docarray/docarray/releases/tag/v0.32.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="subindex-for-document-index-1428">Subindex for document index (<a href="https://github.com/docarray/docarray/pull/1428?ref=jina-ai-gmbh.ghost.io">#1428</a>)</h3><p>The subindex feature allows you to index documents that contain another <code>DocList</code> by automatically creating a separate collection/index for each such <code>DocList</code>:</p><pre><code class="language-python hljs"><span class="hljs-comment"># create nested document schema</span>
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">SimpleDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    tensor: NdArray[<span class="hljs-number">10</span>]
-    text: <span class="hljs-built_in">str</span>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 17, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h1 id="release-note-v0320">Release Note (<code>v0.32.0</code>)</h1><p>This release contains 4 new features, 5 bug fixes and 4 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.32.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.32.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (v0.32.0)This release contains 4 new features, 0 performance improvements, 5 bug fixes and 4 documentation improvements.🆕 FeaturesSubindex for document index (#1428)The subindex fe…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/0f59428c51fd4cbae7cc13ac0b3445b69fbc880bd396830684b5c7d395e8290e/docarray/docarray/releases/tag/v0.32.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="subindex-for-document-index-1428">Subindex for document index (<a href="https://github.com/docarray/docarray/pull/1428?ref=jina-ai-gmbh.ghost.io">#1428</a>)</h3><p>The subindex feature allows you to index documents that contain another <code>DocList</code> by automatically creating a separate collection/index for each such <code>DocList</code>:</p><pre><code class="language-python"># create nested document schema
+class SimpleDoc(BaseDoc):
+    tensor: NdArray[10]
+    text: str
 
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
+class MyDoc(BaseDoc):
     docs: DocList[SimpleDoc]
 
 
-<span class="hljs-comment"># create some docs</span>
+# create some docs
 my_docs = [
     MyDoc(
         docs=DocList[SimpleDoc](
             [
                 SimpleDoc(
-                    tensor=np.ones(<span class="hljs-number">10</span>) * (j + <span class="hljs-number">1</span>),
-                    text=<span class="hljs-string">f"hello <span class="hljs-subst">{j}</span>"</span>,
+                    tensor=np.ones(10) * (j + 1),
+                    text=f"hello {j}",
                 )
-                <span class="hljs-keyword">for</span> j <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">10</span>)
+                for j in range(10)
             ]
         ),
     )
 ]
 
-<span class="hljs-comment"># index them into Elasticsearch</span>
-index = ElasticDocIndex[MyDoc](index_name=<span class="hljs-string">"idx"</span>)
-index.index(my_docs)  <span class="hljs-comment"># index with name 'idx' and 'idx__docs' will be generated</span>
+# index them into Elasticsearch
+index = ElasticDocIndex[MyDoc](index_name="idx")
+index.index(my_docs)  # index with name 'idx' and 'idx__docs' will be generated
 
-<span class="hljs-comment"># search on the nested level (subindex)</span>
-query = np.random.rand(<span class="hljs-number">10</span>)
+# search on the nested level (subindex)
+query = np.random.rand(10)
 matches_root, matches_nested, scores = index.find_subindex(
-    query, search_field=<span class="hljs-string">"docs__tensor"</span>, limit=<span class="hljs-number">5</span>
-)</code></pre><h3 id="openapi-and-fastapi-tensor-shapes-1510">OpenAPI and FastAPI tensor shapes (<a href="https://github.com/docarray/docarray/pull/1510?ref=jina-ai-gmbh.ghost.io">#1510</a>)</h3><p>We have enabled shaped tensors to be properly represented in OpenAPI/SwaggerUI, both in examples and the schema.</p><p>This means that you can now build web APIs using FastAPI where the SwaggerUI properly communicates tensor shapes to your users:</p><pre><code class="language-python hljs"><span class="hljs-keyword">class</span> <span class="hljs-title class_">Doc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    embedding_torch: TorchTensor[<span class="hljs-number">3</span>, <span class="hljs-number">4</span>]
+    query, search_field="docs__tensor", limit=5
+)</code></pre><h3 id="openapi-and-fastapi-tensor-shapes-1510">OpenAPI and FastAPI tensor shapes (<a href="https://github.com/docarray/docarray/pull/1510?ref=jina-ai-gmbh.ghost.io">#1510</a>)</h3><p>We have enabled shaped tensors to be properly represented in OpenAPI/SwaggerUI, both in examples and the schema.</p><p>This means that you can now build web APIs using FastAPI where the SwaggerUI properly communicates tensor shapes to your users:</p><pre><code class="language-python">class Doc(BaseDoc):
+    embedding_torch: TorchTensor[3, 4]
 
 
 app = FastAPI()
 
 
-<span class="hljs-meta">@app.post(<span class="hljs-params"><span class="hljs-string">"/foo"</span>, response_model=Doc, response_class=DocArrayResponse</span>)</span>
-<span class="hljs-keyword">async</span> <span class="hljs-keyword">def</span> <span class="hljs-title function_">foo</span>(<span class="hljs-params">doc: Doc</span>) -&gt; Doc:
-    <span class="hljs-keyword">return</span> Doc(embedding=doc.embedding_np)</code></pre><p>Generated Swagger UI:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/docarray/docarray/assets/44071807/54acef18-483d-44a3-ad93-914563658ee2" class="kg-image" alt="image"></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/docarray/docarray/assets/44071807/e65d0105-7258-4a1d-a2c2-99bd198f8117" class="kg-image" alt="image"></figure><h3 id="save-and-load-in-memory-index-1534">Save and load in-memory index (<a href="https://github.com/docarray/docarray/pull/1534?ref=jina-ai-gmbh.ghost.io">#1534</a>)</h3><p>We added a <code>persist</code> method to the <code>InMemoryExactNNIndex</code> class to save the index to disk.</p><pre><code class="language-python hljs"><span class="hljs-comment"># Save your existing index as a binary file</span>
-doc_index.persist(<span class="hljs-string">'docs.bin'</span>)
-<span class="hljs-comment"># Initialize a new document index using the saved binary file</span>
-new_doc_index = InMemoryExactNNIndex[MyDoc](index_file_path=<span class="hljs-string">'docs.bin'</span>)</code></pre><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="searchfield-should-be-optional-in-hybrid-text-search-1516"><code>search_field</code> should be optional in hybrid text search (<a href="https://github.com/docarray/docarray/pull/1516?ref=jina-ai-gmbh.ghost.io">#1516</a>)</h3><p>We have added a sane default to <code>text_search()</code> for the <code>search_field</code> argument that is now Optional.</p><h3 id="check-if-file-path-exists-for-in-memory-index-1537">Check if file path exists for in-memory index (<a href="https://github.com/docarray/docarray/pull/1537?ref=jina-ai-gmbh.ghost.io">#1537</a>)</h3><p>We have added an internal check to see if <code>index_file_path</code> exists when passed to <code>InMemoryExactNNIndex</code>.</p><h3 id="add-empty-judgement-to-index-search-1533">Add empty judgement to index search (<a href="https://github.com/docarray/docarray/pull/1533?ref=jina-ai-gmbh.ghost.io">#1533</a>)</h3><p>We have ensured that empty indices do not fail when <code>find</code> is called.</p><h3 id="detach-torch-tensors-1526">Detach torch tensors (<a href="https://github.com/docarray/docarray/pull/1526?ref=jina-ai-gmbh.ghost.io">#1526</a>)</h3><p>Serializing tensors with gradients no longer fails.</p><h3 id="docvec-display-fixes-1522"><code>Docvec</code> display fixes (<a href="https://github.com/docarray/docarray/pull/1522?ref=jina-ai-gmbh.ghost.io">#1522</a>)</h3><p>We have resolved <code>Docvec</code> display issues.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Remove erroneous info (<a href="https://github.com/docarray/docarray/pull/1531?ref=jina-ai-gmbh.ghost.io">#1531</a>)</li><li>Fix link to documentation in readme (<a href="https://github.com/docarray/docarray/pull/1525?ref=jina-ai-gmbh.ghost.io">#1525</a>)</li><li>Flatten structure (<a href="https://github.com/docarray/docarray/pull/1520?ref=jina-ai-gmbh.ghost.io">#1520</a>)</li><li>Fix links (<a href="https://github.com/docarray/docarray/pull/1518?ref=jina-ai-gmbh.ghost.io">#1518</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Mohammad Kalim Akram (<a href="https://github.com/makram93?ref=jina-ai-gmbh.ghost.io">@makram93</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li><li>Anne Yang (<a href="https://github.com/AnneYang720?ref=jina-ai-gmbh.ghost.io">@AnneYang720</a>)</li><li>Zhaofeng Miao (<a href="https://github.com/mapleeit?ref=jina-ai-gmbh.ghost.io">@mapleeit</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Kacper Łukawski (<a href="https://github.com/kacperlukawski?ref=jina-ai-gmbh.ghost.io">@kacperlukawski</a>)</li><li>IyadhKhalfallah (<a href="https://github.com/IyadhKhalfallah?ref=jina-ai-gmbh.ghost.io">@IyadhKhalfallah</a>)</li><li>Saba Sturua (<a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-32-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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\ No newline at end of file
+@app.post("/foo", response_model=Doc, response_class=DocArrayResponse)
+async def foo(doc: Doc) -&gt; Doc:
+    return Doc(embedding=doc.embedding_np)</code></pre><p>Generated Swagger UI:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/docarray/docarray/assets/44071807/54acef18-483d-44a3-ad93-914563658ee2" class="kg-image" alt="image"></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/docarray/docarray/assets/44071807/e65d0105-7258-4a1d-a2c2-99bd198f8117" class="kg-image" alt="image"></figure><h3 id="save-and-load-in-memory-index-1534">Save and load in-memory index (<a href="https://github.com/docarray/docarray/pull/1534?ref=jina-ai-gmbh.ghost.io">#1534</a>)</h3><p>We added a <code>persist</code> method to the <code>InMemoryExactNNIndex</code> class to save the index to disk.</p><pre><code class="language-python"># Save your existing index as a binary file
+doc_index.persist('docs.bin')
+# Initialize a new document index using the saved binary file
+new_doc_index = InMemoryExactNNIndex[MyDoc](index_file_path='docs.bin')</code></pre><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="searchfield-should-be-optional-in-hybrid-text-search-1516"><code>search_field</code> should be optional in hybrid text search (<a href="https://github.com/docarray/docarray/pull/1516?ref=jina-ai-gmbh.ghost.io">#1516</a>)</h3><p>We have added a sane default to <code>text_search()</code> for the <code>search_field</code> argument that is now Optional.</p><h3 id="check-if-file-path-exists-for-in-memory-index-1537">Check if file path exists for in-memory index (<a href="https://github.com/docarray/docarray/pull/1537?ref=jina-ai-gmbh.ghost.io">#1537</a>)</h3><p>We have added an internal check to see if <code>index_file_path</code> exists when passed to <code>InMemoryExactNNIndex</code>.</p><h3 id="add-empty-judgement-to-index-search-1533">Add empty judgement to index search (<a href="https://github.com/docarray/docarray/pull/1533?ref=jina-ai-gmbh.ghost.io">#1533</a>)</h3><p>We have ensured that empty indices do not fail when <code>find</code> is called.</p><h3 id="detach-torch-tensors-1526">Detach torch tensors (<a href="https://github.com/docarray/docarray/pull/1526?ref=jina-ai-gmbh.ghost.io">#1526</a>)</h3><p>Serializing tensors with gradients no longer fails.</p><h3 id="docvec-display-fixes-1522"><code>Docvec</code> display fixes (<a href="https://github.com/docarray/docarray/pull/1522?ref=jina-ai-gmbh.ghost.io">#1522</a>)</h3><p>We have resolved <code>Docvec</code> display issues.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Remove erroneous info (<a href="https://github.com/docarray/docarray/pull/1531?ref=jina-ai-gmbh.ghost.io">#1531</a>)</li><li>Fix link to documentation in readme (<a href="https://github.com/docarray/docarray/pull/1525?ref=jina-ai-gmbh.ghost.io">#1525</a>)</li><li>Flatten structure (<a href="https://github.com/docarray/docarray/pull/1520?ref=jina-ai-gmbh.ghost.io">#1520</a>)</li><li>Fix links (<a href="https://github.com/docarray/docarray/pull/1518?ref=jina-ai-gmbh.ghost.io">#1518</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Mohammad Kalim Akram (<a href="https://github.com/makram93?ref=jina-ai-gmbh.ghost.io">@makram93</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li><li>Anne Yang (<a href="https://github.com/AnneYang720?ref=jina-ai-gmbh.ghost.io">@AnneYang720</a>)</li><li>Zhaofeng Miao (<a href="https://github.com/mapleeit?ref=jina-ai-gmbh.ghost.io">@mapleeit</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Kacper Łukawski (<a href="https://github.com/kacperlukawski?ref=jina-ai-gmbh.ghost.io">@kacperlukawski</a>)</li><li>IyadhKhalfallah (<a href="https://github.com/IyadhKhalfallah?ref=jina-ai-gmbh.ghost.io">@IyadhKhalfallah</a>)</li><li>Saba Sturua (<a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-32-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
diff --git a/news/docarray-0-33-update/index.html b/news/docarray-0-33-update/index.html
index 61dafbe074a..f48a69bfd26 100644
--- a/news/docarray-0-33-update/index.html
+++ b/news/docarray-0-33-update/index.html
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.
 
-</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 07, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0330">Release Note (<code>0.33.0</code>)</h2><p>This release contains 1 new feature, 1 performance improvement, 9 bug fixes, and 4 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.33.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.33.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.33.0) Release time: 2023-06-06 14:05:56 This release contains 1 new feature, 1 performance improvement, 9 bug fixes and 4 documentation improvements.🆕 FeaturesAllow coercion bet…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/7368cfa8c512ac2b92d4ce6227add95f330915edd780c6a0e1f08e7f33fc39a0/docarray/docarray/releases/tag/v0.33.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="allow-coercion-between-different-tensor-types-1552-1588">Allow coercion between different Tensor types (<a href="https://github.com/docarray/docarray/pull/1552?ref=jina-ai-gmbh.ghost.io">#1552</a>) (<a href="https://github.com/docarray/docarray/pull/1588?ref=jina-ai-gmbh.ghost.io">#1588</a>)</h3><p>Allow coercing to a <code>TorchTensor</code> from an <code>NdArray</code> or <code>TensorFlowTensor</code> and the other way around.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc
-<span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> TorchTensor
-<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
+</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 07, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0330">Release Note (<code>0.33.0</code>)</h2><p>This release contains 1 new feature, 1 performance improvement, 9 bug fixes, and 4 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.33.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.33.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.33.0) Release time: 2023-06-06 14:05:56 This release contains 1 new feature, 1 performance improvement, 9 bug fixes and 4 documentation improvements.🆕 FeaturesAllow coercion bet…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/7368cfa8c512ac2b92d4ce6227add95f330915edd780c6a0e1f08e7f33fc39a0/docarray/docarray/releases/tag/v0.33.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="allow-coercion-between-different-tensor-types-1552-1588">Allow coercion between different Tensor types (<a href="https://github.com/docarray/docarray/pull/1552?ref=jina-ai-gmbh.ghost.io">#1552</a>) (<a href="https://github.com/docarray/docarray/pull/1588?ref=jina-ai-gmbh.ghost.io">#1588</a>)</h3><p>Allow coercing to a <code>TorchTensor</code> from an <code>NdArray</code> or <code>TensorFlowTensor</code> and the other way around.</p><pre><code class="language-python">from docarray import BaseDoc
+from docarray.typing import TorchTensor
+import numpy as np
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyTensorsDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
+class MyTensorsDoc(BaseDoc):
     tensor: TorchTensor
 
-doc = MyTensorsDoc(tensor=np.zeros(<span class="hljs-number">512</span>))
-doc.summary()</code></pre><pre><code class="language-shell hljs">📄 MyTensorsDoc : 0a10f88 ...
+doc = MyTensorsDoc(tensor=np.zeros(512))
+doc.summary()</code></pre><pre><code class="language-shell">📄 MyTensorsDoc : 0a10f88 ...
 ╭─────────────────────┬────────────────────────────────────────────────────────╮
 │ Attribute           │ Value                                                  │
 ├─────────────────────┼────────────────────────────────────────────────────────┤
 │ tensor: TorchTensor │ TorchTensor of shape (512,), dtype: torch.float64      │
 ╰─────────────────────┴────────────────────────────────────────────────────────╯
-</code></pre><h2 id="%F0%9F%9A%80-performance">🚀 Performance</h2><h3 id="avoid-stack-embedding-for-every-search-1586">Avoid stack embedding for every search (<a href="https://github.com/docarray/docarray/pull/1586?ref=jina-ai-gmbh.ghost.io">#1586</a>)</h3><p>We have made a performance improvement for the <code>find</code> interface for <code>InMemoryExactNNIndex</code> that gives a ~2x speedup.</p><p>The script used to measure this is as follows:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> torch <span class="hljs-keyword">import</span> rand
-<span class="hljs-keyword">from</span> time <span class="hljs-keyword">import</span> perf_counter
+</code></pre><h2 id="%F0%9F%9A%80-performance">🚀 Performance</h2><h3 id="avoid-stack-embedding-for-every-search-1586">Avoid stack embedding for every search (<a href="https://github.com/docarray/docarray/pull/1586?ref=jina-ai-gmbh.ghost.io">#1586</a>)</h3><p>We have made a performance improvement for the <code>find</code> interface for <code>InMemoryExactNNIndex</code> that gives a ~2x speedup.</p><p>The script used to measure this is as follows:</p><pre><code class="language-python">from torch import rand
+from time import perf_counter
 
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocList
-<span class="hljs-keyword">from</span> docarray.index.backends.in_memory <span class="hljs-keyword">import</span> InMemoryExactNNIndex
-<span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> TorchTensor
+from docarray import BaseDoc, DocList
+from docarray.index.backends.in_memory import InMemoryExactNNIndex
+from docarray.typing import TorchTensor
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDocument</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
+class MyDocument(BaseDoc):
     embedding: TorchTensor
     embedding2: TorchTensor
     embedding3: TorchTensor
 
-<span class="hljs-keyword">def</span> <span class="hljs-title function_">generate_doc_list</span>(<span class="hljs-params">num_docs: <span class="hljs-built_in">int</span>, dims: <span class="hljs-built_in">int</span></span>) -&gt; DocList[MyDocument]:
-    <span class="hljs-keyword">return</span> DocList[MyDocument](
+def generate_doc_list(num_docs: int, dims: int) -&gt; DocList[MyDocument]:
+    return DocList[MyDocument](
         [
             MyDocument(
                 embedding=rand(dims),
                 embedding2=rand(dims),
                 embedding3=rand(dims),
             )
-            <span class="hljs-keyword">for</span> _ <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(num_docs)
+            for _ in range(num_docs)
         ]
     )
 
-num_docs, num_queries, dims = <span class="hljs-number">500000</span>, <span class="hljs-number">1000</span>, <span class="hljs-number">128</span>
+num_docs, num_queries, dims = 500000, 1000, 128
 data_list = generate_doc_list(num_docs, dims)
 queries = generate_doc_list(num_queries, dims)
 
 index = InMemoryExactNNIndex[MyDocument](data_list)
 
 start = perf_counter()
-<span class="hljs-keyword">for</span> _ <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">5</span>):
-    matches, scores =  index.find_batched(queries, search_field=<span class="hljs-string">'embedding'</span>)
-
-<span class="hljs-built_in">print</span>(<span class="hljs-string">f"Number of queries: <span class="hljs-subst">{num_queries}</span> \n"</span>
-      <span class="hljs-string">f"Number of indexed documents: <span class="hljs-subst">{num_docs}</span> \n"</span>
-      <span class="hljs-string">f"Total time: <span class="hljs-subst">{(perf_counter() - start)/<span class="hljs-number">5</span>}</span> seconds"</span>)</code></pre><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="respect-limit-parameter-in-filter-for-index-backends-1618">Respect <code>limit</code> parameter in <code>filter</code> for index backends (<a href="https://github.com/docarray/docarray/pull/1618?ref=jina-ai-gmbh.ghost.io">#1618</a>)</h3><p><code>InMemoryExactNNIndex</code> and <code>HnswDocumentIndex</code> now respect the <code>limit</code> parameter in the <code>filter</code> API.</p><h3 id="hnswdocumentindex-can-search-with-limit-greater-than-number-of-documents-1611"><code>HnswDocumentIndex</code> can search with <code>limit</code> greater than number of documents (<a href="https://github.com/docarray/docarray/pull/1611?ref=jina-ai-gmbh.ghost.io">#1611</a>)</h3><p><code>HnswDocumentIndex</code> now allows to call <code>find</code> with a <code>limit</code> parameter larger than the number of indexed documents.</p><h3 id="allow-updating-hnswdocumentindex-1604">Allow updating <code>HnswDocumentIndex</code> (<a href="https://github.com/docarray/docarray/pull/1604?ref=jina-ai-gmbh.ghost.io">#1604</a>)</h3><p><code>HnswDocumentIndex</code> now allows reindexing documents with the same <code>id</code>, updating the original documents.</p><h3 id="dynamically-resize-internal-index-to-adapt-to-increasing-number-of-documents-1602">Dynamically resize internal index to adapt to increasing number of documents (<a href="https://github.com/docarray/docarray/pull/1602?ref=jina-ai-gmbh.ghost.io">#1602</a>)</h3><p><code>HnswDocumentIndex</code> now allows indexing more than <code>max_elements</code>, dynamically adapting the index as it grows.</p><h3 id="fix-simple-usage-of-hnswdocumentindex-1596">Fix simple usage of <code>HnswDocumentIndex</code> (<a href="https://github.com/docarray/docarray/pull/1596?ref=jina-ai-gmbh.ghost.io">#1596</a>)</h3><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray.index <span class="hljs-keyword">import</span> HnswDocumentIndex
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocList, BaseDoc
-<span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> NdArray
-<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
-
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    text: <span class="hljs-built_in">str</span>
-    embedding: NdArray[<span class="hljs-number">128</span>]
-
-docs = [MyDoc(text=<span class="hljs-string">'hey'</span>, embedding=np.random.rand(<span class="hljs-number">128</span>)) <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">200</span>)]
-index = HnswDocumentIndex[MyDoc](work_dir=<span class="hljs-string">'./tmp'</span>, index_name=<span class="hljs-string">'index'</span>)
+for _ in range(5):
+    matches, scores =  index.find_batched(queries, search_field='embedding')
+
+print(f"Number of queries: {num_queries} \n"
+      f"Number of indexed documents: {num_docs} \n"
+      f"Total time: {(perf_counter() - start)/5} seconds")</code></pre><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="respect-limit-parameter-in-filter-for-index-backends-1618">Respect <code>limit</code> parameter in <code>filter</code> for index backends (<a href="https://github.com/docarray/docarray/pull/1618?ref=jina-ai-gmbh.ghost.io">#1618</a>)</h3><p><code>InMemoryExactNNIndex</code> and <code>HnswDocumentIndex</code> now respect the <code>limit</code> parameter in the <code>filter</code> API.</p><h3 id="hnswdocumentindex-can-search-with-limit-greater-than-number-of-documents-1611"><code>HnswDocumentIndex</code> can search with <code>limit</code> greater than number of documents (<a href="https://github.com/docarray/docarray/pull/1611?ref=jina-ai-gmbh.ghost.io">#1611</a>)</h3><p><code>HnswDocumentIndex</code> now allows to call <code>find</code> with a <code>limit</code> parameter larger than the number of indexed documents.</p><h3 id="allow-updating-hnswdocumentindex-1604">Allow updating <code>HnswDocumentIndex</code> (<a href="https://github.com/docarray/docarray/pull/1604?ref=jina-ai-gmbh.ghost.io">#1604</a>)</h3><p><code>HnswDocumentIndex</code> now allows reindexing documents with the same <code>id</code>, updating the original documents.</p><h3 id="dynamically-resize-internal-index-to-adapt-to-increasing-number-of-documents-1602">Dynamically resize internal index to adapt to increasing number of documents (<a href="https://github.com/docarray/docarray/pull/1602?ref=jina-ai-gmbh.ghost.io">#1602</a>)</h3><p><code>HnswDocumentIndex</code> now allows indexing more than <code>max_elements</code>, dynamically adapting the index as it grows.</p><h3 id="fix-simple-usage-of-hnswdocumentindex-1596">Fix simple usage of <code>HnswDocumentIndex</code> (<a href="https://github.com/docarray/docarray/pull/1596?ref=jina-ai-gmbh.ghost.io">#1596</a>)</h3><pre><code class="language-python">from docarray.index import HnswDocumentIndex
+from docarray import DocList, BaseDoc
+from docarray.typing import NdArray
+import numpy as np
+
+class MyDoc(BaseDoc):
+    text: str
+    embedding: NdArray[128]
+
+docs = [MyDoc(text='hey', embedding=np.random.rand(128)) for i in range(200)]
+index = HnswDocumentIndex[MyDoc](work_dir='./tmp', index_name='index')
 index.index(docs=DocList[MyDoc](docs))
-resp = index.find_batched(queries=DocList[MyDoc](docs[<span class="hljs-number">0</span>:<span class="hljs-number">3</span>]), search_field=<span class="hljs-string">'embedding'</span>)</code></pre><p>Previously, this basic usage threw an exception:</p><pre><code class="hljs language-kotlin">TypeError: ModelMeta<span class="hljs-keyword">class</span> <span class="hljs-title class_">object</span> <span class="hljs-title">argument</span> <span class="hljs-title">after</span>  <span class="hljs-title">must</span> <span class="hljs-title">be</span> <span class="hljs-title">a</span> <span class="hljs-title">mapping</span>, <span class="hljs-type">not</span> <span class="hljs-title">MyDoc</span></code></pre><p>Now, it works as expected.</p><h3 id="fix-inmemoryexactnnindex-index-initialization-with-nested-doclist-1582">Fix <code>InMemoryExactNNIndex</code> index initialization with nested <code>DocList</code> (<a href="https://github.com/docarray/docarray/pull/1582?ref=jina-ai-gmbh.ghost.io">#1582</a>)</h3><p>Instantiating an <code>InMemoryExactNNIndex</code> with a <code>Document</code> schema that had a nested <code>DocList</code> previously threw this error:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocList
-<span class="hljs-keyword">from</span> docarray.documents <span class="hljs-keyword">import</span> TextDoc
-<span class="hljs-keyword">from</span> docarray.index <span class="hljs-keyword">import</span> HnswDocumentIndex
+resp = index.find_batched(queries=DocList[MyDoc](docs[0:3]), search_field='embedding')</code></pre><p>Previously, this basic usage threw an exception:</p><pre><code>TypeError: ModelMetaclass object argument after  must be a mapping, not MyDoc</code></pre><p>Now, it works as expected.</p><h3 id="fix-inmemoryexactnnindex-index-initialization-with-nested-doclist-1582">Fix <code>InMemoryExactNNIndex</code> index initialization with nested <code>DocList</code> (<a href="https://github.com/docarray/docarray/pull/1582?ref=jina-ai-gmbh.ghost.io">#1582</a>)</h3><p>Instantiating an <code>InMemoryExactNNIndex</code> with a <code>Document</code> schema that had a nested <code>DocList</code> previously threw this error:</p><pre><code class="language-python">from docarray import BaseDoc, DocList
+from docarray.documents import TextDoc
+from docarray.index import HnswDocumentIndex
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    text: <span class="hljs-built_in">str</span>,
+class MyDoc(BaseDoc):
+    text: str,
     d_list: DocList[TextDoc]
 
-index = HnswDocumentIndex[MyDoc]()</code></pre><pre><code class="hljs language-php"><span class="hljs-built_in">TypeError</span>: docarray.index.<span class="hljs-keyword">abstract</span>.BaseDocIndex.<span class="hljs-title function_ invoke__">__init__</span>() got multiple values <span class="hljs-keyword">for</span> keyword argument <span class="hljs-string">'db_config'</span>
-</code></pre><p>Now it can be successfully instantiated.</p><h3 id="fix-summary-of-document-with-list-1595">Fix summary of document with list (<a href="https://github.com/docarray/docarray/pull/1595?ref=jina-ai-gmbh.ghost.io">#1595</a>)</h3><p>Calling <code>summary</code> on a document with a <code>List</code> attribute previously showed the wrong type:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocList
-<span class="hljs-keyword">from</span> typing <span class="hljs-keyword">import</span> <span class="hljs-type">List</span>
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">TestDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    str_list: <span class="hljs-type">List</span>[<span class="hljs-built_in">str</span>]
+index = HnswDocumentIndex[MyDoc]()</code></pre><pre><code>TypeError: docarray.index.abstract.BaseDocIndex.__init__() got multiple values for keyword argument 'db_config'
+</code></pre><p>Now it can be successfully instantiated.</p><h3 id="fix-summary-of-document-with-list-1595">Fix summary of document with list (<a href="https://github.com/docarray/docarray/pull/1595?ref=jina-ai-gmbh.ghost.io">#1595</a>)</h3><p>Calling <code>summary</code> on a document with a <code>List</code> attribute previously showed the wrong type:</p><pre><code class="language-python">from docarray import BaseDoc, DocList
+from typing import List
+class TestDoc(BaseDoc):
+    str_list: List[str]
 
-dl = DocList[TestDoc]([TestDoc(str_list=[]), TestDoc(str_list=[<span class="hljs-string">"1"</span>])])
-dl.summary()</code></pre><p>Previous output:</p><pre><code class="language-shell hljs">╭─────── DocList Summary ───────╮
+dl = DocList[TestDoc]([TestDoc(str_list=[]), TestDoc(str_list=["1"])])
+dl.summary()</code></pre><p>Previous output:</p><pre><code class="language-shell">╭─────── DocList Summary ───────╮
 │                               │
 │   Type     DocList[TestDoc]   │
 │   Length   2                  │
@@ -108,7 +108,7 @@
 │   └── str_list: str   │
 │                       │
 ╰───────────────────────╯
-</code></pre><p>New output:</p><pre><code class="language-shell hljs">╭─────── DocList Summary ───────╮
+</code></pre><p>New output:</p><pre><code class="language-shell">╭─────── DocList Summary ───────╮
 │                               │
 │   Type     DocList[TestDoc]   │
 │   Length   2                  │
@@ -120,14 +120,14 @@
 │   └── str_list: List[str]   │
 │                             │
 ╰─────────────────────────────╯
-</code></pre><h3 id="solve-issues-caused-by-issubclass-1594">Solve issues caused by <code>issubclass</code> (<a href="https://github.com/docarray/docarray/pull/1594?ref=jina-ai-gmbh.ghost.io">#1594</a>)</h3><p><code>DocArray</code> relies heavily on calling Python's <code>issubclass</code> method which caused multiple issues. We now use a safe version that counts for edge cases and types.</p><h3 id="make-example-payload-a-string-rather-than-bytes-1587">Make example payload a string rather than bytes (<a href="https://github.com/docarray/docarray/pull/1587?ref=jina-ai-gmbh.ghost.io">#1587</a>)</h3><p>The <code>example</code> payload of a given document schema with <code>Tensor</code> attribute was previously of <code>bytes</code> type. This has now been changed to <code>str</code>.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocList, BaseDoc
-<span class="hljs-keyword">from</span> docarray.documents <span class="hljs-keyword">import</span> TextDoc
-<span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> NdArray
-<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
+</code></pre><h3 id="solve-issues-caused-by-issubclass-1594">Solve issues caused by <code>issubclass</code> (<a href="https://github.com/docarray/docarray/pull/1594?ref=jina-ai-gmbh.ghost.io">#1594</a>)</h3><p><code>DocArray</code> relies heavily on calling Python's <code>issubclass</code> method which caused multiple issues. We now use a safe version that counts for edge cases and types.</p><h3 id="make-example-payload-a-string-rather-than-bytes-1587">Make example payload a string rather than bytes (<a href="https://github.com/docarray/docarray/pull/1587?ref=jina-ai-gmbh.ghost.io">#1587</a>)</h3><p>The <code>example</code> payload of a given document schema with <code>Tensor</code> attribute was previously of <code>bytes</code> type. This has now been changed to <code>str</code>.</p><pre><code class="language-python">from docarray import DocList, BaseDoc
+from docarray.documents import TextDoc
+from docarray.typing import NdArray
+import numpy as np
 
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    text: <span class="hljs-built_in">str</span>
-    embedding: NdArray[<span class="hljs-number">128</span>]
+class MyDoc(BaseDoc):
+    text: str
+    embedding: NdArray[128]
 
-<span class="hljs-built_in">print</span>(<span class="hljs-string">f'<span class="hljs-subst">{<span class="hljs-built_in">type</span>(MyDoc.schema()[<span class="hljs-string">"properties"</span>][<span class="hljs-string">"embedding"</span>][<span class="hljs-string">"example"</span>])}</span>'</span>)</code></pre><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Add forward declaration steps to example to avoid pickling error (<a href="https://github.com/docarray/docarray/pull/1615?ref=jina-ai-gmbh.ghost.io">#1615</a>)</li><li>Fix <code>n_dim</code> to <code>dim</code> (<a href="https://github.com/docarray/docarray/pull/1610?ref=jina-ai-gmbh.ghost.io">#1610</a>)</li><li>Add "in memory" to documentation as list of supported vector indexes (<a href="https://github.com/docarray/docarray/pull/1607?ref=jina-ai-gmbh.ghost.io">#1607</a>)</li><li>Add a tensor section (<a href="https://github.com/docarray/docarray/pull/1576?ref=jina-ai-gmbh.ghost.io">#1576</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Mohammad Kalim Akram (<a href="https://github.com/makram93?ref=jina-ai-gmbh.ghost.io">@makram93</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Saba Sturua (<a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>maxwelljin (<a href="https://github.com/maxwelljin?ref=jina-ai-gmbh.ghost.io">@maxwelljin</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-33-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; 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\ No newline at end of file
+print(f'{type(MyDoc.schema()["properties"]["embedding"]["example"])}')</code></pre><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Add forward declaration steps to example to avoid pickling error (<a href="https://github.com/docarray/docarray/pull/1615?ref=jina-ai-gmbh.ghost.io">#1615</a>)</li><li>Fix <code>n_dim</code> to <code>dim</code> (<a href="https://github.com/docarray/docarray/pull/1610?ref=jina-ai-gmbh.ghost.io">#1610</a>)</li><li>Add "in memory" to documentation as list of supported vector indexes (<a href="https://github.com/docarray/docarray/pull/1607?ref=jina-ai-gmbh.ghost.io">#1607</a>)</li><li>Add a tensor section (<a href="https://github.com/docarray/docarray/pull/1576?ref=jina-ai-gmbh.ghost.io">#1576</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Mohammad Kalim Akram (<a href="https://github.com/makram93?ref=jina-ai-gmbh.ghost.io">@makram93</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Saba Sturua (<a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>maxwelljin (<a href="https://github.com/maxwelljin?ref=jina-ai-gmbh.ghost.io">@maxwelljin</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-33-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="745d316d-9542-44c5-bf38-0721399c7802" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="745d316d-9542-44c5-bf38-0721399c7802" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.
-</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 21, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0340"><br>Release Note <code>(0.34.0)</code></h2><p>This release contains 2 breaking changes, 3 new features, 11 bug fixes, and 2 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.34.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.34.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.34.0) Release time: 2023-06-21 08:15:43 This release contains 2 breaking changes, 3 new features, 11 bug fixes, and 2 documentation improvements.💣 Breaking ChangesTerminate Pyth…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/f6095e3c5d7eebaa8dadc9d902529fdb5822430bbe08693b91cc6b0d3a785b4d/docarray/docarray/releases/tag/v0.34.0" alt=""></div></a></figure><h2 id="%F0%9F%92%A3-breaking-changes">💣 Breaking Changes</h2><h3 id="terminate-python-37-support">Terminate Python 3.7 support</h3><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text"><strong>DocArray will now require Python 3.8. We can no longer assure compatibility with Python 3.7.</strong></div></div><p>We decided to drop it for two reasons:</p><ul><li>Several dependencies of DocArray require Python 3.8.</li><li>Python <a href="https://endoflife.date/python?ref=jina-ai-gmbh.ghost.io" rel="nofollow">long-term support for 3.7 is ending</a> this week. This means there will no longer be security updates for Python 3.7, making this a good time for us to change our requirements.</li></ul><h3 id="changes-to-docvec-protobuf-definition-1639">Changes to <code>DocVec</code> Protobuf definition (<a href="https://github.com/docarray/docarray/pull/1639?ref=jina-ai-gmbh.ghost.io">#1639</a>)</h3><p>In order to fix the bug in the <code>DocVec</code> Protobuf serialization described in <a href="https://github.com/docarray/docarray/issues/1561?ref=jina-ai-gmbh.ghost.io">#1561</a>, we have changed the <code>DocVec</code> .proto definition.</p><p>This means that <strong><code>DocVec</code> objects serialized with DocArray v0.33.0 or earlier cannot be deserialized with DocArray v.0.34.0 or later, and vice versa</strong>.</p><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text"><strong>We strongly recommend that everyone using Protobuf with <code>DocVec</code> upgrade to DocArray v0.34.0 or later.</strong></div></div><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="allow-users-to-check-if-a-document-is-already-indexed-in-a-docindex-1633">Allow users to check if a <code>Document</code> is already indexed in a <code>DocIndex</code> (<a href="https://github.com/docarray/docarray/pull/1633?ref=jina-ai-gmbh.ghost.io">#1633</a>)</h3><p>You can now check if a <code>Document</code> has already been indexed by using the <code>in</code> keyword:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray.index <span class="hljs-keyword">import</span> InMemoryExactNNIndex
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocList
-<span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> NdArray
-<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.
+</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 21, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0340"><br>Release Note <code>(0.34.0)</code></h2><p>This release contains 2 breaking changes, 3 new features, 11 bug fixes, and 2 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.34.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.34.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.34.0) Release time: 2023-06-21 08:15:43 This release contains 2 breaking changes, 3 new features, 11 bug fixes, and 2 documentation improvements.💣 Breaking ChangesTerminate Pyth…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/f6095e3c5d7eebaa8dadc9d902529fdb5822430bbe08693b91cc6b0d3a785b4d/docarray/docarray/releases/tag/v0.34.0" alt=""></div></a></figure><h2 id="%F0%9F%92%A3-breaking-changes">💣 Breaking Changes</h2><h3 id="terminate-python-37-support">Terminate Python 3.7 support</h3><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text"><strong>DocArray will now require Python 3.8. We can no longer assure compatibility with Python 3.7.</strong></div></div><p>We decided to drop it for two reasons:</p><ul><li>Several dependencies of DocArray require Python 3.8.</li><li>Python <a href="https://endoflife.date/python?ref=jina-ai-gmbh.ghost.io" rel="nofollow">long-term support for 3.7 is ending</a> this week. This means there will no longer be security updates for Python 3.7, making this a good time for us to change our requirements.</li></ul><h3 id="changes-to-docvec-protobuf-definition-1639">Changes to <code>DocVec</code> Protobuf definition (<a href="https://github.com/docarray/docarray/pull/1639?ref=jina-ai-gmbh.ghost.io">#1639</a>)</h3><p>In order to fix the bug in the <code>DocVec</code> Protobuf serialization described in <a href="https://github.com/docarray/docarray/issues/1561?ref=jina-ai-gmbh.ghost.io">#1561</a>, we have changed the <code>DocVec</code> .proto definition.</p><p>This means that <strong><code>DocVec</code> objects serialized with DocArray v0.33.0 or earlier cannot be deserialized with DocArray v.0.34.0 or later, and vice versa</strong>.</p><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text"><strong>We strongly recommend that everyone using Protobuf with <code>DocVec</code> upgrade to DocArray v0.34.0 or later.</strong></div></div><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="allow-users-to-check-if-a-document-is-already-indexed-in-a-docindex-1633">Allow users to check if a <code>Document</code> is already indexed in a <code>DocIndex</code> (<a href="https://github.com/docarray/docarray/pull/1633?ref=jina-ai-gmbh.ghost.io">#1633</a>)</h3><p>You can now check if a <code>Document</code> has already been indexed by using the <code>in</code> keyword:</p><pre><code class="language-python">from docarray.index import InMemoryExactNNIndex
+from docarray import BaseDoc, DocList
+from docarray.typing import NdArray
+import numpy as np
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    text: <span class="hljs-built_in">str</span>
-    embedding: NdArray[<span class="hljs-number">128</span>]
+class MyDoc(BaseDoc):
+    text: str
+    embedding: NdArray[128]
 
 docs = DocList[MyDoc](
-        [MyDoc(text=<span class="hljs-string">"Example text"</span>, embedding=np.random.rand(<span class="hljs-number">128</span>))
-         <span class="hljs-keyword">for</span> _ <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">2000</span>)])
+        [MyDoc(text="Example text", embedding=np.random.rand(128))
+         for _ in range(2000)])
 
 index = InMemoryExactNNIndex[MyDoc](docs)
-<span class="hljs-keyword">assert</span> docs[<span class="hljs-number">0</span>] <span class="hljs-keyword">in</span> index
-<span class="hljs-keyword">assert</span> MyDoc(text=<span class="hljs-string">'New text'</span>, embedding=np.random.rand(<span class="hljs-number">128</span>)) <span class="hljs-keyword">not</span> <span class="hljs-keyword">in</span> index</code></pre><h3 id="support-subindexes-in-inmemoryexactnnindex-1617">Support subindexes in <code>InMemoryExactNNIndex</code> (<a href="https://github.com/docarray/docarray/pull/1617?ref=jina-ai-gmbh.ghost.io">#1617</a>)</h3><p>You can now use the <a href="https://docs.docarray.org/user_guide/storing/docindex/?ref=jina-ai-gmbh.ghost.io#nested-data-with-subindex" rel="nofollow">find_subindex</a> method with the <code>ExactNNSearch</code> <code>DocIndex</code>.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray.index <span class="hljs-keyword">import</span> InMemoryExactNNIndex
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocList
-<span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> ImageUrl, VideoUrl, AnyTensor
+assert docs[0] in index
+assert MyDoc(text='New text', embedding=np.random.rand(128)) not in index</code></pre><h3 id="support-subindexes-in-inmemoryexactnnindex-1617">Support subindexes in <code>InMemoryExactNNIndex</code> (<a href="https://github.com/docarray/docarray/pull/1617?ref=jina-ai-gmbh.ghost.io">#1617</a>)</h3><p>You can now use the <a href="https://docs.docarray.org/user_guide/storing/docindex/?ref=jina-ai-gmbh.ghost.io#nested-data-with-subindex" rel="nofollow">find_subindex</a> method with the <code>ExactNNSearch</code> <code>DocIndex</code>.</p><pre><code class="language-python">from docarray.index import InMemoryExactNNIndex
+from docarray import BaseDoc, DocList
+from docarray.typing import ImageUrl, VideoUrl, AnyTensor
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">ImageDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
+class ImageDoc(BaseDoc):
     url: ImageUrl
-    tensor_image: AnyTensor = Field(space=<span class="hljs-string">'cosine'</span>, dim=<span class="hljs-number">64</span>)
+    tensor_image: AnyTensor = Field(space='cosine', dim=64)
 
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">VideoDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
+class VideoDoc(BaseDoc):
     url: VideoUrl
     images: DocList[ImageDoc]
-    tensor_video: AnyTensor = Field(space=<span class="hljs-string">'cosine'</span>, dim=<span class="hljs-number">128</span>)
+    tensor_video: AnyTensor = Field(space='cosine', dim=128)
 
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
+class MyDoc(BaseDoc):
     docs: DocList[VideoDoc]
-    tensor: AnyTensor = Field(space=<span class="hljs-string">'cosine'</span>, dim=<span class="hljs-number">256</span>)
+    tensor: AnyTensor = Field(space='cosine', dim=256)
 
 doc_index = InMemoryExactNNIndex[MyDoc]()
 ...
 
-<span class="hljs-comment"># find by the `ImageDoc` tensor when index is populated</span>
+# find by the `ImageDoc` tensor when index is populated
 root_docs, sub_docs, scores = doc_index.find_subindex(
-    np.ones(<span class="hljs-number">64</span>), subindex=<span class="hljs-string">'docs__images'</span>, search_field=<span class="hljs-string">'tensor_image'</span>, limit=<span class="hljs-number">3</span>
-)</code></pre><h3 id="flexible-tensor-types-for-protobuf-deserialization-1645">Flexible tensor types for Protobuf deserialization (<a href="https://github.com/docarray/docarray/pull/1645?ref=jina-ai-gmbh.ghost.io">#1645</a>)</h3><p>You can deserialize any <code>DocVec</code> Protobuf message to any tensor type, by passing the <code>tensor_type</code> parameter to <code>from_protobuf</code>.</p><p>This means that you can choose at deserialization time if you are working with numpy, PyTorch, or TensorFlow tensors.</p><pre><code class="language-python hljs"><span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
+    np.ones(64), subindex='docs__images', search_field='tensor_image', limit=3
+)</code></pre><h3 id="flexible-tensor-types-for-protobuf-deserialization-1645">Flexible tensor types for Protobuf deserialization (<a href="https://github.com/docarray/docarray/pull/1645?ref=jina-ai-gmbh.ghost.io">#1645</a>)</h3><p>You can deserialize any <code>DocVec</code> Protobuf message to any tensor type, by passing the <code>tensor_type</code> parameter to <code>from_protobuf</code>.</p><p>This means that you can choose at deserialization time if you are working with numpy, PyTorch, or TensorFlow tensors.</p><pre><code class="language-python">class MyDoc(BaseDoc):
     tensor: TensorFlowTensor
 
-da = DocVec[MyDoc](...)  <span class="hljs-comment"># doesn't matter what tensor_type is here</span>
+da = DocVec[MyDoc](...)  # doesn't matter what tensor_type is here
 
 proto = da.to_protobuf()
 da_after = DocVec[MyDoc].from_protobuf(proto, tensor_type=TensorFlowTensor)
 
-<span class="hljs-keyword">assert</span> <span class="hljs-built_in">isinstance</span>(da_after.tensor, TensorFlowTensor)</code></pre><h3 id="add-dbconfig-to-inmemoryexactnnsearch">Add <code>DBConfig</code> to <code>InMemoryExactNNSearch</code></h3><p><code>InMemoryExactNNsearch</code> used to get a single parameter <code>index_file_path</code> as a constructor parameter, unlike the rest of the Indexers who accepted their own <code>DBConfig</code>. Now <code>index_file_path</code> is part of the <code>DBConfig</code> which makes it possible to initialize from it. This will allow us to extend this config if more parameters are needed.</p><p>The parameters of <code>DBConfig</code> can be passed at construction time as <code>**kwargs</code> making this change compatible with old usage.</p><p>These two initializations are equivalent.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray.index <span class="hljs-keyword">import</span> InMemoryExactNNIndex
-db_config = InMemoryExactNNIndex.DBConfig(index_file_path=<span class="hljs-string">'index.bin'</span>)
+assert isinstance(da_after.tensor, TensorFlowTensor)</code></pre><h3 id="add-dbconfig-to-inmemoryexactnnsearch">Add <code>DBConfig</code> to <code>InMemoryExactNNSearch</code></h3><p><code>InMemoryExactNNsearch</code> used to get a single parameter <code>index_file_path</code> as a constructor parameter, unlike the rest of the Indexers who accepted their own <code>DBConfig</code>. Now <code>index_file_path</code> is part of the <code>DBConfig</code> which makes it possible to initialize from it. This will allow us to extend this config if more parameters are needed.</p><p>The parameters of <code>DBConfig</code> can be passed at construction time as <code>**kwargs</code> making this change compatible with old usage.</p><p>These two initializations are equivalent.</p><pre><code class="language-python">from docarray.index import InMemoryExactNNIndex
+db_config = InMemoryExactNNIndex.DBConfig(index_file_path='index.bin')
 
 index = InMemoryExactNNIndex[MyDoc](db_config=db_config)
-index = InMemoryExactNNIndex[MyDoc](index_file_path=<span class="hljs-string">'index.bin'</span>)</code></pre><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="allow-protobuf-deserialization-of-basedoc-with-union-type-1655">Allow Protobuf deserialization of <code>BaseDoc</code> with <code>Union</code> type (<a href="https://github.com/docarray/docarray/pull/1655?ref=jina-ai-gmbh.ghost.io">#1655</a>)</h3><p>Serialization of <code>BaseDoc</code> types who have <code>Union</code> types parameter of Python native types is supported.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc
-<span class="hljs-keyword">from</span> typing <span class="hljs-keyword">import</span> <span class="hljs-type">Union</span>
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    union_field: <span class="hljs-type">Union</span>[<span class="hljs-built_in">int</span>, <span class="hljs-built_in">str</span>]
+index = InMemoryExactNNIndex[MyDoc](index_file_path='index.bin')</code></pre><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="allow-protobuf-deserialization-of-basedoc-with-union-type-1655">Allow Protobuf deserialization of <code>BaseDoc</code> with <code>Union</code> type (<a href="https://github.com/docarray/docarray/pull/1655?ref=jina-ai-gmbh.ghost.io">#1655</a>)</h3><p>Serialization of <code>BaseDoc</code> types who have <code>Union</code> types parameter of Python native types is supported.</p><pre><code class="language-python">from docarray import BaseDoc
+from typing import Union
+class MyDoc(BaseDoc):
+    union_field: Union[int, str]
 
-docs1 = DocList[MyDoc]([MyDoc(union_field=<span class="hljs-string">"hello"</span>)])
+docs1 = DocList[MyDoc]([MyDoc(union_field="hello")])
 docs2 = DocList[BasisUnion].from_dataframe(docs_basic.to_dataframe())
-<span class="hljs-keyword">assert</span> docs1 == docs2</code></pre><p>When these <code>Union</code> types involve other <code>BaseDoc</code> types, an exception is thrown.</p><pre><code class="language-python hljs"><span class="hljs-keyword">class</span> <span class="hljs-title class_">CustomDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    ud: <span class="hljs-type">Union</span>[TextDoc, ImageDoc] = TextDoc(text=<span class="hljs-string">'union type'</span>)
+assert docs1 == docs2</code></pre><p>When these <code>Union</code> types involve other <code>BaseDoc</code> types, an exception is thrown.</p><pre><code class="language-python">class CustomDoc(BaseDoc):
+    ud: Union[TextDoc, ImageDoc] = TextDoc(text='union type')
 
-docs = DocList[CustomDoc]([CustomDoc(ud=TextDoc(text=<span class="hljs-string">'union type'</span>))])
+docs = DocList[CustomDoc]([CustomDoc(ud=TextDoc(text='union type'))])
 
-<span class="hljs-comment"># raises an Exception</span>
-DocList[CustomDoc].from_dataframe(docs.to_dataframe())</code></pre><h3 id="cast-limit-to-integer-when-passed-to-hnswdocumentindex-1657-1656">Cast limit to <code>integer</code> when passed to <code>HNSWDocumentIndex</code> (<a href="https://github.com/docarray/docarray/pull/1657?ref=jina-ai-gmbh.ghost.io">#1657</a>, <a href="https://github.com/docarray/docarray/pull/1656?ref=jina-ai-gmbh.ghost.io">#1656</a>)</h3><p>If you call <code>find</code> or <code>find_batched</code> on an <code>HNSWDocumentIndex</code>, the <code>limit</code> parameter will automatically be cast to<code>integer</code>.</p><h3 id="moved-defaultcolumnconfig-from-runtimeconfig-to-dbconfig-1648">Moved <code>default_column_config</code> from <code>RuntimeConfig</code> to <code>DBconfig</code> (<a href="https://github.com/docarray/docarray/pull/1648?ref=jina-ai-gmbh.ghost.io">#1648</a>)</h3><p><code>default_column_config</code> contains specific configuration information about the columns and tables inside the backend's database. This was previously put inside <code>RuntimeConfig</code> which caused an error because this information is required at initialization time. This information has been moved inside <code>DBConfig</code> so you can edit it there.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray.index <span class="hljs-keyword">import</span> HNSWDocumentIndex
-<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
+# raises an Exception
+DocList[CustomDoc].from_dataframe(docs.to_dataframe())</code></pre><h3 id="cast-limit-to-integer-when-passed-to-hnswdocumentindex-1657-1656">Cast limit to <code>integer</code> when passed to <code>HNSWDocumentIndex</code> (<a href="https://github.com/docarray/docarray/pull/1657?ref=jina-ai-gmbh.ghost.io">#1657</a>, <a href="https://github.com/docarray/docarray/pull/1656?ref=jina-ai-gmbh.ghost.io">#1656</a>)</h3><p>If you call <code>find</code> or <code>find_batched</code> on an <code>HNSWDocumentIndex</code>, the <code>limit</code> parameter will automatically be cast to<code>integer</code>.</p><h3 id="moved-defaultcolumnconfig-from-runtimeconfig-to-dbconfig-1648">Moved <code>default_column_config</code> from <code>RuntimeConfig</code> to <code>DBconfig</code> (<a href="https://github.com/docarray/docarray/pull/1648?ref=jina-ai-gmbh.ghost.io">#1648</a>)</h3><p><code>default_column_config</code> contains specific configuration information about the columns and tables inside the backend's database. This was previously put inside <code>RuntimeConfig</code> which caused an error because this information is required at initialization time. This information has been moved inside <code>DBConfig</code> so you can edit it there.</p><pre><code class="language-python">from docarray.index import HNSWDocumentIndex
+import numpy as np
 
 db_config = HNSWDocumentIndex.DBConfig()
-db_conf.default_column_config.get(np.ndarray).update({<span class="hljs-string">'ef'</span>: <span class="hljs-number">2500</span>})
-index = HNSWDocumentIndex[MyDoc](db_config=db_config)</code></pre><h3 id="fix-issue-with-protobuf-deserialization-for-docvec-1639">Fix issue with Protobuf (de)serialization for DocVec (<a href="https://github.com/docarray/docarray/pull/1639?ref=jina-ai-gmbh.ghost.io">#1639</a>)</h3><p>This bug caused raw Protobuf objects to be stored as DocVec columns after they were deserialized from Protobuf, making the data essentially inaccessible. This has now been fixed, and <code>DocVec</code> objects are identical before and after (de)serialization.</p><h3 id="fix-order-of-returned-matches-when-find-and-filter-combination-used-in-inmemoryexactnnindex-1642">Fix order of returned matches when <code>find</code> and <code>filter</code> combination used in <code>InMemoryExactNNIndex</code> (<a href="https://github.com/docarray/docarray/pull/1642?ref=jina-ai-gmbh.ghost.io">#1642</a>)</h3><p>Hybrid search (find+filter) for <code>InMemoryExactNNIndex</code> was prioritizing low similarities (lower scores) for returned matches. Fixed by adding an option to sort matches in a reverse order based on their scores.</p><pre><code class="language-python hljs"><span class="hljs-comment"># prepare a query</span>
-q_doc = MyDoc(embedding=np.random.rand(<span class="hljs-number">128</span>), text=<span class="hljs-string">'query'</span>)
+db_conf.default_column_config.get(np.ndarray).update({'ef': 2500})
+index = HNSWDocumentIndex[MyDoc](db_config=db_config)</code></pre><h3 id="fix-issue-with-protobuf-deserialization-for-docvec-1639">Fix issue with Protobuf (de)serialization for DocVec (<a href="https://github.com/docarray/docarray/pull/1639?ref=jina-ai-gmbh.ghost.io">#1639</a>)</h3><p>This bug caused raw Protobuf objects to be stored as DocVec columns after they were deserialized from Protobuf, making the data essentially inaccessible. This has now been fixed, and <code>DocVec</code> objects are identical before and after (de)serialization.</p><h3 id="fix-order-of-returned-matches-when-find-and-filter-combination-used-in-inmemoryexactnnindex-1642">Fix order of returned matches when <code>find</code> and <code>filter</code> combination used in <code>InMemoryExactNNIndex</code> (<a href="https://github.com/docarray/docarray/pull/1642?ref=jina-ai-gmbh.ghost.io">#1642</a>)</h3><p>Hybrid search (find+filter) for <code>InMemoryExactNNIndex</code> was prioritizing low similarities (lower scores) for returned matches. Fixed by adding an option to sort matches in a reverse order based on their scores.</p><pre><code class="language-python"># prepare a query
+q_doc = MyDoc(embedding=np.random.rand(128), text='query')
 
 query = (
     db.build_query()
-    .find(query=q_doc, search_field=<span class="hljs-string">'embedding'</span>)
-    .<span class="hljs-built_in">filter</span>(filter_query={<span class="hljs-string">'text'</span>: {<span class="hljs-string">'$exists'</span>: <span class="hljs-literal">True</span>}})
+    .find(query=q_doc, search_field='embedding')
+    .filter(filter_query={'text': {'$exists': True}})
     .build()
 )
 
 results = db.execute_query(query)
-<span class="hljs-comment"># Before: results was sorted from worst to best matches</span>
-<span class="hljs-comment"># Now: It's sorted in the correct order, showing better matches first</span></code></pre><h3 id="working-with-external-qdrant-collections-1632">Working with external Qdrant collections (<a href="https://github.com/docarray/docarray/pull/1632?ref=jina-ai-gmbh.ghost.io">#1632</a>)</h3><p>When using <code>QdrandDocumentIndex</code> to connect to a Qdrant DB initialized outside of DocArray raised a <code>KeyError</code>. This has been fixed, and now you can use <code>QdrantDocumentIndex</code> to connect to externally initialized collections.</p><h2 id="other-bug-fixes">Other bug fixes</h2><ul><li>Update text search to match Weaviate client's new sig (<a href="https://github.com/docarray/docarray/pull/1654?ref=jina-ai-gmbh.ghost.io">#1654</a>)</li><li>Fix <code>DocVec</code> equality (<a href="https://github.com/docarray/docarray/pull/1641?ref=jina-ai-gmbh.ghost.io">#1641</a>, <a href="https://github.com/docarray/docarray/pull/1663?ref=jina-ai-gmbh.ghost.io">#1663</a>)</li><li>Fix exception when <code>summary()</code> called for <code>LegacyDocument</code>. (<a href="https://github.com/docarray/docarray/pull/1637?ref=jina-ai-gmbh.ghost.io">#1637</a>)</li><li>Fix <code>DocList</code> and <code>DocVec</code> coercion. (<a href="https://github.com/docarray/docarray/pull/1568?ref=jina-ai-gmbh.ghost.io">#1568</a>)</li><li>Fix <code>update()</code> on <code>BaseDoc</code> with tensors fields (<a href="https://github.com/docarray/docarray/pull/1628?ref=jina-ai-gmbh.ghost.io">#1628</a>)</li></ul><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Enhance <code>DocVec</code> section (<a href="https://github.com/docarray/docarray/pull/1658?ref=jina-ai-gmbh.ghost.io">#1658</a>)</li><li>Qdrant in memory usage (<a href="https://github.com/docarray/docarray/pull/1634?ref=jina-ai-gmbh.ghost.io">#1634</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li><li>Nikolas Pitsillos (<a href="https://github.com/npitsillos?ref=jina-ai-gmbh.ghost.io">@npitsillos</a>)</li><li>Shukri (<a href="https://github.com/hsm207?ref=jina-ai-gmbh.ghost.io">@hsm207</a>)</li><li>Kacper Łukawski (<a href="https://github.com/kacperlukawski?ref=jina-ai-gmbh.ghost.io">@kacperlukawski</a>)</li><li>Aman Agarwal (<a href="https://github.com/agaraman0?ref=jina-ai-gmbh.ghost.io">@agaraman0</a>)</li><li>maxwelljin (<a href="https://github.com/maxwelljin?ref=jina-ai-gmbh.ghost.io">@maxwelljin</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Saba Sturua (<a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-34-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
+# Before: results was sorted from worst to best matches
+# Now: It's sorted in the correct order, showing better matches first</code></pre><h3 id="working-with-external-qdrant-collections-1632">Working with external Qdrant collections (<a href="https://github.com/docarray/docarray/pull/1632?ref=jina-ai-gmbh.ghost.io">#1632</a>)</h3><p>When using <code>QdrandDocumentIndex</code> to connect to a Qdrant DB initialized outside of DocArray raised a <code>KeyError</code>. This has been fixed, and now you can use <code>QdrantDocumentIndex</code> to connect to externally initialized collections.</p><h2 id="other-bug-fixes">Other bug fixes</h2><ul><li>Update text search to match Weaviate client's new sig (<a href="https://github.com/docarray/docarray/pull/1654?ref=jina-ai-gmbh.ghost.io">#1654</a>)</li><li>Fix <code>DocVec</code> equality (<a href="https://github.com/docarray/docarray/pull/1641?ref=jina-ai-gmbh.ghost.io">#1641</a>, <a href="https://github.com/docarray/docarray/pull/1663?ref=jina-ai-gmbh.ghost.io">#1663</a>)</li><li>Fix exception when <code>summary()</code> called for <code>LegacyDocument</code>. (<a href="https://github.com/docarray/docarray/pull/1637?ref=jina-ai-gmbh.ghost.io">#1637</a>)</li><li>Fix <code>DocList</code> and <code>DocVec</code> coercion. (<a href="https://github.com/docarray/docarray/pull/1568?ref=jina-ai-gmbh.ghost.io">#1568</a>)</li><li>Fix <code>update()</code> on <code>BaseDoc</code> with tensors fields (<a href="https://github.com/docarray/docarray/pull/1628?ref=jina-ai-gmbh.ghost.io">#1628</a>)</li></ul><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Enhance <code>DocVec</code> section (<a href="https://github.com/docarray/docarray/pull/1658?ref=jina-ai-gmbh.ghost.io">#1658</a>)</li><li>Qdrant in memory usage (<a href="https://github.com/docarray/docarray/pull/1634?ref=jina-ai-gmbh.ghost.io">#1634</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li><li>Nikolas Pitsillos (<a href="https://github.com/npitsillos?ref=jina-ai-gmbh.ghost.io">@npitsillos</a>)</li><li>Shukri (<a href="https://github.com/hsm207?ref=jina-ai-gmbh.ghost.io">@hsm207</a>)</li><li>Kacper Łukawski (<a href="https://github.com/kacperlukawski?ref=jina-ai-gmbh.ghost.io">@kacperlukawski</a>)</li><li>Aman Agarwal (<a href="https://github.com/agaraman0?ref=jina-ai-gmbh.ghost.io">@agaraman0</a>)</li><li>maxwelljin (<a href="https://github.com/maxwelljin?ref=jina-ai-gmbh.ghost.io">@maxwelljin</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Saba Sturua (<a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-34-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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 <!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.35 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.35 Update"><meta name="description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.
 "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-35-update"><meta property="og:title" content="DocArray 0.35 Update"><meta property="og:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.
 </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 03, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h1 id="release-note-0350">Release Note (<code>0.35.0</code>)</h1><p>This release contains 3 new features, 2 bug fixes, and 1 documentation improvement.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="more-serialization-options-for-docvec-1562">More serialization options for <code>DocVec</code> (<a href="https://github.com/docarray/docarray/pull/1562?ref=jina-ai-gmbh.ghost.io">#1562</a>)</h3><p><code>DocVec</code> now has the <strong>same serialization interface as <code>DocList</code></strong>. This means that that following methods are available for it:</p><ul><li><code>to_protobuf()</code>/<code>from_protobuf()</code></li><li><code>to_base64()</code>/<code>from_base64()</code></li><li><code>save_binary()</code>/<code>load_binary()</code></li><li><code>to_bytes()</code>/<code>from_bytes()</code></li><li><code>to_dataframe()</code>/<code>from_dataframe()</code></li></ul><p>For example, you can now perform Base64 (de)serialization like this:</p><pre><code class="language-Python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocVec
 
 <span class="hljs-keyword">class</span> <span class="hljs-title class_">SimpleDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
@@ -44,4 +44,4 @@
     MyDocPurePython.schema(), <span class="hljs-string">'MyDoc'</span>, {}
 )
 
-new_doc = NewMyDoc(tensor=<span class="hljs-literal">None</span>, texts=[TextDoc(text=<span class="hljs-string">'text'</span>)])</code></pre><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="cap-pydantic-version-1682">Cap Pydantic version (<a href="https://github.com/docarray/docarray/pull/1682?ref=jina-ai-gmbh.ghost.io">#1682</a>)</h3><p>Due to the breaking change in <strong>Pydantic v2</strong>, we have capped the version to avoid problems when installing DocArray.</p><h3 id="better-error-message-when-docvec-is-unusable-1675">Better error message when DocVec is unusable (<a href="https://github.com/docarray/docarray/pull/1675?ref=jina-ai-gmbh.ghost.io">#1675</a>)</h3><p>After calling <code>doc_list = doc_vec.to_doc_list()</code>, <code>doc_vec</code> ends up in an unusable state since its data has been transferred to <code>doc_list</code>. This fix gives users a more informative error message when they try to interact with <code>doc_vec</code> after it has been made unusable.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Fix a reference in README (<a href="https://github.com/docarray/docarray/pull/1674?ref=jina-ai-gmbh.ghost.io">#1674</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Saba Sturua (<a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Han Xiao (<a href="https://github.com/hanxiao?ref=jina-ai-gmbh.ghost.io">@hanxiao</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-35-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; 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\ No newline at end of file
+new_doc = NewMyDoc(tensor=<span class="hljs-literal">None</span>, texts=[TextDoc(text=<span class="hljs-string">'text'</span>)])</code></pre><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="cap-pydantic-version-1682">Cap Pydantic version (<a href="https://github.com/docarray/docarray/pull/1682?ref=jina-ai-gmbh.ghost.io">#1682</a>)</h3><p>Due to the breaking change in <strong>Pydantic v2</strong>, we have capped the version to avoid problems when installing DocArray.</p><h3 id="better-error-message-when-docvec-is-unusable-1675">Better error message when DocVec is unusable (<a href="https://github.com/docarray/docarray/pull/1675?ref=jina-ai-gmbh.ghost.io">#1675</a>)</h3><p>After calling <code>doc_list = doc_vec.to_doc_list()</code>, <code>doc_vec</code> ends up in an unusable state since its data has been transferred to <code>doc_list</code>. This fix gives users a more informative error message when they try to interact with <code>doc_vec</code> after it has been made unusable.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Fix a reference in README (<a href="https://github.com/docarray/docarray/pull/1674?ref=jina-ai-gmbh.ghost.io">#1674</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Saba Sturua (<a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Han Xiao (<a href="https://github.com/hanxiao?ref=jina-ai-gmbh.ghost.io">@hanxiao</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-35-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.
-</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 19, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0360"><br>Release Note (<code>0.36.0</code>)</h2><p>This release contains 2 new features, 5 bug fixes, 1 performance improvement and 1 documentation improvement.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.36.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.36.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.36.0) Release time: 2023-07-18 14:43:28 This release contains 2 new features, 5 bug fixes, 1 performance improvement and 1 documentation improvement.🆕 FeaturesJAX Integration (…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/c4f3c7377505667b80fe81b156023dbf9ea37cee654b7242eb3f66665a60386e/docarray/docarray/releases/tag/v0.36.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="jax-integration-1646">JAX Integration (<a href="https://github.com/docarray/docarray/pull/1646?ref=jina-ai-gmbh.ghost.io">#1646</a>)</h3><p>You can now use JAX with DocArray. We have introduced <code>JaxArray</code> as a new type option for your documents. <code>JaxArray</code> ensures that JAX can now natively process any array-like data in your DocArray documents. Here's how you use of it:</p><pre><code class="language-Python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc
-<span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> JaxArray
-<span class="hljs-keyword">import</span> jax.numpy <span class="hljs-keyword">as</span> jnp
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="1cbd8f1a-e0f2-46a5-b7ca-a9fe66130420" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="1cbd8f1a-e0f2-46a5-b7ca-a9fe66130420" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.
+</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 19, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0360"><br>Release Note (<code>0.36.0</code>)</h2><p>This release contains 2 new features, 5 bug fixes, 1 performance improvement and 1 documentation improvement.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.36.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.36.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.36.0) Release time: 2023-07-18 14:43:28 This release contains 2 new features, 5 bug fixes, 1 performance improvement and 1 documentation improvement.🆕 FeaturesJAX Integration (…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/c4f3c7377505667b80fe81b156023dbf9ea37cee654b7242eb3f66665a60386e/docarray/docarray/releases/tag/v0.36.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="jax-integration-1646">JAX Integration (<a href="https://github.com/docarray/docarray/pull/1646?ref=jina-ai-gmbh.ghost.io">#1646</a>)</h3><p>You can now use JAX with DocArray. We have introduced <code>JaxArray</code> as a new type option for your documents. <code>JaxArray</code> ensures that JAX can now natively process any array-like data in your DocArray documents. Here's how you use of it:</p><pre><code class="language-Python">from docarray import BaseDoc
+from docarray.typing import JaxArray
+import jax.numpy as jnp
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
+class MyDoc(BaseDoc):
     arr: JaxArray
-    image_arr: JaxArray[<span class="hljs-number">3</span>, <span class="hljs-number">224</span>, <span class="hljs-number">224</span>] <span class="hljs-comment"># For images of shape (3, 224, 224)</span>
-    square_crop: JaxArray[<span class="hljs-number">3</span>, ‘x’, ‘x’] <span class="hljs-comment"># For any square image, regardless of dimensions</span>
-    random_image: JaxArray[<span class="hljs-number">3</span>, ...]  <span class="hljs-comment"># For any image with 3 color channels, and arbitrary other dimensions</span>
-</code></pre><p>As you can see, the <code>JaxArray</code> type is extremely flexible and can support a wide range of tensor shapes.</p><h4 id="creating-a-document-with-tensors">Creating a Document with Tensors</h4><p>As you can see, the <code>JaxArray</code> typing is extremely flexible and can support a wide range of tensor shapes.</p><p>Creating a document with tensors is straightforward. Here is an example:</p><pre><code class="language-Python hljs">doc = MyDoc(
-    arr=jnp.zeros((<span class="hljs-number">128</span>,)),
-    image_arr=jnp.zeros((<span class="hljs-number">3</span>, <span class="hljs-number">224</span>, <span class="hljs-number">224</span>)),
-    square_crop=jnp.zeros((<span class="hljs-number">3</span>, <span class="hljs-number">64</span>, <span class="hljs-number">64</span>)),
-    random_image=jnp.zeros((<span class="hljs-number">3</span>, <span class="hljs-number">128</span>, <span class="hljs-number">256</span>)),
+    image_arr: JaxArray[3, 224, 224] # For images of shape (3, 224, 224)
+    square_crop: JaxArray[3, ‘x’, ‘x’] # For any square image, regardless of dimensions
+    random_image: JaxArray[3, ...]  # For any image with 3 color channels, and arbitrary other dimensions
+</code></pre><p>As you can see, the <code>JaxArray</code> type is extremely flexible and can support a wide range of tensor shapes.</p><h4 id="creating-a-document-with-tensors">Creating a Document with Tensors</h4><p>As you can see, the <code>JaxArray</code> typing is extremely flexible and can support a wide range of tensor shapes.</p><p>Creating a document with tensors is straightforward. Here is an example:</p><pre><code class="language-Python">doc = MyDoc(
+    arr=jnp.zeros((128,)),
+    image_arr=jnp.zeros((3, 224, 224)),
+    square_crop=jnp.zeros((3, 64, 64)),
+    random_image=jnp.zeros((3, 128, 256)),
 )
-</code></pre><h3 id="redis-integration-1550">Redis Integration (<a href="https://github.com/docarray/docarray/pull/1550?ref=jina-ai-gmbh.ghost.io">#1550</a>)</h3><p>Leverage the power of Redis in your DocArray project with this latest integration. Here's a simple usage example:</p><pre><code class="language-Python hljs"><span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc
-<span class="hljs-keyword">from</span> docarray.index <span class="hljs-keyword">import</span> RedisDocumentIndex
-<span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> NdArray
+</code></pre><h3 id="redis-integration-1550">Redis Integration (<a href="https://github.com/docarray/docarray/pull/1550?ref=jina-ai-gmbh.ghost.io">#1550</a>)</h3><p>Leverage the power of Redis in your DocArray project with this latest integration. Here's a simple usage example:</p><pre><code class="language-Python">import numpy as np
+from docarray import BaseDoc
+from docarray.index import RedisDocumentIndex
+from docarray.typing import NdArray
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    text: <span class="hljs-built_in">str</span>
-    embedding: NdArray[<span class="hljs-number">10</span>]
-docs = [MyDoc(text=f’text {i}’, embedding=np.random.rand(<span class="hljs-number">10</span>)) <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">10</span>)]
-query = np.random.rand(<span class="hljs-number">10</span>)
+class MyDoc(BaseDoc):
+    text: str
+    embedding: NdArray[10]
+docs = [MyDoc(text=f’text {i}’, embedding=np.random.rand(10)) for i in range(10)]
+query = np.random.rand(10)
 db = RedisDocumentIndex[MyDoc](host=‘localhost’)
 db.index(docs)
-results = db.find(query, search_field=‘embedding’, limit=<span class="hljs-number">10</span>)</code></pre><p>In this example, we're creating a document class with both textual and numeric data. Then, we initialize a Redis-backed document index and use it to index our documents. Finally, we perform a search query.</p><h4 id="supported-functionalities">Supported Functionalities</h4><p><strong>Find</strong>: Vector search for efficient retrieval of similar documents.<br><strong>Filter</strong>: Use Redis syntax to filter based on textual and numeric data.<br><strong>Text Search</strong>: Leverage text search methods, such as BM25, to find relevant documents.<br><strong>Get/Del</strong>: Fetch or delete specific documents from the index.<br><strong>Hybrid Search</strong>: Combine find and filter functionalities for more refined search. Currently, only these two can be combined.<br><strong>Subindex</strong>: Search through nested data.</p><h2 id="%F0%9F%9A%80-performance">🚀 Performance</h2><h3 id="speedup-hnswdocumentindex-by-caching-num-docs-1706">Speedup <code>HnswDocumentIndex</code> by caching num docs (<a href="https://github.com/docarray/docarray/pull/1706?ref=jina-ai-gmbh.ghost.io">#1706</a>)</h3><p>We've optimized the <code>num_docs()</code> operation by caching the document count, addressing previous slowdowns during searches. This change results in a minor increase in indexing time but significantly accelerates search times.</p><pre><code class="language-Python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocList
-<span class="hljs-keyword">from</span> docarray.index <span class="hljs-keyword">import</span> HnswDocumentIndex
-<span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> NdArray
-<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
-<span class="hljs-keyword">import</span> time
+results = db.find(query, search_field=‘embedding’, limit=10)</code></pre><p>In this example, we're creating a document class with both textual and numeric data. Then, we initialize a Redis-backed document index and use it to index our documents. Finally, we perform a search query.</p><h4 id="supported-functionalities">Supported Functionalities</h4><p><strong>Find</strong>: Vector search for efficient retrieval of similar documents.<br><strong>Filter</strong>: Use Redis syntax to filter based on textual and numeric data.<br><strong>Text Search</strong>: Leverage text search methods, such as BM25, to find relevant documents.<br><strong>Get/Del</strong>: Fetch or delete specific documents from the index.<br><strong>Hybrid Search</strong>: Combine find and filter functionalities for more refined search. Currently, only these two can be combined.<br><strong>Subindex</strong>: Search through nested data.</p><h2 id="%F0%9F%9A%80-performance">🚀 Performance</h2><h3 id="speedup-hnswdocumentindex-by-caching-num-docs-1706">Speedup <code>HnswDocumentIndex</code> by caching num docs (<a href="https://github.com/docarray/docarray/pull/1706?ref=jina-ai-gmbh.ghost.io">#1706</a>)</h3><p>We've optimized the <code>num_docs()</code> operation by caching the document count, addressing previous slowdowns during searches. This change results in a minor increase in indexing time but significantly accelerates search times.</p><pre><code class="language-Python">from docarray import BaseDoc, DocList
+from docarray.index import HnswDocumentIndex
+from docarray.typing import NdArray
+import numpy as np
+import time
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    text: <span class="hljs-built_in">str</span>
-    embedding: NdArray[<span class="hljs-number">128</span>]
-docs = [MyDoc(text=‘hey’, embedding=np.random.rand(<span class="hljs-number">128</span>)) <span class="hljs-keyword">for</span> _ <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">20000</span>)]
+class MyDoc(BaseDoc):
+    text: str
+    embedding: NdArray[128]
+docs = [MyDoc(text=‘hey’, embedding=np.random.rand(128)) for _ in range(20000)]
 index = HnswDocumentIndex[MyDoc](work_dir=‘tst’, index_name=‘index’)
 index_start = time.time()
 index.index(docs=DocList[MyDoc](docs))
 index_time = time.time() - index_start
-query = docs[<span class="hljs-number">0</span>]
+query = docs[0]
 find_start = time.time()
-matches, _ = index.find(query, search_field=‘embedding’, limit=<span class="hljs-number">10</span>)
-find_time = time.time() - find_start</code></pre><p>In the above experiment, we observed a 13x improvement in the speed of the search function, reducing its execution time from 0.0238 to 0.0018 seconds.</p><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="put-contains-method-in-the-base-class-1701">Put <code>contains</code> method in the base class (<a href="https://github.com/docarray/docarray/pull/1701?ref=jina-ai-gmbh.ghost.io">#1701</a>)</h3><p>We've moved the contains method into the base class. With this refactoring, the responsibility for checking if a document exists is now delegated to individual backend implementations using the new <code>_doc_exists</code> method.</p><h3 id="more-robust-method-to-detect-duplicate-index-1651">More robust method to detect duplicate index (<a href="https://github.com/docarray/docarray/pull/1651?ref=jina-ai-gmbh.ghost.io">#1651</a>)</h3><p>We have implemented a more robust method of detecting existing indices for <code>WeaviateDocumentIndex</code>.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="weaviatedocumentindex-handles-lowercase-index-names-1711"><code>WeaviateDocumentIndex</code> handles lowercase index names (<a href="https://github.com/docarray/docarray/pull/1711?ref=jina-ai-gmbh.ghost.io">#1711</a>)</h3><p>We've addressed an issue in the <code>WeaviateDocumentIndex</code> where passing a lowercase index name led to mismatches and subsequent errors. This was due to the system automatically capitalizing the index name when creating an index. To resolve this, we've added a <code>post_init</code> function that capitalizes the first letter of the provided index name, ensuring consistent naming and preventing potential errors.</p><h3 id="qdrantdocumentindex-unable-to-see-indexname-1705"><code>QdrantDocumentIndex</code> unable to see <code>index_name</code> (<a href="https://github.com/docarray/docarray/pull/1705?ref=jina-ai-gmbh.ghost.io">#1705</a>)</h3><p>We've resolved an issue where the <code>QdrantDocumentIndex</code> was not properly recognizing the <code>index_name</code> parameter. Previously, the specified <code>index_name</code> was ignored and the system defaulted to the schema name.</p><h3 id="fix-search-in-inmemoryexactnnindex-with-anyembedding-1696">Fix search in <code>InMemoryExactNNIndex</code> with <code>AnyEmbedding</code> (<a href="https://github.com/docarray/docarray/pull/1696?ref=jina-ai-gmbh.ghost.io">#1696</a>)</h3><p>From now on, you can perform search operations in <code>InMemoryExactNNIndex</code> using <code>AnyEmbedding</code></p><h3 id="use-safeissubclass-everywhere-1691">Use <code>safe_issubclass</code> everywhere (<a href="https://github.com/docarray/docarray/pull/1691?ref=jina-ai-gmbh.ghost.io">#1691</a>)</h3><p>We now use <code>safe_issubclass</code> instead of <code>issubclass</code> because it supports non-class inputs, helping us to avoid unexpected errors</p><h3 id="avoid-converting-doclists-in-the-base-index-1685">Avoid converting <code>DocLists</code> in the base index (<a href="https://github.com/docarray/docarray/pull/1685?ref=jina-ai-gmbh.ghost.io">#1685</a>)</h3><p>We added an additional check to avoid passing DocLists to a function that converts a list of dictionaries to a DocList.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Add docs for <code>dict()</code> method (<a href="https://github.com/docarray/docarray/pull/1643?ref=jina-ai-gmbh.ghost.io">#1643</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Puneeth K (<a href="https://github.com/punndcoder28?ref=jina-ai-gmbh.ghost.io">@punndcoder28</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Saba Sturua (<a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a>)</li><li>Aman Agarwal (<a href="https://github.com/agaraman0?ref=jina-ai-gmbh.ghost.io">@agaraman0</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Shukri (<a href="https://github.com/hsm207?ref=jina-ai-gmbh.ghost.io">@hsm207</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-36-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+matches, _ = index.find(query, search_field=‘embedding’, limit=10)
+find_time = time.time() - find_start</code></pre><p>In the above experiment, we observed a 13x improvement in the speed of the search function, reducing its execution time from 0.0238 to 0.0018 seconds.</p><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="put-contains-method-in-the-base-class-1701">Put <code>contains</code> method in the base class (<a href="https://github.com/docarray/docarray/pull/1701?ref=jina-ai-gmbh.ghost.io">#1701</a>)</h3><p>We've moved the contains method into the base class. With this refactoring, the responsibility for checking if a document exists is now delegated to individual backend implementations using the new <code>_doc_exists</code> method.</p><h3 id="more-robust-method-to-detect-duplicate-index-1651">More robust method to detect duplicate index (<a href="https://github.com/docarray/docarray/pull/1651?ref=jina-ai-gmbh.ghost.io">#1651</a>)</h3><p>We have implemented a more robust method of detecting existing indices for <code>WeaviateDocumentIndex</code>.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="weaviatedocumentindex-handles-lowercase-index-names-1711"><code>WeaviateDocumentIndex</code> handles lowercase index names (<a href="https://github.com/docarray/docarray/pull/1711?ref=jina-ai-gmbh.ghost.io">#1711</a>)</h3><p>We've addressed an issue in the <code>WeaviateDocumentIndex</code> where passing a lowercase index name led to mismatches and subsequent errors. This was due to the system automatically capitalizing the index name when creating an index. To resolve this, we've added a <code>post_init</code> function that capitalizes the first letter of the provided index name, ensuring consistent naming and preventing potential errors.</p><h3 id="qdrantdocumentindex-unable-to-see-indexname-1705"><code>QdrantDocumentIndex</code> unable to see <code>index_name</code> (<a href="https://github.com/docarray/docarray/pull/1705?ref=jina-ai-gmbh.ghost.io">#1705</a>)</h3><p>We've resolved an issue where the <code>QdrantDocumentIndex</code> was not properly recognizing the <code>index_name</code> parameter. Previously, the specified <code>index_name</code> was ignored and the system defaulted to the schema name.</p><h3 id="fix-search-in-inmemoryexactnnindex-with-anyembedding-1696">Fix search in <code>InMemoryExactNNIndex</code> with <code>AnyEmbedding</code> (<a href="https://github.com/docarray/docarray/pull/1696?ref=jina-ai-gmbh.ghost.io">#1696</a>)</h3><p>From now on, you can perform search operations in <code>InMemoryExactNNIndex</code> using <code>AnyEmbedding</code></p><h3 id="use-safeissubclass-everywhere-1691">Use <code>safe_issubclass</code> everywhere (<a href="https://github.com/docarray/docarray/pull/1691?ref=jina-ai-gmbh.ghost.io">#1691</a>)</h3><p>We now use <code>safe_issubclass</code> instead of <code>issubclass</code> because it supports non-class inputs, helping us to avoid unexpected errors</p><h3 id="avoid-converting-doclists-in-the-base-index-1685">Avoid converting <code>DocLists</code> in the base index (<a href="https://github.com/docarray/docarray/pull/1685?ref=jina-ai-gmbh.ghost.io">#1685</a>)</h3><p>We added an additional check to avoid passing DocLists to a function that converts a list of dictionaries to a DocList.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Add docs for <code>dict()</code> method (<a href="https://github.com/docarray/docarray/pull/1643?ref=jina-ai-gmbh.ghost.io">#1643</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Puneeth K (<a href="https://github.com/punndcoder28?ref=jina-ai-gmbh.ghost.io">@punndcoder28</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Saba Sturua (<a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a>)</li><li>Aman Agarwal (<a href="https://github.com/agaraman0?ref=jina-ai-gmbh.ghost.io">@agaraman0</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Shukri (<a href="https://github.com/hsm207?ref=jina-ai-gmbh.ghost.io">@hsm207</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-36-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
diff --git a/news/docarray-0-37-update/index.html b/news/docarray-0-37-update/index.html
index 1f6e1ab3e26..887f112abd9 100644
--- a/news/docarray-0-37-update/index.html
+++ b/news/docarray-0-37-update/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.37 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.37 Update"><meta name="description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-37-update"><meta property="og:title" content="DocArray 0.37 Update"><meta property="og:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/docarray-new-banner--5-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-37-update"><meta property="twitter:title" content="DocArray 0.37 Update"><meta property="twitter:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/docarray-new-banner--5-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.37 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.37 Update"><meta name="description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-37-update"><meta property="og:title" content="DocArray 0.37 Update"><meta property="og:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/docarray-new-banner--5-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-37-update"><meta property="twitter:title" content="DocArray 0.37 Update"><meta property="twitter:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/docarray-new-banner--5-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><script src="https://jina-ai-gmbh.ghost.io/public/cards.min.js" async=""></script><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.37 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 03, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0370">Release Note (<code>0.37.0</code>)</h2><p>This release contains 6 new features, 5 bug fixes, 1 performance improvement and 1 documentation improvement.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.37.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.37.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.37.0) Release time: 2023-08-03 03:11:16 This release contains 6 new features, 5 bug fixes, 1 performance improvement and 1 documentation improvement.🆕 FeaturesMilvus Integration…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/0ced410cf1b425fad35a041e2e15ae0d238bd281858167cdda5778ca8bb0ee51/docarray/docarray/releases/tag/v0.37.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="milvus-integration-1681">Milvus Integration (<a href="https://github.com/docarray/docarray/pull/1681?ref=jina-ai-gmbh.ghost.io">#1681</a>)</h3><p>Leverage the power of Milvus in your DocArray project with this latest integration. Here's a simple usage example:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
+    gtag('config', 'G-9T52NXDS9T');</script></head><body class="desktop no-touch body--dark"><div id="q-app" data-v-app class="hidden"><div class="q-layout q-layout--standard" tabindex="-1" style="min-height: 600px;"><header class="q-header q-layout__section--marginal fixed-top text-white lock-blur bg-transparent print-hide"><div class="q-toolbar row no-wrap items-center q-px-none" role="toolbar"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch" tabindex="0" type="button" style="padding: 24px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">reorder</i></span></button><hr class="q-separator q-separator--vertical q-separator--dark" aria-orientation="vertical"><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch" tabindex="0" href="/" style="font-size: 32px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="q-icon" aria-hidden="true" role="img"><img src="/Jina - Dark.svg"></span></span></a><div class="q-space"></div><label class="q-field row no-wrap items-start q-field--borderless q-select q-field--auto-height q-select--without-input q-select--without-chips q-select--single q-field--float q-field--dense q-field--dark" for="f_6b8989b3-cbbc-4d2e-8e2e-835da531d60e"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__prepend q-field__marginal row no-wrap items-center"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">language</i></div><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><div class="q-field__native row items-center"><span>English</span><input class="q-select__focus-target" id="f_6b8989b3-cbbc-4d2e-8e2e-835da531d60e" readonly="" tabindex="0" role="combobox" aria-readonly="false" aria-autocomplete="none" aria-expanded="false" aria-controls="f_6b8989b3-cbbc-4d2e-8e2e-835da531d60e_lb"></div></div><div class="q-field__append q-field__marginal row no-wrap items-center q-anchor--skip"><i class="q-icon fas fa-caret-down q-select__dropdown-icon" aria-hidden="true" role="presentation"> </i></div></div></div></label></div></header><div class="q-drawer-container"><div class="q-drawer__opener fixed-left" aria-hidden="true"></div><div class="fullscreen q-drawer__backdrop hidden" aria-hidden="true" style="background-color: rgba(0, 0, 0, 0);"></div><aside class="q-drawer q-drawer--left q-drawer--bordered q-drawer--dark q-dark q-layout--prevent-focus fixed q-drawer--on-top q-drawer--mobile q-drawer--top-padding" style="width: 300px; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 03, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0370">Release Note (<code>0.37.0</code>)</h2><p>This release contains 6 new features, 5 bug fixes, 1 performance improvement and 1 documentation improvement.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.37.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.37.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.37.0) Release time: 2023-08-03 03:11:16 This release contains 6 new features, 5 bug fixes, 1 performance improvement and 1 documentation improvement.🆕 FeaturesMilvus Integration…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/0ced410cf1b425fad35a041e2e15ae0d238bd281858167cdda5778ca8bb0ee51/docarray/docarray/releases/tag/v0.37.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="milvus-integration-1681">Milvus Integration (<a href="https://github.com/docarray/docarray/pull/1681?ref=jina-ai-gmbh.ghost.io">#1681</a>)</h3><p>Leverage the power of Milvus in your DocArray project with this latest integration. Here's a simple usage example:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
 <span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc
 <span class="hljs-keyword">from</span> docarray.index <span class="hljs-keyword">import</span> MilvusDocumentIndex
 <span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> NdArray
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.38 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.38 Update"><meta name="description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-38-update"><meta property="og:title" content="DocArray 0.38 Update"><meta property="og:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/docarray-new-banner--3-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-38-update"><meta property="twitter:title" content="DocArray 0.38 Update"><meta property="twitter:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/docarray-new-banner--3-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 07, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0380">Release Note &nbsp;(<code>0.38.0</code>)</h2><p>This release contains 3 bug fixes and 4 documentation improvements, including 1 breaking change.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.38.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.38.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.38.0) Release time: 2023-09-07 13:40:16 This release contains 3 bug fixes and 4 documentation improvements, including 1 breaking change.💥 Breaking ChangesChanges to the return t…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/f79c8f1657b21f2a25e1116095c41256f99b916e0405091f06274c3f386158e4/docarray/docarray/releases/tag/v0.38.0" alt=""></div></a></figure><h2 id="%F0%9F%92%A5-breaking-changes">💥 Breaking Changes</h2><h3 id="changes-to-the-return-type-of-doclisttojson-and-docvectojson">Changes to the return type of <code>DocList.to_json()</code> and <code>DocVec.to_json()</code></h3><p>In order to make the <code>to_json</code> method consistent across different classes, we changed its return type in <code>DocList</code> and <code>DocVec</code> to <code>str</code>. This means that, if you use this method in your application, make sure to update your codebase to expect <code>str</code> instead of <code>bytes</code>.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="make-doclisttojson-and-docvectojson-return-str-instead-of-bytes-1769">Make <code>DocList.to_json()</code> and <code>DocVec.to_json()</code> return <code>str</code> instead of <code>bytes</code> (<a href="https://github.com/docarray/docarray/pull/1769?ref=jina-ai-gmbh.ghost.io">#1769</a>)</h3><p>This release changes the return type of the methods <code>DocList.to_json()</code> and <code>DocVec.to_json()</code> in order to be consistent with <code>BaseDoc .to_json()</code> and other pydantic models. After this release, these methods will return <code>str </code> type data instead of <code>bytes</code>.</p><p>💥 Since the return type is changed, this is considered a breaking change.</p><h3 id="casting-in-reduce-before-appending-1758">Casting in <code>reduce</code> before appending (<a href="https://github.com/docarray/docarray/pull/1758?ref=jina-ai-gmbh.ghost.io">#1758</a>)</h3><p>This release introduces type casting internally in the <code>reduce</code> helper function, casting its inputs before appending them to the final result. This will make it possible to reduce documents whose schemas are compatible but not exactly the same.</p><h3 id="skip-doc-attributes-in-annotations-but-not-in-fields-1777">Skip doc attributes in <code>__annotations__</code> but not in <code>__fields__</code> (<a href="https://github.com/docarray/docarray/pull/1777?ref=jina-ai-gmbh.ghost.io">#1777</a>)</h3><p>This release fixes an issue in the <code>create_pure_python_type_model</code> helper function. Starting with this release, only attributes in the class <code>__fields__</code> will be considered during type creation. The previous behavior broke applications when users introduced a ClassVar in an input class:</p><pre><code class="language-Python hljs"><span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 07, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0380">Release Note &nbsp;(<code>0.38.0</code>)</h2><p>This release contains 3 bug fixes and 4 documentation improvements, including 1 breaking change.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.38.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.38.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.38.0) Release time: 2023-09-07 13:40:16 This release contains 3 bug fixes and 4 documentation improvements, including 1 breaking change.💥 Breaking ChangesChanges to the return t…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/f79c8f1657b21f2a25e1116095c41256f99b916e0405091f06274c3f386158e4/docarray/docarray/releases/tag/v0.38.0" alt=""></div></a></figure><h2 id="%F0%9F%92%A5-breaking-changes">💥 Breaking Changes</h2><h3 id="changes-to-the-return-type-of-doclisttojson-and-docvectojson">Changes to the return type of <code>DocList.to_json()</code> and <code>DocVec.to_json()</code></h3><p>In order to make the <code>to_json</code> method consistent across different classes, we changed its return type in <code>DocList</code> and <code>DocVec</code> to <code>str</code>. This means that, if you use this method in your application, make sure to update your codebase to expect <code>str</code> instead of <code>bytes</code>.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="make-doclisttojson-and-docvectojson-return-str-instead-of-bytes-1769">Make <code>DocList.to_json()</code> and <code>DocVec.to_json()</code> return <code>str</code> instead of <code>bytes</code> (<a href="https://github.com/docarray/docarray/pull/1769?ref=jina-ai-gmbh.ghost.io">#1769</a>)</h3><p>This release changes the return type of the methods <code>DocList.to_json()</code> and <code>DocVec.to_json()</code> in order to be consistent with <code>BaseDoc .to_json()</code> and other pydantic models. After this release, these methods will return <code>str </code> type data instead of <code>bytes</code>.</p><p>💥 Since the return type is changed, this is considered a breaking change.</p><h3 id="casting-in-reduce-before-appending-1758">Casting in <code>reduce</code> before appending (<a href="https://github.com/docarray/docarray/pull/1758?ref=jina-ai-gmbh.ghost.io">#1758</a>)</h3><p>This release introduces type casting internally in the <code>reduce</code> helper function, casting its inputs before appending them to the final result. This will make it possible to reduce documents whose schemas are compatible but not exactly the same.</p><h3 id="skip-doc-attributes-in-annotations-but-not-in-fields-1777">Skip doc attributes in <code>__annotations__</code> but not in <code>__fields__</code> (<a href="https://github.com/docarray/docarray/pull/1777?ref=jina-ai-gmbh.ghost.io">#1777</a>)</h3><p>This release fixes an issue in the <code>create_pure_python_type_model</code> helper function. Starting with this release, only attributes in the class <code>__fields__</code> will be considered during type creation. The previous behavior broke applications when users introduced a ClassVar in an input class:</p><pre><code class="language-Python hljs"><span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
     endpoint: ClassVar[<span class="hljs-built_in">str</span>] = <span class="hljs-string">"my_endpoint"</span>
     input_test: <span class="hljs-built_in">str</span> = <span class="hljs-string">""</span>
     field_info = model.__fields__[field_name].field_info
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.39.1 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.39.1 Update"><meta name="description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-39-1-update"><meta property="og:title" content="DocArray 0.39.1 Update"><meta property="og:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-DocArray-dak-1.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-39-1-update"><meta property="twitter:title" content="DocArray 0.39.1 Update"><meta property="twitter:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-DocArray-dak-1.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 23, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0391">Release Note (<code>0.39.1</code>)</h2><p>This release contains 2 bug fixes.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.39.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v0.39.1 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.39.1) Release time: 2023-10-23 08:56:38 This release contains 2 bug fixes.
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.39.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 23, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0391">Release Note (<code>0.39.1</code>)</h2><p>This release contains 2 bug fixes.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.39.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v0.39.1 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.39.1) Release time: 2023-10-23 08:56:38 This release contains 2 bug fixes.
 🐞 Bug Fixes
 From_dataframe with numpy==1.26.1 (#1823)
 A recent update to numpy has changed some of the v…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/2cc6511b791fbb31b8bb33b69f7a6fb2948965f11790323434871815a729578d/docarray/docarray/releases/tag/v0.39.1" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fromdataframe-with-numpy1261-1823">From_dataframe with numpy==1.26.1 (<a href="https://github.com/docarray/docarray/pull/1823?ref=jina-ai-gmbh.ghost.io">#1823</a>)</h3><p>A recent update to numpy has changed some of the versioning semantics, breaking DocArray's&nbsp;<code>from_dataframe()</code>&nbsp;method in some cases where the dataframe contains a numpy array. This has now been now fixed.</p><pre><code class="language-Python hljs"><span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
@@ -33,4 +33,4 @@
 )
 df_da = da.to_dataframe()
 <span class="hljs-comment"># This broke before and is now fixed</span>
-da2 = DocVec[MyDoc].from_dataframe(df_da, tensor_type=NdArray)</code></pre><h3 id="type-handling-in-python-39-1823">Type handling in python 3.9 (<a href="https://github.com/docarray/docarray/pull/1823?ref=jina-ai-gmbh.ghost.io">#1823</a>)</h3><p>Starting with Python 3.9,&nbsp;<code>Optional.__args__</code>&nbsp;is not always available, leading to some compatibility problems. This has been fixed by using the&nbsp;<code>typing.get_args</code>&nbsp;helper.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>&nbsp;)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-39-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; 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+da2 = DocVec[MyDoc].from_dataframe(df_da, tensor_type=NdArray)</code></pre><h3 id="type-handling-in-python-39-1823">Type handling in python 3.9 (<a href="https://github.com/docarray/docarray/pull/1823?ref=jina-ai-gmbh.ghost.io">#1823</a>)</h3><p>Starting with Python 3.9,&nbsp;<code>Optional.__args__</code>&nbsp;is not always available, leading to some compatibility problems. This has been fixed by using the&nbsp;<code>typing.get_args</code>&nbsp;helper.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>&nbsp;)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-39-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.39 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.39 Update"><meta name="description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-39-update"><meta property="og:title" content="DocArray 0.39 Update"><meta property="og:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-DocArray-dak.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-39-update"><meta property="twitter:title" content="DocArray 0.39 Update"><meta property="twitter:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-DocArray-dak.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.39 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.39 Update"><meta name="description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-39-update"><meta property="og:title" content="DocArray 0.39 Update"><meta property="og:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-DocArray-dak.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-39-update"><meta property="twitter:title" content="DocArray 0.39 Update"><meta property="twitter:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-DocArray-dak.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.39 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 02, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0390"><br>Release Note (0.39.0)</h2><p>This release contains 4 new features, 8 bug fixes, and 7 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.39.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.39.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.39.0) Release time: 2023-10-02 13:06:02 This release contains 4 new features, 8 bug fixes, and 7 documentation improvements.🆕 FeaturesSupport for Pydantic v2 🚀 (#1652)The bigge…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/6046718f1e879a210b994daf388d030e8249404f7f7d70a9a3675722a1870488/docarray/docarray/releases/tag/v0.39.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="support-for-pydantic-v2-%F0%9F%9A%80-1652">Support for Pydantic v2 🚀 (<a href="https://github.com/docarray/docarray/pull/1652?ref=jina-ai-gmbh.ghost.io">#1652</a>)</h3><p>The biggest feature of this release is <strong>full support for Pydantic v2</strong>! We are <strong>continuing to support Pydantic v1</strong> at the same time.</p><p>If you use Pydantic v2, you will need to adapt your DocArray code to the new Pydantic API. Check out their migration guide <a href="https://docs.pydantic.dev/latest/migration/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">here</a>.</p><p>Pydantic v2 has its core written in Rust and provides significant performance improvements to DocArray: <strong>JSON serialization is 240% faster</strong> and <strong>validation</strong> of BaseDoc and DocList with non-native types like <code>TorchTensor</code> is <strong>20% faster</strong>.</p><h3 id="add-basedocwithoutid-1803">Add BaseDocWithoutId (<a href="https://github.com/docarray/docarray/pull/1803?ref=jina-ai-gmbh.ghost.io">#1803</a>)</h3><p>A <code>BaseDoc</code> by default includes an <code>id</code> field. This can be problematic if you want to build an API that requires a model without this ID field. Therefore, <strong>we now provide a <code>BaseDocWithoutId</code> which is, as its name suggests, is BaseDoc without the ID field</strong>.</p><p>Please use this Document with caution, BaseDoc is still the base class to use unless you specifically need to remove the ID.</p><p>⚠️ <strong><code>BaseDocWithoutId</code> is not compatible with <code>DocIndex</code></strong> or any feature requiring a vector database. This is because DocIndex needs the id field to store and retrieve documents.</p><h2 id="%F0%9F%92%A3-breaking-change">💣 Breaking change</h2><h3 id="remove-jina-ai-cloud-pushpull-1791">Remove Jina AI cloud push/pull (<a href="https://github.com/docarray/docarray/pull/1791?ref=jina-ai-gmbh.ghost.io">#1791</a>)</h3><p>Jina AI Cloud is being discontinued. Therefore, we are removing the <code>push/pull</code> feature related to Jina AI cloud.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-doclist-subscription-error">Fix DocList subscription error</h3><p><code>DocList</code> can be typed from BaseDoc using the following syntax <code>DocList[MyDoc]()</code>.</p><p>In this release, we have fixed a bug that allowed users to specify the type of a <code>DocList</code> multiple times</p><p>Doing <code>DocList[MyDoc1][MyDoc2]</code> won't work anymore (<a href="https://github.com/docarray/docarray/pull/1800?ref=jina-ai-gmbh.ghost.io">#1800</a>)</p><p>We also fixed a bug that caused a silent failure when users passed <code>DocList</code> the wrong type, for example <code>DocList[doc()]</code>. (<a href="https://github.com/docarray/docarray/pull/1794?ref=jina-ai-gmbh.ghost.io">#1794</a>)</p><h3 id="milvus-connection-parameter-missing-1802">Milvus connection parameter missing (<a href="https://github.com/docarray/docarray/pull/1802?ref=jina-ai-gmbh.ghost.io">#1802</a>)</h3><p>We fixed a small bug that incorrectly set the port of the Milvus client.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Fix Documentation for pydantic v2 (<a href="https://github.com/docarray/docarray/pull/1815?ref=jina-ai-gmbh.ghost.io">docs: fix documentation for pydantic v2 #1815</a>)</li><li>Adding field descriptions to predefined mesh 3D Document (<a href="https://github.com/docarray/docarray/pull/1789?ref=jina-ai-gmbh.ghost.io">docs: adding field descriptions to predefined mesh 3D document #1789</a>)</li><li>Adding field descriptions to predefined point cloud 3D Document (<a href="https://github.com/docarray/docarray/pull/1792?ref=jina-ai-gmbh.ghost.io">docs: adding field descriptions to predefined point cloud 3D document #1792</a>)</li><li>Adding field descriptions to predefined video Document (<a href="https://github.com/docarray/docarray/pull/1775?ref=jina-ai-gmbh.ghost.io">docs: adding field descriptions to predefined video document #1775</a>)</li><li>Adding field descriptions to predefined text Document (<a href="https://github.com/docarray/docarray/pull/1770?ref=jina-ai-gmbh.ghost.io">docs: adding field descriptions to predefined text document #1770</a>)</li><li>Adding field descriptions to predefined image Document (<a href="https://github.com/docarray/docarray/pull/1772?ref=jina-ai-gmbh.ghost.io">docs: adding field descriptions to predefined image document #1772</a>)</li><li>Adding field descriptions to predefined audio Document (<a href="https://github.com/docarray/docarray/pull/1774?ref=jina-ai-gmbh.ghost.io">docs: adding field descriptions to predefined audio document #1774</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>lvzi (<a href="https://github.com/lvzii?ref=jina-ai-gmbh.ghost.io">@lvzii</a> )</li><li>Puneeth K (<a href="https://github.com/punndcoder28?ref=jina-ai-gmbh.ghost.io">@punndcoder28</a> )</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a> )</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-39-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.39 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 02, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0390"><br>Release Note (0.39.0)</h2><p>This release contains 4 new features, 8 bug fixes, and 7 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.39.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.39.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.39.0) Release time: 2023-10-02 13:06:02 This release contains 4 new features, 8 bug fixes, and 7 documentation improvements.🆕 FeaturesSupport for Pydantic v2 🚀 (#1652)The bigge…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/6046718f1e879a210b994daf388d030e8249404f7f7d70a9a3675722a1870488/docarray/docarray/releases/tag/v0.39.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="support-for-pydantic-v2-%F0%9F%9A%80-1652">Support for Pydantic v2 🚀 (<a href="https://github.com/docarray/docarray/pull/1652?ref=jina-ai-gmbh.ghost.io">#1652</a>)</h3><p>The biggest feature of this release is <strong>full support for Pydantic v2</strong>! We are <strong>continuing to support Pydantic v1</strong> at the same time.</p><p>If you use Pydantic v2, you will need to adapt your DocArray code to the new Pydantic API. Check out their migration guide <a href="https://docs.pydantic.dev/latest/migration/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">here</a>.</p><p>Pydantic v2 has its core written in Rust and provides significant performance improvements to DocArray: <strong>JSON serialization is 240% faster</strong> and <strong>validation</strong> of BaseDoc and DocList with non-native types like <code>TorchTensor</code> is <strong>20% faster</strong>.</p><h3 id="add-basedocwithoutid-1803">Add BaseDocWithoutId (<a href="https://github.com/docarray/docarray/pull/1803?ref=jina-ai-gmbh.ghost.io">#1803</a>)</h3><p>A <code>BaseDoc</code> by default includes an <code>id</code> field. This can be problematic if you want to build an API that requires a model without this ID field. Therefore, <strong>we now provide a <code>BaseDocWithoutId</code> which is, as its name suggests, is BaseDoc without the ID field</strong>.</p><p>Please use this Document with caution, BaseDoc is still the base class to use unless you specifically need to remove the ID.</p><p>⚠️ <strong><code>BaseDocWithoutId</code> is not compatible with <code>DocIndex</code></strong> or any feature requiring a vector database. This is because DocIndex needs the id field to store and retrieve documents.</p><h2 id="%F0%9F%92%A3-breaking-change">💣 Breaking change</h2><h3 id="remove-jina-ai-cloud-pushpull-1791">Remove Jina AI cloud push/pull (<a href="https://github.com/docarray/docarray/pull/1791?ref=jina-ai-gmbh.ghost.io">#1791</a>)</h3><p>Jina AI Cloud is being discontinued. Therefore, we are removing the <code>push/pull</code> feature related to Jina AI cloud.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-doclist-subscription-error">Fix DocList subscription error</h3><p><code>DocList</code> can be typed from BaseDoc using the following syntax <code>DocList[MyDoc]()</code>.</p><p>In this release, we have fixed a bug that allowed users to specify the type of a <code>DocList</code> multiple times</p><p>Doing <code>DocList[MyDoc1][MyDoc2]</code> won't work anymore (<a href="https://github.com/docarray/docarray/pull/1800?ref=jina-ai-gmbh.ghost.io">#1800</a>)</p><p>We also fixed a bug that caused a silent failure when users passed <code>DocList</code> the wrong type, for example <code>DocList[doc()]</code>. (<a href="https://github.com/docarray/docarray/pull/1794?ref=jina-ai-gmbh.ghost.io">#1794</a>)</p><h3 id="milvus-connection-parameter-missing-1802">Milvus connection parameter missing (<a href="https://github.com/docarray/docarray/pull/1802?ref=jina-ai-gmbh.ghost.io">#1802</a>)</h3><p>We fixed a small bug that incorrectly set the port of the Milvus client.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Fix Documentation for pydantic v2 (<a href="https://github.com/docarray/docarray/pull/1815?ref=jina-ai-gmbh.ghost.io">docs: fix documentation for pydantic v2 #1815</a>)</li><li>Adding field descriptions to predefined mesh 3D Document (<a href="https://github.com/docarray/docarray/pull/1789?ref=jina-ai-gmbh.ghost.io">docs: adding field descriptions to predefined mesh 3D document #1789</a>)</li><li>Adding field descriptions to predefined point cloud 3D Document (<a href="https://github.com/docarray/docarray/pull/1792?ref=jina-ai-gmbh.ghost.io">docs: adding field descriptions to predefined point cloud 3D document #1792</a>)</li><li>Adding field descriptions to predefined video Document (<a href="https://github.com/docarray/docarray/pull/1775?ref=jina-ai-gmbh.ghost.io">docs: adding field descriptions to predefined video document #1775</a>)</li><li>Adding field descriptions to predefined text Document (<a href="https://github.com/docarray/docarray/pull/1770?ref=jina-ai-gmbh.ghost.io">docs: adding field descriptions to predefined text document #1770</a>)</li><li>Adding field descriptions to predefined image Document (<a href="https://github.com/docarray/docarray/pull/1772?ref=jina-ai-gmbh.ghost.io">docs: adding field descriptions to predefined image document #1772</a>)</li><li>Adding field descriptions to predefined audio Document (<a href="https://github.com/docarray/docarray/pull/1774?ref=jina-ai-gmbh.ghost.io">docs: adding field descriptions to predefined audio document #1774</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>lvzi (<a href="https://github.com/lvzii?ref=jina-ai-gmbh.ghost.io">@lvzii</a> )</li><li>Puneeth K (<a href="https://github.com/punndcoder28?ref=jina-ai-gmbh.ghost.io">@punndcoder28</a> )</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a> )</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-39-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray 0.40.0 Update</title><meta charset="utf-8"><meta name="title" content="DocArray 0.40.0 Update"><meta name="description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-0-40-0-update"><meta property="og:title" content="DocArray 0.40.0 Update"><meta property="og:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-0-40-0-update"><meta property="twitter:title" content="DocArray 0.40.0 Update"><meta property="twitter:description" content="DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 22, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0400">Release Note (<code>0.40.0</code>)</h2><p>This release contains 1 new feature, 3 bug fixes, and 2 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.40.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.40.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.40.0) Release time: 2023-12-22 12:12:15 This release contains 1 new feature, 3 bug fixes and 2 documentation improvements.
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray 0.40.0 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 22, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-0400">Release Note (<code>0.40.0</code>)</h2><p>This release contains 1 new feature, 3 bug fixes, and 2 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.40.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.40.0 · docarray/docarray</div><div class="kg-bookmark-description">Release Note (0.40.0) Release time: 2023-12-22 12:12:15 This release contains 1 new feature, 3 bug fixes and 2 documentation improvements.
 🆕 Features
 Add Epsilla connector (#1835)
-We have integra…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/668ee783e022a27964faa8e5f0a854cc1dea3f036e49bb10f4413288f5b2066f/docarray/docarray/releases/tag/v0.40.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="add-epsilla-connector-1835">Add Epsilla connector (<a href="https://github.com/docarray/docarray/pull/1835?ref=jina-ai-gmbh.ghost.io">#1835</a>)</h3><p>We have integrated&nbsp;<a href="https://epsilla.com/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Epsilla</a>&nbsp;into DocArray.</p><p>Here's a simple example of how to use it:</p><pre><code class="language-Python hljs"><span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc
-<span class="hljs-keyword">from</span> docarray.index <span class="hljs-keyword">import</span> EpsillaDocumentIndex
-<span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> NdArray
-<span class="hljs-keyword">from</span> pydantic <span class="hljs-keyword">import</span> Field
+We have integra…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/668ee783e022a27964faa8e5f0a854cc1dea3f036e49bb10f4413288f5b2066f/docarray/docarray/releases/tag/v0.40.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="add-epsilla-connector-1835">Add Epsilla connector (<a href="https://github.com/docarray/docarray/pull/1835?ref=jina-ai-gmbh.ghost.io">#1835</a>)</h3><p>We have integrated&nbsp;<a href="https://epsilla.com/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Epsilla</a>&nbsp;into DocArray.</p><p>Here's a simple example of how to use it:</p><pre><code class="language-Python">import numpy as np
+from docarray import BaseDoc
+from docarray.index import EpsillaDocumentIndex
+from docarray.typing import NdArray
+from pydantic import Field
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    text: <span class="hljs-built_in">str</span>
-    embedding: NdArray[<span class="hljs-number">10</span>] = Field(is_embedding=<span class="hljs-literal">True</span>)
+class MyDoc(BaseDoc):
+    text: str
+    embedding: NdArray[10] = Field(is_embedding=True)
 
-docs = [MyDoc(text=<span class="hljs-string">f'text <span class="hljs-subst">{i}</span>'</span>, embedding=np.random.rand(<span class="hljs-number">10</span>)) <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">10</span>)]
-query = np.random.rand(<span class="hljs-number">10</span>)
+docs = [MyDoc(text=f'text {i}', embedding=np.random.rand(10)) for i in range(10)]
+query = np.random.rand(10)
 db = EpsillaDocumentIndex[MyDoc]()
 db.index(docs)
-results = db.find(query, limit=<span class="hljs-number">10</span>)</code></pre><p>In this example, we create a document class with both textual and numeric data. Then, we initialize an Epsilla-backed document index and use it to index our documents. Finally, we perform a search query.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fixed-type-hints-error-in-python-312-1840">Fixed type hints error in Python 3.12 (<a href="https://github.com/docarray/docarray/pull/1840?ref=jina-ai-gmbh.ghost.io">#1840</a>)</h3><p>DocArray type-hinting is now available for Python 3.12.</p><h3 id="fix-issue-serializing-and-deserializing-complex-schemas-1836">Fix issue serializing and deserializing complex schemas (<a href="https://github.com/docarray/docarray/pull/1836?ref=jina-ai-gmbh.ghost.io">#1836</a>)</h3><p>There was an issue when serializing and deserializing&nbsp;<code>protobuf</code>&nbsp;documents with nested documents in dictionaries and other complex structures.</p><h3 id="fix-storage-issue-in-torchtensor-class-1833">Fix storage issue in TorchTensor class (<a href="https://github.com/docarray/docarray/pull/1833?ref=jina-ai-gmbh.ghost.io">#1833</a>)</h3><p>There was a bug when deep-copying a&nbsp;<code>TorchTensor</code>&nbsp;object if its&nbsp;<code>dtype</code>&nbsp;was not&nbsp;<code>float32</code>. This has now been fixed.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Add Epsilla integration guide (<a href="https://github.com/docarray/docarray/pull/1838?ref=jina-ai-gmbh.ghost.io">docs(epsilla): add epsilla integration guide #1838</a>)</li><li>Fix sign commit command in docs (<a href="https://github.com/docarray/docarray/pull/1834?ref=jina-ai-gmbh.ghost.io">docs: fix sign commit commad in docs #1834</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Tony Yang (<a href="https://github.com/tonyyanga?ref=jina-ai-gmbh.ghost.io">@tonyyanga</a>&nbsp;)</li><li>Naymul Islam (<a href="https://github.com/ai-naymul?ref=jina-ai-gmbh.ghost.io">@ai-naymul</a>&nbsp;)</li><li>Ben Shaver (<a href="https://github.com/bpshaver?ref=jina-ai-gmbh.ghost.io">@bpshaver</a>&nbsp;)</li><li>Joan Fontanals (@<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>954 (<a href="https://github.com/954-Ivory?ref=jina-ai-gmbh.ghost.io">@954-Ivory</a>&nbsp;)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-40-0-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+results = db.find(query, limit=10)</code></pre><p>In this example, we create a document class with both textual and numeric data. Then, we initialize an Epsilla-backed document index and use it to index our documents. Finally, we perform a search query.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fixed-type-hints-error-in-python-312-1840">Fixed type hints error in Python 3.12 (<a href="https://github.com/docarray/docarray/pull/1840?ref=jina-ai-gmbh.ghost.io">#1840</a>)</h3><p>DocArray type-hinting is now available for Python 3.12.</p><h3 id="fix-issue-serializing-and-deserializing-complex-schemas-1836">Fix issue serializing and deserializing complex schemas (<a href="https://github.com/docarray/docarray/pull/1836?ref=jina-ai-gmbh.ghost.io">#1836</a>)</h3><p>There was an issue when serializing and deserializing&nbsp;<code>protobuf</code>&nbsp;documents with nested documents in dictionaries and other complex structures.</p><h3 id="fix-storage-issue-in-torchtensor-class-1833">Fix storage issue in TorchTensor class (<a href="https://github.com/docarray/docarray/pull/1833?ref=jina-ai-gmbh.ghost.io">#1833</a>)</h3><p>There was a bug when deep-copying a&nbsp;<code>TorchTensor</code>&nbsp;object if its&nbsp;<code>dtype</code>&nbsp;was not&nbsp;<code>float32</code>. This has now been fixed.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Add Epsilla integration guide (<a href="https://github.com/docarray/docarray/pull/1838?ref=jina-ai-gmbh.ghost.io">docs(epsilla): add epsilla integration guide #1838</a>)</li><li>Fix sign commit command in docs (<a href="https://github.com/docarray/docarray/pull/1834?ref=jina-ai-gmbh.ghost.io">docs: fix sign commit commad in docs #1834</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Tony Yang (<a href="https://github.com/tonyyanga?ref=jina-ai-gmbh.ghost.io">@tonyyanga</a>&nbsp;)</li><li>Naymul Islam (<a href="https://github.com/ai-naymul?ref=jina-ai-gmbh.ghost.io">@ai-naymul</a>&nbsp;)</li><li>Ben Shaver (<a href="https://github.com/bpshaver?ref=jina-ai-gmbh.ghost.io">@bpshaver</a>&nbsp;)</li><li>Joan Fontanals (@<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>954 (<a href="https://github.com/954-Ivory?ref=jina-ai-gmbh.ghost.io">@954-Ivory</a>&nbsp;)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-0-40-0-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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diff --git a/news/docarray-and-the-otter-model-native-multi-modal-ai-meets-native-multi-modal-data-structures/index.html b/news/docarray-and-the-otter-model-native-multi-modal-ai-meets-native-multi-modal-data-structures/index.html
index 447fb644cd7..7d8c2955e00 100644
--- a/news/docarray-and-the-otter-model-native-multi-modal-ai-meets-native-multi-modal-data-structures/index.html
+++ b/news/docarray-and-the-otter-model-native-multi-modal-ai-meets-native-multi-modal-data-structures/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray and the Otter Model: Native multi-modal AI meets native multi-modal data structures</title><meta charset="utf-8"><meta name="title" content="DocArray and the Otter Model: Native multi-modal AI meets native multi-modal data structures"><meta name="description" content="We all love when a perfect couple finds each other, like DocArray and Otter."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-and-the-otter-model-native-multi-modal-ai-meets-native-multi-modal-data-structures"><meta property="og:title" content="DocArray and the Otter Model: Native multi-modal AI meets native multi-modal data structures"><meta property="og:description" content="We all love when a perfect couple finds each other, like DocArray and Otter."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/two_otters_4.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-and-the-otter-model-native-multi-modal-ai-meets-native-multi-modal-data-structures"><meta property="twitter:title" content="DocArray and the Otter Model: Native multi-modal AI meets native multi-modal data structures"><meta property="twitter:description" content="We all love when a perfect couple finds each other, like DocArray and Otter."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/two_otters_4.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray and the Otter Model: Native multi-modal AI meets native multi-modal data structures</title><meta charset="utf-8"><meta name="title" content="DocArray and the Otter Model: Native multi-modal AI meets native multi-modal data structures"><meta name="description" content="We all love when a perfect couple finds each other, like DocArray and Otter."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-and-the-otter-model-native-multi-modal-ai-meets-native-multi-modal-data-structures"><meta property="og:title" content="DocArray and the Otter Model: Native multi-modal AI meets native multi-modal data structures"><meta property="og:description" content="We all love when a perfect couple finds each other, like DocArray and Otter."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/two_otters_4.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-and-the-otter-model-native-multi-modal-ai-meets-native-multi-modal-data-structures"><meta property="twitter:title" content="DocArray and the Otter Model: Native multi-modal AI meets native multi-modal data structures"><meta property="twitter:description" content="We all love when a perfect couple finds each other, like DocArray and Otter."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/two_otters_4.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray and the Otter Model: Native multi-modal AI meets native multi-modal data structures</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">We all love when a perfect couple finds each other, like DocArray and Otter.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/GeJin.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Ge Jin, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 04, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Some things go together, like peanut butter and jelly, tea and biscuits, gin and tonic, or <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray</a> and <a href="https://otter-ntu.github.io/?ref=jina-ai-gmbh.ghost.io">Otter</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Welcome to DocArray!</div><div class="kg-bookmark-description">:arrow_up: DocArray v2: We are currently working on v2 of DocArray. Keep reading here if you are interested in the current (stable) version, or check out the v2 alpha branch and v2 roadmap! DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, v…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docarray.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">DocArray 0.21.0 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docarray.jina.ai/_static/banner.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://otter-ntu.github.io/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Otter</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://otter-ntu.github.io/assets/images/logo/otter_logo.ico" alt=""><span class="kg-bookmark-publisher">Bo Li*,♠,1</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://otter-ntu.github.io/assets/images/logo/otter_logo.png" alt=""></div></a></figure><p>We live in a world where information is usually multimodal — where texts, images, videos, and other media co-exist and come mixed together. The emergence of large language models has transformed the way we process, understand, and gain insights from this kind of complex, poorly structured multimedia data.</p><p>The nature of the Otter model — reading in combinations of images, videos, and texts as prompts — makes DocArray almost perfectly suited to it.</p><p>With DocArray, you can represent, send, and store multi-modal data easily. It integrates seamlessly with a wide array of databases, including <a href="https://docarray.jina.ai/advanced/document-store/weaviate?ref=jina-ai-gmbh.ghost.io">Weaviate</a>, <a href="https://docarray.jina.ai/advanced/document-store/qdrant/?ref=jina-ai-gmbh.ghost.io">Qdrant</a>, and <a href="https://docarray.jina.ai/advanced/document-store/elasticsearch/?ref=jina-ai-gmbh.ghost.io">ElasticSearch</a><a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">,</a> presenting users with a consistent API format for vector search. With DocArray, you can navigate your multimodal data effortlessly.</p><p>DocArray was designed for the data our complex, multimedia, multi-modal world naturally generates, exactly the same kind of data that Otter was designed to process. This article will show you how to bring the two together to get the most out of the Otter model.</p><h2 id="the-otter-model">The Otter model</h2><p>The Otter Model is a multimodal model fine-tuned for <a href="https://en.wikipedia.org/wiki/In-context_learning_(natural_language_processing)?ref=jina-ai-gmbh.ghost.io">in-context instruction</a>. It has been adapted from the <a href="https://github.com/mlfoundations/open_flamingo?ref=jina-ai-gmbh.ghost.io">OpenFlamingo</a> model from LAION, which is an open-source reproduction of DeepMind's <a href="https://doi.org/10.48550/arXiv.2204.14198?ref=jina-ai-gmbh.ghost.io">Flamingo</a> model. To train it, Otter’s developers created a partially human-curated dataset of 2.8 million instruction sets with examples.</p><p>The way in-context instruction works is to not just ask the AI model to respond to some prompt but to give it, as part of the prompt, a few examples of how you want it to respond. Instead of “zero-shot learning”, where the model responds without new information, this is “few-shot learning”, where it’s given a bit of positive instruction in the form of a small example set of inputs and appropriate responses.</p><p>For example:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/otter_drawing_1_small.png" class="kg-image" alt="" width="350" height="521"></figure><p>Now using the same images, the same question, but different answers in the examples:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/otter_drawing_2_small.png" class="kg-image" alt="" width="350" height="505"></figure><p>You can see in this example how Otter learns from the two examples given in each prompt what class of answer is required. When the question is <em>“Where was this picture taken?” “Paris”</em> is the same kind of answer as <em>“Rome”</em> and <em>“London”</em>, while “<em>at the Eiffel Tower</em>” is the same kind of answer as “<em>at the Colosseum</em>” and “<em>near Tower Bridge</em>”. This is the kind of processing Otter was trained for.</p><h2 id="building-multi-modal-prompts-with-docarray">Building multi-modal prompts with DocArray</h2><h3 id="prerequisites">Prerequisites</h3><p>First, Otter is an enormous model and will require a great deal of memory and very powerful GPUs. You will need either two GTX 3090 24G or a single A100.</p><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">Otter has a very high hardware requirement. You may have to rent a compatible cloud instance.</div></div><p>If you have secured the necessary hardware, the next step is to install DocArray. Assuming you have Python and pip installed and they are on the path, perform the following command in a terminal:</p><pre><code class="language-bash hljs">pip install docarray</code></pre><p>Next, download the environment for the Otter model from GitHub:</p><pre><code class="language-bash hljs">git <span class="hljs-built_in">clone</span> https://github.com/Luodian/Otter.git</code></pre><p>Finally, use <code>conda</code> to create a new virtual Python environment and install all necessary dependencies in it:</p><pre><code class="language-bash hljs">conda <span class="hljs-built_in">env</span> create -f environment.yml</code></pre><p>The file <code>environment.yml</code> is in the root directory of the git downloaded in the previous step.</p><h3 id="creating-the-classes-and-functions-with-docarray">Creating the classes and functions with DocArray</h3><p>A multi-modal prompt is a combination of different data types in a single prompt. This is where DocArray can shine because it allows us to tap into the richer, multi-faceted contexts that diverse data types offer.</p><p>For this article, we will build a small application that answers questions about pictures, with prompts that contain example images with example answers.</p><p>First, we will define the prompt object format in DocArray:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray and the Otter Model: Native multi-modal AI meets native multi-modal data structures</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">We all love when a perfect couple finds each other, like DocArray and Otter.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/GeJin.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Ge Jin, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 04, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Some things go together, like peanut butter and jelly, tea and biscuits, gin and tonic, or <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray</a> and <a href="https://otter-ntu.github.io/?ref=jina-ai-gmbh.ghost.io">Otter</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Welcome to DocArray!</div><div class="kg-bookmark-description">:arrow_up: DocArray v2: We are currently working on v2 of DocArray. Keep reading here if you are interested in the current (stable) version, or check out the v2 alpha branch and v2 roadmap! DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, v…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docarray.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">DocArray 0.21.0 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docarray.jina.ai/_static/banner.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://otter-ntu.github.io/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Otter</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://otter-ntu.github.io/assets/images/logo/otter_logo.ico" alt=""><span class="kg-bookmark-publisher">Bo Li*,♠,1</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://otter-ntu.github.io/assets/images/logo/otter_logo.png" alt=""></div></a></figure><p>We live in a world where information is usually multimodal — where texts, images, videos, and other media co-exist and come mixed together. The emergence of large language models has transformed the way we process, understand, and gain insights from this kind of complex, poorly structured multimedia data.</p><p>The nature of the Otter model — reading in combinations of images, videos, and texts as prompts — makes DocArray almost perfectly suited to it.</p><p>With DocArray, you can represent, send, and store multi-modal data easily. It integrates seamlessly with a wide array of databases, including <a href="https://docarray.jina.ai/advanced/document-store/weaviate?ref=jina-ai-gmbh.ghost.io">Weaviate</a>, <a href="https://docarray.jina.ai/advanced/document-store/qdrant/?ref=jina-ai-gmbh.ghost.io">Qdrant</a>, and <a href="https://docarray.jina.ai/advanced/document-store/elasticsearch/?ref=jina-ai-gmbh.ghost.io">ElasticSearch</a><a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">,</a> presenting users with a consistent API format for vector search. With DocArray, you can navigate your multimodal data effortlessly.</p><p>DocArray was designed for the data our complex, multimedia, multi-modal world naturally generates, exactly the same kind of data that Otter was designed to process. This article will show you how to bring the two together to get the most out of the Otter model.</p><h2 id="the-otter-model">The Otter model</h2><p>The Otter Model is a multimodal model fine-tuned for <a href="https://en.wikipedia.org/wiki/In-context_learning_(natural_language_processing)?ref=jina-ai-gmbh.ghost.io">in-context instruction</a>. It has been adapted from the <a href="https://github.com/mlfoundations/open_flamingo?ref=jina-ai-gmbh.ghost.io">OpenFlamingo</a> model from LAION, which is an open-source reproduction of DeepMind's <a href="https://doi.org/10.48550/arXiv.2204.14198?ref=jina-ai-gmbh.ghost.io">Flamingo</a> model. To train it, Otter’s developers created a partially human-curated dataset of 2.8 million instruction sets with examples.</p><p>The way in-context instruction works is to not just ask the AI model to respond to some prompt but to give it, as part of the prompt, a few examples of how you want it to respond. Instead of “zero-shot learning”, where the model responds without new information, this is “few-shot learning”, where it’s given a bit of positive instruction in the form of a small example set of inputs and appropriate responses.</p><p>For example:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/otter_drawing_1_small.png" class="kg-image" alt="" width="350" height="521"></figure><p>Now using the same images, the same question, but different answers in the examples:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/otter_drawing_2_small.png" class="kg-image" alt="" width="350" height="505"></figure><p>You can see in this example how Otter learns from the two examples given in each prompt what class of answer is required. When the question is <em>“Where was this picture taken?” “Paris”</em> is the same kind of answer as <em>“Rome”</em> and <em>“London”</em>, while “<em>at the Eiffel Tower</em>” is the same kind of answer as “<em>at the Colosseum</em>” and “<em>near Tower Bridge</em>”. This is the kind of processing Otter was trained for.</p><h2 id="building-multi-modal-prompts-with-docarray">Building multi-modal prompts with DocArray</h2><h3 id="prerequisites">Prerequisites</h3><p>First, Otter is an enormous model and will require a great deal of memory and very powerful GPUs. You will need either two GTX 3090 24G or a single A100.</p><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">Otter has a very high hardware requirement. You may have to rent a compatible cloud instance.</div></div><p>If you have secured the necessary hardware, the next step is to install DocArray. Assuming you have Python and pip installed and they are on the path, perform the following command in a terminal:</p><pre><code class="language-bash hljs">pip install docarray</code></pre><p>Next, download the environment for the Otter model from GitHub:</p><pre><code class="language-bash hljs">git <span class="hljs-built_in">clone</span> https://github.com/Luodian/Otter.git</code></pre><p>Finally, use <code>conda</code> to create a new virtual Python environment and install all necessary dependencies in it:</p><pre><code class="language-bash hljs">conda <span class="hljs-built_in">env</span> create -f environment.yml</code></pre><p>The file <code>environment.yml</code> is in the root directory of the git downloaded in the previous step.</p><h3 id="creating-the-classes-and-functions-with-docarray">Creating the classes and functions with DocArray</h3><p>A multi-modal prompt is a combination of different data types in a single prompt. This is where DocArray can shine because it allows us to tap into the richer, multi-faceted contexts that diverse data types offer.</p><p>For this article, we will build a small application that answers questions about pictures, with prompts that contain example images with example answers.</p><p>First, we will define the prompt object format in DocArray:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc
 <span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> ImageUrl
 
 <span class="hljs-keyword">class</span> <span class="hljs-title class_">OtterDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray and Weaviate: Your Guide to Hybrid Search</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Discover the power of hybrid search, a cutting-edge technology bridging keyword precision with vector versatility for a tailored search experience. Dive into how hybrid search works, its essential components, and using DocArray with Weaviate for optimized searches on your data.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/IMG_2892.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Isabelle Mohr, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 24, 2023 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Hybrid search is an innovative approach that unites the best of both worlds in search technology! It fuses the precision of keyword-based algorithms with the versatility of vector search techniques, creating a search experience tailored for modern users. By harnessing the strengths of various algorithms, hybrid search ensures improved accuracy and relevance in search results, revolutionizing the way we explore the vast expanse of digital information.</p><p>In this blog post, you will learn how hybrid search works, its component algorithms, and how to use <a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io">DocArray</a> with <a href="https://weaviate.io/?ref=jina-ai-gmbh.ghost.io">Weaviate</a> as a vector database to perform an optimized hybrid search on your data easily.</p><h2 id="hybrid-search"><strong>Hybrid Search</strong></h2><p>Hybrid search uses sparse and dense vectors to represent the meaning and context of search queries and documents. Let’s look at these in turn.</p><h3 id="sparse-vectors-smart-keyword-scoring">Sparse Vectors: Smart Keyword Scoring</h3><p>Sparse vectors, receiving their name by consisting mainly of zero values with a few non-zero values, are generated by algorithms like <a href="https://en.wikipedia.org/wiki/Okapi_BM25?ref=jina-ai-gmbh.ghost.io">BM25 </a>and <a href="https://github.com/naver/splade?ref=jina-ai-gmbh.ghost.io">SPLADE</a>. These consider the appearance of keywords in queries and documents.</p><p>BM25, which we will be using in the hybrid search experiment later, is like the smarter sibling of TF-IDF: They both rank search results based on exact matches in your text documents. These algorithms consider your documents and queries as high-dimensional sparse vectors, where each dimension corresponds to a unique term (word or word-piece) from your collection of documents. Most of these dimensions will be zero for a given document because there are a lot of words and most don't appear in any one document. Only a few will contain non-zero values, hence the name "sparse" vectors.</p><p>BM25 considers how often a term appears in a document (just like TF-IDF), but it knows not to overvalue a word just because it appears a lot. It also levels the playing field between long and short documents, so a term does not get extra points just for being in a longer piece. In a nutshell, BM25 is a more refined way of figuring out what documents match your search query best.</p><p>Here are some of the advantages of sparse vectors in search:</p><ul><li><strong>Storage and Computational Efficiency</strong>: Sparse vectors are memory efficient as they store only non-zero values, thereby conserving computational resources.</li><li><strong>Relevance Identification</strong>: They effectively capture the occurrence of less frequent but potentially more relevant terms, helping to identify the relevance of documents even with rare keywords.</li><li><strong>Scalability</strong>: Sparse vectors can efficiently handle large-scale, high-dimensional data, which is a common characteristic of text data in information retrieval.</li><li><strong>Fine-tuning</strong>: The ability to adjust parameters in BM25 helps in customizing the algorithm for specific datasets, improving the precision of search results.</li><li><strong>Better Noise Handling</strong>: Sparse vectors are better at handling 'noise' in the data (such as common words that might be less informative), as they focus on relevant, non-zero elements.</li><li><strong>Easy to Debug</strong>: Unlike dense vectors, sparse vectors are easier to debug and understand due to their non-zero focus. You only need to investigate the non-zero elements, which are typically fewer, significantly simplifying the process of troubleshooting and understanding model behavior. This transparency in the data representation aids in diagnosing and resolving potential issues more effectively.</li></ul><h3 id="dense-vectors-packed-with-information">Dense Vectors: Packed with Information</h3><p>Dense vectors, on the other hand, predominantly contain non-zero values and are produced by machine learning models such as <a href="https://nlp.stanford.edu/projects/glove/?ref=jina-ai-gmbh.ghost.io">GloVe</a> and <a href="https://en.wikipedia.org/wiki/Transformer_(machine_learning_model)?ref=jina-ai-gmbh.ghost.io">Transformers</a>. Given that different machine learning models support various modalities, dense vectors can represent various types of data stored in a database, including (but not limited to) text and images. These embeddings are generated by machine learning models that convert data into densely-packed vectors filled with non-zero values. Vector databases like Weaviate store these embeddings and enable lightning-fast retrieval based on the distance between them, using, for example, cosine similarity. In other words, vector databases add an additional vector-based index, which allows you to quickly discover data objects based on the similarity or dissimilarity between documents in this latent space.</p><p>In our experiments below, we will use a <a href="https://www.sbert.net/docs/pretrained_models.html?ref=jina-ai-gmbh.ghost.io">language model from sentence transformers</a> (Sentence-BERT) to create dense representations of our textual data.</p><h2 id="the-power-of-hybrid-search"><strong>The Power of Hybrid Search</strong></h2><p>Hybrid search seamlessly blends dense and sparse vectors, delivering the best features of both search methods. Dense vectors excel at making sense of the context of a query, while sparse vectors master keyword matches. For instance, consider the query “red heels with bow”. The dense vector representation can distinguish the word “heel” as meaning “high-heeled shoes” instead of “the back part of the foot” by considering the contextual words “red” and “bow”. In contrast, the sparse vector search will contribute higher scores for exact matches of the keyword “red”, making your search results more accurate. Hybrid search brilliantly combines the strengths of both sparse and dense vectors.</p><p>Now that we have a good understanding of hybrid search and the gains we can get from it, we can jump into a working example using DocArray!</p><p>You can find all related code in a Jupyter Notebook in this <a href="https://github.com/violenil/docarray-weaviate-hybrid-search?ref=jina-ai-gmbh.ghost.io">GitHub repository</a>. You can try it out in Google Colab by following the link below:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://colab.research.google.com/github/violenil/docarray-weaviate-hybrid-search/blob/main/hybrid_demo.ipynb?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Google Colaboratory</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ssl.gstatic.com/colaboratory-static/common/5d71429ee6657823934f508bf7362902/img/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://colab.research.google.com/img/colab_favicon_256px.png" alt=""></div></a></figure><h3 id="what-is-docarray-and-how-does-it-work-with-weaviate">What is DocArray and how does it work with Weaviate?</h3><p><br>The integration of Weaviate as a document store in DocArray provides a high-performing solution for the storage and retrieval of multimodal data. Weaviate, a vector database, can be utilized to store DocumentArray instances, which are used to handle nested, unstructured, and multimodal data including text, image, audio, video, 3D mesh, and more. This configuration significantly enhances the capabilities for document retrieval on embeddings, making functions like <code>.match()</code> and <code>.find()</code> more efficient and rapid.</p><p>The process of setting up Weaviate as the storage backend is streamlined and user-friendly. After installing the necessary package <code>weaviate-client</code> using <code>pip</code>, users can launch the Weaviate service by creating and running a Docker Compose configuration. The Weaviate service is designed with restart-on-failure capabilities, enabling consistent performance and reliability. Once the service is started and configured (with a default server address at <a href="http://localhost:8080/?ref=jina-ai-gmbh.ghost.io">http://localhost:8080</a>), users can instantiate a DocumentArray with Weaviate storage in a single line of code.</p><p>An additional advantage of integrating Weaviate as a document store in DocArray is the seamless access to formerly-persisted DocumentArrays. Users can connect to the server by specifying the name, host, port, and protocol. The name parameter is required for this function, but all other parameters are optional, offering a versatile solution for different scenarios and configurations. Despite the changes in the backend storage, all other functions behave the same as in an in-memory DocumentArray, ensuring continuity in the user experience and functionality. This integration, therefore, presents a robust and efficient solution for managing and retrieving unstructured and multimodal data in various applications.</p><h3 id="setup-weaviate">Setup Weaviate</h3><p>Ensure you have a docker instance with Weaviate running locally or set credentials for connecting to a remote instance. To run Weaviate locally, first download the <code>docker-compose.yml</code> and then run <code>docker-compose</code> as follows:</p><pre><code class="language-shell hljs">curl -o docker-compose.yml "https://configuration.weaviate.io/v2/docker-compose/docker-compose.yml?modules=standalone&amp;runtime=docker-compose&amp;weaviate_version=v1.19.2"
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray and Weaviate: Your Guide to Hybrid Search</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Discover the power of hybrid search, a cutting-edge technology bridging keyword precision with vector versatility for a tailored search experience. Dive into how hybrid search works, its essential components, and using DocArray with Weaviate for optimized searches on your data.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/IMG_2892.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Isabelle Mohr, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 24, 2023 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Hybrid search is an innovative approach that unites the best of both worlds in search technology! It fuses the precision of keyword-based algorithms with the versatility of vector search techniques, creating a search experience tailored for modern users. By harnessing the strengths of various algorithms, hybrid search ensures improved accuracy and relevance in search results, revolutionizing the way we explore the vast expanse of digital information.</p><p>In this blog post, you will learn how hybrid search works, its component algorithms, and how to use <a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io">DocArray</a> with <a href="https://weaviate.io/?ref=jina-ai-gmbh.ghost.io">Weaviate</a> as a vector database to perform an optimized hybrid search on your data easily.</p><h2 id="hybrid-search"><strong>Hybrid Search</strong></h2><p>Hybrid search uses sparse and dense vectors to represent the meaning and context of search queries and documents. Let’s look at these in turn.</p><h3 id="sparse-vectors-smart-keyword-scoring">Sparse Vectors: Smart Keyword Scoring</h3><p>Sparse vectors, receiving their name by consisting mainly of zero values with a few non-zero values, are generated by algorithms like <a href="https://en.wikipedia.org/wiki/Okapi_BM25?ref=jina-ai-gmbh.ghost.io">BM25 </a>and <a href="https://github.com/naver/splade?ref=jina-ai-gmbh.ghost.io">SPLADE</a>. These consider the appearance of keywords in queries and documents.</p><p>BM25, which we will be using in the hybrid search experiment later, is like the smarter sibling of TF-IDF: They both rank search results based on exact matches in your text documents. These algorithms consider your documents and queries as high-dimensional sparse vectors, where each dimension corresponds to a unique term (word or word-piece) from your collection of documents. Most of these dimensions will be zero for a given document because there are a lot of words and most don't appear in any one document. Only a few will contain non-zero values, hence the name "sparse" vectors.</p><p>BM25 considers how often a term appears in a document (just like TF-IDF), but it knows not to overvalue a word just because it appears a lot. It also levels the playing field between long and short documents, so a term does not get extra points just for being in a longer piece. In a nutshell, BM25 is a more refined way of figuring out what documents match your search query best.</p><p>Here are some of the advantages of sparse vectors in search:</p><ul><li><strong>Storage and Computational Efficiency</strong>: Sparse vectors are memory efficient as they store only non-zero values, thereby conserving computational resources.</li><li><strong>Relevance Identification</strong>: They effectively capture the occurrence of less frequent but potentially more relevant terms, helping to identify the relevance of documents even with rare keywords.</li><li><strong>Scalability</strong>: Sparse vectors can efficiently handle large-scale, high-dimensional data, which is a common characteristic of text data in information retrieval.</li><li><strong>Fine-tuning</strong>: The ability to adjust parameters in BM25 helps in customizing the algorithm for specific datasets, improving the precision of search results.</li><li><strong>Better Noise Handling</strong>: Sparse vectors are better at handling 'noise' in the data (such as common words that might be less informative), as they focus on relevant, non-zero elements.</li><li><strong>Easy to Debug</strong>: Unlike dense vectors, sparse vectors are easier to debug and understand due to their non-zero focus. You only need to investigate the non-zero elements, which are typically fewer, significantly simplifying the process of troubleshooting and understanding model behavior. This transparency in the data representation aids in diagnosing and resolving potential issues more effectively.</li></ul><h3 id="dense-vectors-packed-with-information">Dense Vectors: Packed with Information</h3><p>Dense vectors, on the other hand, predominantly contain non-zero values and are produced by machine learning models such as <a href="https://nlp.stanford.edu/projects/glove/?ref=jina-ai-gmbh.ghost.io">GloVe</a> and <a href="https://en.wikipedia.org/wiki/Transformer_(machine_learning_model)?ref=jina-ai-gmbh.ghost.io">Transformers</a>. Given that different machine learning models support various modalities, dense vectors can represent various types of data stored in a database, including (but not limited to) text and images. These embeddings are generated by machine learning models that convert data into densely-packed vectors filled with non-zero values. Vector databases like Weaviate store these embeddings and enable lightning-fast retrieval based on the distance between them, using, for example, cosine similarity. In other words, vector databases add an additional vector-based index, which allows you to quickly discover data objects based on the similarity or dissimilarity between documents in this latent space.</p><p>In our experiments below, we will use a <a href="https://www.sbert.net/docs/pretrained_models.html?ref=jina-ai-gmbh.ghost.io">language model from sentence transformers</a> (Sentence-BERT) to create dense representations of our textual data.</p><h2 id="the-power-of-hybrid-search"><strong>The Power of Hybrid Search</strong></h2><p>Hybrid search seamlessly blends dense and sparse vectors, delivering the best features of both search methods. Dense vectors excel at making sense of the context of a query, while sparse vectors master keyword matches. For instance, consider the query “red heels with bow”. The dense vector representation can distinguish the word “heel” as meaning “high-heeled shoes” instead of “the back part of the foot” by considering the contextual words “red” and “bow”. In contrast, the sparse vector search will contribute higher scores for exact matches of the keyword “red”, making your search results more accurate. Hybrid search brilliantly combines the strengths of both sparse and dense vectors.</p><p>Now that we have a good understanding of hybrid search and the gains we can get from it, we can jump into a working example using DocArray!</p><p>You can find all related code in a Jupyter Notebook in this <a href="https://github.com/violenil/docarray-weaviate-hybrid-search?ref=jina-ai-gmbh.ghost.io">GitHub repository</a>. You can try it out in Google Colab by following the link below:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://colab.research.google.com/github/violenil/docarray-weaviate-hybrid-search/blob/main/hybrid_demo.ipynb?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Google Colaboratory</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ssl.gstatic.com/colaboratory-static/common/5d71429ee6657823934f508bf7362902/img/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://colab.research.google.com/img/colab_favicon_256px.png" alt=""></div></a></figure><h3 id="what-is-docarray-and-how-does-it-work-with-weaviate">What is DocArray and how does it work with Weaviate?</h3><p><br>The integration of Weaviate as a document store in DocArray provides a high-performing solution for the storage and retrieval of multimodal data. Weaviate, a vector database, can be utilized to store DocumentArray instances, which are used to handle nested, unstructured, and multimodal data including text, image, audio, video, 3D mesh, and more. This configuration significantly enhances the capabilities for document retrieval on embeddings, making functions like <code>.match()</code> and <code>.find()</code> more efficient and rapid.</p><p>The process of setting up Weaviate as the storage backend is streamlined and user-friendly. After installing the necessary package <code>weaviate-client</code> using <code>pip</code>, users can launch the Weaviate service by creating and running a Docker Compose configuration. The Weaviate service is designed with restart-on-failure capabilities, enabling consistent performance and reliability. Once the service is started and configured (with a default server address at <a href="http://localhost:8080/?ref=jina-ai-gmbh.ghost.io">http://localhost:8080</a>), users can instantiate a DocumentArray with Weaviate storage in a single line of code.</p><p>An additional advantage of integrating Weaviate as a document store in DocArray is the seamless access to formerly-persisted DocumentArrays. Users can connect to the server by specifying the name, host, port, and protocol. The name parameter is required for this function, but all other parameters are optional, offering a versatile solution for different scenarios and configurations. Despite the changes in the backend storage, all other functions behave the same as in an in-memory DocumentArray, ensuring continuity in the user experience and functionality. This integration, therefore, presents a robust and efficient solution for managing and retrieving unstructured and multimodal data in various applications.</p><h3 id="setup-weaviate">Setup Weaviate</h3><p>Ensure you have a docker instance with Weaviate running locally or set credentials for connecting to a remote instance. To run Weaviate locally, first download the <code>docker-compose.yml</code> and then run <code>docker-compose</code> as follows:</p><pre><code class="language-shell hljs">curl -o docker-compose.yml "https://configuration.weaviate.io/v2/docker-compose/docker-compose.yml?modules=standalone&amp;runtime=docker-compose&amp;weaviate_version=v1.19.2"
 
 docker-compose up -d</code></pre><p>This will start the Weaviate cluster locally. Note that we have specified the version <code>v1.19.2</code> above, which should be updated with the latest release from Weaviate (check the <a href="https://github.com/weaviate/weaviate/releases?ref=jina-ai-gmbh.ghost.io">latest version here</a>).</p><p>Next, you will need to create a virtual environment with all requirements from the <a href="https://github.com/violenil/docarray-weaviate-hybrid-search?ref=jina-ai-gmbh.ghost.io">GitHub repository</a> installed:</p><pre><code class="language-bash hljs">python3 -m venv hybrid-venv
 <span class="hljs-built_in">source</span> hybrid-venv/bin/activate
diff --git a/news/docarray-v2-update/index.html b/news/docarray-v2-update/index.html
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>DocArray v2 Release</title><meta charset="utf-8"><meta name="title" content="DocArray v2 Release"><meta name="description" content="Announcing the brand new rewrite of DocArray. If you're building a machine learning application that deals with multimodal data, then DocArray is the way to go"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/docarray-v2-update"><meta property="og:title" content="DocArray v2 Release"><meta property="og:description" content="Announcing the brand new rewrite of DocArray. If you're building a machine learning application that deals with multimodal data, then DocArray is the way to go"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/docarray-3.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/docarray-v2-update"><meta property="twitter:title" content="DocArray v2 Release"><meta property="twitter:description" content="Announcing the brand new rewrite of DocArray. If you're building a machine learning application that deals with multimodal data, then DocArray is the way to go"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/docarray-3.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">DocArray v2 Release</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Announcing the brand new rewrite of DocArray. If you're building a machine learning application that deals with multimodal data, then DocArray is the way to go</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 20, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-v0300-aka-docarray-v2">Release v0.30.0 (a.k.a DocArray v2)</h2><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">This version of DocArrray is a complete rewrite, therefore it includes several (more than breaking) changes. Be sure to check the <a href="https://docs.docarray.org/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">documentation</a> to prepare your migration.</div></div><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.30.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.30.0 · docarray/docarray</div><div class="kg-bookmark-description">💫 Release v0.30.0 (a.k.a DocArray v2) WarningThis version of DocArrray is a complete rewrite, therefore it includes several (more than breaking) changes. Be sure to check the documentation to pre…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/8ad0709931def46c076a48235f4547197e42cd19f532c3b88e54ba484ed73664/docarray/docarray/releases/tag/v0.30.0" alt=""></div></a></figure><h2 id="changelog">Changelog</h2><p>If you have been using recent versions of DocArray, you will already be familiar with its <a href="https://docarray.jina.ai/fundamentals/dataclass/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">dataclass API</a>.</p><p>DocArray v2 is that idea, taken seriously. Every Document is created through a dataclass-like interface, courtesy of <a href="https://pydantic-docs.helpmanual.io/usage/models/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Pydantic</a>.</p><p>This has the following advantages:</p><ul><li><strong>Flexibility:</strong> No need to conform to a fixed set of fields -- your data defines the schema.</li><li><strong>Multimodality:</strong> Easily store multiple modalities and multiple embeddings in the same Document.</li><li><strong>Language agnostic:</strong> At their core, Documents are just dictionaries, and this makes it easy to create and send them from any language, not just Python.</li></ul><p>You may also be familiar with our old <a href="https://docarray.jina.ai/advanced/document-store/?ref=jina-ai-gmbh.ghost.io">Document Store</a> for vector database integration. They are now called <strong>Document Indexes</strong> and offer the following improvements:</p><ul><li><strong>Hybrid search:</strong> You can now combine vector search with text search and even filter by arbitrary fields.</li><li><strong>Production-ready:</strong> The new Document Indexes are a much thinner wrapper around the various vector DB libraries, making them more robust and easier to maintain.</li><li><strong>Increased flexibility:</strong> We strive to support any configuration or setting you could perform through the vector DB's first-party client.</li></ul><p>Document Indexes currently support <strong><a href="https://weaviate.io/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Weaviate</a></strong>, <strong><a href="https://qdrant.tech/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Qdrant</a></strong>, <strong><a href="https://www.elastic.co/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">ElasticSearch</a></strong>, and <strong><a href="https://github.com/nmslib/hnswlib?ref=jina-ai-gmbh.ghost.io">HNSWLib</a></strong>, with more to come.</p><h2 id="changes-to-document">Changes to <code>Document</code></h2><ul><li><code>Document</code> has been renamed<a href="https://docs.docarray.org/API_reference/base_doc/base_doc/?ref=jina-ai-gmbh.ghost.io" rel="nofollow"><code>BaseDoc</code></a>.</li><li><code>BaseDoc</code> cannot be used directly but instead has to be extended. Therefore, each document class is created through a dataclass-like interface.</li><li>Following from the previous point, extending <code>BaseDoc</code> allows for a flexible schema compared to the <code>Document</code> class in v1 which only allowed for a fixed schema, with one of <code>tensor</code>, <code>text</code> and <code>blob</code>, and additional <code>chunks</code> and <code>matches</code>.</li><li>Due to the added flexibility, one can not know what fields your document class will provide. Therefore, various methods from v1 (such as <code>.load_uri_to_image_tensor()</code>) are not supported in v2. Instead, we provide some of those methods on the <a href="https://github.com/docarray/docarray/blob/v0.30.0/docs/data_types/first_steps.md?ref=jina-ai-gmbh.ghost.io">typing level</a>.</li><li>In v2, we have the <code><a href="https://docs.docarray.org/API_reference/documents/documents/?ref=jina-ai-gmbh.ghost.io#docarray.documents.legacy.LegacyDocument" rel="nofollow">LegacyDocument</a></code> class, which extends <code>BaseDoc</code> while following the same schema as v1's <code>Document</code>. The <code>LegacyDocument</code> can be helpful to start migrating your codebase from v1 to v2. Nevertheless, the API is not fully compatible with DocArray v1 <code>Document</code>. Indeed, none of the methods associated with <code>Document</code> are present. Only the schema of the data is similar.</li></ul><h2 id="changes-to-documentarray">Changes to <code>DocumentArray</code></h2><h3 id="doclist">DocList</h3><ul><li>The <code>DocumentArray</code> class from v1 has been renamed <code><a href="https://docs.docarray.org/API_reference/array/da/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">DocList</a></code>. This better describes its actual functionality since it is a list of <code>BaseDoc</code>.</li></ul><h3 id="docvec">DocVec</h3><ul><li>Additionally, we have introduced the class <a href="https://docs.docarray.org/API_reference/array/da_stack/?ref=jina-ai-gmbh.ghost.io" rel="nofollow"><code>DocVec</code></a>, which is a column-based representation of <code>BaseDoc</code>. Both <code>DocVec</code> and <code>DocList</code> extend <code>AnyDocArray</code>.</li><li><code>DocVec</code> is a container of Documents appropriate for computations that require batches of data (i.e., matrix multiplication, distance calculation, deep learning forward pass).</li><li>A <code>DocVec</code> has a similar interface to <code>DocList</code> but with an underlying implementation that is column-based instead of row-based. Each field of the schema of the <code>DocVec</code> (the <code>.doc_type</code> which is a <code>BaseDoc</code>) will be stored in a column. If the field is a tensor, the data from all Documents will be stored as a single <code>doc_vec</code> (Torch/TensorFlow/NumPy) tensor. If the tensor field is <code>AnyTensor</code> or a union of tensor types, the <code>.tensor_type</code> will be used to determine the type of the <code>doc_vec</code> column.</li></ul><h3 id="parameterized-doclist">Parameterized DocList</h3><ul><li>Because you now have the flexibility to design your own document schema, when initializing a <code>DocList</code>, the contents do not have to all be of the same type.</li><li>If you want a homogenous <code>DocList</code> you can parameterize it at initialization time:</li></ul><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocList
-<span class="hljs-keyword">from</span> docarray.documents <span class="hljs-keyword">import</span> ImageDoc
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Announcing the brand new rewrite of DocArray. If you're building a machine learning application that deals with multimodal data, then DocArray is the way to go</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 20, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-v0300-aka-docarray-v2">Release v0.30.0 (a.k.a DocArray v2)</h2><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">This version of DocArrray is a complete rewrite, therefore it includes several (more than breaking) changes. Be sure to check the <a href="https://docs.docarray.org/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">documentation</a> to prepare your migration.</div></div><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray/releases/tag/v0.30.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v0.30.0 · docarray/docarray</div><div class="kg-bookmark-description">💫 Release v0.30.0 (a.k.a DocArray v2) WarningThis version of DocArrray is a complete rewrite, therefore it includes several (more than breaking) changes. Be sure to check the documentation to pre…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/8ad0709931def46c076a48235f4547197e42cd19f532c3b88e54ba484ed73664/docarray/docarray/releases/tag/v0.30.0" alt=""></div></a></figure><h2 id="changelog">Changelog</h2><p>If you have been using recent versions of DocArray, you will already be familiar with its <a href="https://docarray.jina.ai/fundamentals/dataclass/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">dataclass API</a>.</p><p>DocArray v2 is that idea, taken seriously. Every Document is created through a dataclass-like interface, courtesy of <a href="https://pydantic-docs.helpmanual.io/usage/models/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Pydantic</a>.</p><p>This has the following advantages:</p><ul><li><strong>Flexibility:</strong> No need to conform to a fixed set of fields -- your data defines the schema.</li><li><strong>Multimodality:</strong> Easily store multiple modalities and multiple embeddings in the same Document.</li><li><strong>Language agnostic:</strong> At their core, Documents are just dictionaries, and this makes it easy to create and send them from any language, not just Python.</li></ul><p>You may also be familiar with our old <a href="https://docarray.jina.ai/advanced/document-store/?ref=jina-ai-gmbh.ghost.io">Document Store</a> for vector database integration. They are now called <strong>Document Indexes</strong> and offer the following improvements:</p><ul><li><strong>Hybrid search:</strong> You can now combine vector search with text search and even filter by arbitrary fields.</li><li><strong>Production-ready:</strong> The new Document Indexes are a much thinner wrapper around the various vector DB libraries, making them more robust and easier to maintain.</li><li><strong>Increased flexibility:</strong> We strive to support any configuration or setting you could perform through the vector DB's first-party client.</li></ul><p>Document Indexes currently support <strong><a href="https://weaviate.io/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Weaviate</a></strong>, <strong><a href="https://qdrant.tech/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Qdrant</a></strong>, <strong><a href="https://www.elastic.co/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">ElasticSearch</a></strong>, and <strong><a href="https://github.com/nmslib/hnswlib?ref=jina-ai-gmbh.ghost.io">HNSWLib</a></strong>, with more to come.</p><h2 id="changes-to-document">Changes to <code>Document</code></h2><ul><li><code>Document</code> has been renamed<a href="https://docs.docarray.org/API_reference/base_doc/base_doc/?ref=jina-ai-gmbh.ghost.io" rel="nofollow"><code>BaseDoc</code></a>.</li><li><code>BaseDoc</code> cannot be used directly but instead has to be extended. Therefore, each document class is created through a dataclass-like interface.</li><li>Following from the previous point, extending <code>BaseDoc</code> allows for a flexible schema compared to the <code>Document</code> class in v1 which only allowed for a fixed schema, with one of <code>tensor</code>, <code>text</code> and <code>blob</code>, and additional <code>chunks</code> and <code>matches</code>.</li><li>Due to the added flexibility, one can not know what fields your document class will provide. Therefore, various methods from v1 (such as <code>.load_uri_to_image_tensor()</code>) are not supported in v2. Instead, we provide some of those methods on the <a href="https://github.com/docarray/docarray/blob/v0.30.0/docs/data_types/first_steps.md?ref=jina-ai-gmbh.ghost.io">typing level</a>.</li><li>In v2, we have the <code><a href="https://docs.docarray.org/API_reference/documents/documents/?ref=jina-ai-gmbh.ghost.io#docarray.documents.legacy.LegacyDocument" rel="nofollow">LegacyDocument</a></code> class, which extends <code>BaseDoc</code> while following the same schema as v1's <code>Document</code>. The <code>LegacyDocument</code> can be helpful to start migrating your codebase from v1 to v2. Nevertheless, the API is not fully compatible with DocArray v1 <code>Document</code>. Indeed, none of the methods associated with <code>Document</code> are present. Only the schema of the data is similar.</li></ul><h2 id="changes-to-documentarray">Changes to <code>DocumentArray</code></h2><h3 id="doclist">DocList</h3><ul><li>The <code>DocumentArray</code> class from v1 has been renamed <code><a href="https://docs.docarray.org/API_reference/array/da/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">DocList</a></code>. This better describes its actual functionality since it is a list of <code>BaseDoc</code>.</li></ul><h3 id="docvec">DocVec</h3><ul><li>Additionally, we have introduced the class <a href="https://docs.docarray.org/API_reference/array/da_stack/?ref=jina-ai-gmbh.ghost.io" rel="nofollow"><code>DocVec</code></a>, which is a column-based representation of <code>BaseDoc</code>. Both <code>DocVec</code> and <code>DocList</code> extend <code>AnyDocArray</code>.</li><li><code>DocVec</code> is a container of Documents appropriate for computations that require batches of data (i.e., matrix multiplication, distance calculation, deep learning forward pass).</li><li>A <code>DocVec</code> has a similar interface to <code>DocList</code> but with an underlying implementation that is column-based instead of row-based. Each field of the schema of the <code>DocVec</code> (the <code>.doc_type</code> which is a <code>BaseDoc</code>) will be stored in a column. If the field is a tensor, the data from all Documents will be stored as a single <code>doc_vec</code> (Torch/TensorFlow/NumPy) tensor. If the tensor field is <code>AnyTensor</code> or a union of tensor types, the <code>.tensor_type</code> will be used to determine the type of the <code>doc_vec</code> column.</li></ul><h3 id="parameterized-doclist">Parameterized DocList</h3><ul><li>Because you now have the flexibility to design your own document schema, when initializing a <code>DocList</code>, the contents do not have to all be of the same type.</li><li>If you want a homogenous <code>DocList</code> you can parameterize it at initialization time:</li></ul><pre><code class="language-python">from docarray import DocList
+from docarray.documents import ImageDoc
 
-docs = DocList[ImageDoc]()</code></pre><ul><li>Methods like <code>.from_csv()</code> or <code>.pull()</code> only work with a parameterized <code>DocList</code>.</li></ul><h3 id="access-attributes-of-your-documentarray">Access attributes of your DocumentArray</h3><ul><li>In v1, you could access an attribute of all Documents in your DocumentArray by calling the plural of the attribute's name on your DocArray instance.</li><li>In v2, you don't have to use the plural; instead, use the Document's attribute name since <code>AnyDocArray</code> it will expose the same attributes as the <code>BaseDoc</code>s it contains. This will return a list of <code>type(attribute)</code>. However, this works only if all the <code>BaseDoc</code>s in the <code>AnyDocArray</code> have the same schema. Therefore only this works:</li></ul><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocList
+docs = DocList[ImageDoc]()</code></pre><ul><li>Methods like <code>.from_csv()</code> or <code>.pull()</code> only work with a parameterized <code>DocList</code>.</li></ul><h3 id="access-attributes-of-your-documentarray">Access attributes of your DocumentArray</h3><ul><li>In v1, you could access an attribute of all Documents in your DocumentArray by calling the plural of the attribute's name on your DocArray instance.</li><li>In v2, you don't have to use the plural; instead, use the Document's attribute name since <code>AnyDocArray</code> it will expose the same attributes as the <code>BaseDoc</code>s it contains. This will return a list of <code>type(attribute)</code>. However, this works only if all the <code>BaseDoc</code>s in the <code>AnyDocArray</code> have the same schema. Therefore only this works:</li></ul><pre><code class="language-python">from docarray import BaseDoc, DocList
 
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">Book</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
-    title: <span class="hljs-built_in">str</span>
-    author: <span class="hljs-built_in">str</span> = <span class="hljs-literal">None</span>
+class Book(BaseDoc):
+    title: str
+    author: str = None
 
 
-docs = DocList[Book]([Book(title=<span class="hljs-string">f'title <span class="hljs-subst">{i}</span>'</span>) <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">5</span>)])
-book_titles = docs.title  <span class="hljs-comment"># returns a list[str]</span>
+docs = DocList[Book]([Book(title=f'title {i}') for i in range(5)])
+book_titles = docs.title  # returns a list[str]
 
-<span class="hljs-comment"># this would fail</span>
-<span class="hljs-comment"># docs = DocList([Book(title=f'title {i}') for i in range(5)])</span>
-<span class="hljs-comment"># book_titles = docs.title</span></code></pre><h2 id="changes-to-document-store">Changes to Document Store</h2><p>In v2, the Document Store has been renamed <code><a href="https://docs.docarray.org/user_guide/storing/first_step/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">DocIndex</a></code> and can be used for fast retrieval using vector similarity. DocArray v2 <code>DocIndex</code> supports:</p><ul><li><a href="https://weaviate.io/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Weaviate</a></li><li><a href="https://qdrant.tech/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Qdrant</a></li><li><a href="https://www.elastic.co/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">ElasticSearch</a></li><li><a href="https://github.com/nmslib/hnswlib?ref=jina-ai-gmbh.ghost.io">HNSWLib</a></li></ul><p>Instead of creating a <code>DocumentArray</code> instance and setting the <code>storage</code> parameter to a vector database of your choice, in v2 you can initialize a <code>DocIndex</code> object of your choice, such as:</p><pre><code class="language-python hljs">db = HnswDocumentIndex[MyDoc](work_dir=<span class="hljs-string">'/my/work/dir'</span>)</code></pre><p>Furthermore, <a href="https://docs.docarray.org/user_guide/storing/first_step/?ref=jina-ai-gmbh.ghost.io#document-store" rel="nofollow"><code>DocStore</code></a> in v2 can be used for simple long-term storage, such as with AWS S3 buckets or Jina AI Cloud.</p><p>Thank you to all of the contributors to this release:</p><ul><li><a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a></li><li><a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a></li><li><a href="https://github.com/anna-charlotte?ref=jina-ai-gmbh.ghost.io">@anna-charlotte</a></li><li><a href="https://github.com/AnneYang720?ref=jina-ai-gmbh.ghost.io">@AnneYang720</a></li><li><a href="https://github.com/hsm207?ref=jina-ai-gmbh.ghost.io">@hsm207</a></li><li><a href="https://github.com/kacperlukawski?ref=jina-ai-gmbh.ghost.io">@kacperlukawski</a></li><li><a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a></li><li><a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a></li><li><a href="https://github.com/Jackmin801?ref=jina-ai-gmbh.ghost.io">@Jackmin801</a></li><li><a href="https://github.com/nan-wang?ref=jina-ai-gmbh.ghost.io">@nan-wang</a></li><li><a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a></li><li><a href="https://github.com/azayz?ref=jina-ai-gmbh.ghost.io">@azayz</a></li><li><a href="https://github.com/agaraman0?ref=jina-ai-gmbh.ghost.io">@agaraman0</a></li><li><a href="https://github.com/hrik2001?ref=jina-ai-gmbh.ghost.io">@hrik2001</a></li><li><a href="https://github.com/srini047?ref=jina-ai-gmbh.ghost.io">@srini047</a></li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-v2-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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\ No newline at end of file
+# this would fail
+# docs = DocList([Book(title=f'title {i}') for i in range(5)])
+# book_titles = docs.title</code></pre><h2 id="changes-to-document-store">Changes to Document Store</h2><p>In v2, the Document Store has been renamed <code><a href="https://docs.docarray.org/user_guide/storing/first_step/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">DocIndex</a></code> and can be used for fast retrieval using vector similarity. DocArray v2 <code>DocIndex</code> supports:</p><ul><li><a href="https://weaviate.io/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Weaviate</a></li><li><a href="https://qdrant.tech/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Qdrant</a></li><li><a href="https://www.elastic.co/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">ElasticSearch</a></li><li><a href="https://github.com/nmslib/hnswlib?ref=jina-ai-gmbh.ghost.io">HNSWLib</a></li></ul><p>Instead of creating a <code>DocumentArray</code> instance and setting the <code>storage</code> parameter to a vector database of your choice, in v2 you can initialize a <code>DocIndex</code> object of your choice, such as:</p><pre><code class="language-python">db = HnswDocumentIndex[MyDoc](work_dir='/my/work/dir')</code></pre><p>Furthermore, <a href="https://docs.docarray.org/user_guide/storing/first_step/?ref=jina-ai-gmbh.ghost.io#document-store" rel="nofollow"><code>DocStore</code></a> in v2 can be used for simple long-term storage, such as with AWS S3 buckets or Jina AI Cloud.</p><p>Thank you to all of the contributors to this release:</p><ul><li><a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a></li><li><a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a></li><li><a href="https://github.com/anna-charlotte?ref=jina-ai-gmbh.ghost.io">@anna-charlotte</a></li><li><a href="https://github.com/AnneYang720?ref=jina-ai-gmbh.ghost.io">@AnneYang720</a></li><li><a href="https://github.com/hsm207?ref=jina-ai-gmbh.ghost.io">@hsm207</a></li><li><a href="https://github.com/kacperlukawski?ref=jina-ai-gmbh.ghost.io">@kacperlukawski</a></li><li><a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a></li><li><a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a></li><li><a href="https://github.com/Jackmin801?ref=jina-ai-gmbh.ghost.io">@Jackmin801</a></li><li><a href="https://github.com/nan-wang?ref=jina-ai-gmbh.ghost.io">@nan-wang</a></li><li><a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a></li><li><a href="https://github.com/azayz?ref=jina-ai-gmbh.ghost.io">@azayz</a></li><li><a href="https://github.com/agaraman0?ref=jina-ai-gmbh.ghost.io">@agaraman0</a></li><li><a href="https://github.com/hrik2001?ref=jina-ai-gmbh.ghost.io">@hrik2001</a></li><li><a href="https://github.com/srini047?ref=jina-ai-gmbh.ghost.io">@srini047</a></li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdocarray-v2-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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diff --git a/news/donate-docarray-lf-for-inclusive-standard-multimodal-data-model/index.html b/news/donate-docarray-lf-for-inclusive-standard-multimodal-data-model/index.html
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>We're Donating DocArray to LF for an Inclusive and Standard Multimodal Data Model</title><meta charset="utf-8"><meta name="title" content="We're Donating DocArray to LF for an Inclusive and Standard Multimodal Data Model"><meta name="description" content="DocArray is now hosted under the Linux Foundation AI &amp; Data - a neutral home to build and support an open AI and data community. This is the start of a new day for DocArray."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/donate-docarray-lf-for-inclusive-standard-multimodal-data-model"><meta property="og:title" content="We're Donating DocArray to LF for an Inclusive and Standard Multimodal Data Model"><meta property="og:description" content="DocArray is now hosted under the Linux Foundation AI &amp; Data - a neutral home to build and support an open AI and data community. This is the start of a new day for DocArray."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--37-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/donate-docarray-lf-for-inclusive-standard-multimodal-data-model"><meta property="twitter:title" content="We're Donating DocArray to LF for an Inclusive and Standard Multimodal Data Model"><meta property="twitter:description" content="DocArray is now hosted under the Linux Foundation AI &amp; Data - a neutral home to build and support an open AI and data community. This is the start of a new day for DocArray."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--37-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">We're Donating DocArray to LF for an Inclusive and Standard Multimodal Data Model</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is now hosted under the Linux Foundation AI &amp; Data - a neutral home to build and support an open AI and data community. This is the start of a new day for DocArray.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 21, 2022 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>November is a big time for Jina AI. From this month, DocArray will be hosted under the Linux Foundation AI &amp; Data - a neutral home to build and support an open AI and data community. This is the start of a new day for DocArray.</p><p>In the ten months since DocArray's first release, we've seen more and more adoption and contributions from the open-source community. Today DocArray has over 150,000 downloads per month and powers hundreds of multimodal AI applications. At Jina AI, we're committed to delivering a powerful and easy-to-use tool for deep-learning engineers to represent, embed, search, store, and transfer multimodal data. But now we're sharing this commitment with you, our community and industry partners. Together with LF AI &amp; Data, we're bringing together companies and individual contributors to build <strong>a neutral, inclusive and common standard multimodal data model</strong>. By donating DocArray to LF AI, we're letting it spread its wings and fly.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - docarray/docarray: 🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store</div><div class="kg-bookmark-description">🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store - GitHub - docarray/docarray: 🧬 The data structure for unstructured multimodal data · Neural S...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/438303578/57aae8cb-5b20-4e35-a46c-9a742af1470c" alt=""></div></a><figcaption>The GitHub repository of DocArray is now moved from Jina AI to the DocArray organization owned by the Linux Foundation</figcaption></figure><div class="kg-card kg-toggle-card" data-kg-toggle-state="close"><div class="kg-toggle-heading"><h4 class="kg-toggle-heading-text">What does it mean to host a project at LF?</h4><button class="kg-toggle-card-icon"><svg id="Regular" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path class="cls-1" d="M23.25,7.311,12.53,18.03a.749.749,0,0,1-1.06,0L.75,7.311"></path></svg></button></div><div class="kg-toggle-content"><p>Hosting a project with the Linux Foundation follows <a href="https://github.com/opengovernance/opengovernance.dev?ref=jina-ai-gmbh.ghost.io" rel="noreferrer noopener">open governance</a>, meaning there is no one company or individual in control of a project. When maintainers of an open source project decide to host it at the Linux Foundation, they specifically transfer the project's trademark ownership to the Linux Foundation.</p></div></div><p>In this post we'll review the history of DocArray and unveil our future roadmap. In particular, we'll demonstrate some cool features that we're already developing and will roll out in an upcoming release.</p><h2 id="a-brief-history-of-docarray">A Brief History of DocArray</h2><p>We introduced the concept of "DocArray" in Jina 0.8 in late 2020. It was the <code>jina.types</code> module, intending to complete neural search design patterns by clarifying low-level data representation in Jina. Rather than working with Protobuf directly, the new <code>Document</code> class offered a simpler and safer high-level API <strong>to represent multimodal data</strong>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/blog-types-01.svg" class="kg-image" alt="" width="300" height="120"><figcaption>The green box labeled with `jina.types` in the right diagram is the first version of DocArray.</figcaption></figure><p>Over time, we extended <code>jina.types</code> and moved beyond a simple Pythonic interface of Protobuf. We added <code>DocumentArray</code> to ease batch operations on multiple <code>DocumentArray</code>s. Then we brought in IO and pre-processing functions for different data modalities, like text, image, video, audio, and 3D meshes. The <code>Executor</code> class started to use <code>DocumentArray</code> for input and output. In Jina 2.0 (released in mid 2021) the design became stronger still. Document, Executor and Flow became Jina's three fundamental concepts:</p><ul><li><strong>Document</strong> is the data IO in Jina</li><li><strong>Executor</strong> defines the logic of processing Documents</li><li><strong>Flow</strong> ties Executors together to accomplish a task.</li></ul><p>The community loved the new design, as it greatly improved developer experience by hiding unnecessary complexity. This let developers focus on the things that really matter.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-9.png" class="kg-image" alt="" width="2000" height="996" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-9.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-9.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-9.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/image-9.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>The new design since Jina 2.0, where `jina.types` served as the fundamental element of Jina for building a multimodal AI service.</figcaption></figure><p>As <code>jina.types</code> grew, it became conceptually independent from Jina. <code>jina.types</code> was more about building locally, while the rest of Jina focused on service-ization. Trying to achieve two very different targets in one codebase created maintenance hurdles: On the one hand, <code>jina.types</code> had to evolve fast and keep adding features to meet the needs of the rapidly-evolving AI community. On the other hand, Jina itself had to remain stable and robust as it served as infrastructure. The result? A slowdown in development.</p><p>We tackled this by decoupling <code>jina.types</code> from Jina in late 2021. This refactoring served as the foundation of the later DocArray. It was then that DocArray's mission crystallized for the team: to provide a data structure for AI engineers to easily represent, store, transmit and embed multimodal data. <strong>DocArray focuses on local developer experience, optimized for fast prototyping. Jina scales things up and uplifts prototypes into services in production. </strong>With that in mind, we released DocArray 0.1 in parallel with Jina 3.0 in early 2022, independently as a new open source project.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">We chose the name <strong>DocArray</strong> because we want to make something as fundamental and widely-used as NumPy's <strong>ndarray</strong>.</div></div><figure class="kg-card kg-embed-card kg-card-hascaption"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 859px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1480561866711650306&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdonate-docarray-lf-for-inclusive-standard-multimodal-data-model%2F&amp;sessionId=9f85cb2fd6c181214d23f37c70596c5892667da4&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1480561866711650306"></iframe></div>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">We're Donating DocArray to LF for an Inclusive and Standard Multimodal Data Model</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray is now hosted under the Linux Foundation AI &amp; Data - a neutral home to build and support an open AI and data community. This is the start of a new day for DocArray.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 21, 2022 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>November is a big time for Jina AI. From this month, DocArray will be hosted under the Linux Foundation AI &amp; Data - a neutral home to build and support an open AI and data community. This is the start of a new day for DocArray.</p><p>In the ten months since DocArray's first release, we've seen more and more adoption and contributions from the open-source community. Today DocArray has over 150,000 downloads per month and powers hundreds of multimodal AI applications. At Jina AI, we're committed to delivering a powerful and easy-to-use tool for deep-learning engineers to represent, embed, search, store, and transfer multimodal data. But now we're sharing this commitment with you, our community and industry partners. Together with LF AI &amp; Data, we're bringing together companies and individual contributors to build <strong>a neutral, inclusive and common standard multimodal data model</strong>. By donating DocArray to LF AI, we're letting it spread its wings and fly.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - docarray/docarray: 🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store</div><div class="kg-bookmark-description">🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store - GitHub - docarray/docarray: 🧬 The data structure for unstructured multimodal data · Neural S...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/438303578/57aae8cb-5b20-4e35-a46c-9a742af1470c" alt=""></div></a><figcaption>The GitHub repository of DocArray is now moved from Jina AI to the DocArray organization owned by the Linux Foundation</figcaption></figure><div class="kg-card kg-toggle-card" data-kg-toggle-state="close"><div class="kg-toggle-heading"><h4 class="kg-toggle-heading-text">What does it mean to host a project at LF?</h4><button class="kg-toggle-card-icon"><svg id="Regular" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path class="cls-1" d="M23.25,7.311,12.53,18.03a.749.749,0,0,1-1.06,0L.75,7.311"></path></svg></button></div><div class="kg-toggle-content"><p>Hosting a project with the Linux Foundation follows <a href="https://github.com/opengovernance/opengovernance.dev?ref=jina-ai-gmbh.ghost.io" rel="noreferrer noopener">open governance</a>, meaning there is no one company or individual in control of a project. When maintainers of an open source project decide to host it at the Linux Foundation, they specifically transfer the project's trademark ownership to the Linux Foundation.</p></div></div><p>In this post we'll review the history of DocArray and unveil our future roadmap. In particular, we'll demonstrate some cool features that we're already developing and will roll out in an upcoming release.</p><h2 id="a-brief-history-of-docarray">A Brief History of DocArray</h2><p>We introduced the concept of "DocArray" in Jina 0.8 in late 2020. It was the <code>jina.types</code> module, intending to complete neural search design patterns by clarifying low-level data representation in Jina. Rather than working with Protobuf directly, the new <code>Document</code> class offered a simpler and safer high-level API <strong>to represent multimodal data</strong>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/blog-types-01.svg" class="kg-image" alt="" width="300" height="120"><figcaption>The green box labeled with `jina.types` in the right diagram is the first version of DocArray.</figcaption></figure><p>Over time, we extended <code>jina.types</code> and moved beyond a simple Pythonic interface of Protobuf. We added <code>DocumentArray</code> to ease batch operations on multiple <code>DocumentArray</code>s. Then we brought in IO and pre-processing functions for different data modalities, like text, image, video, audio, and 3D meshes. The <code>Executor</code> class started to use <code>DocumentArray</code> for input and output. In Jina 2.0 (released in mid 2021) the design became stronger still. Document, Executor and Flow became Jina's three fundamental concepts:</p><ul><li><strong>Document</strong> is the data IO in Jina</li><li><strong>Executor</strong> defines the logic of processing Documents</li><li><strong>Flow</strong> ties Executors together to accomplish a task.</li></ul><p>The community loved the new design, as it greatly improved developer experience by hiding unnecessary complexity. This let developers focus on the things that really matter.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-9.png" class="kg-image" alt="" width="2000" height="996" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-9.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-9.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-9.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/image-9.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>The new design since Jina 2.0, where `jina.types` served as the fundamental element of Jina for building a multimodal AI service.</figcaption></figure><p>As <code>jina.types</code> grew, it became conceptually independent from Jina. <code>jina.types</code> was more about building locally, while the rest of Jina focused on service-ization. Trying to achieve two very different targets in one codebase created maintenance hurdles: On the one hand, <code>jina.types</code> had to evolve fast and keep adding features to meet the needs of the rapidly-evolving AI community. On the other hand, Jina itself had to remain stable and robust as it served as infrastructure. The result? A slowdown in development.</p><p>We tackled this by decoupling <code>jina.types</code> from Jina in late 2021. This refactoring served as the foundation of the later DocArray. It was then that DocArray's mission crystallized for the team: to provide a data structure for AI engineers to easily represent, store, transmit and embed multimodal data. <strong>DocArray focuses on local developer experience, optimized for fast prototyping. Jina scales things up and uplifts prototypes into services in production. </strong>With that in mind, we released DocArray 0.1 in parallel with Jina 3.0 in early 2022, independently as a new open source project.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">We chose the name <strong>DocArray</strong> because we want to make something as fundamental and widely-used as NumPy's <strong>ndarray</strong>.</div></div><figure class="kg-card kg-embed-card kg-card-hascaption"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 859px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1480561866711650306&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdonate-docarray-lf-for-inclusive-standard-multimodal-data-model%2F&amp;sessionId=653fac438373ea2760bec783e0852ec179b6ea6e&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1480561866711650306"></iframe></div>
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 <figcaption>The first release of DocArray receives quite a welcome from the community</figcaption></figure><p>Today, DocArray is the entrypoint of many multimodal AI applications, like the popular <a href="https://github.com/jina-ai/dalle-flow?ref=jina-ai-gmbh.ghost.io">DALLE-Flow</a> and <a href="https://github.com/jina-ai/discoart?ref=jina-ai-gmbh.ghost.io">DiscoArt</a>. We've introduced new and powerful features such as dataclass and document store to improve usability even more. DocArray has allied with open-source partners like Weaviate, Qdrant, Redis, Elasticsearch, FastAPI, pydantic and Jupyter for integration and most importantly for seeking a common standard. <a href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io">With the paradigm shift towards multimodal AI</a>, we see great potential for DocArray as a key player in this revolution.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/mesh_man_point_cloud_notebook.gif" class="kg-image" alt="" width="904" height="546" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/mesh_man_point_cloud_notebook.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/mesh_man_point_cloud_notebook.gif 904w" sizes="(min-width: 720px) 720px"><figcaption>In the DocArray 0.19 (released on Nov. 15), you can easily represent and process 3D mesh data.</figcaption></figure><h2 id="the-future-of-docarray">The Future of DocArray</h2><p>Donating DocArray to LF marks an important milestone where we share our commitment with the open source community openly, inclusively and constructively.</p><p>The next release of DocArray focuses on four tasks:</p><ul><li><strong>Representing: </strong>support Python idioms for representing complicated, nested multimodal data with ease.</li><li><strong>Embedding: </strong>provide smooth interfaces for mainstream deep learning models to embed data efficiently.</li><li><strong>Storing: </strong>support multiple vector databases for efficient persistence and approximate nearest neighbour retrieval.</li><li><strong>Transiting</strong>: allow fast (de)serialization and become a standard wire protocol on gRPC, HTTP and WebSockets.</li></ul><p>We invited two core maintainers of DocArray, Sami Jaghouar and Johannes Messner, to give you a taste of the next release.</p><h3 id="all-in-dataclass">All-in-Dataclass</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Modern-Business-personal-quote-with-a-photo-Instagram-Post--1580---1080-px---1-.png" class="kg-image" alt="" width="1580" height="1080" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Modern-Business-personal-quote-with-a-photo-Instagram-Post--1580---1080-px---1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Modern-Business-personal-quote-with-a-photo-Instagram-Post--1580---1080-px---1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Modern-Business-personal-quote-with-a-photo-Instagram-Post--1580---1080-px---1-.png 1580w" sizes="(min-width: 720px) 720px"></figure><p>In DocArray, dataclass is a high-level API for representing a multimodal document. It follows the design and idiom of the standard <a href="https://docs.python.org/3/library/dataclasses.html?ref=jina-ai-gmbh.ghost.io">Python dataclass</a>, letting users represent complicated multimodal documents intuitively and process them easily via DocArray's API. <strong>The new release makes dataclass a first class citizen and refactors its old implementation by using pydantic V2.</strong></p><p>Let's preview how to use the new dataclass. First, a Document is a pydantic model with a random ID and the Protobuf interface:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document</code></pre><p>To create your own multimodal data type you just need to subclass from <code>Document</code>:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document
 <span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> Tensor
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Don’t Build the Thing, Build the Thing that Builds the Thing!</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Dev-GPT is a tool that uses LLMs to build custom microservices, replacing the traditional software development process with AI. Just describe a service in natural language and a virtual development team will generate, debug, and deploy it for you.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Florian Hönicke, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 28, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="once-upon-a-time-in-the-future">Once upon a time, in the future</h2><p><em>An Introduction to Computer Programming class at Metaverse University. The holographic professor stands before the class in the formal uniform of IT engineers: A ratty AC/DC t-shirt and faded blue jeans, her hair frazzled and tangled in uncombed knots in the style customary among STEM professionals.</em></p><p><em>She begins her lecture.</em></p><p>“In olden times, a programmer’s day consisted of reading JIRA tickets and then going to <a href="https://stackoverflow.com/?ref=jina-ai-gmbh.ghost.io">Stack Overflow</a> to find code snippets that would do the job specified. This was considered highly skilled work, requiring considerable background knowledge and experience.”</p><p>“But in 2023, things changed. Primitive conversational AI began to seep into the job.”</p><p>“At first, it wasn’t much more than an error-prone personification of Stack Overflow and dozens of similar programmer forums. A programmer might routinely ask it: <em>I encountered the following error.”</em></p><p>“Then they would control-c/control-v some error message and ask: <em>How do I solve it?”</em></p><p>“The fundamental laziness at the heart of all skilled programming could never abide having to actually press two buttons at the same time and then mouse over to another application, moving data from one window to another, much less tolerate having to do all that typing. So before long, companies started building solutions like <a href="https://github.com/features/copilot?ref=jina-ai-gmbh.ghost.io">GitHub Copilot</a> to bind programmers’ development environments directly to the AI.”</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/holo.png" class="kg-image" alt="" width="1000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/holo.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/holo.png 1000w" sizes="(min-width: 720px) 720px"></figure><p>“This was fine for a while, but before long the programmer’s instinct for recursive self-reflection changed the paradigm: They no longer thought of these developments as tools for solving specific problems but as automated factories that generate solutions for whole classes of problems.”</p><p>“The focus of software development shifted from <em>building the thing we need</em>, to <em>building the thing that builds the thing we need</em>. The introduction of large language models moved software engineering to a higher level of abstraction.”</p><p>“The whole history of programming is a history of rising to higher levels of abstraction, letting software handle more and more of the details. As far back as the 1940s, assembly language abstracted from hand-coded 0’s and 1’s. Early programming languages abstracted from assembly language. Progressively higher-level languages took greater charge of the details that humans previously dealt with directly.”</p><p>“But AI did more than just move the programmer one level further up on the ladder of abstraction. It changed our entire understanding of the process of software development.”</p><h2 id="what-is-dev-gpt"><strong>What is Dev-GPT?</strong></h2><p><a href="https://github.com/jina-ai/dev-gpt?ref=jina-ai-gmbh.ghost.io">Jina AI’s Dev-GPT</a> is a tool that uses <a href="https://platform.openai.com/docs/models?ref=jina-ai-gmbh.ghost.io">OpenAI’s GPT-3.5-turbo or GPT-4</a> to build custom microservices, replacing the traditional software development process with AI automation. You can simply describe a service in natural language and a virtual development team will generate, debug, and deploy it for you.</p><p>To do this, Dev-GPT instantiates three AI agents:</p><ul><li><strong>Product Manager</strong>: The Product Manager interacts with you to clarify the requirements and make sure even the corner cases are well-defined.</li><li><strong>Developer</strong>: The refined requirements are then handed over to the Developer agent, which writes code to implement the microservice, writes test cases, and debugs the code until the tests pass.</li><li><strong>DevOps</strong>: Finally, the DevOps agent deploys the microservice and monitors it.</li></ul><p>Let’s look at a specific example. Run <code>dev-gpt generate</code> at the command prompt:</p><pre><code class="language-Text hljs">% dev-gpt generate   
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Dev-GPT is a tool that uses LLMs to build custom microservices, replacing the traditional software development process with AI. Just describe a service in natural language and a virtual development team will generate, debug, and deploy it for you.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Florian Hönicke, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 28, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="once-upon-a-time-in-the-future">Once upon a time, in the future</h2><p><em>An Introduction to Computer Programming class at Metaverse University. The holographic professor stands before the class in the formal uniform of IT engineers: A ratty AC/DC t-shirt and faded blue jeans, her hair frazzled and tangled in uncombed knots in the style customary among STEM professionals.</em></p><p><em>She begins her lecture.</em></p><p>“In olden times, a programmer’s day consisted of reading JIRA tickets and then going to <a href="https://stackoverflow.com/?ref=jina-ai-gmbh.ghost.io">Stack Overflow</a> to find code snippets that would do the job specified. This was considered highly skilled work, requiring considerable background knowledge and experience.”</p><p>“But in 2023, things changed. Primitive conversational AI began to seep into the job.”</p><p>“At first, it wasn’t much more than an error-prone personification of Stack Overflow and dozens of similar programmer forums. A programmer might routinely ask it: <em>I encountered the following error.”</em></p><p>“Then they would control-c/control-v some error message and ask: <em>How do I solve it?”</em></p><p>“The fundamental laziness at the heart of all skilled programming could never abide having to actually press two buttons at the same time and then mouse over to another application, moving data from one window to another, much less tolerate having to do all that typing. So before long, companies started building solutions like <a href="https://github.com/features/copilot?ref=jina-ai-gmbh.ghost.io">GitHub Copilot</a> to bind programmers’ development environments directly to the AI.”</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/holo.png" class="kg-image" alt="" width="1000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/holo.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/holo.png 1000w" sizes="(min-width: 720px) 720px"></figure><p>“This was fine for a while, but before long the programmer’s instinct for recursive self-reflection changed the paradigm: They no longer thought of these developments as tools for solving specific problems but as automated factories that generate solutions for whole classes of problems.”</p><p>“The focus of software development shifted from <em>building the thing we need</em>, to <em>building the thing that builds the thing we need</em>. The introduction of large language models moved software engineering to a higher level of abstraction.”</p><p>“The whole history of programming is a history of rising to higher levels of abstraction, letting software handle more and more of the details. As far back as the 1940s, assembly language abstracted from hand-coded 0’s and 1’s. Early programming languages abstracted from assembly language. Progressively higher-level languages took greater charge of the details that humans previously dealt with directly.”</p><p>“But AI did more than just move the programmer one level further up on the ladder of abstraction. It changed our entire understanding of the process of software development.”</p><h2 id="what-is-dev-gpt"><strong>What is Dev-GPT?</strong></h2><p><a href="https://github.com/jina-ai/dev-gpt?ref=jina-ai-gmbh.ghost.io">Jina AI’s Dev-GPT</a> is a tool that uses <a href="https://platform.openai.com/docs/models?ref=jina-ai-gmbh.ghost.io">OpenAI’s GPT-3.5-turbo or GPT-4</a> to build custom microservices, replacing the traditional software development process with AI automation. You can simply describe a service in natural language and a virtual development team will generate, debug, and deploy it for you.</p><p>To do this, Dev-GPT instantiates three AI agents:</p><ul><li><strong>Product Manager</strong>: The Product Manager interacts with you to clarify the requirements and make sure even the corner cases are well-defined.</li><li><strong>Developer</strong>: The refined requirements are then handed over to the Developer agent, which writes code to implement the microservice, writes test cases, and debugs the code until the tests pass.</li><li><strong>DevOps</strong>: Finally, the DevOps agent deploys the microservice and monitors it.</li></ul><p>Let’s look at a specific example. Run <code>dev-gpt generate</code> at the command prompt:</p><pre><code class="language-Text">% dev-gpt generate   
 👩‍💼👋 Hi, I'm Susana, a PM at Jina AI. Gathering the requirements
 for our engineers.
 👩‍💼❓ What should your microservice do?
-you:</code></pre><p>Susana, your AI project manager asks what you want to build.</p><p>So tell her in plain English:</p><pre><code class="language-Text hljs">you: Translate English to French
-</code></pre><p>And she answers:</p><pre><code class="language-Text hljs">I suggest that we implement the following microservice:
+you:</code></pre><p>Susana, your AI project manager asks what you want to build.</p><p>So tell her in plain English:</p><pre><code class="language-Text">you: Translate English to French
+</code></pre><p>And she answers:</p><pre><code class="language-Text">I suggest that we implement the following microservice:
 
 This microservice receives an input text in English and translates it to 
 French using gpt_3_5_turbo. The input parameters include the "input_text" 
@@ -24,7 +24,7 @@
 the microservice is the "translated_text", a string containing the translated 
 text in French.
 Do you agree? [y/n]
-</code></pre><p>This is your chance to clarify the specs with your project manager. When you are done:</p><pre><code class="language-Text hljs">👩‍💼 👍 Great, I will handover the following requirements to our engineers:
+</code></pre><p>This is your chance to clarify the specs with your project manager. When you are done:</p><pre><code class="language-Text">👩‍💼 👍 Great, I will handover the following requirements to our engineers:
 
 Microservice Description:
 
@@ -33,11 +33,11 @@
 which is a string containing the English text to be translated. The output of 
 the microservice is the "translated_text", a string containing the translated 
 text in French.
-</code></pre><p>Susana then passes this spec to the developers:</p><pre><code class="hljs language-css">Great! <span class="hljs-selector-tag">I</span> will hand this over <span class="hljs-selector-tag">to</span> the developers!
-</code></pre><p>The developers will:</p><ol><li>Generate microservice Python code.</li><li>Separately, generate test code from the spec.</li><li>Test the generated code using the test code, and debug if needed.</li></ol><p>If you add the <code>--verbose</code> flag to the command, you will see detailed log information about this process.</p><p>Finally, you are given a choice of DevOps:</p><pre><code class="hljs language-xml">You can now run or deploy your microservice:
-dev-gpt run --path <span class="hljs-tag">&lt;<span class="hljs-name">project</span> <span class="hljs-attr">path</span>&gt;</span>/microservice
-dev-gpt deploy --path <span class="hljs-tag">&lt;<span class="hljs-name">project</span> <span class="hljs-attr">path</span>&gt;</span>/microservice
-</code></pre><p>The first will run it locally (in a Docker if possible) and the second will deploy to <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a>, which requires <a href="https://docs.jina.ai/jina-ai-cloud/login/?ref=jina-ai-gmbh.ghost.io">an account and login</a>.</p><p>If you deploy to Jina AI Cloud, your virtual DevOps engineer will eventually respond with something like:</p><pre><code class="language-Text hljs">% dev-gpt deploy --path ./microservice
+</code></pre><p>Susana then passes this spec to the developers:</p><pre><code>Great! I will hand this over to the developers!
+</code></pre><p>The developers will:</p><ol><li>Generate microservice Python code.</li><li>Separately, generate test code from the spec.</li><li>Test the generated code using the test code, and debug if needed.</li></ol><p>If you add the <code>--verbose</code> flag to the command, you will see detailed log information about this process.</p><p>Finally, you are given a choice of DevOps:</p><pre><code>You can now run or deploy your microservice:
+dev-gpt run --path &lt;project path&gt;/microservice
+dev-gpt deploy --path &lt;project path&gt;/microservice
+</code></pre><p>The first will run it locally (in a Docker if possible) and the second will deploy to <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a>, which requires <a href="https://docs.jina.ai/jina-ai-cloud/login/?ref=jina-ai-gmbh.ghost.io">an account and login</a>.</p><p>If you deploy to Jina AI Cloud, your virtual DevOps engineer will eventually respond with something like:</p><pre><code class="language-Text">% dev-gpt deploy --path ./microservice
 Deploy a jina flow
 INFO     Successfully submitted flow with ID gptdeploy-c2ba13c314             
 INFO     Check the Flow deployment logs: https://cloud.jina.ai/ !
@@ -54,30 +54,30 @@
 and is available at https://gptdeploy-c2ba13c314.wolf.jina.ai/playground
 We open now the playground in your browser.
 
-waiting for app to be ready...</code></pre><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">These are example values and URIs. Pay attention to Dev-GPT’s screen output because your own values will be different.</div></div><p>You can then use this new microservice via a web interface:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Screenshot-2023-06-26-at-14.41.05.png" class="kg-image" alt="" width="1514" height="1228" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Screenshot-2023-06-26-at-14.41.05.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/Screenshot-2023-06-26-at-14.41.05.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Screenshot-2023-06-26-at-14.41.05.png 1514w" sizes="(min-width: 720px) 720px"></figure><p>Or interact directly with its REST endpoint:</p><pre><code class="language-bash hljs">% curl -X <span class="hljs-string">"POST"</span> <span class="hljs-string">"&lt;https://gptdeploy-c2ba13c314.wolf.jina.ai/post&gt;"</span> 
--H <span class="hljs-string">"accept: application/json"</span> -H <span class="hljs-string">"Content-Type: application/json"</span> 
--d <span class="hljs-string">'{"data": [{"text": "{\\"english_text\\": \\"This is not a pipe.\\"}"}]}'</span></code></pre><p>Which returns:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
-  <span class="hljs-attr">"header"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span> ... <span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-attr">"parameters"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span><span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-attr">"routes"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span> ... <span class="hljs-punctuation">]</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-attr">"data"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span>
-    <span class="hljs-punctuation">{</span>
-      <span class="hljs-attr">"id"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"5a51dfb440e83c532a1cc8f9df4518b7"</span><span class="hljs-punctuation">,</span>
-		  ... <span class="hljs-punctuation">,</span>
-      <span class="hljs-attr">"text"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"{\\"</span>french_text\\<span class="hljs-string">": \\"</span>Ce n'est pas une pipe.\\<span class="hljs-string">"}"</span><span class="hljs-punctuation">,</span>
+waiting for app to be ready...</code></pre><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">These are example values and URIs. Pay attention to Dev-GPT’s screen output because your own values will be different.</div></div><p>You can then use this new microservice via a web interface:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Screenshot-2023-06-26-at-14.41.05.png" class="kg-image" alt="" width="1514" height="1228" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Screenshot-2023-06-26-at-14.41.05.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/Screenshot-2023-06-26-at-14.41.05.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Screenshot-2023-06-26-at-14.41.05.png 1514w" sizes="(min-width: 720px) 720px"></figure><p>Or interact directly with its REST endpoint:</p><pre><code class="language-bash">% curl -X "POST" "&lt;https://gptdeploy-c2ba13c314.wolf.jina.ai/post&gt;" 
+-H "accept: application/json" -H "Content-Type: application/json" 
+-d '{"data": [{"text": "{\\"english_text\\": \\"This is not a pipe.\\"}"}]}'</code></pre><p>Which returns:</p><pre><code class="language-json">{
+  "header": { ... },
+  "parameters": {},
+  "routes": [ ... ],
+  "data": [
+    {
+      "id": "5a51dfb440e83c532a1cc8f9df4518b7",
+		  ... ,
+      "text": "{\\"french_text\\": \\"Ce n'est pas une pipe.\\"}",
        ... 
-    <span class="hljs-punctuation">}</span>
-  <span class="hljs-punctuation">]</span>
-<span class="hljs-punctuation">}</span>
-</code></pre><p>Try it out yourself at <a href="https://gptdeploy-c2ba13c314.wolf.jina.ai/playground?ref=jina-ai-gmbh.ghost.io">https://gptdeploy-c2ba13c314.wolf.jina.ai/playground</a>.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">This service is available as of 28 June 2023. It won't stay online for very long, so if you are reading this long after publication, the URL may not work.</div></div><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled-4.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Untitled-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/Untitled-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled-4.png 1024w" sizes="(min-width: 720px) 720px"></figure><h2 id="why-build-the-thing-that-builds-the-thing">Why build <strong>the thing that builds the thing?</strong></h2><p>Why does this represent the future of software development?</p><p>The way Dev-GPT uses AI models in programming signals a change of paradigm for software developers. It is a major break from traditional, labor-intensive coding processes. Instead, Dev-GPT deploys the power of the latest large language models to ensure that the microservices generated are robust and efficient.</p><p>An AI-driven approach has a lot of benefits over traditional software development:</p><h3 id="cost"><strong>Cost</strong></h3><p>With Dev-GPT, the development cost for a microservice can be as low as 4 to 20 cents, depending on the AI model, the number of calls to it, and the cost per call. This makes possible the development of large numbers of diverse microservices for a fraction of the cost of hiring a team to develop even one.</p><h3 id="speed">Speed</h3><p>Building the "thing that builds the thing" also saves time. Rather than spending hours to weeks writing, testing, and debugging code, Dev-GPT generates microservices in minutes. Companies can bring new services online quickly in response to new needs and market changes.</p><h3 id="simplicity"><strong>Simplicity</strong></h3><p>Dev-GPT simplifies development by taking care of everything from conception to deployment. No more tickets and scrums!</p><h3 id="promoting-creativity"><strong>Promoting creativity</strong></h3><p>Dev-GPT frees engineering staff and technical managers to focus on more complex, strategic questions that demand creativity. Removing the grunt work from the development process moves the focus from <em>getting things done</em> to <em>what can and should be done?</em> &nbsp;It creates greater space for imagination and innovation.</p><h2 id="examples"><strong>Examples</strong></h2><p>It is up to you to decide what you want to build. You can let your creativity run free. Here are some examples to inspire you and give you a feeling of what is possible:</p><h3 id="rainbow-tweet-%F0%9F%8C%88"><strong>Rainbow Tweet 🌈</strong></h3><p>Do you know someone who gets irrationally angry about pineapple on pizza?</p><p>Are you sick of vitriolic Internet debates over minutiae?</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Someone-is-wrong-on-internet.png" class="kg-image" alt="" width="500" height="550"><figcaption>“Duty Calls” - <a href="https://xkcd.com/386/?ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">https://xkcd.com/386/</a></figcaption></figure><p>Do you just not care what angry little pearl of wisdom has made someone the main character on Twitter this week?</p><p>That’s why I used Dev-GPT to build <a href="https://chrome.google.com/webstore/detail/rainbow-tweet/ckjindkmeaoifikfdcjlffmaajjfbddh?ref=jina-ai-gmbh.ghost.io">Rainbow Tweet</a>. It's a Chrome extension that turns negative speech into fluffy rainbow speech, showing how easy it is to bring creative applications to life using <a href="https://github.com/jina-ai/dev-gpt?ref=jina-ai-gmbh.ghost.io">Dev-GPT</a>.</p><p>Here is the prompt I used to create the backend for the plugin:</p><pre><code class="language-Text hljs">Input is a tweet that contains passive-aggressive language. The output is the 
-positive version of that tweet.</code></pre><p>And here is the result:</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/rainbow-tweet-yannic-music.mp4" poster="https://img.spacergif.org/v1/1920x1080/0a/spacer.png" width="1920" height="1080" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/06/media-thumbnail-ember684.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h3 id="chemical-structure-diagram">Chemical Structure Diagram</h3><pre><code class="language-bash hljs">dev-gpt generate \\
---description <span class="hljs-string">"Convert a chemical formula into a 2D chemical structure diagram. Example inputs: C=C, CN=C=O, CCC(=O)O"</span> \\
+    }
+  ]
+}
+</code></pre><p>Try it out yourself at <a href="https://gptdeploy-c2ba13c314.wolf.jina.ai/playground?ref=jina-ai-gmbh.ghost.io">https://gptdeploy-c2ba13c314.wolf.jina.ai/playground</a>.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">This service is available as of 28 June 2023. It won't stay online for very long, so if you are reading this long after publication, the URL may not work.</div></div><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled-4.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Untitled-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/Untitled-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled-4.png 1024w" sizes="(min-width: 720px) 720px"></figure><h2 id="why-build-the-thing-that-builds-the-thing">Why build <strong>the thing that builds the thing?</strong></h2><p>Why does this represent the future of software development?</p><p>The way Dev-GPT uses AI models in programming signals a change of paradigm for software developers. It is a major break from traditional, labor-intensive coding processes. Instead, Dev-GPT deploys the power of the latest large language models to ensure that the microservices generated are robust and efficient.</p><p>An AI-driven approach has a lot of benefits over traditional software development:</p><h3 id="cost"><strong>Cost</strong></h3><p>With Dev-GPT, the development cost for a microservice can be as low as 4 to 20 cents, depending on the AI model, the number of calls to it, and the cost per call. This makes possible the development of large numbers of diverse microservices for a fraction of the cost of hiring a team to develop even one.</p><h3 id="speed">Speed</h3><p>Building the "thing that builds the thing" also saves time. Rather than spending hours to weeks writing, testing, and debugging code, Dev-GPT generates microservices in minutes. Companies can bring new services online quickly in response to new needs and market changes.</p><h3 id="simplicity"><strong>Simplicity</strong></h3><p>Dev-GPT simplifies development by taking care of everything from conception to deployment. No more tickets and scrums!</p><h3 id="promoting-creativity"><strong>Promoting creativity</strong></h3><p>Dev-GPT frees engineering staff and technical managers to focus on more complex, strategic questions that demand creativity. Removing the grunt work from the development process moves the focus from <em>getting things done</em> to <em>what can and should be done?</em> &nbsp;It creates greater space for imagination and innovation.</p><h2 id="examples"><strong>Examples</strong></h2><p>It is up to you to decide what you want to build. You can let your creativity run free. Here are some examples to inspire you and give you a feeling of what is possible:</p><h3 id="rainbow-tweet-%F0%9F%8C%88"><strong>Rainbow Tweet 🌈</strong></h3><p>Do you know someone who gets irrationally angry about pineapple on pizza?</p><p>Are you sick of vitriolic Internet debates over minutiae?</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Someone-is-wrong-on-internet.png" class="kg-image" alt="" width="500" height="550"><figcaption>“Duty Calls” - <a href="https://xkcd.com/386/?ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">https://xkcd.com/386/</a></figcaption></figure><p>Do you just not care what angry little pearl of wisdom has made someone the main character on Twitter this week?</p><p>That’s why I used Dev-GPT to build <a href="https://chrome.google.com/webstore/detail/rainbow-tweet/ckjindkmeaoifikfdcjlffmaajjfbddh?ref=jina-ai-gmbh.ghost.io">Rainbow Tweet</a>. It's a Chrome extension that turns negative speech into fluffy rainbow speech, showing how easy it is to bring creative applications to life using <a href="https://github.com/jina-ai/dev-gpt?ref=jina-ai-gmbh.ghost.io">Dev-GPT</a>.</p><p>Here is the prompt I used to create the backend for the plugin:</p><pre><code class="language-Text">Input is a tweet that contains passive-aggressive language. The output is the 
+positive version of that tweet.</code></pre><p>And here is the result:</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/rainbow-tweet-yannic-music.mp4" poster="https://img.spacergif.org/v1/1920x1080/0a/spacer.png" width="1920" height="1080" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/06/media-thumbnail-ember684.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h3 id="chemical-structure-diagram">Chemical Structure Diagram</h3><pre><code class="language-bash">dev-gpt generate \\
+--description "Convert a chemical formula into a 2D chemical structure diagram. Example inputs: C=C, CN=C=O, CCC(=O)O" \\
+--model gpt-4
+</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--2-.png" class="kg-image" alt="" width="654" height="826" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Untitled--2-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--2-.png 654w"></figure><h3 id="word-cloud-generator">Word Cloud Generator</h3><pre><code class="language-bash">dev-gpt generate \\
+--description "Generate a word cloud from a given text" \\
 --model gpt-4
-</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--2-.png" class="kg-image" alt="" width="654" height="826" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Untitled--2-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--2-.png 654w"></figure><h3 id="word-cloud-generator">Word Cloud Generator</h3><pre><code class="language-bash hljs">dev-gpt generate \\
---description <span class="hljs-string">"Generate a word cloud from a given text"</span> \\
+</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--3-.png" class="kg-image" alt="Untitled" width="732" height="951" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Untitled--3-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--3-.png 732w" sizes="(min-width: 720px) 720px"></figure><hr><h3 id="audio-to-mel-spectrogram">Audio to Mel Spectrogram</h3><p>Mel spectrograms are frequency spectrograms that use the <a href="https://en.wikipedia.org/wiki/Mel_scale?ref=jina-ai-gmbh.ghost.io">mel scale</a>.</p><pre><code>dev-gpt generate \\
+--description "Create mel spectrogram from audio file. Example: &lt;https://cdn.pixabay.com/download/audio/2023/02/28/audio_550d815fa5.mp3&gt;" \\
 --model gpt-4
-</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--3-.png" class="kg-image" alt="Untitled" width="732" height="951" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Untitled--3-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--3-.png 732w" sizes="(min-width: 720px) 720px"></figure><hr><h3 id="audio-to-mel-spectrogram">Audio to Mel Spectrogram</h3><p>Mel spectrograms are frequency spectrograms that use the <a href="https://en.wikipedia.org/wiki/Mel_scale?ref=jina-ai-gmbh.ghost.io">mel scale</a>.</p><pre><code class="hljs language-lua">dev-gpt generate \\
-<span class="hljs-comment">--description "Create mel spectrogram from audio file. Example: &lt;https://cdn.pixabay.com/download/audio/2023/02/28/audio_550d815fa5.mp3&gt;" \\</span>
-<span class="hljs-comment">--model gpt-4</span>
-</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--4-.png" class="kg-image" alt="Untitled" width="732" height="663" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Untitled--4-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--4-.png 732w" sizes="(min-width: 720px) 720px"></figure><h2 id="back-to-the-future">Back to the Future</h2><p><em>The professor wraps up her Introduction to Computer Programming class at Metaverse University. Much of the class is visibly paying her no attention.</em></p><p>“In the aftermath of Dev-GPT and its descendants, programming became increasingly a question of nudging and cajoling large language models to correctly understand the desired outcome. This why today most of you, the programmers of tomorrow, have come to this field with previous experience as physical trainers, coaches for sports teams, theatre directors, and elementary school teachers. Your capacity to get stubborn people to do things transfers to getting AI models to do them.”</p><p><em>She looks over the class, knowing only half of them were listening at best, and then dismisses them with a gesture before her hologram flickers away, momentarily replaced by a stylized image of birds carrying a whale before disappearing entirely.</em></p><h2 id="get-started-with-dev-gpt">Get started with Dev-GPT</h2><p>To get started with Dev-GPT, just install the package:</p><pre><code class="language-bash hljs">pip install dev-gpt</code></pre><p>Then start generating:</p><pre><code class="language-bash hljs">dev-gpt generate --description <span class="hljs-string">"&lt;description of the microservice&gt;"</span>
-</code></pre><p>And get in touch with the Dev-GPT community on <a href="https://discord.gg/nfQyTbUsh7?ref=jina-ai-gmbh.ghost.io">Discord</a>.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://discord.com/channels/1106542220112302130/1106544097637957702?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Dev-GPT on the Jina AI Discord</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdont-build-the-thing-build-the-thing-that-builds-the-thing%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--4-.png" class="kg-image" alt="Untitled" width="732" height="663" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Untitled--4-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--4-.png 732w" sizes="(min-width: 720px) 720px"></figure><h2 id="back-to-the-future">Back to the Future</h2><p><em>The professor wraps up her Introduction to Computer Programming class at Metaverse University. Much of the class is visibly paying her no attention.</em></p><p>“In the aftermath of Dev-GPT and its descendants, programming became increasingly a question of nudging and cajoling large language models to correctly understand the desired outcome. This why today most of you, the programmers of tomorrow, have come to this field with previous experience as physical trainers, coaches for sports teams, theatre directors, and elementary school teachers. Your capacity to get stubborn people to do things transfers to getting AI models to do them.”</p><p><em>She looks over the class, knowing only half of them were listening at best, and then dismisses them with a gesture before her hologram flickers away, momentarily replaced by a stylized image of birds carrying a whale before disappearing entirely.</em></p><h2 id="get-started-with-dev-gpt">Get started with Dev-GPT</h2><p>To get started with Dev-GPT, just install the package:</p><pre><code class="language-bash">pip install dev-gpt</code></pre><p>Then start generating:</p><pre><code class="language-bash">dev-gpt generate --description "&lt;description of the microservice&gt;"
+</code></pre><p>And get in touch with the Dev-GPT community on <a href="https://discord.gg/nfQyTbUsh7?ref=jina-ai-gmbh.ghost.io">Discord</a>.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://discord.com/channels/1106542220112302130/1106544097637957702?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Dev-GPT on the Jina AI Discord</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fdont-build-the-thing-build-the-thing-that-builds-the-thing%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
diff --git a/news/embeddings-in-depth/index.html b/news/embeddings-in-depth/index.html
index 756b3c5e908..286652352d4 100644
--- a/news/embeddings-in-depth/index.html
+++ b/news/embeddings-in-depth/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Embeddings in Depth</title><meta charset="utf-8"><meta name="title" content="Embeddings in Depth"><meta name="description" content="This second article in our series on embedding technology is much more concrete. It explains where embeddings come from and how they are used."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/embeddings-in-depth"><meta property="og:title" content="Embeddings in Depth"><meta property="og:description" content="This second article in our series on embedding technology is much more concrete. It explains where embeddings come from and how they are used."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--18--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/embeddings-in-depth"><meta property="twitter:title" content="Embeddings in Depth"><meta property="twitter:description" content="This second article in our series on embedding technology is much more concrete. It explains where embeddings come from and how they are used."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--18--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Embeddings in Depth</title><meta charset="utf-8"><meta name="title" content="Embeddings in Depth"><meta name="description" content="This second article in our series on embedding technology is much more concrete. It explains where embeddings come from and how they are used."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/embeddings-in-depth"><meta property="og:title" content="Embeddings in Depth"><meta property="og:description" content="This second article in our series on embedding technology is much more concrete. It explains where embeddings come from and how they are used."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--18--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/embeddings-in-depth"><meta property="twitter:title" content="Embeddings in Depth"><meta property="twitter:description" content="This second article in our series on embedding technology is much more concrete. It explains where embeddings come from and how they are used."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--18--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><script src="https://jina-ai-gmbh.ghost.io/public/cards.min.js" async=""></script><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Embeddings in Depth</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">This second article in our series on embedding technology is much more concrete. It explains where embeddings come from and how they are used.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 15, 2023 • 17 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>This article is the second in our series on embedding technology. In the <a href="https://jina.ai/news/how-embeddings-drive-ai-a-guide/?ref=jina-ai-gmbh.ghost.io">previous article, we discussed</a> embeddings in very abstract terms, but this one will be much more concrete. It explains where embeddings come from and how they are used.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text"><b><strong style="white-space: pre-wrap;">Trigger Warning:</strong></b> This article contains some light algebra, and although it tries to avoid complicated math, there are some notational conventions from vector algebra.</div></div><p>An <em>embedding</em> is a <em>mapping</em> of objects to <em>vectors</em>. Those objects may be real things or digital objects like images and files.</p><p>For example, imagine a robot that harvests tomatoes:</p><figure class="kg-card kg-embed-card"><iframe width="200" height="113" src="https://www.youtube.com/embed/JsZJWyMVBtY?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen="" title="This Tomato-Picking Robot Is the Future of Farming 🍅 🤖"></iframe></figure><p>This robot selects tomatoes on the vine that are ready to harvest, and then snips their stalks and takes them away. Recognizing which tomatoes are ripe is a good application of image embeddings. Each tomato on the vine is assigned a representative vector based on digital images taken by the robot’s cameras. It then uses these embeddings to decide whether or not to harvest a particular tomato.</p><p>Similarly, we might use embeddings to study and predict customer behavior. These embedding vectors stand in for a person — a real human being who presumably exists somewhere — but we construct their embedding vectors from digital information about that person. For a study of consumer buying behavior, this is likely to be some combination of demographic information and purchasing records.</p><p>In the previous article, we discussed how vectors are just ordered lists of numbers that we decide to interpret as points in a high-dimensional space. Data stored in a computer is also just an ordered list of numbers. Embeddings are, therefore, made by translating input vectors in one vector space — the one that contains the source data — into vectors in a different space called the <strong><em>embedding space</em></strong>.</p><p>But not just any mapping between vector spaces is an embedding. The translation into embeddings is purposeful. The placement of embedding vectors relative to each other should be informative in some way about the objects they represent.</p><h2 id="cosines-how-we-compare-embeddings">Cosines: How We Compare Embeddings</h2><p>When we use embeddings in applications, the thing we most often do is compare two embeddings and calculate how close or far apart they are. This is indicative of the similarity or dissimilarity of the objects those embeddings stand in for with respect to some set of properties.</p><p>To do this, we use a metric called the <strong>cosine</strong>. This section explains cosines and how we calculate them in high-dimensional vector spaces.</p><p>An embedding is a vector, and as we showed in the previous section, we can interpret a vector as a point in a multi-dimensional space. However, it also has an interpretation as a direction and magnitude. Traditionally, we visualize this interpretation with an arrow:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-19.png" class="kg-image" alt="" width="1350" height="1560" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-19.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-19.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-19.png 1350w" sizes="(min-width: 720px) 720px"></figure><p>The <em>direction</em> of this three-dimensional vector is specified by the $(x,y,z)$ coordinates, and the <em>magnitude</em> is just the length of the vector, i.e., the distance from the coordinate $(x,y,z)$ to the origin at $(0,0,0)$. The length is calculated using a multidimensional extension of <a href="https://en.wikipedia.org/wiki/Pythagorean_theorem?ref=jina-ai-gmbh.ghost.io">Pythagoras' theorem</a>:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-20.png" class="kg-image" alt="" width="1500" height="300" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-20.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-20.png 1500w" sizes="(min-width: 720px) 720px"></figure><p>The double bars around a vector $\|\vec{v}\|$ indicate the vector's <em>length</em> (or <em>magnitude</em>).</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Although this example uses only three dimensions, all these formulas apply exactly the same to arbitrarily large vectors of any number of dimensions.</div></div><p>We can see that different vectors can have the same direction but different lengths. For example, if we have the vectors $(4,2)$ and $(2,1)$, they have different lengths ($\sqrt{20} \approx 4.47$ and $\sqrt{5} \approx 2.23$ respectively) but they point in the same direction.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-21.png" class="kg-image" alt="" width="2000" height="938" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-21.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/11/image-21.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>How do we know they point in the same direction? We measure the angle between the two vectors. If the angle is zero, they point in the same direction.</p><p>To show how this works, let’s consider two vectors: $\vec{a}=(3,2,5)$ and $\vec{b}=(4,5,2)$:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-52.png" class="kg-image" alt="" width="2000" height="1140" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-52.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-52.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-52.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-52.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>To calculate the angle, we have a formula that scales up to any number of dimensions: The cosine.</p><p>The cosine of the angle&nbsp;$\theta$&nbsp;between vectors&nbsp;$\vec{a}$&nbsp;and&nbsp;$\vec{b}$&nbsp;is:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-50.png" class="kg-image" alt="" width="2000" height="208" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-50.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-50.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-50.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-50.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>The numerator of this fraction, $a⋅b$,&nbsp;is the&nbsp;<em>dot product</em>&nbsp;of the two vectors, and it’s easy to calculate:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-49.png" class="kg-image" alt="" width="2000" height="288" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-49.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-49.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-49.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-49.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>As for&nbsp;‖<em>a</em>‖&nbsp;and&nbsp;‖<em>b</em>‖, those are the lengths of the two vectors: $\|\vec{a}\| = \sqrt{38} \approx 6.164$ and $\vec{b} = \sqrt{45} \approx 6.708$. Therefore, to calculate&nbsp;$cosθ$:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-22.png" class="kg-image" alt="" width="1550" height="587" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-22.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-22.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-22.png 1550w" sizes="(min-width: 720px) 720px"></figure><p>This cosine corresponds to an angle of approximately 39.3 degrees, but in machine learning, we typically stop once we’ve calculated the cosine because if all the numbers in both vectors are greater than zero, then the cosine of the angle will be between 0 and 1. A cosine of 1 means the angle between two vectors is 0 degrees, i.e., the vectors have the same direction (although they may have different lengths). A cosine of 0 means they have an angle of 90 degrees. i.e., they are <em>perpendicular</em> or <em>orthogonal</em>.</p><p>So let’s compare $\vec{a}=(4,2)$&nbsp;and&nbsp;$\vec{b}=(2,1)$:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-23.png" class="kg-image" alt="" width="1550" height="1184" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-23.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-23.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-23.png 1550w" sizes="(min-width: 720px) 720px"></figure><p>When the cosine of two vectors is one, they point in the same direction, even though they may have different lengths.</p><p>Another way to do the same operation is to take each vector and <em>normalize</em> it. Normalizing a vector means creating a new vector that points in the same direction but has a length of exactly 1. If two vectors point in the same direction, they will normalize to identical vectors.</p><p>To normalize a vector, divide it in each dimension by the vector’s length. If $\vec{v} = (3,2,5)$ and $\hat{v} = norm(\vec{v})$ then:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-24.png" class="kg-image" alt="" width="1550" height="1232" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-24.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-24.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-24.png 1550w" sizes="(min-width: 720px) 720px"></figure><p>If two vectors $\vec{a}$ and $\vec{b}$ have an angle between them $\theta$, then their normalized forms $\hat{a}$ and $\hat{b}$ will have the same angle $\theta$ between them. Cosine is a measure that is indifferent to the magnitudes of vectors.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">When we compare embeddings to decide how near or far they are from each other, we almost always use cosines.</div></div><p>The reason for this is that the magnitudes of embedding vectors are not usually informative about anything. Most neural network architectures perform normalizations between some or all of their layers, rendering the magnitudes of embedding vectors typically useless.</p><h2 id="neural-networks-as-vector-mappings">Neural Networks As Vector Mappings</h2><p>Embedding vectors work because they are placed so that things that have common properties have cosines that are closer to 1, and those that do not have cosines closer to 0. An embedding model takes input vectors and translates them into embedding vectors.</p><p>Although there are many techniques for performing such translations, today, embedding models are exclusively neural networks.</p><p>A neural network is a sequence of vector transformations. In formal mathematical terms, for each layer of the network, we multiply the vector output of the previous layer by a matrix, and then generally add a <em>bias.</em> A <em>bias</em> is a set of values that we add or subtract from the resulting vector. We take the result and make that the input to the next layer of the network.</p><p>More formally, the values of the $m$th layer of the network are $\vec{m}$ and are transformed into the values of the $n$th layer ($\vec{n}$) by:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-25.png" class="kg-image" alt="" width="2000" height="325" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-25.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-25.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-25.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-25.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>Where $\textbf{W}$ is a matrix and $\vec{bias}$ is the vector of bias values.</p><p>It’s customary to think of it as a network of “nodes” bearing numerical values, connected by “weights”. This is truer to the roots of neural network theory but is exactly equivalent to multiplying a vector by a matrix.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-38.png" class="kg-image" alt="" width="650" height="1100" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-38.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-38.png 650w"></figure><p>If we have a vector $\vec{m} = (m_1,m_2m_3)$, this one neural network layer transforms it into a vector $\vec{n} = (n_1,n_2,n_3,n_4,n_5)$. It does that by multiplying the values in $\vec{m}$ by a set of weights (also called <em>parameters</em>), then adding them up, and adding the bias vector $\vec{bias} = (bias_1,bias_2,bias_3,bias_4,bias_5)$</p><p>Each line between nodes in the diagram above is one weight. If we designate the weight from $m_1$ to $n_1$ as $w_{11}$, from $m_2$ to $n_3$ as $w_{23}$, etc., then:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-26.png" class="kg-image" alt="" width="2000" height="600" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-26.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-26.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-26.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>In matrix algebra notation, this is the same as multiplying the 3-dimensional vector $\vec{n}$ by a $3x5$ matrix to get $\vec{m}$:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-27.png" class="kg-image" alt="" width="2000" height="472" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-27.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-27.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-27.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/11/image-27.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>Neural networks have multiple layers, so the output of this matrix multiplication is multiplied by another matrix and then another, typically with some kind of thresholding or normalization between multiplications and sometimes other tricks. The most common way of doing this today is to apply the <strong>ReLU</strong> (<a href="https://en.wikipedia.org/wiki/Rectifier_(neural_networks)?ref=jina-ai-gmbh.ghost.io">rectified linear activation unit</a>) activation function. If the value of any node is below zero, it’s replaced with a zero, and otherwise, left unchanged.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-28.png" class="kg-image" alt="" width="520" height="198"></figure><p>Otherwise, a neural network is just a series of transformations like the one above from $\vec{m}$ to $\vec{n}$.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-40.png" class="kg-image" alt="" width="2000" height="261" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-40.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-40.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-40.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-40.png 2300w" sizes="(min-width: 720px) 720px"></figure><p>This structure has some important properties. The most important is that:</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">In theory, any kind of vector transformation is possible with enough layers. Any problem that can be expressed as a mapping from a vector space $\vec{x} \in \textit{A}$ to vectors in another vector space $\vec{y} \in \textit{B}$ has some solution that looks just like a neural network.</div></div><p>It may be impractical to construct a large enough network for a given problem, and there may be no procedure for correctly calculating the weights. AI models are not guaranteed in advance to be able to learn or perform any task at all.</p><p>What happens in practice is that neural networks <strong><em>approximate</em></strong> a solution by learning from examples. How good a solution that approximation is depends on a lot of factors and can’t typically be known in advance of training a model.</p><p>There is an aphorism attributed to the British statistician George Box:</p><div class="kg-card kg-callout-card kg-callout-card-white"><div class="kg-callout-text"><i><em class="italic" style="white-space: pre-wrap;">All models are wrong, but some are useful.</em></i></div></div><p>Neural networks can be very good approximations, but they are still approximations, and it’s not possible to know for certain how good they are at something until you put them into production. The real measure of an AI model is its usefulness, and that’s hard to know in advance.</p><h2 id="turning-problems-into-vector-mappings">Turning Problems Into Vector Mappings</h2><p>Defining neural networks as mappings from one vector space to another sounds very limiting. We don’t naturally see the kinds of things we want AI models to do in those terms.</p><p>However, many of the most visible developments in recent AI are really just ways of using vector-to-vector mappings in clever ways. Large language models like ChatGPT translate input texts, rendered as vectors, into vectors that designate a single word. They write texts by adding the single-word output to the end of the input and then running again to get the next word.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-42.png" class="kg-image" alt="" width="2000" height="2000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-42.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-42.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-42.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/11/image-42.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>It may take some creativity and engineering to find a way to express some task as a vector mapping, but as recent developments show, it is surprisingly often possible.</p><h2 id="where-do-embeddings-fit-in">Where Do Embeddings Fit In?</h2><p>When you train an AI model, you do it with some goal in mind. In the typical scenario, you have training data that consists of inputs and matching correct outputs. For example, let’s say you want to classify tweets by their emotional content. This is a common benchmarking task used to evaluate text AI models.</p><p>One widely used dataset (<a href="https://github.com/dair-ai/emotion_dataset?ref=jina-ai-gmbh.ghost.io">DAIR.AI Emotion</a>) sorts tweets into eight emotional categories:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-58.png" class="kg-image" alt="" width="740" height="420" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-58.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-58.png 740w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-55.png" class="kg-image" alt="" width="1500" height="1106" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-55.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-55.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-55.png 1500w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Number of tweets per emotion category in the </span><a href="http://dair.ai/?ref=jina-ai-gmbh.ghost.io"><span style="white-space: pre-wrap;">DAIR.AI</span></a><span style="white-space: pre-wrap;"> Emotion dataset</span></figcaption></figure><p>To train a model to do this task, you need to decide two things:</p><ol><li>How to map the output category labels to vectors.</li><li>How to map the input texts to vectors</li></ol><p>The easiest way to encode these emotion labels is to create six-dimensional vectors where each value corresponds to one category. For example, if we make a list of emotions, like the one above, “anger” is the third in the list. So if a tweet has angry content, we train the network to output a six-dimensional vector with zero values everywhere except the third item in it, which is set to one:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-30.png" class="kg-image" alt="" width="589" height="81"></figure><p>This approach is called <em>zero-hot encoding</em> among AI engineers.</p><p>We also have to encode the tweets as vectors. There is more than one way to do this, but most text-processing models follow broadly the same pattern:</p><p>First, input texts are split into <em>tokens</em>, which you can understand as something like splitting it into words. The exact mechanisms vary somewhat, but the procedure broadly follows the following steps:</p><ol><li>Normalize the case, i.e., make everything lowercase.</li><li>Split a text on punctuation and spaces.</li><li>Look up each resulting subsegment of text in a dictionary (which is a part of the AI model bundle) and accept it if it is in the dictionary.</li><li>For segments not in the dictionary, split them into the smallest number of parts that are in the dictionary, and then accept those segments.</li></ol><p>So, for example, let’s say we wanted an embedding for this famous line from <em>Alice in Wonderland</em>:</p><div class="kg-card kg-callout-card kg-callout-card-white"><div class="kg-callout-text"><i><em class="italic" style="white-space: pre-wrap;">Why, sometimes I've believed as many as six impossible things before breakfast.</em></i></div></div><p>Jina Embeddings’ text tokenizer will split it up into 18 tokens like this:</p><pre><code class="hljs language-swift">[<span class="hljs-type">CLS</span>] why , sometimes i ' ve believed <span class="hljs-keyword">as</span> many <span class="hljs-keyword">as</span> six impossible 
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Embeddings in Depth</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">This second article in our series on embedding technology is much more concrete. It explains where embeddings come from and how they are used.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 15, 2023 • 17 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>This article is the second in our series on embedding technology. In the <a href="https://jina.ai/news/how-embeddings-drive-ai-a-guide/?ref=jina-ai-gmbh.ghost.io">previous article, we discussed</a> embeddings in very abstract terms, but this one will be much more concrete. It explains where embeddings come from and how they are used.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text"><b><strong style="white-space: pre-wrap;">Trigger Warning:</strong></b> This article contains some light algebra, and although it tries to avoid complicated math, there are some notational conventions from vector algebra.</div></div><p>An <em>embedding</em> is a <em>mapping</em> of objects to <em>vectors</em>. Those objects may be real things or digital objects like images and files.</p><p>For example, imagine a robot that harvests tomatoes:</p><figure class="kg-card kg-embed-card"><iframe width="200" height="113" src="https://www.youtube.com/embed/JsZJWyMVBtY?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen="" title="This Tomato-Picking Robot Is the Future of Farming 🍅 🤖"></iframe></figure><p>This robot selects tomatoes on the vine that are ready to harvest, and then snips their stalks and takes them away. Recognizing which tomatoes are ripe is a good application of image embeddings. Each tomato on the vine is assigned a representative vector based on digital images taken by the robot’s cameras. It then uses these embeddings to decide whether or not to harvest a particular tomato.</p><p>Similarly, we might use embeddings to study and predict customer behavior. These embedding vectors stand in for a person — a real human being who presumably exists somewhere — but we construct their embedding vectors from digital information about that person. For a study of consumer buying behavior, this is likely to be some combination of demographic information and purchasing records.</p><p>In the previous article, we discussed how vectors are just ordered lists of numbers that we decide to interpret as points in a high-dimensional space. Data stored in a computer is also just an ordered list of numbers. Embeddings are, therefore, made by translating input vectors in one vector space — the one that contains the source data — into vectors in a different space called the <strong><em>embedding space</em></strong>.</p><p>But not just any mapping between vector spaces is an embedding. The translation into embeddings is purposeful. The placement of embedding vectors relative to each other should be informative in some way about the objects they represent.</p><h2 id="cosines-how-we-compare-embeddings">Cosines: How We Compare Embeddings</h2><p>When we use embeddings in applications, the thing we most often do is compare two embeddings and calculate how close or far apart they are. This is indicative of the similarity or dissimilarity of the objects those embeddings stand in for with respect to some set of properties.</p><p>To do this, we use a metric called the <strong>cosine</strong>. This section explains cosines and how we calculate them in high-dimensional vector spaces.</p><p>An embedding is a vector, and as we showed in the previous section, we can interpret a vector as a point in a multi-dimensional space. However, it also has an interpretation as a direction and magnitude. Traditionally, we visualize this interpretation with an arrow:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-19.png" class="kg-image" alt="" width="1350" height="1560" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-19.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-19.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-19.png 1350w" sizes="(min-width: 720px) 720px"></figure><p>The <em>direction</em> of this three-dimensional vector is specified by the $(x,y,z)$ coordinates, and the <em>magnitude</em> is just the length of the vector, i.e., the distance from the coordinate $(x,y,z)$ to the origin at $(0,0,0)$. The length is calculated using a multidimensional extension of <a href="https://en.wikipedia.org/wiki/Pythagorean_theorem?ref=jina-ai-gmbh.ghost.io">Pythagoras' theorem</a>:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-20.png" class="kg-image" alt="" width="1500" height="300" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-20.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-20.png 1500w" sizes="(min-width: 720px) 720px"></figure><p>The double bars around a vector $\|\vec{v}\|$ indicate the vector's <em>length</em> (or <em>magnitude</em>).</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Although this example uses only three dimensions, all these formulas apply exactly the same to arbitrarily large vectors of any number of dimensions.</div></div><p>We can see that different vectors can have the same direction but different lengths. For example, if we have the vectors $(4,2)$ and $(2,1)$, they have different lengths ($\sqrt{20} \approx 4.47$ and $\sqrt{5} \approx 2.23$ respectively) but they point in the same direction.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-21.png" class="kg-image" alt="" width="2000" height="938" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-21.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/11/image-21.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>How do we know they point in the same direction? We measure the angle between the two vectors. If the angle is zero, they point in the same direction.</p><p>To show how this works, let’s consider two vectors: $\vec{a}=(3,2,5)$ and $\vec{b}=(4,5,2)$:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-52.png" class="kg-image" alt="" width="2000" height="1140" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-52.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-52.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-52.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-52.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>To calculate the angle, we have a formula that scales up to any number of dimensions: The cosine.</p><p>The cosine of the angle&nbsp;$\theta$&nbsp;between vectors&nbsp;$\vec{a}$&nbsp;and&nbsp;$\vec{b}$&nbsp;is:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-50.png" class="kg-image" alt="" width="2000" height="208" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-50.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-50.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-50.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-50.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>The numerator of this fraction, $a⋅b$,&nbsp;is the&nbsp;<em>dot product</em>&nbsp;of the two vectors, and it’s easy to calculate:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-49.png" class="kg-image" alt="" width="2000" height="288" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-49.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-49.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-49.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-49.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>As for&nbsp;‖<em>a</em>‖&nbsp;and&nbsp;‖<em>b</em>‖, those are the lengths of the two vectors: $\|\vec{a}\| = \sqrt{38} \approx 6.164$ and $\vec{b} = \sqrt{45} \approx 6.708$. Therefore, to calculate&nbsp;$cosθ$:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-22.png" class="kg-image" alt="" width="1550" height="587" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-22.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-22.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-22.png 1550w" sizes="(min-width: 720px) 720px"></figure><p>This cosine corresponds to an angle of approximately 39.3 degrees, but in machine learning, we typically stop once we’ve calculated the cosine because if all the numbers in both vectors are greater than zero, then the cosine of the angle will be between 0 and 1. A cosine of 1 means the angle between two vectors is 0 degrees, i.e., the vectors have the same direction (although they may have different lengths). A cosine of 0 means they have an angle of 90 degrees. i.e., they are <em>perpendicular</em> or <em>orthogonal</em>.</p><p>So let’s compare $\vec{a}=(4,2)$&nbsp;and&nbsp;$\vec{b}=(2,1)$:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-23.png" class="kg-image" alt="" width="1550" height="1184" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-23.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-23.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-23.png 1550w" sizes="(min-width: 720px) 720px"></figure><p>When the cosine of two vectors is one, they point in the same direction, even though they may have different lengths.</p><p>Another way to do the same operation is to take each vector and <em>normalize</em> it. Normalizing a vector means creating a new vector that points in the same direction but has a length of exactly 1. If two vectors point in the same direction, they will normalize to identical vectors.</p><p>To normalize a vector, divide it in each dimension by the vector’s length. If $\vec{v} = (3,2,5)$ and $\hat{v} = norm(\vec{v})$ then:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-24.png" class="kg-image" alt="" width="1550" height="1232" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-24.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-24.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-24.png 1550w" sizes="(min-width: 720px) 720px"></figure><p>If two vectors $\vec{a}$ and $\vec{b}$ have an angle between them $\theta$, then their normalized forms $\hat{a}$ and $\hat{b}$ will have the same angle $\theta$ between them. Cosine is a measure that is indifferent to the magnitudes of vectors.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">When we compare embeddings to decide how near or far they are from each other, we almost always use cosines.</div></div><p>The reason for this is that the magnitudes of embedding vectors are not usually informative about anything. Most neural network architectures perform normalizations between some or all of their layers, rendering the magnitudes of embedding vectors typically useless.</p><h2 id="neural-networks-as-vector-mappings">Neural Networks As Vector Mappings</h2><p>Embedding vectors work because they are placed so that things that have common properties have cosines that are closer to 1, and those that do not have cosines closer to 0. An embedding model takes input vectors and translates them into embedding vectors.</p><p>Although there are many techniques for performing such translations, today, embedding models are exclusively neural networks.</p><p>A neural network is a sequence of vector transformations. In formal mathematical terms, for each layer of the network, we multiply the vector output of the previous layer by a matrix, and then generally add a <em>bias.</em> A <em>bias</em> is a set of values that we add or subtract from the resulting vector. We take the result and make that the input to the next layer of the network.</p><p>More formally, the values of the $m$th layer of the network are $\vec{m}$ and are transformed into the values of the $n$th layer ($\vec{n}$) by:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-25.png" class="kg-image" alt="" width="2000" height="325" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-25.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-25.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-25.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-25.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>Where $\textbf{W}$ is a matrix and $\vec{bias}$ is the vector of bias values.</p><p>It’s customary to think of it as a network of “nodes” bearing numerical values, connected by “weights”. This is truer to the roots of neural network theory but is exactly equivalent to multiplying a vector by a matrix.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-38.png" class="kg-image" alt="" width="650" height="1100" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-38.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-38.png 650w"></figure><p>If we have a vector $\vec{m} = (m_1,m_2m_3)$, this one neural network layer transforms it into a vector $\vec{n} = (n_1,n_2,n_3,n_4,n_5)$. It does that by multiplying the values in $\vec{m}$ by a set of weights (also called <em>parameters</em>), then adding them up, and adding the bias vector $\vec{bias} = (bias_1,bias_2,bias_3,bias_4,bias_5)$</p><p>Each line between nodes in the diagram above is one weight. If we designate the weight from $m_1$ to $n_1$ as $w_{11}$, from $m_2$ to $n_3$ as $w_{23}$, etc., then:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-26.png" class="kg-image" alt="" width="2000" height="600" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-26.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-26.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-26.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>In matrix algebra notation, this is the same as multiplying the 3-dimensional vector $\vec{n}$ by a $3x5$ matrix to get $\vec{m}$:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-27.png" class="kg-image" alt="" width="2000" height="472" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-27.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-27.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-27.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/11/image-27.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>Neural networks have multiple layers, so the output of this matrix multiplication is multiplied by another matrix and then another, typically with some kind of thresholding or normalization between multiplications and sometimes other tricks. The most common way of doing this today is to apply the <strong>ReLU</strong> (<a href="https://en.wikipedia.org/wiki/Rectifier_(neural_networks)?ref=jina-ai-gmbh.ghost.io">rectified linear activation unit</a>) activation function. If the value of any node is below zero, it’s replaced with a zero, and otherwise, left unchanged.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-28.png" class="kg-image" alt="" width="520" height="198"></figure><p>Otherwise, a neural network is just a series of transformations like the one above from $\vec{m}$ to $\vec{n}$.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-40.png" class="kg-image" alt="" width="2000" height="261" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-40.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-40.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-40.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-40.png 2300w" sizes="(min-width: 720px) 720px"></figure><p>This structure has some important properties. The most important is that:</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">In theory, any kind of vector transformation is possible with enough layers. Any problem that can be expressed as a mapping from a vector space $\vec{x} \in \textit{A}$ to vectors in another vector space $\vec{y} \in \textit{B}$ has some solution that looks just like a neural network.</div></div><p>It may be impractical to construct a large enough network for a given problem, and there may be no procedure for correctly calculating the weights. AI models are not guaranteed in advance to be able to learn or perform any task at all.</p><p>What happens in practice is that neural networks <strong><em>approximate</em></strong> a solution by learning from examples. How good a solution that approximation is depends on a lot of factors and can’t typically be known in advance of training a model.</p><p>There is an aphorism attributed to the British statistician George Box:</p><div class="kg-card kg-callout-card kg-callout-card-white"><div class="kg-callout-text"><i><em class="italic" style="white-space: pre-wrap;">All models are wrong, but some are useful.</em></i></div></div><p>Neural networks can be very good approximations, but they are still approximations, and it’s not possible to know for certain how good they are at something until you put them into production. The real measure of an AI model is its usefulness, and that’s hard to know in advance.</p><h2 id="turning-problems-into-vector-mappings">Turning Problems Into Vector Mappings</h2><p>Defining neural networks as mappings from one vector space to another sounds very limiting. We don’t naturally see the kinds of things we want AI models to do in those terms.</p><p>However, many of the most visible developments in recent AI are really just ways of using vector-to-vector mappings in clever ways. Large language models like ChatGPT translate input texts, rendered as vectors, into vectors that designate a single word. They write texts by adding the single-word output to the end of the input and then running again to get the next word.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-42.png" class="kg-image" alt="" width="2000" height="2000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-42.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-42.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-42.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/11/image-42.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>It may take some creativity and engineering to find a way to express some task as a vector mapping, but as recent developments show, it is surprisingly often possible.</p><h2 id="where-do-embeddings-fit-in">Where Do Embeddings Fit In?</h2><p>When you train an AI model, you do it with some goal in mind. In the typical scenario, you have training data that consists of inputs and matching correct outputs. For example, let’s say you want to classify tweets by their emotional content. This is a common benchmarking task used to evaluate text AI models.</p><p>One widely used dataset (<a href="https://github.com/dair-ai/emotion_dataset?ref=jina-ai-gmbh.ghost.io">DAIR.AI Emotion</a>) sorts tweets into eight emotional categories:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-58.png" class="kg-image" alt="" width="740" height="420" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-58.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-58.png 740w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-55.png" class="kg-image" alt="" width="1500" height="1106" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-55.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-55.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-55.png 1500w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Number of tweets per emotion category in the </span><a href="http://dair.ai/?ref=jina-ai-gmbh.ghost.io"><span style="white-space: pre-wrap;">DAIR.AI</span></a><span style="white-space: pre-wrap;"> Emotion dataset</span></figcaption></figure><p>To train a model to do this task, you need to decide two things:</p><ol><li>How to map the output category labels to vectors.</li><li>How to map the input texts to vectors</li></ol><p>The easiest way to encode these emotion labels is to create six-dimensional vectors where each value corresponds to one category. For example, if we make a list of emotions, like the one above, “anger” is the third in the list. So if a tweet has angry content, we train the network to output a six-dimensional vector with zero values everywhere except the third item in it, which is set to one:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-30.png" class="kg-image" alt="" width="589" height="81"></figure><p>This approach is called <em>zero-hot encoding</em> among AI engineers.</p><p>We also have to encode the tweets as vectors. There is more than one way to do this, but most text-processing models follow broadly the same pattern:</p><p>First, input texts are split into <em>tokens</em>, which you can understand as something like splitting it into words. The exact mechanisms vary somewhat, but the procedure broadly follows the following steps:</p><ol><li>Normalize the case, i.e., make everything lowercase.</li><li>Split a text on punctuation and spaces.</li><li>Look up each resulting subsegment of text in a dictionary (which is a part of the AI model bundle) and accept it if it is in the dictionary.</li><li>For segments not in the dictionary, split them into the smallest number of parts that are in the dictionary, and then accept those segments.</li></ol><p>So, for example, let’s say we wanted an embedding for this famous line from <em>Alice in Wonderland</em>:</p><div class="kg-card kg-callout-card kg-callout-card-white"><div class="kg-callout-text"><i><em class="italic" style="white-space: pre-wrap;">Why, sometimes I've believed as many as six impossible things before breakfast.</em></i></div></div><p>Jina Embeddings’ text tokenizer will split it up into 18 tokens like this:</p><pre><code class="hljs language-swift">[<span class="hljs-type">CLS</span>] why , sometimes i ' ve believed <span class="hljs-keyword">as</span> many <span class="hljs-keyword">as</span> six impossible 
 things before breakfast . [<span class="hljs-type">SEP</span>]
 </code></pre><p>The <code>[CLS]</code> and <code>[SEP]</code> are special tokens added to the text to indicate the beginning and end, but otherwise, you can see that the splits are between words on spaces and between letters and punctuation.</p><p>If the tokenizer encounters a sentence with words that are not in the dictionary, it tries to match the parts to entries in its dictionary. For example:</p><div class="kg-card kg-callout-card kg-callout-card-white"><div class="kg-callout-text"><i><em class="italic" style="white-space: pre-wrap;">Klaatu barada nikto</em></i></div></div><p>This is rendered in the Jina tokenizer as:</p><pre><code class="hljs language-less"><span class="hljs-selector-attr">[CLS]</span> <span class="hljs-selector-tag">k</span> #<span class="hljs-selector-id">#la</span> #<span class="hljs-selector-id">#at</span> #<span class="hljs-selector-id">#u</span> <span class="hljs-selector-tag">bar</span> #<span class="hljs-selector-id">#ada</span> <span class="hljs-selector-tag">nik</span> #<span class="hljs-selector-id">#to</span> <span class="hljs-selector-attr">[SEP]</span>
 </code></pre><p>The <code>##</code> indicates a segment appearing elsewhere than the beginning of a word.</p><p>This approach guarantees that every possible string can be tokenized and can always be processed by the AI model, even if it’s a new word or a nonsense string of letters.</p><p>Once the input text is transformed into a list of tokens, we replace each token with a unique vector from a lookup table. Then, we concatenate those vectors into one long vector.</p><p>Many text-processing AI models (including Jina Embeddings 2 models) use vectors of 512 dimensions for each token. All text-processing models are limited in the number of tokens they can accept as input. Jina Embeddings 2 models accept 8,192 tokens, but most models only take 512 or fewer.</p><p>If we use 512 for this example, then to do emotion classification for these tweets, we need to build a model that takes an input vector of $512 \times 512 = 262144$ dimensions, and outputs a vector of 6 dimensions:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-43.png" class="kg-image" alt="" width="1350" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-43.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-43.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-43.png 1350w" sizes="(min-width: 720px) 720px"></figure><p>Neural networks are often presented as a kind of black box in which the parts on the inside are not described in depth. This is not wrong, but it’s not very informative. In practice, large, modern AI models tend to have three components, although this is not always true, and the boundaries between them are not always clear:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-44.png" class="kg-image" alt="" width="1400" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-44.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-44.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-44.png 1400w" sizes="(min-width: 720px) 720px"></figure><p>The vocabulary for some of this is not entirely codified, and this schema does not apply to all AI models, but in general, a trained model has three parts:</p><ol><li><strong>An input processor or encoder</strong><br><br>Especially for networks that take in very large input vectors, there is some part of the network devoted to correlating all parts of the input with each other. This section of the network can be very large, and it can be structurally complex. Many of the biggest breakthroughs in AI in the last two decades have involved innovative structures in this part of the model.<br></li><li><strong>A multi-layer perceptron</strong><br><br>There isn’t a consistent term for this “middle” part of the model, but “MLP” or “multi-layer perceptron” appear to be the most common terms in the technical literature. The term itself is a bit old-fashioned, recalling the “perceptron”, a kind of small single-layer neural network invented in the 1950s that is ancestral to modern AI models.<br><br>The MLP typically consists of a number of connected layers of the same size. For example, the smallest of the ViT image processing models has twelve layers with 192 dimensions in each, while the largest has 24 layers, each with 768 dimensions.<br><br>The size and structure of the MLP are key design variables in an AI model.<br></li><li><strong>The “Classifier”</strong><br><br>This is usually the smallest part of the model, typically much smaller than the MLP. It may be as small as one layer but typically has more in modern models. This part of the model translates the output of the MLP into the exact form specified for the output, like the thousand-dimension one-hot vectors used for Imagenet-1k. It may not actually be a classifier. This final section of the model may be trained to do some other task.</li></ol><p>The size of the input encoder is mostly determined by your planned input sizes and the size of the first layer of the MLP. The size of the “classifier” is mostly determined by the training objective and the size of the last layer of the MLP. You have relatively few design choices in those areas. The MLP is the only part where you can make free decisions about your model.</p><p>The size of the MLP is a design choice balancing three factors:</p><ul><li>Smaller MLPs learn faster, run faster, and take less memory than large MLPs.</li><li>Large MLPs typically learn more and perform better, all else being equal.</li><li>Large MLPs are more likely to “overfit” than small MLPs. There is a risk that instead of generalizing from their training examples, they will memorize them and not learn effectively.</li></ul><p>The optimal balance depends on your use case and context, and it is very difficult to calculate the optimum in advance.</p><p>Most of the learning takes place in the MLP. The MLP learns to recognize those features of the inputs that are useful in calculating the correct output. The last layer of the MLP outputs vectors that are closer together the more they share those features. The “classifier” then has the relatively easy task of translating that into the correct output, like what class a particular input belongs to..</p><p>So, for example, if we train a text classifier with the six emotion labels from our dataset, we would expect the outputs of the MLP to be a high-dimensional analog of something like this:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-53.png" class="kg-image" alt="" width="1800" height="1250" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-53.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-53.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-53.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-53.png 1800w" sizes="(min-width: 720px) 720px"></figure><p>In short, the output of the last layer of the MLP has all the properties we want in an embedding: It puts similar things close together and dissimilar things further apart.</p><p>We typically construct embedding models by taking a model we’ve trained for something — often classification, but not necessarily — and throwing away the “classifier” part of the model. We just stop at the last layer of the MLP and use its outputs as embeddings.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-47.png" class="kg-image" alt="" width="1200" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-47.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-47.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-47.png 1200w" sizes="(min-width: 720px) 720px"></figure><p>There are four key points to take from this:</p><ol><li>Embeddings put things close to each other that are similar based on a set of features.</li><li>The set of features that embeddings encode is not usually specified in advance. It comes from training a neural network to do a task and consists of the features the model discovered were relevant to doing that task.</li><li>Embedding vectors are typically very high-dimensional but are usually much, much smaller than input vectors.</li><li>Most models have an embedding layer in them somewhere, even if they never expose it or use it as a source of embedding vectors.</li></ol><h2 id="text-embeddings">Text Embeddings</h2><p>Text embeddings work in very much the same way we’ve described above, but while it’s easy to understand how apples are like other apples and unlike oranges, it’s not so easy to understand what makes texts similar to each other.</p><p>The first and most prototypical application of text embeddings is for search and information retrieval. In this kind of application, we start with a collection of texts:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-31.png" class="kg-image" alt="" width="2000" height="1778" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-31.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-31.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-31.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-31.png 2250w" sizes="(min-width: 720px) 720px"></figure><p>We then calculate and store their embeddings:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-32.png" class="kg-image" alt="" width="2000" height="391" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-32.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-32.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-32.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-32.png 2250w" sizes="(min-width: 720px) 720px"></figure><p>When users want to search this document collection, they write a query in normal language:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-33.png" class="kg-image" alt="" width="2000" height="171" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-33.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-33.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-33.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-33.png 2250w" sizes="(min-width: 720px) 720px"></figure><p>We also convert this text into its corresponding embedding:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-34.png" class="kg-image" alt="" width="2000" height="171" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-34.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-34.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-34.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-34.png 2250w" sizes="(min-width: 720px) 720px"></figure><p>We perform search by taking the cosine between $\vec{q}$ and each of the document embeddings $\vec{d}_1,\vec{d}_2,\vec{d}_3$, identifying the one with the highest cosine (and thus is closest to the query embedding). We then return to the user the corresponding document.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-35.png" class="kg-image" alt="" width="2000" height="164" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-35.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-35.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-35.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-35.png 2250w" sizes="(min-width: 720px) 720px"></figure><p>So, one training goal for text similarity is information retrieval: If we train a model to be a good search engine, it will give us embeddings that put two documents close to each other in proportion to how much the same queries will retrieve them both.</p><p>There are other possible goals we can use to train text embeddings, like classifying texts by genre, type, or author, which will lead to embeddings that preserve different features. There are a number of ways we can train text embedding models, but we will discuss that topic in the next article, which will go into detail about training and adapting AI models. What matters is what you’ve trained the AI model to see as a text's most relevant features.</p><h2 id="jina-embeddings">Jina Embeddings</h2><p>As a concrete example, the <a href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Jina Embeddings 2</a> models represent each token with a 512-dimension vector and can accept a maximum of 8192 tokens as input. This AI model, therefore, has an input vector size of 512x8192 or 4,194,304 dimensions. If the input text is less than 8192 tokens long, the rest of the input vector is set to zeros. If longer, it’s truncated.</p><p>The model outputs a 512-dimension embedding vector to represent the input text.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-48.png" class="kg-image" alt="" width="1400" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-48.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-48.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-48.png 1400w" sizes="(min-width: 720px) 720px"></figure><p>As a developer or user, you don’t have to deal directly with any of these complexities. They are hidden from you by software libraries and web APIs that make using embeddings very straightforward. To transform a text into an embedding can involve as little as one line of code:</p><pre><code class="language-bash hljs">curl &lt;https://api.jina.ai/v1/embeddings&gt; \\
@@ -21,4 +21,4 @@
     "input": ["Your text string goes here", "You can send multiple texts"],
     "model": "jina-embeddings-v2-base-en"
   }'</span>
-</code></pre><p>Go to the <a href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io">Jina Embeddings page</a> to get a token and see code snippets for how to get embeddings in your development environment and programming language.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Embedding API</div><div class="kg-bookmark-description">Top-performing, 8192-token length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/banner-embedding-api.png" alt=""></div></a></figure><h2 id="embeddings-the-heart-of-ai">Embeddings: The Heart of AI</h2><p>Practically all models have an embedding layer in them, even if it's only implicit, and most AI projects can be built on top of embedding models. That's why good embeddings are so important to the effective use of AI technologies.</p><p>This series of articles is designed to demystify embeddings so that you can better understand and oversee the introduction of this technology in your business. Read the <a href="https://jina.ai/news/how-embeddings-drive-ai-a-guide/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">first installment here</a>. Next, we will dive further into this technology, and provide hands-on tutorials with code you can use in your own projects.</p><p>Jina AI is committed to providing you with tools and help for creating, optimizing, evaluating, and implementing embedding models for your enterprise. We’re here to help you navigate the new world of business AI. Contact us via our&nbsp;<a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">website</a>&nbsp;or join our&nbsp;<a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">community on Discord</a>&nbsp;to get started.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI - Your Portal to Multimodal AI</div><div class="kg-bookmark-description">Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; 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+</code></pre><p>Go to the <a href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io">Jina Embeddings page</a> to get a token and see code snippets for how to get embeddings in your development environment and programming language.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Embedding API</div><div class="kg-bookmark-description">Top-performing, 8192-token length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/banner-embedding-api.png" alt=""></div></a></figure><h2 id="embeddings-the-heart-of-ai">Embeddings: The Heart of AI</h2><p>Practically all models have an embedding layer in them, even if it's only implicit, and most AI projects can be built on top of embedding models. That's why good embeddings are so important to the effective use of AI technologies.</p><p>This series of articles is designed to demystify embeddings so that you can better understand and oversee the introduction of this technology in your business. Read the <a href="https://jina.ai/news/how-embeddings-drive-ai-a-guide/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">first installment here</a>. Next, we will dive further into this technology, and provide hands-on tutorials with code you can use in your own projects.</p><p>Jina AI is committed to providing you with tools and help for creating, optimizing, evaluating, and implementing embedding models for your enterprise. We’re here to help you navigate the new world of business AI. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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diff --git a/news/embeddings-the-swiss-army-knife-of-ai/index.html b/news/embeddings-the-swiss-army-knife-of-ai/index.html
index 0a94dfa7610..6d3bfcde3e6 100644
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@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Embeddings: The Swiss Army Knife of AI</title><meta charset="utf-8"><meta name="title" content="Embeddings: The Swiss Army Knife of AI"><meta name="description" content="Embeddings are an essential technology for modern AI. This article explains what they are and how they work."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/embeddings-the-swiss-army-knife-of-ai"><meta property="og:title" content="Embeddings: The Swiss Army Knife of AI"><meta property="og:description" content="Embeddings are an essential technology for modern AI. This article explains what they are and how they work."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--21-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/embeddings-the-swiss-army-knife-of-ai"><meta property="twitter:title" content="Embeddings: The Swiss Army Knife of AI"><meta property="twitter:description" content="Embeddings are an essential technology for modern AI. This article explains what they are and how they work."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--21-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Embeddings: The Swiss Army Knife of AI</title><meta charset="utf-8"><meta name="title" content="Embeddings: The Swiss Army Knife of AI"><meta name="description" content="Embeddings are an essential technology for modern AI. This article explains what they are and how they work."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/embeddings-the-swiss-army-knife-of-ai"><meta property="og:title" content="Embeddings: The Swiss Army Knife of AI"><meta property="og:description" content="Embeddings are an essential technology for modern AI. This article explains what they are and how they work."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--21-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/embeddings-the-swiss-army-knife-of-ai"><meta property="twitter:title" content="Embeddings: The Swiss Army Knife of AI"><meta property="twitter:description" content="Embeddings are an essential technology for modern AI. This article explains what they are and how they work."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--21-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Embeddings: The Swiss Army Knife of AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Embeddings are an essential technology for modern AI. This article explains what they are and how they work.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 13, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>A Swiss Army knife is a versatile, compact tool that you can keep in your pocket until you need it. It’s handy and designed to meet common unplanned needs. Have to cut something? It’s a knife. Have to unscrew something? It’s a screwdriver. Need to open a bottle or a can? It can do that, too. They’ve become so famous that “to be the Swiss Army knife of something” is now a figure of speech used for any versatile, adaptable, and highly useful tool.</p><p>AI tools are a bit too abstract to put in your pocket, but just because a tool is abstract doesn’t mean that words like <em>specialized</em>, <em>versatile</em>, and <em>adaptable</em> don’t apply to it! </p><p>One of AI's most versatile, adaptable, albeit abstract, tools goes by the name <em>embeddings</em>. Embeddings are actively in use for:</p><ul><li>Search and information retrieval for all media types</li><li>Question-answering systems</li><li>Recommender systems</li><li>Outlier detection (often as part of fraud detection)</li><li>Spellchecking and grammar correction</li><li>Natural language understanding</li><li>Machine translation</li></ul><p>This is a far from exhaustive list. Nearly every AI application uses them. Even image generators and chatbots like ChatGPT rely on embeddings internally.</p><h2 id="what-is-an-embedding">What is an embedding?</h2><p>An <em>embedding</em> is a representation of some data object as a <em>vector</em>, constructed so that some properties of the data object are encoded into the geometric properties of its vector representation.</p><p>That’s awfully abstract, but it’s not really as complicated as it sounds.</p><p>First, we need to introduce a little (very little) bit of math. A <em>vector</em> is two things that sound like they're different but are actually the same:</p><ol><li>A vector is a point in a multidimensional space.</li><li>A vector is an ordered list of scalar values, i.e., numbers.</li></ol><p>To see how this works, consider lists of two numbers. For example, $(6, 4)$ and $(2, 8)$.  You see that we could treat them as coordinates on an x-y axis, with each list corresponding to a point in a two-dimensional space:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/xy_coords.png" class="kg-image" alt="" width="1425" height="1400" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/xy_coords.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/xy_coords.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/xy_coords.png 1425w" sizes="(min-width: 720px) 720px"></figure><p>If we have three numbers, like $(3, 2, 5)$ and $(4, 5, 2)$, then this corresponds to points in a three-dimensional space:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/3d.png" class="kg-image" alt="" width="1079" height="937" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/3d.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/3d.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/3d.png 1079w" sizes="(min-width: 720px) 720px"></figure><p>The important point is that we could extend this into more dimensions: four, five, a hundred, a thousand, even millions or billions. Drawing a space with a thousand dimensions is very hard, and imagining one is all but impossible, but mathematically, it’s really easy.</p><p>For example, the distance between points $(6, 4)$ and $(2, 8)$ is simply an application of <a href="https://en.wikipedia.org/wiki/Pythagorean_theorem?ref=jina-ai-gmbh.ghost.io">Pythagoras’ theorem</a>. Given two points $a = (x_1, y_1)$ and $b = (x_2, y_2)$, the distance between them is:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-7-1.png" class="kg-image" alt="" width="1600" height="198" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-7-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-7-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-7-1.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>For $(6, 4)$ and $(2, 8)$, this means:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-15.png" class="kg-image" alt="" width="1600" height="375" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-15.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-15.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>For three dimensions, we just extend the formula by adding a term. For $a = (3, 2, 5)$ and $b = (4, 5, 2)$:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-16.png" class="kg-image" alt="" width="1600" height="365" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-16.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-16.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>We can extend this formula to vectors in any number of dimensions. We just add more terms, the same way we did by going from two to three dimensions.</p><p>Besides distance, another measurement we use in high-dimensional vector spaces is the cosine of the angle between the two vectors. If you see each vector not just as a point but as a line from the origin (the point designated by the vector $(0,0,0,...)$), then you can calculate the angle between the two vectors ($\theta$ in the image below).</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/cosine2.png" class="kg-image" alt="" width="1611" height="918" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/cosine2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/cosine2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/cosine2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/cosine2.png 1611w" sizes="(min-width: 720px) 720px"></figure><p>To calculate this, we have another formula that scales up to any number of dimensions. We know that the cosine of the angle $\theta$ between vectors $a$ and $b$ is:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-11.png" class="kg-image" alt="" width="2000" height="208" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-11.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-11.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-11.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-11.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>This is more complicated than it looks, but not much. $a \cdot b$ is called the <em>dot product</em> of the two vectors, and it’s easy to calculate. If $a = (3, 2, 5)$ and $b = (4, 5, 2)$, then:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-19.png" class="kg-image" alt="" width="1600" height="230" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-19.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-19.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-19.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>As for $‖a‖$ and $‖b‖$, those are the lengths of the vectors, i.e., the distance from the origin to that point. So:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-18.png" class="kg-image" alt="" width="1600" height="980" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-18.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-18.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-18.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>Therefore, to calculate $cos \theta$:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-17.png" class="kg-image" alt="" width="1600" height="379" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-17.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-17.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>This cosine corresponds to an angle of approximately 39.3°, but in machine learning, we typically stop once we’ve calculated the cosine because if all the numbers in both vectors are greater than zero, then the cosine of the angle will be between 0 and 1.</p><p>This looks like a lot of math, but if you look it over, you’ll see that it’s just addition, subtraction, multiplication, division, one exponent, and a square root. Simple but boring and repetitive stuff. <strong>You don’t actually have to do any of this math. The whole reason we keep computers around is to do that sort of thing.</strong> But you should understand that vectors are lists of numbers, understand the concept of working with vectors, and understand how, no matter how many dimensions a vector has, we can still do things like calculate distances and angles.</p><p>What makes this so important is that any data we keep on a computer is also just a list of numbers. Every data item — digital pictures, texts, audio recordings, 3D model files, anything you can think of that you can put into a computer file — is a vector if we choose to look at it that way.</p><h2 id="how-do-we-assign-embedding-vectors-to-things">How do we assign embedding vectors to things?</h2><p>The point of embeddings is to assign vectors to data objects so that their placement in high-dimensional spaces encodes useful information about them. The data objects — texts or images or whatever else we’re working with — are already vectors if we choose to look at them that way. The locations of those vectors don’t tell us anything useful about them.</p><p>Consider these four images:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/ApplesAndOranges.png" class="kg-image" alt="" width="900" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/ApplesAndOranges.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/ApplesAndOranges.png 900w" sizes="(min-width: 720px) 720px"></figure><p>Each is a 450x450 pixel image colored with the standard RGB palette. This means the picture consists of 202,500 pixels, each with one number between 0 and 255 for its red, green, and blue values. To turn this into a vector with 607,500 dimensions is trivial.</p><p>We could take any pair of images and calculate the distance between them or measure their cosine, but it would be very unlikely that the apples would be especially close to each other or especially far from the oranges. At least, it would be very unlikely if we used hundreds of pictures of apples and oranges instead of just four.</p><p>More likely, we would get something like this:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/scatterplot.png" class="kg-image" alt="" width="617" height="548" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/scatterplot.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/scatterplot.png 617w"></figure><p>We can’t draw pictures in 600,000 dimensions, so this picture uses just two dimensions to demonstrate the point: We should expect that the apples and oranges are semi-randomly placed and mixed up together.</p><p>We want to assign to each image a unique embedding such that the apples are close together and far from the oranges, and vice-versa. We want something like this:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/unscatteredplot--1-.png" class="kg-image" alt="" width="617" height="548" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/unscatteredplot--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/unscatteredplot--1-.png 617w"></figure><p>To do that, we construct a neural network (which we’re going to call an <em>embedding model</em>) that takes 607,500 dimension vectors as input and outputs some other vector, typically with fewer dimensions. For example, the widely used <a href="https://huggingface.co/sentence-transformers/clip-ViT-B-32?ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">ViT-B-32</a> image embedding model transforms input images into 512-dimension embedding vectors.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-20.png" class="kg-image" alt="" width="1300" height="775" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-20.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-20.png 1300w" sizes="(min-width: 720px) 720px"></figure><p>We then train the embedding model with labeled pictures of apples and oranges, instructing it to adjust the network’s weights slowly to separate the embedding vectors for apples and oranges. After many cycles of training, we expect that when we give the model pictures of apples as input, it will output vectors that are closer to each other than they are to the vectors we get when we give it pictures of oranges as inputs.</p><p>Those output vectors are <em>embeddings</em>, and they collectively form an <em>embedding space</em>. Individual embeddings’ locations encode useful information about their corresponding data objects: In this case, whether something is a picture of an apple or an orange.</p><p>Telling apples from oranges is a very simplistic scenario, but you might easily imagine scaling it up to many features.</p><p>In some use cases, we can even construct embeddings where we don’t explicitly say what features are relevant, and we let the neural network figure it out in the training process. For example, we can construct a face recognition system by taking pictures of people’s faces and training an embedding model to output embeddings that place pictures of the same person close together. We can then construct a database of people's pictures with their embedding vectors as keys.</p><p>We would expect the stored faces to be distributed through the embedding space:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Faces1.png" class="kg-image" alt="" width="801" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Faces1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Faces1.png 801w" sizes="(min-width: 720px) 720px"></figure><p>We might expect that this embedding space would encode a lot of features that we had never explicitly trained it to encode. For example, it might segregate men from women:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/FacesMenWomen.png" class="kg-image" alt="" width="801" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/FacesMenWomen.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/FacesMenWomen.png 801w" sizes="(min-width: 720px) 720px"></figure><p>Or we might find people clustered together by features of their hair, like baldness or grey:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/FacesHair.png" class="kg-image" alt="" width="801" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/FacesHair.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/FacesHair.png 801w" sizes="(min-width: 720px) 720px"></figure><p>But we would expect that if we gave it another picture of someone in the database, the embedding for that new picture would be closer to the picture we stored of that person than to anyone else:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Winona.png" class="kg-image" alt="" width="1100" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Winona.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/Winona.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Winona.png 1100w" sizes="(min-width: 720px) 720px"></figure><p>Of course, it would also find people who just <em>look</em> similar, although we hope that they wouldn’t be as close together as two people who are actually the same:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Elijah.png" class="kg-image" alt="" width="1100" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Elijah.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/Elijah.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Elijah.png 1100w" sizes="(min-width: 720px) 720px"></figure><p>This highlights the logic of embedding spaces: Inputs are diverse, but by translating them into embeddings, we turn features — sometimes complex, hidden, subtle, or non-obvious features —  into geometric properties that software can easily identify.</p><p>Embedding spaces can also support diverse input types, like text and images, creating a common embedding space and enabling you to map between the two.</p><p>For example, if we have a database of pictures with descriptive captions, we can co-train two embedding models — one for images and one for texts — to output vectors in the same embedding space. The result is that embeddings of descriptions of images and embeddings of the images themselves will be near each other.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/DualEmbedding.png" class="kg-image" alt="" width="800" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/DualEmbedding.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/DualEmbedding.png 800w" sizes="(min-width: 720px) 720px"></figure><p>In principle, any kind of digital data can serve as input for creating embeddings, and any paired data types — not just text and images — can serve to create multi-modal joint embedding spaces.</p><h2 id="what-are-embeddings-good-for">What are embeddings good for?</h2><p>Like the Swiss Army knife, the question should be, <em>what aren’t they good for?</em></p><p>We’ve already shown how you can use embeddings for image classification and face recognition, but that’s far from exhausting the possibilities. For example, AI image production from text descriptions (a.k.a. “AI art”) starts by constructing a joint embedding space for text and images, and then, when the user enters a text, it calculates that text’s embedding and tries to construct an image that will produce a nearby embedding.</p><p>Embeddings are so generally useful that they see applications all over AI and machine learning. Any application that requires similarity/dissimilarity evaluation, relies on hidden or non-obvious features, or requires implicit context-sensitive mappings between different inputs and outputs, likely uses embeddings in some form.</p><h2 id="conclusion">Conclusion</h2><p>Embeddings are an essential technology for modern machine learning and AI, present in some form across the spectrum of AI applications. Properly understanding and mastering this technology positions you to leverage AI models to add the most value to your business.</p><p>The theory behind embeddings isn’t even complicated: All it involves is a map from data objects to points in a high dimensional vector space where things that have properties in common that matter to you cluster together. Using them is just a matter of measuring vector distances and cosines, which is computationally trivial math!</p><p>Unfortunately, the practice of constructing and training embedding models is more complex than using them. Jina AI is developing a collection of high-performance specialized embedding models that you can download or use via our public API, without any of the complexities of AI development. We are also preparing a suite of open-source tools in Python to help you integrate embedding models into your tech stack.</p><p>Jina AI is committed to providing you with tools and help for creating, optimizing, evaluating, and implementing embedding models for your enterprise. We’re here to help you navigate the new world of business AI. Contact us via our <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">website</a> or join our <a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io">community on Discord</a> to get started.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI - Your Portal to Multimodal AI</div><div class="kg-bookmark-description">Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Embeddings: The Swiss Army Knife of AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Embeddings are an essential technology for modern AI. This article explains what they are and how they work.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 13, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>A Swiss Army knife is a versatile, compact tool that you can keep in your pocket until you need it. It’s handy and designed to meet common unplanned needs. Have to cut something? It’s a knife. Have to unscrew something? It’s a screwdriver. Need to open a bottle or a can? It can do that, too. They’ve become so famous that “to be the Swiss Army knife of something” is now a figure of speech used for any versatile, adaptable, and highly useful tool.</p><p>AI tools are a bit too abstract to put in your pocket, but just because a tool is abstract doesn’t mean that words like <em>specialized</em>, <em>versatile</em>, and <em>adaptable</em> don’t apply to it! </p><p>One of AI's most versatile, adaptable, albeit abstract, tools goes by the name <em>embeddings</em>. Embeddings are actively in use for:</p><ul><li>Search and information retrieval for all media types</li><li>Question-answering systems</li><li>Recommender systems</li><li>Outlier detection (often as part of fraud detection)</li><li>Spellchecking and grammar correction</li><li>Natural language understanding</li><li>Machine translation</li></ul><p>This is a far from exhaustive list. Nearly every AI application uses them. Even image generators and chatbots like ChatGPT rely on embeddings internally.</p><h2 id="what-is-an-embedding">What is an embedding?</h2><p>An <em>embedding</em> is a representation of some data object as a <em>vector</em>, constructed so that some properties of the data object are encoded into the geometric properties of its vector representation.</p><p>That’s awfully abstract, but it’s not really as complicated as it sounds.</p><p>First, we need to introduce a little (very little) bit of math. A <em>vector</em> is two things that sound like they're different but are actually the same:</p><ol><li>A vector is a point in a multidimensional space.</li><li>A vector is an ordered list of scalar values, i.e., numbers.</li></ol><p>To see how this works, consider lists of two numbers. For example, $(6, 4)$ and $(2, 8)$.  You see that we could treat them as coordinates on an x-y axis, with each list corresponding to a point in a two-dimensional space:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/xy_coords.png" class="kg-image" alt="" width="1425" height="1400" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/xy_coords.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/xy_coords.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/xy_coords.png 1425w" sizes="(min-width: 720px) 720px"></figure><p>If we have three numbers, like $(3, 2, 5)$ and $(4, 5, 2)$, then this corresponds to points in a three-dimensional space:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/3d.png" class="kg-image" alt="" width="1079" height="937" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/3d.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/3d.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/3d.png 1079w" sizes="(min-width: 720px) 720px"></figure><p>The important point is that we could extend this into more dimensions: four, five, a hundred, a thousand, even millions or billions. Drawing a space with a thousand dimensions is very hard, and imagining one is all but impossible, but mathematically, it’s really easy.</p><p>For example, the distance between points $(6, 4)$ and $(2, 8)$ is simply an application of <a href="https://en.wikipedia.org/wiki/Pythagorean_theorem?ref=jina-ai-gmbh.ghost.io">Pythagoras’ theorem</a>. Given two points $a = (x_1, y_1)$ and $b = (x_2, y_2)$, the distance between them is:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-7-1.png" class="kg-image" alt="" width="1600" height="198" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-7-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-7-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-7-1.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>For $(6, 4)$ and $(2, 8)$, this means:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-15.png" class="kg-image" alt="" width="1600" height="375" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-15.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-15.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>For three dimensions, we just extend the formula by adding a term. For $a = (3, 2, 5)$ and $b = (4, 5, 2)$:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-16.png" class="kg-image" alt="" width="1600" height="365" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-16.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-16.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>We can extend this formula to vectors in any number of dimensions. We just add more terms, the same way we did by going from two to three dimensions.</p><p>Besides distance, another measurement we use in high-dimensional vector spaces is the cosine of the angle between the two vectors. If you see each vector not just as a point but as a line from the origin (the point designated by the vector $(0,0,0,...)$), then you can calculate the angle between the two vectors ($\theta$ in the image below).</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/cosine2.png" class="kg-image" alt="" width="1611" height="918" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/cosine2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/cosine2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/cosine2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/cosine2.png 1611w" sizes="(min-width: 720px) 720px"></figure><p>To calculate this, we have another formula that scales up to any number of dimensions. We know that the cosine of the angle $\theta$ between vectors $a$ and $b$ is:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-11.png" class="kg-image" alt="" width="2000" height="208" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-11.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-11.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-11.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-11.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>This is more complicated than it looks, but not much. $a \cdot b$ is called the <em>dot product</em> of the two vectors, and it’s easy to calculate. If $a = (3, 2, 5)$ and $b = (4, 5, 2)$, then:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-19.png" class="kg-image" alt="" width="1600" height="230" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-19.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-19.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-19.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>As for $‖a‖$ and $‖b‖$, those are the lengths of the vectors, i.e., the distance from the origin to that point. So:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-18.png" class="kg-image" alt="" width="1600" height="980" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-18.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-18.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-18.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>Therefore, to calculate $cos \theta$:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-17.png" class="kg-image" alt="" width="1600" height="379" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-17.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-17.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>This cosine corresponds to an angle of approximately 39.3°, but in machine learning, we typically stop once we’ve calculated the cosine because if all the numbers in both vectors are greater than zero, then the cosine of the angle will be between 0 and 1.</p><p>This looks like a lot of math, but if you look it over, you’ll see that it’s just addition, subtraction, multiplication, division, one exponent, and a square root. Simple but boring and repetitive stuff. <strong>You don’t actually have to do any of this math. The whole reason we keep computers around is to do that sort of thing.</strong> But you should understand that vectors are lists of numbers, understand the concept of working with vectors, and understand how, no matter how many dimensions a vector has, we can still do things like calculate distances and angles.</p><p>What makes this so important is that any data we keep on a computer is also just a list of numbers. Every data item — digital pictures, texts, audio recordings, 3D model files, anything you can think of that you can put into a computer file — is a vector if we choose to look at it that way.</p><h2 id="how-do-we-assign-embedding-vectors-to-things">How do we assign embedding vectors to things?</h2><p>The point of embeddings is to assign vectors to data objects so that their placement in high-dimensional spaces encodes useful information about them. The data objects — texts or images or whatever else we’re working with — are already vectors if we choose to look at them that way. The locations of those vectors don’t tell us anything useful about them.</p><p>Consider these four images:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/ApplesAndOranges.png" class="kg-image" alt="" width="900" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/ApplesAndOranges.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/ApplesAndOranges.png 900w" sizes="(min-width: 720px) 720px"></figure><p>Each is a 450x450 pixel image colored with the standard RGB palette. This means the picture consists of 202,500 pixels, each with one number between 0 and 255 for its red, green, and blue values. To turn this into a vector with 607,500 dimensions is trivial.</p><p>We could take any pair of images and calculate the distance between them or measure their cosine, but it would be very unlikely that the apples would be especially close to each other or especially far from the oranges. At least, it would be very unlikely if we used hundreds of pictures of apples and oranges instead of just four.</p><p>More likely, we would get something like this:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/scatterplot.png" class="kg-image" alt="" width="617" height="548" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/scatterplot.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/scatterplot.png 617w"></figure><p>We can’t draw pictures in 600,000 dimensions, so this picture uses just two dimensions to demonstrate the point: We should expect that the apples and oranges are semi-randomly placed and mixed up together.</p><p>We want to assign to each image a unique embedding such that the apples are close together and far from the oranges, and vice-versa. We want something like this:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/unscatteredplot--1-.png" class="kg-image" alt="" width="617" height="548" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/unscatteredplot--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/unscatteredplot--1-.png 617w"></figure><p>To do that, we construct a neural network (which we’re going to call an <em>embedding model</em>) that takes 607,500 dimension vectors as input and outputs some other vector, typically with fewer dimensions. For example, the widely used <a href="https://huggingface.co/sentence-transformers/clip-ViT-B-32?ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">ViT-B-32</a> image embedding model transforms input images into 512-dimension embedding vectors.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-20.png" class="kg-image" alt="" width="1300" height="775" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-20.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-20.png 1300w" sizes="(min-width: 720px) 720px"></figure><p>We then train the embedding model with labeled pictures of apples and oranges, instructing it to adjust the network’s weights slowly to separate the embedding vectors for apples and oranges. After many cycles of training, we expect that when we give the model pictures of apples as input, it will output vectors that are closer to each other than they are to the vectors we get when we give it pictures of oranges as inputs.</p><p>Those output vectors are <em>embeddings</em>, and they collectively form an <em>embedding space</em>. Individual embeddings’ locations encode useful information about their corresponding data objects: In this case, whether something is a picture of an apple or an orange.</p><p>Telling apples from oranges is a very simplistic scenario, but you might easily imagine scaling it up to many features.</p><p>In some use cases, we can even construct embeddings where we don’t explicitly say what features are relevant, and we let the neural network figure it out in the training process. For example, we can construct a face recognition system by taking pictures of people’s faces and training an embedding model to output embeddings that place pictures of the same person close together. We can then construct a database of people's pictures with their embedding vectors as keys.</p><p>We would expect the stored faces to be distributed through the embedding space:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Faces1.png" class="kg-image" alt="" width="801" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Faces1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Faces1.png 801w" sizes="(min-width: 720px) 720px"></figure><p>We might expect that this embedding space would encode a lot of features that we had never explicitly trained it to encode. For example, it might segregate men from women:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/FacesMenWomen.png" class="kg-image" alt="" width="801" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/FacesMenWomen.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/FacesMenWomen.png 801w" sizes="(min-width: 720px) 720px"></figure><p>Or we might find people clustered together by features of their hair, like baldness or grey:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/FacesHair.png" class="kg-image" alt="" width="801" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/FacesHair.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/FacesHair.png 801w" sizes="(min-width: 720px) 720px"></figure><p>But we would expect that if we gave it another picture of someone in the database, the embedding for that new picture would be closer to the picture we stored of that person than to anyone else:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Winona.png" class="kg-image" alt="" width="1100" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Winona.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/Winona.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Winona.png 1100w" sizes="(min-width: 720px) 720px"></figure><p>Of course, it would also find people who just <em>look</em> similar, although we hope that they wouldn’t be as close together as two people who are actually the same:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Elijah.png" class="kg-image" alt="" width="1100" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Elijah.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/Elijah.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Elijah.png 1100w" sizes="(min-width: 720px) 720px"></figure><p>This highlights the logic of embedding spaces: Inputs are diverse, but by translating them into embeddings, we turn features — sometimes complex, hidden, subtle, or non-obvious features —  into geometric properties that software can easily identify.</p><p>Embedding spaces can also support diverse input types, like text and images, creating a common embedding space and enabling you to map between the two.</p><p>For example, if we have a database of pictures with descriptive captions, we can co-train two embedding models — one for images and one for texts — to output vectors in the same embedding space. The result is that embeddings of descriptions of images and embeddings of the images themselves will be near each other.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/DualEmbedding.png" class="kg-image" alt="" width="800" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/DualEmbedding.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/DualEmbedding.png 800w" sizes="(min-width: 720px) 720px"></figure><p>In principle, any kind of digital data can serve as input for creating embeddings, and any paired data types — not just text and images — can serve to create multi-modal joint embedding spaces.</p><h2 id="what-are-embeddings-good-for">What are embeddings good for?</h2><p>Like the Swiss Army knife, the question should be, <em>what aren’t they good for?</em></p><p>We’ve already shown how you can use embeddings for image classification and face recognition, but that’s far from exhausting the possibilities. For example, AI image production from text descriptions (a.k.a. “AI art”) starts by constructing a joint embedding space for text and images, and then, when the user enters a text, it calculates that text’s embedding and tries to construct an image that will produce a nearby embedding.</p><p>Embeddings are so generally useful that they see applications all over AI and machine learning. Any application that requires similarity/dissimilarity evaluation, relies on hidden or non-obvious features, or requires implicit context-sensitive mappings between different inputs and outputs, likely uses embeddings in some form.</p><h2 id="conclusion">Conclusion</h2><p>Embeddings are an essential technology for modern machine learning and AI, present in some form across the spectrum of AI applications. Properly understanding and mastering this technology positions you to leverage AI models to add the most value to your business.</p><p>The theory behind embeddings isn’t even complicated: All it involves is a map from data objects to points in a high dimensional vector space where things that have properties in common that matter to you cluster together. Using them is just a matter of measuring vector distances and cosines, which is computationally trivial math!</p><p>Unfortunately, the practice of constructing and training embedding models is more complex than using them. Jina AI is developing a collection of high-performance specialized embedding models that you can download or use via our public API, without any of the complexities of AI development. We are also preparing a suite of open-source tools in Python to help you integrate embedding models into your tech stack.</p><p>Jina AI is committed to providing you with tools and help for creating, optimizing, evaluating, and implementing embedding models for your enterprise. We’re here to help you navigate the new world of business AI. Contact us via our <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">website</a> or join our <a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io">community on Discord</a> to get started.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI - Your Portal to Multimodal AI</div><div class="kg-bookmark-description">Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</title><meta charset="utf-8"><meta name="title" content="Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations"><meta name="description" content="Explore SceneXplain's impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations"><meta property="og:title" content="Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations"><meta property="og:description" content="Explore SceneXplain's impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations"><meta property="twitter:title" content="Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations"><meta property="twitter:description" content="Explore SceneXplain's impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</title><meta charset="utf-8"><meta name="title" content="Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations"><meta name="description" content="Explore SceneXplain's impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations"><meta property="og:title" content="Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations"><meta property="og:description" content="Explore SceneXplain's impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations"><meta property="twitter:title" content="Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations"><meta property="twitter:description" content="Explore SceneXplain's impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Explore SceneXplain's impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 07, 2023 • 17 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>On a crisp autumn morning in Paris, Marie, a visually impaired woman in her early thirties, settles down in her favorite café with a warm cup of coffee. She eagerly opens her smartphone and navigates to a popular news website using her screen reader. As Marie listens to the headlines, she stumbles upon an article about a groundbreaking art exhibition. </p><p>"I wonder what the artwork looks like," she thinks aloud, as the screen reader describes the images as "Photo 1" and "Photo 2." </p><p>Frustrated, she sighs, "If only I could get a sense of the art, too."</p><p>Marie's experience is not unique; millions of visually impaired individuals worldwide face similar challenges in accessing digital content. According to the World Health Organization, there are approximately 285 million visually impaired people worldwide, with 39 million being blind. Digital accessibility is a critical issue, especially for the public sector. Governments and organizations are responsible for ensuring that their digital platforms are inclusive and accessible to all citizens, regardless of their abilities. A 2020 report by the European Commission found that only 34% of public sector websites in the EU met basic accessibility standards, highlighting the urgent need for improvement.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.who.int/news-room/fact-sheets/detail/blindness-and-visual-impairment?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Vision impairment and blindness</div><div class="kg-bookmark-description">WHO fact sheet on blindness and visual impairment providing key facts, definitions, causes, who is at risk, global and WHO response.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.who.int/apple-touch-icon-precomposed.png" alt=""><span class="kg-bookmark-author">World Health Organization</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn.who.int/media/images/default-source/imported/vision-impairment-fact-sheet.tmb-1200v.jpg?sfvrsn=9dcda712_12" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://op.europa.eu/en/publication-detail/-/publication/8eb9074c-8712-454b-9a7d-5c13d10f8f4e?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Monitoring e-accessibility in Europe: 2010-2011 : annual report.</div><div class="kg-bookmark-description">Developments in European Union (EU) policies over the past decade have increasingly acknowledged that inclusive Information and Communication Technologies (ICT) and Assistive Technologies (AT) are essential to ensuring full participation in society for many of the population segments at risk of digi…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://op.europa.eu/o/OPPortalEE/images/favicon.ico" alt=""><span class="kg-bookmark-author">DisplayLogo Publications Office of the European Union</span><span class="kg-bookmark-publisher">CNIPA</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://op.europa.eu/o/opportal-service/thumbnail/cellar/8eb9074c-8712-454b-9a7d-5c13d10f8f4e.0001.01/DOC_2" alt=""></div></a></figure><p>One of the key components of web accessibility is providing descriptive information for images, commonly known as <a href="https://www.w3schools.com/tags/att_img_alt.asp?ref=jina-ai-gmbh.ghost.io">"alt text"</a> or <a href="https://accessibility.huit.harvard.edu/describe-content-images?ref=jina-ai-gmbh.ghost.io">"image descriptions."</a> A well-written image description can convey the essence of an image, allowing visually impaired users to comprehend the content and context of the image. However, even for seasoned content creators, crafting accurate and informative image descriptions is not always easy. This is where SceneXplain, a groundbreaking AI-driven solution, steps in to revolutionize how we create accessible multimedia content.</p><p>This article will explore the significance of digital accessibility, the role of image descriptions, and the challenges with existing solutions. We will then introduce <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a>, its advantages, and its potential applications in enhancing digital accessibility for the public sector. We will also discuss how SceneXplain can help organizations comply with European accessibility regulations and provide a roadmap for implementing SceneXplain in public sector websites and applications.</p><h2 id="the-role-of-image-descriptions-in-web-accessibility">The Role of Image Descriptions in Web Accessibility</h2><p>Image descriptions, also known as "alt text" or "alternative text," play a vital role in web accessibility by providing a textual representation of the visual content for users who cannot perceive it. The concept of image alt text dates back to the early days of the World Wide Web. As an example, an HTML code snippet for including an image with alt text would look like this:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-3.png" class="kg-image" alt="" width="612" height="408" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-3.png 612w"></figure><pre><code class="language-html hljs language-xml"><span class="hljs-tag">&lt;<span class="hljs-name">img</span> <span class="hljs-attr">src</span>=<span class="hljs-string">"image.jpg"</span> <span class="hljs-attr">alt</span>=<span class="hljs-string">"A beautiful sunset with the sun setting behind a mountain"</span>&gt;</span>
-</code></pre><p>In this example, the alt text "A beautiful sunset with the sun setting behind a mountain" briefly describes the image, which can be read by assistive technologies or displayed when the image fails to load.</p><p>According to the Web Content Accessibility Guidelines (WCAG) 2.1, providing text alternatives for non-text content is one of the fundamental principles of web accessibility. This ensures that users who rely on assistive technologies, such as screen readers, can access and understand the visual information on websites and applications. Image descriptions are crucial in providing an inclusive and equitable online experience for people with visual impairments, those with cognitive and learning disabilities, or those with limited bandwidth or slow internet connections.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.w3.org/TR/WCAG21/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Web Content Accessibility Guidelines (WCAG) 2.1</div><div class="kg-bookmark-description">Web Content Accessibility Guidelines (WCAG) 2.1 covers a wide range of recommendations for making Web content more accessible. Following these guidelines will make content more accessible to a wider range of people with disabilities, including accommodations for blindness and low vision, deafness an…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.w3.org/favicon.ico" alt=""><span class="kg-bookmark-author">W3C</span><span class="kg-bookmark-publisher">Andrew Kirkpatrick</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://www.w3.org/StyleSheets/TR/2016/logos/W3C" alt=""></div></a></figure><p>Despite the importance of image descriptions, a study by WebAIM found that only 66.3% of images on the top one million websites had alt text attributes in 2020. This demonstrates that there is still considerable room for improvement in ensuring that websites and applications are accessible to all users. Manual creation of image descriptions is often time-consuming and can be inconsistent in quality.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://webaim.org/projects/million/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">WebAIM: The WebAIM Million - The 2023 report on the accessibility of the top 1,000,000 home pages</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://webaim.org/media/favicon.ico" alt=""><span class="kg-bookmark-author">The 2023 report on the accessibility of the top 1,000,000 home pages</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://webaim.org/projects/million/media/HomePageElements2023.png" alt=""></div></a></figure><p>As we move into the era of artificial intelligence, there have been efforts to leverage AI-driven solutions to create image descriptions more efficiently. However, these solutions have their own set of limitations and shortcomings. In the following section, we will explore the challenges with existing image captioning solutions and discuss the need for more advanced and reliable tools to support digital accessibility efforts.</p><h2 id="challenges-with-existing-image-captioning-solutions"><br>Challenges with Existing Image Captioning Solutions</h2><p>To understand the challenges with existing image captioning solutions, we will examine the common issues faced by both industry tools and academic approaches to image description generation.</p><h3 id="overly-simplified-or-generic-captions">Overly Simplified or Generic Captions</h3><p>One significant issue with existing image captioning solutions is the generation of overly simplified or generic captions. While these captions may be accurate in a broad sense, they often lack the necessary detail or context to provide a comprehensive understanding of the image. This shortcoming can be especially problematic for users relying on alt text for image comprehension.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-4.png" class="kg-image" alt="" width="1719" height="1162" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-4.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-4.png 1719w" sizes="(min-width: 720px) 720px"><figcaption>"A man and a dog" is given by most image captioning algorithms where there are more objects and stories behind the scene. Why are they camping? What are they doing outside, and does the backpack on the right suggest anything? <a href="https://explorersweb.com/first-dog-10th-man-to-walk-around-the-world/?ref=jina-ai-gmbh.ghost.io">Source</a></figcaption></figure><h3 id="missing-nuances-and-relationships">Missing Nuances and Relationships</h3><p>Another challenge current image captioning algorithms face is their inability to capture the nuanced relationships between objects in a scene. In many cases, these solutions may accurately identify individual objects but fail to describe the interactions or spatial relationships between them, resulting in a less informative image description.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-5.png" class="kg-image" alt="" width="565" height="381"><figcaption>A captioning algorithm that simply emits "Object A and Object B" is far from enough.The spatial relation between them conveys very different meanings. <a href="https://www.sciencedirect.com/science/article/abs/pii/S0166361516300598?ref=jina-ai-gmbh.ghost.io">Source</a></figcaption></figure><h3 id="handling-noise-and-bad-image-quality">Handling Noise and Bad Image Quality </h3><p>Existing image captioning solutions often struggle with handling noisy or poor-quality images. In cases where the image has artifacts, low resolution, or poor lighting, these algorithms may fail to identify the correct objects or actions in the scene, leading to inaccurate or irrelevant captions. Users who rely on image descriptions for accessibility may face difficulties in understanding the true context of the image when the generated captions fail to accurately describe the content due to noise or bad quality.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-6.png" class="kg-image" alt="" width="727" height="285" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-6.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-6.png 727w" sizes="(min-width: 720px) 720px"><figcaption>The original image is "attacked" using the adversarial perturbation shown in the middle; as a result, the image caption algorithm mis-classifies the example although the change is ‐ for human eyes ‐ not perceivable. Source: Daniel Jakubovitz and Raja Giryes. <i>Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization</i>. In: arXiv.org abs/1803.08680 (2018).</figcaption></figure><h3 id="difficulty-handling-complex-images">Difficulty Handling Complex Images</h3><p>Many existing image captioning algorithms struggle to generate accurate and meaningful captions for complex images. When faced with intricate scenes that contain multiple objects, actions, or interactions, these solutions may produce descriptions that fail to capture the depth and richness of the images they describe.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-7.png" class="kg-image" alt="" width="750" height="422" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-7.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-7.png 750w" sizes="(min-width: 720px) 720px"><figcaption>The caption "The Birth of Venus by Botticelli" is a common output provided by many image captioning algorithms. While it may not be technically incorrect, such a description holds little meaning for a visually impaired person. This caption fails to convey sufficient information to allow them to comprehend the image truly. As an image alt tag, this description falls short in its ability to promote digital accessibility and provide meaningful insight into the visual content.</figcaption></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">👓</div><div class="kg-callout-text">The above image described by SceneXplain<br><br>A captivating rendition of the iconic "Birth of Venus" painting unfolds before the eyes, as the goddess Venus emerges from a seashell. The ethereal beauty is surrounded by mythical beings and celestial figures, including a mermaid, an angel, and a woman bearing a bouquet of flowers. The delicate interplay of these characters creates a sense of enchantment and wonder, as they appear to celebrate the arrival of Venus into the world. This masterful composition invites viewers to delve into the realm of mythology and marvel at the splendor and grace that define this timeless scene.</div></div><p>In summary, existing image captioning solutions from the industry and academia have made significant progress in generating relevant and accurate captions. However, they often fail to provide the detail, context, and nuance necessary for truly accessible image descriptions. This is where SceneXplain can make a real difference, offering a more advanced solution for generating comprehensive and context-rich image descriptions that enhance digital accessibility.</p><h2 id="how-scenexplain-addresses-the-challenges-in-creating-accessible-multimedia-content">How SceneXplain addresses the challenges in creating accessible multimedia content</h2><p>SceneXplain is a cutting-edge AI-driven service that generates sophisticated textual descriptions and reveals the rich narratives hidden within images. It transcends the limitations of conventional captioning algorithms, delivering engaging, concise, and professional image storytelling experiences. With a user-friendly interface, seamless API integration, and robust multilingual support, SceneXplain empowers developers to incorporate its advanced capabilities into their multimodal applications effortlessly.</p><figure class="kg-card kg-image-card"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates--100-.png" class="kg-image" alt="" width="2000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/Jina-AI-Website-Banners-Templates--100-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/Jina-AI-Website-Banners-Templates--100-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/Jina-AI-Website-Banners-Templates--100-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/04/Jina-AI-Website-Banners-Templates--100-.png 2400w" sizes="(min-width: 720px) 720px"></a></figure><h3 id="outperforming-the-competition-scenexplains-consistent-quality-and-performance">Outperforming the Competition: SceneXplain's Consistent Quality and Performance</h3><p>SceneXplain's AI algorithms set the benchmark for consistent quality and performance in image captioning. In a comprehensive comparison with other popular image captioning algorithms and tools, SceneXplain consistently outperformed its competitors, capturing the most detail and context in its descriptions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docs.google.com/spreadsheets/d/1_jNAP0JsvUzEU5CyxUUmckpLWMarFfFGAwuoFrKulsk/edit?ref=jina-ai-gmbh.ghost.io#gid=0"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Benchmark of SceneX, Midjourney, BLIP2, CLIPInterogator2</div><div class="kg-bookmark-description">Sheet1 id,image,SceneX,Midjourney /describe,CLIP Interrogator 2.1,BLIP2tE8WEjOKtuWf7fInIofg,https://storage.googleapis.com/causal-diffusion.appspot.com/imagePrompts%2F0rw369i5h9t%2Foriginal.png,In a heartwarming scene, Totoro and a young girl find themselves caught in the rain. The girl, equipp…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ssl.gstatic.com/docs/spreadsheets/favicon3.ico" alt=""><span class="kg-bookmark-author">Google Docs</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://lh3.googleusercontent.com/docs/AG8NV2YLnglaSjXiMzpATWn0PwP1blZ-WM-jl6QbEhwwbTcKK0F-iUK3062XmUy2eONTmrVFvPQEwIJ0mMNxJm8Bp7eEMPz6XiPowp02oM_Hg9P_=w1200-h630-p" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-unleash-advanced-image-captioning-storytelling/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain: Unleash the Advanced Image Captioning &amp; Storytelling</div><div class="kg-bookmark-description">Uncover the game-changing potential of SceneXplain, an advanced image captioning solution powered by LLMs. Check out the benchmark against Midjourney, CLIP, BLIP2, and other alternatives. Dive into our blog post and experience the revolution firsthand!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates--98-.png" alt=""></div></a></figure><p>SceneXplain accurately depicts spatial relationships between objects and characters within a scene, creating rich and engaging storytelling that brings images to life. Although there is a minor tendency to hallucinate certain aspects of the scene, this can be attributed to the model's training on a vast amount of data, enabling it to make educated guesses based on similar scenarios it has encountered. Despite this, SceneXplain's performance is unrivaled, providing clear and meaningful image descriptions suitable for use as image alt tags or accessibility text for visually impaired individuals.</p><p>In contrast, solutions like Midjourney /describe and CLIP Interrogator 2.1 focus on generating creative prompts for images, rather than easily readable natural language descriptions. Meanwhile, BLIP2 generates short and concise captions, which may be suitable for simple scenes but often fail to capture more complex visuals' nuances and intricate details. Some examples are shown below; full<a href="https://docs.google.com/spreadsheets/d/1_jNAP0JsvUzEU5CyxUUmckpLWMarFfFGAwuoFrKulsk/edit?ref=jina-ai-gmbh.ghost.io#gid=0"> 30 images evaluation can be found here.</a></p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-12.png" class="kg-image" alt="" width="464" height="367"><figcaption><code>SceneX</code>: In a scene replete with historical and emotional significance, a woman proudly hoists the French flag, symbolizing the Liberation of Paris. A group of men brandishing weapons stands nearby, prepared to defend their cause. Among them, a young boy clutches his gun with determination. The tableau is interspersed with poignant scenes, such as the Crucifixion of Jesus and groups of people lying on the ground, evoking a sense of sacrifice and resilience. This powerful image serves as a testament to the human spirit and its capacity for triumph in the face of adversity.<code>Midjourney /describe</code>: the liberation of paris in 1832 by gustave lutin, in the style of feminist art and contemporary feminist, light navy and dark bronze, heavy use of palette knives, irony, trompe-l'œil illusionistic detail, rangercore, joyful chaos --ar 58:45<code>BLIP2</code>: liberty leading the people<code>CLIP Interrogator 2.1</code>: a painting of a woman holding a flag, an album cover, by Eugene Delacroix, flickr, arms held high in triumph, iconic shot, menacing!!!, trending photo</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-13.png" class="kg-image" alt="" width="1024" height="512" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-13.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-13.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-13.png 1024w" sizes="(min-width: 720px) 720px"><figcaption><code>SceneX</code>: An eye-catching billboard displays the phrase "DTF Head Over Heels," capturing the attention of passersby with its vibrant imagery and bold statement. The advertisement features various romantic scenarios, including two women sharing a tender kiss against a backdrop of a pink sky, a man and woman embracing in a heartfelt hug, and another pair of women hugging affectionately. The billboard also showcases more unconventional elements, such as a close-up of a woman's feet and the silhouette of an expectant mother. An OkCupid dating design adds context to these diverse depictions of love and relationships, inviting viewers to contemplate the vast spectrum of human connection and emotion embodied in this striking visual display.<code>Midjourney /describe</code>: the billboard dtf head-over-heels , in the style of feminine imagery, humor meets heart, humor meets heart, colorized, playful imagery, hikecore, sandalpunk --ar 2:1<code>BLIP2</code>: a billboard with the words dtf all over heels<code>CLIP Interrogator 2.1</code>: a billboard that says dtf all head over heels, by Adam Dario Keel, cupid, ocult, product placement, attractive female</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-14.png" class="kg-image" alt="" width="800" height="533" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-14.png 800w" sizes="(min-width: 720px) 720px"><figcaption><code>SceneX</code>: A bustling city street teems with life as pedestrians traverse the urban landscape, surrounded by an array of buildings that impart a sense of metropolitan charm. The heart of Berlin, Germany, reveals itself in this dynamic scene, where people walk along the sidewalks and a tram awaits passengers at a nearby train station. The vibrant atmosphere is palpable as individuals go about their daily routines, navigating the streets and engaging with their surroundings. This lively tableau encapsulates the essence of city living, showcasing the energy and excitement inherent in urban environments.<code>Midjourney /describe</code>: a busy city street with a bus driving, in the style of deutscher werkbund, consumer culture critique, impressive panoramas, award-winning, poignant, passage, hypnotic symmetry --ar 50:33<code>BLIP2</code>: a busy city street with people walking and cars driving<code>CLIP Interrogator 2.1</code>: a street filled with lots of traffic next to tall buildings, by Micha Klein, shutterstock, berlin secession, tram, stock photo, people at work, stock image</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-15.png" class="kg-image" alt="" width="1024" height="678" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-15.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-15.png 1024w" sizes="(min-width: 720px) 720px"><figcaption><code>SceneX</code>: In a bustling medieval theater, two valiant knights clad in armor engage in a thrilling joust, their lances poised for impact. The audience, dressed in period attire, watches the spectacle with bated breath. Among the onlookers are groups of men and women adorned with hats, their keen eyes following the action. Behind the scenes, a pigeon rests in its cage, seemingly indifferent to the excitement unfolding before it. This riveting scene transports viewers to a bygone era of chivalry and pageantry, where honor and bravery were celebrated through thrilling contests of skill and strength.<code>Midjourney /describe</code>: a drawing shows two men fighting in an arena, in the style of quirky caricatures, lively interiors, swordpunk, watercolor technique, school of london, ritualistic masks, grid-based --ar 32:21<code>BLIP2</code>: a drawing of men fighting in the middle of a crowd<code>CLIP Interrogator 2.1</code>: a couple of men standing next to each other on a stage, by George Cruikshank, shutterstock, renaissance, facing off in a duel, in medieval armoury, school class, still image from the movie</figcaption></figure><p>SceneXplain's advanced capabilities and versatility make it a powerful tool for a wide range of applications, from providing image alt tags for accessibility to enhancing user experiences with engaging visual storytelling. With its consistent quality and performance, SceneXplain is the best choice for organizations seeking to improve digital accessibility through accurate, detailed, and contextually rich image descriptions.</p><h3 id="resilience-to-noise-and-varying-image-quality">Resilience to noise and varying image quality</h3><p>SceneXplain's robust AI algorithms have been designed to handle varying image quality and noise levels, ensuring that the generated descriptions remain accurate and relevant even when the input image is less than ideal.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.58421 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-10.png" width="1204" height="760" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-10.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-10.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-10.png 1204w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50995 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-9.png" width="1214" height="804" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-9.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-9.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-9.png 1214w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.51128 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-16.png" width="1206" height="798" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-16.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-16.png 1206w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.5733 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-17.png" width="1202" height="764" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-17.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-17.png 1202w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>SceneXplain descriptions for the original (top-left) and the noisy variants.</figcaption></figure><h3 id="multilingual-support-for-enhanced-accessibility">Multilingual Support for Enhanced Accessibility</h3><p>One of the key features of SceneXplain that sets it apart from other image captioning solutions is its robust multilingual support. Catering to the diverse linguistic landscape of the European Union and beyond, SceneXplain can generate context-rich image descriptions in multiple languages, making it an invaluable tool for enhancing accessibility on a global scale.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/04/af7d2ee6fde456c928fae730fd85287c.mp4" poster="https://img.spacergif.org/v1/1742x618/0a/spacer.png" width="1742" height="618" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/04/media-thumbnail-ember734.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>This multilingual capability allows organizations to provide accurate and engaging image descriptions to users of different languages, ensuring their content is accessible to a broader audience. By offering this linguistic versatility, SceneXplain demonstrates its commitment to fostering an inclusive digital environment that embraces the rich cultural and linguistic diversity of the European Union and the world.</p><p>By addressing these key challenges, SceneXplain is poised to revolutionize the way accessible multimedia content is created and consumed. Its advanced capabilities hold great potential for enhancing the digital accessibility landscape, making the web a more inclusive space for all users.</p><h2 id="ensuring-compliance-with-european-accessibility-standards">Ensuring Compliance with European Accessibility Standards</h2><p>Digital accessibility has become a priority for governments and organizations around the world. In Europe, several regulations and guidelines have been established to ensure digital content is accessible to all users, including those with disabilities. The Web Content Accessibility Guidelines (WCAG) are globally recognized recommendations for making web content more accessible. Additionally, the European Union has implemented the Web Accessibility Directive, which requires public sector organizations to adhere to WCAG 2.1 Level AA standards.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://digital-barrierefrei.de/rechtsgrundlagen.php?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Digitale Barrierefreiheit München | Rechtliche Grundlagen</div><div class="kg-bookmark-description">Im Zusammenhang mit digitaler Barrierefreiheit werden viele Richtlinien und Verordnungen genannt. Nachfolgend eine kurze Erläuterung der wichtigsten Begriffe: BITV 2.0, WCAG 2.1, EU-Richtlinie 2016/2102</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://digital-barrierefrei.de/favicon.ico" alt=""><span class="kg-bookmark-author">Logo Digital Barrierefrei - zur Startseite</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://digital-barrierefrei.de/images/digital-barrierefrei-logo.jpg" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://digital-strategy.ec.europa.eu/en/policies/web-accessibility?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Web Accessibility</div><div class="kg-bookmark-description">What is web accessibility? Web accessibility allows everyone, including people with disabilities, to perceive, understand, navigate and interact with the Internet.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://chatbot-cnect.s3.eu-central-1.amazonaws.com/avatars/chatbot-dsm-icon.png" alt=""><span class="kg-bookmark-author">Shaping Europe’s digital future</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://digital-strategy.ec.europa.eu/sites/default/files/styles/extra_large/public/2021-03/accessibility-key.jpg?itok=lVEV6amH" alt=""></div></a></figure><p>According to the European Commission, around 80 million Europeans have a disability. With the growing need for accessible content, non-compliance with accessibility regulations can lead to lawsuits and fines. In 2018, a study conducted by the European Disability Forum found that 89% of European public sector websites failed to meet accessibility standards, highlighting the urgent need for improvement.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://digital-strategy.ec.europa.eu/en/library/study-supporting-review-web-accessibility-directive?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Study supporting the review of the Web Accessibility Directive</div><div class="kg-bookmark-description">The aim of the study is to support the review of the Web Accessibility Directive and its implementing acts, covering the first three years of their application (2018-2021).</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://chatbot-cnect.s3.eu-central-1.amazonaws.com/avatars/chatbot-dsm-icon.png" alt=""><span class="kg-bookmark-author">Shaping Europe’s digital future</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://digital-strategy.ec.europa.eu/sites/default/files/styles/large/public/newsroom/items/GettyImages1147350187__GOCMEN__iStock_Getty_Images_Plus_k0d5ioZfq327rJTgDftyvrRdU94_112636.jpg?itok=QVjhr2UH" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.edf-feph.org/web-accessibility-directive/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Web Accessibility Directive - European Disability Forum</div><div class="kg-bookmark-description">Web Accessibility Directive</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.edf-feph.org/content/uploads/2019/07/48-x-48@3x.png" alt=""><span class="kg-bookmark-author">European Disability Forum</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://www.edf-feph.org/content/uploads/2019/07/48-x-48@3x.png" alt=""></div></a></figure><h3 id="how-scenexplain-helps-organizations-meet-accessibility-requirements">How SceneXplain Helps Organizations Meet Accessibility Requirements</h3><p>SceneXplain is designed to help organizations comply with European accessibility standards by providing accurate, detailed, and contextually rich image descriptions. By integrating SceneXplain's advanced image captioning capabilities, public sector websites and applications can generate image alt tags and other accessible multimedia content that adheres to the WCAG 2.1 Level AA guidelines. This ensures visually impaired users can better understand and engage with the content, resulting in a more inclusive digital experience.</p><p>SceneXplain's multilingual support further enhances its potential to meet accessibility requirements in the European context. By providing context-rich translations for image descriptions, SceneXplain enables organizations to cater to the diverse linguistic needs of users across the EU, ensuring that content remains accessible in multiple languages.</p><h3 id="benefits-of-using-scenexplain-in-public-sector-websites-and-applications">Benefits of Using SceneXplain in Public Sector Websites and Applications</h3><p>There are several benefits to incorporating SceneXplain into public sector websites and applications:</p><ol><li><strong>Improved Accessibility:</strong> SceneXplain's advanced image captioning algorithms generate detailed and accurate descriptions, ensuring that visually impaired users can better understand and engage with multimedia content.</li><li><strong>Compliance with Regulations</strong>: Integrating SceneXplain helps public sector organizations comply with the Web Accessibility Directive and WCAG 2.1 Level AA guidelines, minimizing the risk of non-compliance penalties. In recent years, several high-profile lawsuits have involved website accessibility, emphasizing the importance of adhering to these guidelines to avoid legal repercussions.</li><li><strong>Enhanced User Experience:</strong> By providing engaging and informative image descriptions, SceneXplain enriches the overall user experience for all users, not just those with disabilities.</li><li><strong>Multilingual Support:</strong> SceneXplain's ability to generate context-rich translations for image descriptions enables organizations to cater to the diverse linguistic needs of users across the EU, further enhancing accessibility.</li></ol><p>By leveraging SceneXplain's advanced image captioning capabilities, European public sector organizations can ensure compliance with accessibility standards and create a more inclusive digital environment for all users. The urgency of adhering to these regulations is highlighted by the growing number of people with disabilities, the risk of lawsuits, and the need to provide everyone with equal access to digital content.</p><h2 id="integration-process-of-scenexplain-with-public-sector-websites-and-applications">Integration Process of SceneXplain with Public Sector Websites and Applications</h2><p>Integrating SceneXplain with public sector websites and applications can significantly enhance digital accessibility. SceneXplain offers multiple integration options to cater to the diverse needs of organizations. Here, we will explore three ways to integrate SceneXplain:</p><h3 id="create-accessible-image-via-scenexplain-ui">Create Accessible Image via SceneXplain UI</h3><p>SceneXplain's user-friendly web interface allows organizations to quickly and easily generate image descriptions without the need for extensive technical knowledge. By uploading images directly to the web platform, users can obtain detailed textual descriptions that can then be incorporated into their website's image alt tags or other accessibility features. This approach is ideal for organizations with limited technical resources or those who require occasional image captioning services.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-11.png" class="kg-image" alt="" width="1960" height="1132" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-11.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-11.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-11.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-11.png 1960w" sizes="(min-width: 720px) 720px"><figcaption>You can use SceneXplain on either desktop or mobile device.</figcaption></figure><h3 id="batch-process-images-via-scenexplain-api">Batch Process Images via SceneXplain API</h3><p>For organizations seeking an automated and seamless integration, SceneXplain offers a robust, scalable, and secure API for their systems. The fast batch API allows describing up to 128 images in one batch within 40 seconds, ideal for those requiring high volumes of image captioning services.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-18.png" class="kg-image" alt="" width="1980" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-18.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-18.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-18.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-18.png 1980w" sizes="(min-width: 720px) 720px"></figure><p>Organizations can automatically generate image descriptions by connecting SceneXplain's API to websites or applications, ensuring accessibility compliance with European standards. The API integration suits organizations with dedicated technical teams or those needing large-scale image captioning. Secure data handling ensures privacy and data protection during integration, providing a seamless experience while enhancing digital accessibility for all users.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-21.png" class="kg-image" alt="" width="2000" height="1151" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-21.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/04/image-21.png 2400w" sizes="(min-width: 720px) 720px"></figure><h3 id="privacy-preserved-solution-in-on-prem">Privacy-Preserved Solution in On-prem</h3><p>SceneXplain also provides an on-premises solution for organizations that prefer to maintain full control over their data and systems. By deploying SceneXplain on their servers, organizations can ensure that their sensitive data remains within their network while benefiting from the advanced image captioning capabilities of SceneXplain. This option is particularly relevant for public sector organizations with strict data security and privacy requirements.</p><div class="kg-card kg-button-card kg-align-center"><a href="mailto:scenex@jina.ai" class="kg-btn kg-btn-accent">Book a call with our team about the on-prem solution</a></div><p>Each integration option offers unique benefits and caters to different organizational needs. By choosing the most suitable integration method, public sector organizations can effectively harness the power of SceneXplain to enhance digital accessibility and comply with European accessibility regulations.</p><h2 id="conclusion">Conclusion</h2><p>In conclusion, SceneXplain is a groundbreaking solution advancing digital accessibility in the public sector. By leveraging its advanced AI capabilities, SceneXplain generates precise, context-rich, and engaging image descriptions, ensuring that multimedia content is accessible to all users, including those with visual impairments.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-20.png" class="kg-image" alt="" width="1344" height="896" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-20.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-20.png 1344w" sizes="(min-width: 720px) 720px"></figure><p>As digital accessibility becomes increasingly essential, public sector organizations must adopt innovative tools like SceneXplain to meet the demands of an inclusive online experience. Integrating SceneXplain not only ensures compliance with European accessibility standards but also enhances the overall user experience for all citizens.</p><p>Now is the time for public sector organizations to take the initiative and harness the power of SceneXplain to create a more inclusive digital landscape. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Explore SceneXplain's impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 07, 2023 • 17 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>On a crisp autumn morning in Paris, Marie, a visually impaired woman in her early thirties, settles down in her favorite café with a warm cup of coffee. She eagerly opens her smartphone and navigates to a popular news website using her screen reader. As Marie listens to the headlines, she stumbles upon an article about a groundbreaking art exhibition. </p><p>"I wonder what the artwork looks like," she thinks aloud, as the screen reader describes the images as "Photo 1" and "Photo 2." </p><p>Frustrated, she sighs, "If only I could get a sense of the art, too."</p><p>Marie's experience is not unique; millions of visually impaired individuals worldwide face similar challenges in accessing digital content. According to the World Health Organization, there are approximately 285 million visually impaired people worldwide, with 39 million being blind. Digital accessibility is a critical issue, especially for the public sector. Governments and organizations are responsible for ensuring that their digital platforms are inclusive and accessible to all citizens, regardless of their abilities. A 2020 report by the European Commission found that only 34% of public sector websites in the EU met basic accessibility standards, highlighting the urgent need for improvement.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.who.int/news-room/fact-sheets/detail/blindness-and-visual-impairment?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Vision impairment and blindness</div><div class="kg-bookmark-description">WHO fact sheet on blindness and visual impairment providing key facts, definitions, causes, who is at risk, global and WHO response.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.who.int/apple-touch-icon-precomposed.png" alt=""><span class="kg-bookmark-author">World Health Organization</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn.who.int/media/images/default-source/imported/vision-impairment-fact-sheet.tmb-1200v.jpg?sfvrsn=9dcda712_12" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://op.europa.eu/en/publication-detail/-/publication/8eb9074c-8712-454b-9a7d-5c13d10f8f4e?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Monitoring e-accessibility in Europe: 2010-2011 : annual report.</div><div class="kg-bookmark-description">Developments in European Union (EU) policies over the past decade have increasingly acknowledged that inclusive Information and Communication Technologies (ICT) and Assistive Technologies (AT) are essential to ensuring full participation in society for many of the population segments at risk of digi…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://op.europa.eu/o/OPPortalEE/images/favicon.ico" alt=""><span class="kg-bookmark-author">DisplayLogo Publications Office of the European Union</span><span class="kg-bookmark-publisher">CNIPA</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://op.europa.eu/o/opportal-service/thumbnail/cellar/8eb9074c-8712-454b-9a7d-5c13d10f8f4e.0001.01/DOC_2" alt=""></div></a></figure><p>One of the key components of web accessibility is providing descriptive information for images, commonly known as <a href="https://www.w3schools.com/tags/att_img_alt.asp?ref=jina-ai-gmbh.ghost.io">"alt text"</a> or <a href="https://accessibility.huit.harvard.edu/describe-content-images?ref=jina-ai-gmbh.ghost.io">"image descriptions."</a> A well-written image description can convey the essence of an image, allowing visually impaired users to comprehend the content and context of the image. However, even for seasoned content creators, crafting accurate and informative image descriptions is not always easy. This is where SceneXplain, a groundbreaking AI-driven solution, steps in to revolutionize how we create accessible multimedia content.</p><p>This article will explore the significance of digital accessibility, the role of image descriptions, and the challenges with existing solutions. We will then introduce <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a>, its advantages, and its potential applications in enhancing digital accessibility for the public sector. We will also discuss how SceneXplain can help organizations comply with European accessibility regulations and provide a roadmap for implementing SceneXplain in public sector websites and applications.</p><h2 id="the-role-of-image-descriptions-in-web-accessibility">The Role of Image Descriptions in Web Accessibility</h2><p>Image descriptions, also known as "alt text" or "alternative text," play a vital role in web accessibility by providing a textual representation of the visual content for users who cannot perceive it. The concept of image alt text dates back to the early days of the World Wide Web. As an example, an HTML code snippet for including an image with alt text would look like this:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-3.png" class="kg-image" alt="" width="612" height="408" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-3.png 612w"></figure><pre><code class="language-html">&lt;img src="image.jpg" alt="A beautiful sunset with the sun setting behind a mountain"&gt;
+</code></pre><p>In this example, the alt text "A beautiful sunset with the sun setting behind a mountain" briefly describes the image, which can be read by assistive technologies or displayed when the image fails to load.</p><p>According to the Web Content Accessibility Guidelines (WCAG) 2.1, providing text alternatives for non-text content is one of the fundamental principles of web accessibility. This ensures that users who rely on assistive technologies, such as screen readers, can access and understand the visual information on websites and applications. Image descriptions are crucial in providing an inclusive and equitable online experience for people with visual impairments, those with cognitive and learning disabilities, or those with limited bandwidth or slow internet connections.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.w3.org/TR/WCAG21/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Web Content Accessibility Guidelines (WCAG) 2.1</div><div class="kg-bookmark-description">Web Content Accessibility Guidelines (WCAG) 2.1 covers a wide range of recommendations for making Web content more accessible. Following these guidelines will make content more accessible to a wider range of people with disabilities, including accommodations for blindness and low vision, deafness an…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.w3.org/favicon.ico" alt=""><span class="kg-bookmark-author">W3C</span><span class="kg-bookmark-publisher">Andrew Kirkpatrick</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://www.w3.org/StyleSheets/TR/2016/logos/W3C" alt=""></div></a></figure><p>Despite the importance of image descriptions, a study by WebAIM found that only 66.3% of images on the top one million websites had alt text attributes in 2020. This demonstrates that there is still considerable room for improvement in ensuring that websites and applications are accessible to all users. Manual creation of image descriptions is often time-consuming and can be inconsistent in quality.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://webaim.org/projects/million/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">WebAIM: The WebAIM Million - The 2023 report on the accessibility of the top 1,000,000 home pages</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://webaim.org/media/favicon.ico" alt=""><span class="kg-bookmark-author">The 2023 report on the accessibility of the top 1,000,000 home pages</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://webaim.org/projects/million/media/HomePageElements2023.png" alt=""></div></a></figure><p>As we move into the era of artificial intelligence, there have been efforts to leverage AI-driven solutions to create image descriptions more efficiently. However, these solutions have their own set of limitations and shortcomings. In the following section, we will explore the challenges with existing image captioning solutions and discuss the need for more advanced and reliable tools to support digital accessibility efforts.</p><h2 id="challenges-with-existing-image-captioning-solutions"><br>Challenges with Existing Image Captioning Solutions</h2><p>To understand the challenges with existing image captioning solutions, we will examine the common issues faced by both industry tools and academic approaches to image description generation.</p><h3 id="overly-simplified-or-generic-captions">Overly Simplified or Generic Captions</h3><p>One significant issue with existing image captioning solutions is the generation of overly simplified or generic captions. While these captions may be accurate in a broad sense, they often lack the necessary detail or context to provide a comprehensive understanding of the image. This shortcoming can be especially problematic for users relying on alt text for image comprehension.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-4.png" class="kg-image" alt="" width="1719" height="1162" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-4.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-4.png 1719w" sizes="(min-width: 720px) 720px"><figcaption>"A man and a dog" is given by most image captioning algorithms where there are more objects and stories behind the scene. Why are they camping? What are they doing outside, and does the backpack on the right suggest anything? <a href="https://explorersweb.com/first-dog-10th-man-to-walk-around-the-world/?ref=jina-ai-gmbh.ghost.io">Source</a></figcaption></figure><h3 id="missing-nuances-and-relationships">Missing Nuances and Relationships</h3><p>Another challenge current image captioning algorithms face is their inability to capture the nuanced relationships between objects in a scene. In many cases, these solutions may accurately identify individual objects but fail to describe the interactions or spatial relationships between them, resulting in a less informative image description.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-5.png" class="kg-image" alt="" width="565" height="381"><figcaption>A captioning algorithm that simply emits "Object A and Object B" is far from enough.The spatial relation between them conveys very different meanings. <a href="https://www.sciencedirect.com/science/article/abs/pii/S0166361516300598?ref=jina-ai-gmbh.ghost.io">Source</a></figcaption></figure><h3 id="handling-noise-and-bad-image-quality">Handling Noise and Bad Image Quality </h3><p>Existing image captioning solutions often struggle with handling noisy or poor-quality images. In cases where the image has artifacts, low resolution, or poor lighting, these algorithms may fail to identify the correct objects or actions in the scene, leading to inaccurate or irrelevant captions. Users who rely on image descriptions for accessibility may face difficulties in understanding the true context of the image when the generated captions fail to accurately describe the content due to noise or bad quality.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-6.png" class="kg-image" alt="" width="727" height="285" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-6.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-6.png 727w" sizes="(min-width: 720px) 720px"><figcaption>The original image is "attacked" using the adversarial perturbation shown in the middle; as a result, the image caption algorithm mis-classifies the example although the change is ‐ for human eyes ‐ not perceivable. Source: Daniel Jakubovitz and Raja Giryes. <i>Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization</i>. In: arXiv.org abs/1803.08680 (2018).</figcaption></figure><h3 id="difficulty-handling-complex-images">Difficulty Handling Complex Images</h3><p>Many existing image captioning algorithms struggle to generate accurate and meaningful captions for complex images. When faced with intricate scenes that contain multiple objects, actions, or interactions, these solutions may produce descriptions that fail to capture the depth and richness of the images they describe.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-7.png" class="kg-image" alt="" width="750" height="422" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-7.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-7.png 750w" sizes="(min-width: 720px) 720px"><figcaption>The caption "The Birth of Venus by Botticelli" is a common output provided by many image captioning algorithms. While it may not be technically incorrect, such a description holds little meaning for a visually impaired person. This caption fails to convey sufficient information to allow them to comprehend the image truly. As an image alt tag, this description falls short in its ability to promote digital accessibility and provide meaningful insight into the visual content.</figcaption></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">👓</div><div class="kg-callout-text">The above image described by SceneXplain<br><br>A captivating rendition of the iconic "Birth of Venus" painting unfolds before the eyes, as the goddess Venus emerges from a seashell. The ethereal beauty is surrounded by mythical beings and celestial figures, including a mermaid, an angel, and a woman bearing a bouquet of flowers. The delicate interplay of these characters creates a sense of enchantment and wonder, as they appear to celebrate the arrival of Venus into the world. This masterful composition invites viewers to delve into the realm of mythology and marvel at the splendor and grace that define this timeless scene.</div></div><p>In summary, existing image captioning solutions from the industry and academia have made significant progress in generating relevant and accurate captions. However, they often fail to provide the detail, context, and nuance necessary for truly accessible image descriptions. This is where SceneXplain can make a real difference, offering a more advanced solution for generating comprehensive and context-rich image descriptions that enhance digital accessibility.</p><h2 id="how-scenexplain-addresses-the-challenges-in-creating-accessible-multimedia-content">How SceneXplain addresses the challenges in creating accessible multimedia content</h2><p>SceneXplain is a cutting-edge AI-driven service that generates sophisticated textual descriptions and reveals the rich narratives hidden within images. It transcends the limitations of conventional captioning algorithms, delivering engaging, concise, and professional image storytelling experiences. With a user-friendly interface, seamless API integration, and robust multilingual support, SceneXplain empowers developers to incorporate its advanced capabilities into their multimodal applications effortlessly.</p><figure class="kg-card kg-image-card"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates--100-.png" class="kg-image" alt="" width="2000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/Jina-AI-Website-Banners-Templates--100-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/Jina-AI-Website-Banners-Templates--100-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/Jina-AI-Website-Banners-Templates--100-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/04/Jina-AI-Website-Banners-Templates--100-.png 2400w" sizes="(min-width: 720px) 720px"></a></figure><h3 id="outperforming-the-competition-scenexplains-consistent-quality-and-performance">Outperforming the Competition: SceneXplain's Consistent Quality and Performance</h3><p>SceneXplain's AI algorithms set the benchmark for consistent quality and performance in image captioning. In a comprehensive comparison with other popular image captioning algorithms and tools, SceneXplain consistently outperformed its competitors, capturing the most detail and context in its descriptions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docs.google.com/spreadsheets/d/1_jNAP0JsvUzEU5CyxUUmckpLWMarFfFGAwuoFrKulsk/edit?ref=jina-ai-gmbh.ghost.io#gid=0"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Benchmark of SceneX, Midjourney, BLIP2, CLIPInterogator2</div><div class="kg-bookmark-description">Sheet1 id,image,SceneX,Midjourney /describe,CLIP Interrogator 2.1,BLIP2tE8WEjOKtuWf7fInIofg,https://storage.googleapis.com/causal-diffusion.appspot.com/imagePrompts%2F0rw369i5h9t%2Foriginal.png,In a heartwarming scene, Totoro and a young girl find themselves caught in the rain. The girl, equipp…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ssl.gstatic.com/docs/spreadsheets/favicon3.ico" alt=""><span class="kg-bookmark-author">Google Docs</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://lh3.googleusercontent.com/docs/AG8NV2YLnglaSjXiMzpATWn0PwP1blZ-WM-jl6QbEhwwbTcKK0F-iUK3062XmUy2eONTmrVFvPQEwIJ0mMNxJm8Bp7eEMPz6XiPowp02oM_Hg9P_=w1200-h630-p" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-unleash-advanced-image-captioning-storytelling/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain: Unleash the Advanced Image Captioning &amp; Storytelling</div><div class="kg-bookmark-description">Uncover the game-changing potential of SceneXplain, an advanced image captioning solution powered by LLMs. Check out the benchmark against Midjourney, CLIP, BLIP2, and other alternatives. Dive into our blog post and experience the revolution firsthand!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates--98-.png" alt=""></div></a></figure><p>SceneXplain accurately depicts spatial relationships between objects and characters within a scene, creating rich and engaging storytelling that brings images to life. Although there is a minor tendency to hallucinate certain aspects of the scene, this can be attributed to the model's training on a vast amount of data, enabling it to make educated guesses based on similar scenarios it has encountered. Despite this, SceneXplain's performance is unrivaled, providing clear and meaningful image descriptions suitable for use as image alt tags or accessibility text for visually impaired individuals.</p><p>In contrast, solutions like Midjourney /describe and CLIP Interrogator 2.1 focus on generating creative prompts for images, rather than easily readable natural language descriptions. Meanwhile, BLIP2 generates short and concise captions, which may be suitable for simple scenes but often fail to capture more complex visuals' nuances and intricate details. Some examples are shown below; full<a href="https://docs.google.com/spreadsheets/d/1_jNAP0JsvUzEU5CyxUUmckpLWMarFfFGAwuoFrKulsk/edit?ref=jina-ai-gmbh.ghost.io#gid=0"> 30 images evaluation can be found here.</a></p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-12.png" class="kg-image" alt="" width="464" height="367"><figcaption><code>SceneX</code>: In a scene replete with historical and emotional significance, a woman proudly hoists the French flag, symbolizing the Liberation of Paris. A group of men brandishing weapons stands nearby, prepared to defend their cause. Among them, a young boy clutches his gun with determination. The tableau is interspersed with poignant scenes, such as the Crucifixion of Jesus and groups of people lying on the ground, evoking a sense of sacrifice and resilience. This powerful image serves as a testament to the human spirit and its capacity for triumph in the face of adversity.<code>Midjourney /describe</code>: the liberation of paris in 1832 by gustave lutin, in the style of feminist art and contemporary feminist, light navy and dark bronze, heavy use of palette knives, irony, trompe-l'œil illusionistic detail, rangercore, joyful chaos --ar 58:45<code>BLIP2</code>: liberty leading the people<code>CLIP Interrogator 2.1</code>: a painting of a woman holding a flag, an album cover, by Eugene Delacroix, flickr, arms held high in triumph, iconic shot, menacing!!!, trending photo</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-13.png" class="kg-image" alt="" width="1024" height="512" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-13.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-13.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-13.png 1024w" sizes="(min-width: 720px) 720px"><figcaption><code>SceneX</code>: An eye-catching billboard displays the phrase "DTF Head Over Heels," capturing the attention of passersby with its vibrant imagery and bold statement. The advertisement features various romantic scenarios, including two women sharing a tender kiss against a backdrop of a pink sky, a man and woman embracing in a heartfelt hug, and another pair of women hugging affectionately. The billboard also showcases more unconventional elements, such as a close-up of a woman's feet and the silhouette of an expectant mother. An OkCupid dating design adds context to these diverse depictions of love and relationships, inviting viewers to contemplate the vast spectrum of human connection and emotion embodied in this striking visual display.<code>Midjourney /describe</code>: the billboard dtf head-over-heels , in the style of feminine imagery, humor meets heart, humor meets heart, colorized, playful imagery, hikecore, sandalpunk --ar 2:1<code>BLIP2</code>: a billboard with the words dtf all over heels<code>CLIP Interrogator 2.1</code>: a billboard that says dtf all head over heels, by Adam Dario Keel, cupid, ocult, product placement, attractive female</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-14.png" class="kg-image" alt="" width="800" height="533" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-14.png 800w" sizes="(min-width: 720px) 720px"><figcaption><code>SceneX</code>: A bustling city street teems with life as pedestrians traverse the urban landscape, surrounded by an array of buildings that impart a sense of metropolitan charm. The heart of Berlin, Germany, reveals itself in this dynamic scene, where people walk along the sidewalks and a tram awaits passengers at a nearby train station. The vibrant atmosphere is palpable as individuals go about their daily routines, navigating the streets and engaging with their surroundings. This lively tableau encapsulates the essence of city living, showcasing the energy and excitement inherent in urban environments.<code>Midjourney /describe</code>: a busy city street with a bus driving, in the style of deutscher werkbund, consumer culture critique, impressive panoramas, award-winning, poignant, passage, hypnotic symmetry --ar 50:33<code>BLIP2</code>: a busy city street with people walking and cars driving<code>CLIP Interrogator 2.1</code>: a street filled with lots of traffic next to tall buildings, by Micha Klein, shutterstock, berlin secession, tram, stock photo, people at work, stock image</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-15.png" class="kg-image" alt="" width="1024" height="678" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-15.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-15.png 1024w" sizes="(min-width: 720px) 720px"><figcaption><code>SceneX</code>: In a bustling medieval theater, two valiant knights clad in armor engage in a thrilling joust, their lances poised for impact. The audience, dressed in period attire, watches the spectacle with bated breath. Among the onlookers are groups of men and women adorned with hats, their keen eyes following the action. Behind the scenes, a pigeon rests in its cage, seemingly indifferent to the excitement unfolding before it. This riveting scene transports viewers to a bygone era of chivalry and pageantry, where honor and bravery were celebrated through thrilling contests of skill and strength.<code>Midjourney /describe</code>: a drawing shows two men fighting in an arena, in the style of quirky caricatures, lively interiors, swordpunk, watercolor technique, school of london, ritualistic masks, grid-based --ar 32:21<code>BLIP2</code>: a drawing of men fighting in the middle of a crowd<code>CLIP Interrogator 2.1</code>: a couple of men standing next to each other on a stage, by George Cruikshank, shutterstock, renaissance, facing off in a duel, in medieval armoury, school class, still image from the movie</figcaption></figure><p>SceneXplain's advanced capabilities and versatility make it a powerful tool for a wide range of applications, from providing image alt tags for accessibility to enhancing user experiences with engaging visual storytelling. With its consistent quality and performance, SceneXplain is the best choice for organizations seeking to improve digital accessibility through accurate, detailed, and contextually rich image descriptions.</p><h3 id="resilience-to-noise-and-varying-image-quality">Resilience to noise and varying image quality</h3><p>SceneXplain's robust AI algorithms have been designed to handle varying image quality and noise levels, ensuring that the generated descriptions remain accurate and relevant even when the input image is less than ideal.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-10.png" width="1204" height="760" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-10.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-10.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-10.png 1204w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-9.png" width="1214" height="804" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-9.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-9.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-9.png 1214w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-16.png" width="1206" height="798" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-16.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-16.png 1206w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-17.png" width="1202" height="764" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-17.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-17.png 1202w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>SceneXplain descriptions for the original (top-left) and the noisy variants.</figcaption></figure><h3 id="multilingual-support-for-enhanced-accessibility">Multilingual Support for Enhanced Accessibility</h3><p>One of the key features of SceneXplain that sets it apart from other image captioning solutions is its robust multilingual support. Catering to the diverse linguistic landscape of the European Union and beyond, SceneXplain can generate context-rich image descriptions in multiple languages, making it an invaluable tool for enhancing accessibility on a global scale.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/04/af7d2ee6fde456c928fae730fd85287c.mp4" poster="https://img.spacergif.org/v1/1742x618/0a/spacer.png" width="1742" height="618" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/04/media-thumbnail-ember734.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>This multilingual capability allows organizations to provide accurate and engaging image descriptions to users of different languages, ensuring their content is accessible to a broader audience. By offering this linguistic versatility, SceneXplain demonstrates its commitment to fostering an inclusive digital environment that embraces the rich cultural and linguistic diversity of the European Union and the world.</p><p>By addressing these key challenges, SceneXplain is poised to revolutionize the way accessible multimedia content is created and consumed. Its advanced capabilities hold great potential for enhancing the digital accessibility landscape, making the web a more inclusive space for all users.</p><h2 id="ensuring-compliance-with-european-accessibility-standards">Ensuring Compliance with European Accessibility Standards</h2><p>Digital accessibility has become a priority for governments and organizations around the world. In Europe, several regulations and guidelines have been established to ensure digital content is accessible to all users, including those with disabilities. The Web Content Accessibility Guidelines (WCAG) are globally recognized recommendations for making web content more accessible. Additionally, the European Union has implemented the Web Accessibility Directive, which requires public sector organizations to adhere to WCAG 2.1 Level AA standards.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://digital-barrierefrei.de/rechtsgrundlagen.php?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Digitale Barrierefreiheit München | Rechtliche Grundlagen</div><div class="kg-bookmark-description">Im Zusammenhang mit digitaler Barrierefreiheit werden viele Richtlinien und Verordnungen genannt. Nachfolgend eine kurze Erläuterung der wichtigsten Begriffe: BITV 2.0, WCAG 2.1, EU-Richtlinie 2016/2102</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://digital-barrierefrei.de/favicon.ico" alt=""><span class="kg-bookmark-author">Logo Digital Barrierefrei - zur Startseite</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://digital-barrierefrei.de/images/digital-barrierefrei-logo.jpg" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://digital-strategy.ec.europa.eu/en/policies/web-accessibility?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Web Accessibility</div><div class="kg-bookmark-description">What is web accessibility? Web accessibility allows everyone, including people with disabilities, to perceive, understand, navigate and interact with the Internet.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://chatbot-cnect.s3.eu-central-1.amazonaws.com/avatars/chatbot-dsm-icon.png" alt=""><span class="kg-bookmark-author">Shaping Europe’s digital future</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://digital-strategy.ec.europa.eu/sites/default/files/styles/extra_large/public/2021-03/accessibility-key.jpg?itok=lVEV6amH" alt=""></div></a></figure><p>According to the European Commission, around 80 million Europeans have a disability. With the growing need for accessible content, non-compliance with accessibility regulations can lead to lawsuits and fines. In 2018, a study conducted by the European Disability Forum found that 89% of European public sector websites failed to meet accessibility standards, highlighting the urgent need for improvement.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://digital-strategy.ec.europa.eu/en/library/study-supporting-review-web-accessibility-directive?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Study supporting the review of the Web Accessibility Directive</div><div class="kg-bookmark-description">The aim of the study is to support the review of the Web Accessibility Directive and its implementing acts, covering the first three years of their application (2018-2021).</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://chatbot-cnect.s3.eu-central-1.amazonaws.com/avatars/chatbot-dsm-icon.png" alt=""><span class="kg-bookmark-author">Shaping Europe’s digital future</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://digital-strategy.ec.europa.eu/sites/default/files/styles/large/public/newsroom/items/GettyImages1147350187__GOCMEN__iStock_Getty_Images_Plus_k0d5ioZfq327rJTgDftyvrRdU94_112636.jpg?itok=QVjhr2UH" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.edf-feph.org/web-accessibility-directive/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Web Accessibility Directive - European Disability Forum</div><div class="kg-bookmark-description">Web Accessibility Directive</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.edf-feph.org/content/uploads/2019/07/48-x-48@3x.png" alt=""><span class="kg-bookmark-author">European Disability Forum</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://www.edf-feph.org/content/uploads/2019/07/48-x-48@3x.png" alt=""></div></a></figure><h3 id="how-scenexplain-helps-organizations-meet-accessibility-requirements">How SceneXplain Helps Organizations Meet Accessibility Requirements</h3><p>SceneXplain is designed to help organizations comply with European accessibility standards by providing accurate, detailed, and contextually rich image descriptions. By integrating SceneXplain's advanced image captioning capabilities, public sector websites and applications can generate image alt tags and other accessible multimedia content that adheres to the WCAG 2.1 Level AA guidelines. This ensures visually impaired users can better understand and engage with the content, resulting in a more inclusive digital experience.</p><p>SceneXplain's multilingual support further enhances its potential to meet accessibility requirements in the European context. By providing context-rich translations for image descriptions, SceneXplain enables organizations to cater to the diverse linguistic needs of users across the EU, ensuring that content remains accessible in multiple languages.</p><h3 id="benefits-of-using-scenexplain-in-public-sector-websites-and-applications">Benefits of Using SceneXplain in Public Sector Websites and Applications</h3><p>There are several benefits to incorporating SceneXplain into public sector websites and applications:</p><ol><li><strong>Improved Accessibility:</strong> SceneXplain's advanced image captioning algorithms generate detailed and accurate descriptions, ensuring that visually impaired users can better understand and engage with multimedia content.</li><li><strong>Compliance with Regulations</strong>: Integrating SceneXplain helps public sector organizations comply with the Web Accessibility Directive and WCAG 2.1 Level AA guidelines, minimizing the risk of non-compliance penalties. In recent years, several high-profile lawsuits have involved website accessibility, emphasizing the importance of adhering to these guidelines to avoid legal repercussions.</li><li><strong>Enhanced User Experience:</strong> By providing engaging and informative image descriptions, SceneXplain enriches the overall user experience for all users, not just those with disabilities.</li><li><strong>Multilingual Support:</strong> SceneXplain's ability to generate context-rich translations for image descriptions enables organizations to cater to the diverse linguistic needs of users across the EU, further enhancing accessibility.</li></ol><p>By leveraging SceneXplain's advanced image captioning capabilities, European public sector organizations can ensure compliance with accessibility standards and create a more inclusive digital environment for all users. The urgency of adhering to these regulations is highlighted by the growing number of people with disabilities, the risk of lawsuits, and the need to provide everyone with equal access to digital content.</p><h2 id="integration-process-of-scenexplain-with-public-sector-websites-and-applications">Integration Process of SceneXplain with Public Sector Websites and Applications</h2><p>Integrating SceneXplain with public sector websites and applications can significantly enhance digital accessibility. SceneXplain offers multiple integration options to cater to the diverse needs of organizations. Here, we will explore three ways to integrate SceneXplain:</p><h3 id="create-accessible-image-via-scenexplain-ui">Create Accessible Image via SceneXplain UI</h3><p>SceneXplain's user-friendly web interface allows organizations to quickly and easily generate image descriptions without the need for extensive technical knowledge. By uploading images directly to the web platform, users can obtain detailed textual descriptions that can then be incorporated into their website's image alt tags or other accessibility features. This approach is ideal for organizations with limited technical resources or those who require occasional image captioning services.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-11.png" class="kg-image" alt="" width="1960" height="1132" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-11.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-11.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-11.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-11.png 1960w" sizes="(min-width: 720px) 720px"><figcaption>You can use SceneXplain on either desktop or mobile device.</figcaption></figure><h3 id="batch-process-images-via-scenexplain-api">Batch Process Images via SceneXplain API</h3><p>For organizations seeking an automated and seamless integration, SceneXplain offers a robust, scalable, and secure API for their systems. The fast batch API allows describing up to 128 images in one batch within 40 seconds, ideal for those requiring high volumes of image captioning services.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-18.png" class="kg-image" alt="" width="1980" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-18.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-18.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-18.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-18.png 1980w" sizes="(min-width: 720px) 720px"></figure><p>Organizations can automatically generate image descriptions by connecting SceneXplain's API to websites or applications, ensuring accessibility compliance with European standards. The API integration suits organizations with dedicated technical teams or those needing large-scale image captioning. Secure data handling ensures privacy and data protection during integration, providing a seamless experience while enhancing digital accessibility for all users.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-21.png" class="kg-image" alt="" width="2000" height="1151" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-21.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/04/image-21.png 2400w" sizes="(min-width: 720px) 720px"></figure><h3 id="privacy-preserved-solution-in-on-prem">Privacy-Preserved Solution in On-prem</h3><p>SceneXplain also provides an on-premises solution for organizations that prefer to maintain full control over their data and systems. By deploying SceneXplain on their servers, organizations can ensure that their sensitive data remains within their network while benefiting from the advanced image captioning capabilities of SceneXplain. This option is particularly relevant for public sector organizations with strict data security and privacy requirements.</p><div class="kg-card kg-button-card kg-align-center"><a href="mailto:scenex@jina.ai" class="kg-btn kg-btn-accent">Book a call with our team about the on-prem solution</a></div><p>Each integration option offers unique benefits and caters to different organizational needs. By choosing the most suitable integration method, public sector organizations can effectively harness the power of SceneXplain to enhance digital accessibility and comply with European accessibility regulations.</p><h2 id="conclusion">Conclusion</h2><p>In conclusion, SceneXplain is a groundbreaking solution advancing digital accessibility in the public sector. By leveraging its advanced AI capabilities, SceneXplain generates precise, context-rich, and engaging image descriptions, ensuring that multimedia content is accessible to all users, including those with visual impairments.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-20.png" class="kg-image" alt="" width="1344" height="896" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-20.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-20.png 1344w" sizes="(min-width: 720px) 720px"></figure><p>As digital accessibility becomes increasingly essential, public sector organizations must adopt innovative tools like SceneXplain to meet the demands of an inclusive online experience. Integrating SceneXplain not only ensures compliance with European accessibility standards but also enhances the overall user experience for all citizens.</p><p>Now is the time for public sector organizations to take the initiative and harness the power of SceneXplain to create a more inclusive digital landscape. Embrace the change and join the movement towards a more accessible and equal online world for everyone.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fenhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Fine-Tuning Falcon40b for Code Generation</title><meta charset="utf-8"><meta name="title" content="Fine-Tuning Falcon40b for Code Generation"><meta name="description" content="Falcon40b is an open-source commercial-use friendly large language model. We've trained it to write code."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/fine-tuning-falcon40b-for-code-generation"><meta property="og:title" content="Fine-Tuning Falcon40b for Code Generation"><meta property="og:description" content="Falcon40b is an open-source commercial-use friendly large language model. We've trained it to write code."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_detailed_anatomical_drawing_of_a_falcon_in_the_s_9d5ef79e-fad6-4cae-92cc-3be6b4ec764a.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/fine-tuning-falcon40b-for-code-generation"><meta property="twitter:title" content="Fine-Tuning Falcon40b for Code Generation"><meta property="twitter:description" content="Falcon40b is an open-source commercial-use friendly large language model. We've trained it to write code."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_detailed_anatomical_drawing_of_a_falcon_in_the_s_9d5ef79e-fad6-4cae-92cc-3be6b4ec764a.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="51dd63fd-92ff-4aec-bc6f-bceace2a61c5" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="51dd63fd-92ff-4aec-bc6f-bceace2a61c5" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Fine-Tuning Falcon40b for Code Generation</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Falcon40b is an open-source commercial-use friendly large language model. We've trained it to write code.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 105px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 132.812%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/PXL_20221116_122857628.PORTRAIT.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 151.086%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/MWI_6577--1-.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 75px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Sami Jaghouar, Alaeddine Abdessalem, Sebastian Weisshaar, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 24, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><a href="https://huggingface.co/tiiuae/falcon-40b?ref=jina-ai-gmbh.ghost.io">Falcon40b</a> is one of the biggest open-source LLMs currently available and comes with a commercial-use-friendly Apache 2.0 license. This makes it interesting for developers looking to bring NLP products to market.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/tiiuae/falcon-40b?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">tiiuae/falcon-40b · Hugging Face</div><div class="kg-bookmark-description">We’re on a journey to advance and democratize artificial intelligence through open source and open science.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/models/tiiuae/falcon-40b.png" alt=""></div></a></figure><p>The <a href="https://huggingface.co/tiiuae/falcon-40b-instruct?ref=jina-ai-gmbh.ghost.io">Falcon-40b-Instruct</a> model, which is the base Falcon40b model fine-tuned for instruction-taking and chat, ranks <a href="https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?ref=jina-ai-gmbh.ghost.io">near the top of the Hugging Face LLM benchmark</a>, with only models based on Meta’s non-open-source Llama family performing better. Falcon40b’s performance is far superior to other open-source models.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/tiiuae/falcon-40b-instruct?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">tiiuae/falcon-40b-instruct · Hugging Face</div><div class="kg-bookmark-description">We’re on a journey to advance and democratize artificial intelligence through open source and open science.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/models/tiiuae/falcon-40b-instruct.png" alt=""></div></a></figure><p>The Falcon family of models belongs to the recent wave of open-source LLMs inspired by the Llama family. The underlying insight behind them is to train smaller models longer (for more epochs) and with more data (over a trillion tokens in this case). <a href="https://arxiv.org/abs/2001.08361?ref=jina-ai-gmbh.ghost.io">The empirical literature on LLM scaling</a> suggests that model size, training compute, and training dataset size should rise in tandem, but this family of models uses far more compute and training data than would be expected for a model of this size.</p><h3 id="fine-tuning-with-codealpaca">Fine-tuning with CodeAlpaca</h3><p>Falcon40b is a pre-trained model but has not been trained for any specific task. Its zero-shot performance is not especially good, and it needs to be trained to function as a chatbot or to follow instructions.</p><p>When we want it to follow instructions, we train it using a collection of instruction-response pairs like the <a href="https://huggingface.co/datasets/tatsu-lab/alpaca?ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">Alpaca dataset</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/datasets/tatsu-lab/alpaca?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">tatsu-lab/alpaca · Datasets at Hugging Face</div><div class="kg-bookmark-description">We’re on a journey to advance and democratize artificial intelligence through open source and open science.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/datasets/tatsu-lab/alpaca.png" alt=""></div></a></figure><p>For example, this instruction-response pair comes from Alpaca:</p><pre><code class="language-Text hljs">Below is an instruction that describes a task. Write a response that 
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Falcon40b is an open-source commercial-use friendly large language model. We've trained it to write code.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 105px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 132.812%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/PXL_20221116_122857628.PORTRAIT.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 151.086%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/MWI_6577--1-.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 75px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Sami Jaghouar, Alaeddine Abdessalem, Sebastian Weisshaar, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 24, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><a href="https://huggingface.co/tiiuae/falcon-40b?ref=jina-ai-gmbh.ghost.io">Falcon40b</a> is one of the biggest open-source LLMs currently available and comes with a commercial-use-friendly Apache 2.0 license. This makes it interesting for developers looking to bring NLP products to market.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/tiiuae/falcon-40b?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">tiiuae/falcon-40b · Hugging Face</div><div class="kg-bookmark-description">We’re on a journey to advance and democratize artificial intelligence through open source and open science.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/models/tiiuae/falcon-40b.png" alt=""></div></a></figure><p>The <a href="https://huggingface.co/tiiuae/falcon-40b-instruct?ref=jina-ai-gmbh.ghost.io">Falcon-40b-Instruct</a> model, which is the base Falcon40b model fine-tuned for instruction-taking and chat, ranks <a href="https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?ref=jina-ai-gmbh.ghost.io">near the top of the Hugging Face LLM benchmark</a>, with only models based on Meta’s non-open-source Llama family performing better. Falcon40b’s performance is far superior to other open-source models.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/tiiuae/falcon-40b-instruct?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">tiiuae/falcon-40b-instruct · Hugging Face</div><div class="kg-bookmark-description">We’re on a journey to advance and democratize artificial intelligence through open source and open science.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/models/tiiuae/falcon-40b-instruct.png" alt=""></div></a></figure><p>The Falcon family of models belongs to the recent wave of open-source LLMs inspired by the Llama family. The underlying insight behind them is to train smaller models longer (for more epochs) and with more data (over a trillion tokens in this case). <a href="https://arxiv.org/abs/2001.08361?ref=jina-ai-gmbh.ghost.io">The empirical literature on LLM scaling</a> suggests that model size, training compute, and training dataset size should rise in tandem, but this family of models uses far more compute and training data than would be expected for a model of this size.</p><h3 id="fine-tuning-with-codealpaca">Fine-tuning with CodeAlpaca</h3><p>Falcon40b is a pre-trained model but has not been trained for any specific task. Its zero-shot performance is not especially good, and it needs to be trained to function as a chatbot or to follow instructions.</p><p>When we want it to follow instructions, we train it using a collection of instruction-response pairs like the <a href="https://huggingface.co/datasets/tatsu-lab/alpaca?ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">Alpaca dataset</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/datasets/tatsu-lab/alpaca?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">tatsu-lab/alpaca · Datasets at Hugging Face</div><div class="kg-bookmark-description">We’re on a journey to advance and democratize artificial intelligence through open source and open science.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/datasets/tatsu-lab/alpaca.png" alt=""></div></a></figure><p>For example, this instruction-response pair comes from Alpaca:</p><pre><code class="language-Text hljs">Below is an instruction that describes a task. Write a response that 
 appropriately completes the request.
 
 ### Instruction:
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 25, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the ever-evolving landscape of Large Language Model (LLM), OpenAI's unveiling of fine-tuning for GPT-3.5 Turbo stands out as a noteworthy milestone. This advancement beckons with the tantalizing prospect of leveraging the vast prowess of this AI powerhouse, tailored to specific nuances. Yet, as is often the case with groundbreaking innovations, a closer look can offer a more nuanced understanding.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://openai.com/blog/gpt-3-5-turbo-fine-tuning-and-api-updates?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GPT-3.5 Turbo fine-tuning and API updates</div><div class="kg-bookmark-description">Developers can now bring their own data to customize GPT-3.5 Turbo for their use cases.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://openai.com/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://images.openai.com/blob/d8d965fd-e54c-4c9b-9d7d-b5d9910d38b2/gpt-3-5-turbo-fine-tuning-and-api-updates.png?trim=0%2C0%2C0%2C0" alt=""></div></a></figure><h2 id="comparing-prompt-engineering-vs-fine-tuning">Comparing Prompt Engineering vs. Fine-Tuning</h2><p>Before venturing deeper, let's acquaint ourselves with these two trending players in the LLM arena: <strong>prompt engineering</strong> and <strong>fine-tuning</strong>.</p><p>Imagine the colossal GPT-3.5 Turbo as a grand piano, its keys sprawling in multitude. Prompt engineering is akin to an artist subtly mastering those keys to elicit the desired tunes. With just the right prompts (questions or statements you feed into the LLM), you can navigate the vast spectrum of the model's knowledge. This approach is nimble, adaptable, and remarkably effective. For those looking to perfect this craft, tools like <strong>PromptPerfect</strong> subtly rise as a beacon, crafting the perfect harmony between user intent and AI response.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, MidJourney and StableDiffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficienc…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><p>On the other hand, fine-tuning is a more profound process. If prompt engineering is about mastering the keys, fine-tuning is about recalibrating the piano itself. It allows for a deeper, more tailored customization, aligning the model's behavior meticulously with specific datasets. </p><h2 id="fine-tuned-language-beyond-the-machines-syntax">Fine-Tuned Language: Beyond The Machine's Syntax</h2><p>At their core, LLMs like GPT-4 have astounded us with their capabilities. Their prose, though often coherent, has been criticized for lacking the nuanced, idiomatic quality inherent to human language. Now, fine-tuning attempts to blend the machine's efficiency with a touch of human-like idiosyncrasy.</p><p>OpenAI’s fine-tuning promises to take these models a step further into the realm of nuanced understanding. Preliminary tests hint at a fine-tuned GPT-3.5 Turbo standing shoulder-to-shoulder with the mightier GPT-4 in specific domains. Such precision could mean AI transcends beyond mere transactional interactions, evolving into a more collaborative partner, displaying comprehension, imagination, and even a semblance of empathy.</p><h3 id="the-true-potential-bridging-gaps-and-deepening-connections">The True Potential: Bridging Gaps and Deepening Connections</h3><p>To truly grasp this, let's delve into a few envisioned applications:</p><ol><li><strong>Medical Chatbots</strong>: Picture a chatbot, equipped not just with medical facts but with genuine warmth. Trained on medical research, patient experiences, and counseling techniques, these AI companions could stand as pillars of support for patients, empathetically navigating their concerns and emotions. With inputs from medical journals, patient forums, and consultation transcripts, they could potentially merge hard medical knowledge with compassionate human wisdom.</li><li><strong>Writing Assistants</strong>: The dreaded writer’s block could find its match in an AI muse, tailored to resonate with an author's unique style and influences. Using fine-tuning, one could create an AI writing companion infused with the essence of literary greats, from Vonnegut to Woolf. These would be more than mere tools; they'd be partners in the creative process, guiding writers into realms of unbridled creativity.</li><li><strong>Farsi-speaking Retail Chatbots</strong>: In the world of e-commerce, language should not be a barrier. For Iranian businesses, fine-tuned chatbots equipped with product knowledge and a nuanced understanding of Farsi linguistics could bridge cultural and linguistic divides, ensuring every customer feels at home.</li></ol><p>This exploration paints a vivid picture. Fine-tuning has the potential to infuse AI systems with curated human wisdom, elevating their capacities to comfort, inspire, and connect. As we progress, ensuring these models reflect our higher values could lead to an AI that appreciates the myriad hues of human experience, transcending its binary origins.</p><p><strong>Yet, with promise comes price.</strong></p><p>And this is where we find ourselves at a crossroads. While the allure of deep customization through fine-tuning is undeniable, the economic implications are equally compelling.</p><h2 id="the-realities-of-the-fine-tuning-wallet">The Realities of the Fine-Tuning Wallet</h2><p>Now, the brass tacks. While the siren song of customization is tempting, the costs of heeding its call can be steep.</p><p>A conversation spanning 1,000 tokens on GPT-3.5 will gently knock your wallet for $0.0035. But, if you're looking at its fine-tuned avatar:</p><ul><li>Training demands $0.0080 for every 1,000 tokens.</li><li>Input costs soar to $0.0120 per 1,000 tokens — 8 times the basic version.</li><li>Outputs? A lofty $0.0160 for each 1,000 tokens.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-13.png" class="kg-image" alt="" width="1992" height="1074" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-13.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-13.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-13.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-13.png 1992w" sizes="(min-width: 720px) 720px"></figure><p>Hence, our innocent 1,000-token chat now demands a 10-fold premium at $0.0360, excluding the initial training.</p><p>Let’s extrapolate. Imagine a bustling chatbot, engaging in 10,000 daily chit-chats, each 2,000 tokens long:</p><ul><li>GPT-3.5’s bill stands at a palatable $35 per day.</li><li>The fine-tuned variant? A whopping $360 daily, translating to an additional $10,000 every month.</li></ul><p>When dissected, the proposition becomes evident: for the lion's share of applications, fine-tuning GPT-3.5’s lofty claims hardly align with its exorbitant fees. If astute prompt engineering can procure 90% of your performance goals at a mere tenth of the price, the economics for that additional, often imperceptible improvement begins to wane.</p><h2 id="strategizing-in-the-ai-epoch">Strategizing in the AI Epoch</h2><p>There's no denying that certain niches, craving pixel-perfect precision, will find the premiums of fine-tuning justifiable. Yet, for the broader spectrum, the costs might be hard to reconcile with the benefits.</p><table>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 25, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the ever-evolving landscape of Large Language Model (LLM), OpenAI's unveiling of fine-tuning for GPT-3.5 Turbo stands out as a noteworthy milestone. This advancement beckons with the tantalizing prospect of leveraging the vast prowess of this AI powerhouse, tailored to specific nuances. Yet, as is often the case with groundbreaking innovations, a closer look can offer a more nuanced understanding.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://openai.com/blog/gpt-3-5-turbo-fine-tuning-and-api-updates?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GPT-3.5 Turbo fine-tuning and API updates</div><div class="kg-bookmark-description">Developers can now bring their own data to customize GPT-3.5 Turbo for their use cases.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://openai.com/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://images.openai.com/blob/d8d965fd-e54c-4c9b-9d7d-b5d9910d38b2/gpt-3-5-turbo-fine-tuning-and-api-updates.png?trim=0%2C0%2C0%2C0" alt=""></div></a></figure><h2 id="comparing-prompt-engineering-vs-fine-tuning">Comparing Prompt Engineering vs. Fine-Tuning</h2><p>Before venturing deeper, let's acquaint ourselves with these two trending players in the LLM arena: <strong>prompt engineering</strong> and <strong>fine-tuning</strong>.</p><p>Imagine the colossal GPT-3.5 Turbo as a grand piano, its keys sprawling in multitude. Prompt engineering is akin to an artist subtly mastering those keys to elicit the desired tunes. With just the right prompts (questions or statements you feed into the LLM), you can navigate the vast spectrum of the model's knowledge. This approach is nimble, adaptable, and remarkably effective. For those looking to perfect this craft, tools like <strong>PromptPerfect</strong> subtly rise as a beacon, crafting the perfect harmony between user intent and AI response.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, MidJourney and StableDiffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficienc…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><p>On the other hand, fine-tuning is a more profound process. If prompt engineering is about mastering the keys, fine-tuning is about recalibrating the piano itself. It allows for a deeper, more tailored customization, aligning the model's behavior meticulously with specific datasets. </p><h2 id="fine-tuned-language-beyond-the-machines-syntax">Fine-Tuned Language: Beyond The Machine's Syntax</h2><p>At their core, LLMs like GPT-4 have astounded us with their capabilities. Their prose, though often coherent, has been criticized for lacking the nuanced, idiomatic quality inherent to human language. Now, fine-tuning attempts to blend the machine's efficiency with a touch of human-like idiosyncrasy.</p><p>OpenAI’s fine-tuning promises to take these models a step further into the realm of nuanced understanding. Preliminary tests hint at a fine-tuned GPT-3.5 Turbo standing shoulder-to-shoulder with the mightier GPT-4 in specific domains. Such precision could mean AI transcends beyond mere transactional interactions, evolving into a more collaborative partner, displaying comprehension, imagination, and even a semblance of empathy.</p><h3 id="the-true-potential-bridging-gaps-and-deepening-connections">The True Potential: Bridging Gaps and Deepening Connections</h3><p>To truly grasp this, let's delve into a few envisioned applications:</p><ol><li><strong>Medical Chatbots</strong>: Picture a chatbot, equipped not just with medical facts but with genuine warmth. Trained on medical research, patient experiences, and counseling techniques, these AI companions could stand as pillars of support for patients, empathetically navigating their concerns and emotions. With inputs from medical journals, patient forums, and consultation transcripts, they could potentially merge hard medical knowledge with compassionate human wisdom.</li><li><strong>Writing Assistants</strong>: The dreaded writer’s block could find its match in an AI muse, tailored to resonate with an author's unique style and influences. Using fine-tuning, one could create an AI writing companion infused with the essence of literary greats, from Vonnegut to Woolf. These would be more than mere tools; they'd be partners in the creative process, guiding writers into realms of unbridled creativity.</li><li><strong>Farsi-speaking Retail Chatbots</strong>: In the world of e-commerce, language should not be a barrier. For Iranian businesses, fine-tuned chatbots equipped with product knowledge and a nuanced understanding of Farsi linguistics could bridge cultural and linguistic divides, ensuring every customer feels at home.</li></ol><p>This exploration paints a vivid picture. Fine-tuning has the potential to infuse AI systems with curated human wisdom, elevating their capacities to comfort, inspire, and connect. As we progress, ensuring these models reflect our higher values could lead to an AI that appreciates the myriad hues of human experience, transcending its binary origins.</p><p><strong>Yet, with promise comes price.</strong></p><p>And this is where we find ourselves at a crossroads. While the allure of deep customization through fine-tuning is undeniable, the economic implications are equally compelling.</p><h2 id="the-realities-of-the-fine-tuning-wallet">The Realities of the Fine-Tuning Wallet</h2><p>Now, the brass tacks. While the siren song of customization is tempting, the costs of heeding its call can be steep.</p><p>A conversation spanning 1,000 tokens on GPT-3.5 will gently knock your wallet for $0.0035. But, if you're looking at its fine-tuned avatar:</p><ul><li>Training demands $0.0080 for every 1,000 tokens.</li><li>Input costs soar to $0.0120 per 1,000 tokens — 8 times the basic version.</li><li>Outputs? A lofty $0.0160 for each 1,000 tokens.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-13.png" class="kg-image" alt="" width="1992" height="1074" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-13.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-13.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-13.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-13.png 1992w" sizes="(min-width: 720px) 720px"></figure><p>Hence, our innocent 1,000-token chat now demands a 10-fold premium at $0.0360, excluding the initial training.</p><p>Let’s extrapolate. Imagine a bustling chatbot, engaging in 10,000 daily chit-chats, each 2,000 tokens long:</p><ul><li>GPT-3.5’s bill stands at a palatable $35 per day.</li><li>The fine-tuned variant? A whopping $360 daily, translating to an additional $10,000 every month.</li></ul><p>When dissected, the proposition becomes evident: for the lion's share of applications, fine-tuning GPT-3.5’s lofty claims hardly align with its exorbitant fees. If astute prompt engineering can procure 90% of your performance goals at a mere tenth of the price, the economics for that additional, often imperceptible improvement begins to wane.</p><h2 id="strategizing-in-the-ai-epoch">Strategizing in the AI Epoch</h2><p>There's no denying that certain niches, craving pixel-perfect precision, will find the premiums of fine-tuning justifiable. Yet, for the broader spectrum, the costs might be hard to reconcile with the benefits.</p><table>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Fine-Tuning: How To Get the Most of Your AI Investments</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">If you are looking at integrating AI into your business, fine-tuning is essential to getting the most value out of your AI investments. Jina AI can help with software, services, and consultants for organizations of all kinds, sizes, and technical experience.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 02, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The latest generation of large AI models does many very impressive things. Anyone with access to the internet can try out talking with ChatGPT or making pictures with DALL-E or MidJourney.</p><p>So far, very few businesses have been built around them. This technology is very new, and it may take some time to see real productivity growth from them. But in the meantime, many existing businesses are looking at places in their own operations where they might usefully deploy AI.</p><p>Large AI models have been trained on large databases of unspecialized data, often texts and images taken from the internet with minimal filtering. This gives them impressive-seeming abilities over a potentially unbounded array of scenarios. However, when applied to specific problems, their performance can be disappointing. Whatever your application is, most of the functionality of a large AI model is useless to you, while the functionality that is useful to you is not directly designed to address your use case.</p><p>Building a whole new AI model on the scale of recent breakthroughs, focused on just your business interests, is not very practical. The major AI companies don't usually disclose how much time, energy, or money it takes to train their state-of-the-art models. Estimates start in the millions of euros, with <a href="https://www.wired.com/story/openai-ceo-sam-altman-the-age-of-giant-ai-models-is-already-over/?ref=jina-ai-gmbh.ghost.io">some claiming GPT-4 cost over 100 million US dollars to train</a>. Even for the best-funded businesses, it is a challenge to find and retain sufficient engineering talent with experience in AI and another challenge to obtain the vast quantities of data required to train these models. Successfully training very large models from scratch may take months on even the largest and fastest clusters at a cost of potentially millions of euros. And this is before even addressing error handling and integration costs.</p><p>There is another way.</p><h2 id="pre-training">Pre-training</h2><p>One of the breakthroughs that led to today's impressive new AI models is the discovery that it often requires much less time and data to adapt an already trained model to a new task than to train a new one from scratch. Techniques for "pre-training" networks — training them to do tasks that are indirectly related to your use case but for which there is ample data and easy-to-assess goals — are a big part of how we can create these large models. For example, large language models are typically pre-trained using large quantities of text, with the training goal of filling in the blanks from the surrounding context. For example:</p><blockquote><em>On Saturday, New Jersey Gov. Phil Murphy _________ that Sept. 23 will _______ be declared "Bruce Springsteen Day" in ______ of the singer's birthday.</em></blockquote><p>By learning to do this task — one with little value by itself — AI models learn a great deal about the relationships between words. Then, after the model has learned as much as it can from this task, developers train it to do more sophisticated things, like answering questions or holding conversations.</p><p>Image-processing AI models are pre-trained using similar techniques. Typically, this means training to fill in the blank squares in pictures or by distorting or adding noise to images and training the model to "fix" them. This teaches the model a lot about what kinds of things appear in pictures and what they should look like.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.671141 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Untitled--12--1.png" width="1000" height="1490" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/Untitled--12--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/Untitled--12--1.png 1000w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.671141 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Untitled--13-.png" width="1000" height="1490" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/Untitled--13-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/Untitled--13-.png 1000w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>The <em>Mona Lisa</em>, one with a section cut out, one with added blurring.</figcaption></figure><p>AI models that have already learned some relevant things are much easier to train than ones that start without knowing anything. This is called <strong><strong><strong><strong><strong><strong><strong><strong><em>transfer learning</em></strong></strong></strong></strong></strong></strong></strong></strong>, and it's a very intuitive idea. It's much easier to teach someone who knows how to drive a car to safely drive a large truck than to teach someone who has never driven at all. AI models work in a similar way.</p><h2 id="fine-tuning">Fine-tuning</h2><p>You can take advantage of transfer learning to adapt AI to your business and your specific use cases without making a multi-year, multi-million euro investment. The impressive performance of large AI models on general tasks means that they need much less data and training time to learn to do well at some specific task.</p><p>For example, let's consider an online fashion retailer that offers shoppers a search function. There are AI models that match pictures to descriptions, but they are trained on a very wide variety of images. It does the retailer no good to have AI that can efficiently identify pictures of dogs and cats when they want an AI that can tell the difference between jeans and dress slacks or between an A-line skirt and a pleated skirt.</p><p>An AI model that can recognize thousands of different objects has already learned how to make fine distinctions based on the features of images. Training it to know the difference between chinos and cargo pants takes relatively few examples compared to training an AI model that doesn't even know what pants are!</p><p>This kind of training is called <em><strong><strong><strong><strong><strong>fine-tuning</strong></strong></strong></strong></strong></em> because most of what it does is not really learning new things but learning to focus the things that the model already knows on the specific tasks you have in mind.</p><p>Although performance is almost always going to be better the more training data you have, we have found that <a href="https://jina.ai/news/fine-tuning-with-low-budget-and-high-expectations/?ref=jina-ai-gmbh.ghost.io">mere hundreds of items of training data are enough to get most of the gains</a> from fine-tuning in many highly realistic test cases. Acquiring a few hundred examples is a much cheaper proposition than acquiring the millions to billions of data items used to train the original model.</p><p>This makes fine-tuning an extremely attractive value proposition for anyone looking to integrate AI into their business.</p><h2 id="finetuner-from-jina-ai">Finetuner from Jina AI</h2><p><a href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI's Finetuner</a> is a flexible and efficient cloud-native solution for fine-tuning state-of-the-art AI models. It provides an intuitive Python interface that can securely upload your data to our cloud and return a fine-tuned model without requiring you to invest in any special hardware or tech stack. Our solution includes testing and evaluation methods that quantify performance improvements and provide intuitive reports, so you can see directly how much value fine-tuning adds.</p><p>It is impossible for us — or anyone else — to guarantee a specific outcome from a machine learning process. However, we are unaware of any case in which fine-tuning with adequately representative data did not improve the task-specific performance of an AI model.</p><p>We strive to keep the Finetuner as intuitive and easy to use as possible, but we understand that machine learning can be an inherently messy process involving choices that no software can ever automate. For this reason, we offer <a href="https://finetunerplus.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner+</a>, a service where our engineers collaborate with you in planning and executing AI integration. We can:</p><ul><li>Advise you on selecting an AI model appropriate to your use case.</li><li>Help you to acquire and prepare training data for the Finetuner.</li><li>Manage and evaluate Finetuner runs for you.</li><li>Assist you in integrating the resulting AI models into your business processes.</li></ul><p>Furthermore, if your data security needs are very strict, we can assist you in setting up and running Finetuner on-site at your company.</p><p>If you are looking at integrating AI into your business, fine-tuning is essential to getting the most value out of your AI investments. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Fine-Tuning: How To Get the Most of Your AI Investments</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">If you are looking at integrating AI into your business, fine-tuning is essential to getting the most value out of your AI investments. Jina AI can help with software, services, and consultants for organizations of all kinds, sizes, and technical experience.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 02, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The latest generation of large AI models does many very impressive things. Anyone with access to the internet can try out talking with ChatGPT or making pictures with DALL-E or MidJourney.</p><p>So far, very few businesses have been built around them. This technology is very new, and it may take some time to see real productivity growth from them. But in the meantime, many existing businesses are looking at places in their own operations where they might usefully deploy AI.</p><p>Large AI models have been trained on large databases of unspecialized data, often texts and images taken from the internet with minimal filtering. This gives them impressive-seeming abilities over a potentially unbounded array of scenarios. However, when applied to specific problems, their performance can be disappointing. Whatever your application is, most of the functionality of a large AI model is useless to you, while the functionality that is useful to you is not directly designed to address your use case.</p><p>Building a whole new AI model on the scale of recent breakthroughs, focused on just your business interests, is not very practical. The major AI companies don't usually disclose how much time, energy, or money it takes to train their state-of-the-art models. Estimates start in the millions of euros, with <a href="https://www.wired.com/story/openai-ceo-sam-altman-the-age-of-giant-ai-models-is-already-over/?ref=jina-ai-gmbh.ghost.io">some claiming GPT-4 cost over 100 million US dollars to train</a>. Even for the best-funded businesses, it is a challenge to find and retain sufficient engineering talent with experience in AI and another challenge to obtain the vast quantities of data required to train these models. Successfully training very large models from scratch may take months on even the largest and fastest clusters at a cost of potentially millions of euros. And this is before even addressing error handling and integration costs.</p><p>There is another way.</p><h2 id="pre-training">Pre-training</h2><p>One of the breakthroughs that led to today's impressive new AI models is the discovery that it often requires much less time and data to adapt an already trained model to a new task than to train a new one from scratch. Techniques for "pre-training" networks — training them to do tasks that are indirectly related to your use case but for which there is ample data and easy-to-assess goals — are a big part of how we can create these large models. For example, large language models are typically pre-trained using large quantities of text, with the training goal of filling in the blanks from the surrounding context. For example:</p><blockquote><em>On Saturday, New Jersey Gov. Phil Murphy _________ that Sept. 23 will _______ be declared "Bruce Springsteen Day" in ______ of the singer's birthday.</em></blockquote><p>By learning to do this task — one with little value by itself — AI models learn a great deal about the relationships between words. Then, after the model has learned as much as it can from this task, developers train it to do more sophisticated things, like answering questions or holding conversations.</p><p>Image-processing AI models are pre-trained using similar techniques. Typically, this means training to fill in the blank squares in pictures or by distorting or adding noise to images and training the model to "fix" them. This teaches the model a lot about what kinds of things appear in pictures and what they should look like.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.671141 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Untitled--12--1.png" width="1000" height="1490" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/Untitled--12--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/Untitled--12--1.png 1000w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.671141 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Untitled--13-.png" width="1000" height="1490" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/Untitled--13-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/Untitled--13-.png 1000w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>The <em>Mona Lisa</em>, one with a section cut out, one with added blurring.</figcaption></figure><p>AI models that have already learned some relevant things are much easier to train than ones that start without knowing anything. This is called <strong><strong><strong><strong><strong><strong><strong><strong><em>transfer learning</em></strong></strong></strong></strong></strong></strong></strong></strong>, and it's a very intuitive idea. It's much easier to teach someone who knows how to drive a car to safely drive a large truck than to teach someone who has never driven at all. AI models work in a similar way.</p><h2 id="fine-tuning">Fine-tuning</h2><p>You can take advantage of transfer learning to adapt AI to your business and your specific use cases without making a multi-year, multi-million euro investment. The impressive performance of large AI models on general tasks means that they need much less data and training time to learn to do well at some specific task.</p><p>For example, let's consider an online fashion retailer that offers shoppers a search function. There are AI models that match pictures to descriptions, but they are trained on a very wide variety of images. It does the retailer no good to have AI that can efficiently identify pictures of dogs and cats when they want an AI that can tell the difference between jeans and dress slacks or between an A-line skirt and a pleated skirt.</p><p>An AI model that can recognize thousands of different objects has already learned how to make fine distinctions based on the features of images. Training it to know the difference between chinos and cargo pants takes relatively few examples compared to training an AI model that doesn't even know what pants are!</p><p>This kind of training is called <em><strong><strong><strong><strong><strong>fine-tuning</strong></strong></strong></strong></strong></em> because most of what it does is not really learning new things but learning to focus the things that the model already knows on the specific tasks you have in mind.</p><p>Although performance is almost always going to be better the more training data you have, we have found that <a href="https://jina.ai/news/fine-tuning-with-low-budget-and-high-expectations/?ref=jina-ai-gmbh.ghost.io">mere hundreds of items of training data are enough to get most of the gains</a> from fine-tuning in many highly realistic test cases. Acquiring a few hundred examples is a much cheaper proposition than acquiring the millions to billions of data items used to train the original model.</p><p>This makes fine-tuning an extremely attractive value proposition for anyone looking to integrate AI into their business.</p><h2 id="finetuner-from-jina-ai">Finetuner from Jina AI</h2><p><a href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI's Finetuner</a> is a flexible and efficient cloud-native solution for fine-tuning state-of-the-art AI models. It provides an intuitive Python interface that can securely upload your data to our cloud and return a fine-tuned model without requiring you to invest in any special hardware or tech stack. Our solution includes testing and evaluation methods that quantify performance improvements and provide intuitive reports, so you can see directly how much value fine-tuning adds.</p><p>It is impossible for us — or anyone else — to guarantee a specific outcome from a machine learning process. However, we are unaware of any case in which fine-tuning with adequately representative data did not improve the task-specific performance of an AI model.</p><p>We strive to keep the Finetuner as intuitive and easy to use as possible, but we understand that machine learning can be an inherently messy process involving choices that no software can ever automate. For this reason, we offer <a href="https://finetunerplus.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner+</a>, a service where our engineers collaborate with you in planning and executing AI integration. We can:</p><ul><li>Advise you on selecting an AI model appropriate to your use case.</li><li>Help you to acquire and prepare training data for the Finetuner.</li><li>Manage and evaluate Finetuner runs for you.</li><li>Assist you in integrating the resulting AI models into your business processes.</li></ul><p>Furthermore, if your data security needs are very strict, we can assist you in setting up and running Finetuner on-site at your company.</p><p>If you are looking at integrating AI into your business, fine-tuning is essential to getting the most value out of your AI investments. Jina AI can help with software, services, and consultants for organizations of all kinds, sizes, and technical experience.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffine-tuning-how-to-get-the-most-of-your-ai-investments%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Fine-tuning: Unlocking the full potential of AI for businesses</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Fine-tuning is a way of "tweaking" an AI model, like how a musician can fine-tune an instrument, and in the case of AI models, it can make an enormous difference.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 66.6875%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/WhatsApp-Image-2022-12-06-at-15.46.39.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Susana Guzmán</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 17, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Developments in artificial intelligence are moving fast, and it feels like there's something new going on with large AI models almost every day. These breakthroughs have opened up a world of possibilities for various industries. But to make the most of AI-powered processes and tools, it is essential to adapt them to your specific business and use case. That's where <strong><strong><strong><strong><strong><em>fine-tuning</em></strong></strong></strong></strong></strong> comes in.</p><p>In this blog post, we'll look at the concept of fine-tuning and why it's crucial for businesses to unlock the full potential of AI.</p><h2 id="what-is-fine-tuning">What is fine-tuning?</h2><p>Fine-tuning is the process of taking a pre-trained AI model and further training it to perform specific tasks or operate within a particular domain or scope of activity. This can mean either:</p><ul><li>Taking an unspecialized AI model, like GPT-4, and further training it to specialize.</li><li>Taking an AI model specialized for one task or domain and further training it to specialize in a different but related domain.</li></ul><p>This requires additional data specific to the task or domain. Fine-tuning takes advantage of everything the pre-trained AI model already knows, then refocuses it on the kind of work you are interested in using it for. It's a way of "tweaking" the model, like how a musician can fine-tune an instrument, and in the case of AI models, it can make an enormous difference.</p><h2 id="why-should-you-fine-tune">Why should you fine-tune?</h2><p>Large AI models are often pretty good out of the box. But don't let first impressions fool you. When you hire a new employee, no matter how impressive their resumé is, they will not be at their best until they know and understand your business processes and their role. In the same way, AI models with general-purpose training may seem impressively human, but like humans, they make mistakes, misunderstand, and sometimes go completely off the rails.</p><p>Fine-tuning is an AI analog of employee training and apprenticeship. It reduces error and inaccuracy.</p><p><a href="https://finetunerplus.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI's Finetuner</a> can unlock the full potential of large AI models for your company by:</p><h3 id="enhancing-accuracy-and-performance-through-customization">Enhancing accuracy and performance through customization</h3><p>You can't just download AI models that know your business and processes from the internet. Having state-of-the-art high-performance AI, producing high-quality results specialized for your use case, gives you a competitive advantage. Once it is in place, it can open the door to further innovation, improved customer satisfaction, and higher rates of return.</p><h3 id="costing-less">Costing less</h3><p>Developing a new AI model from scratch, competitive with the state-of-the-art, is a daunting expense. Hiring the technical expertise and maintaining the computer hardware needed for such a task is difficult enough. Add to that the truly enormous quantities of data required to train it, and it becomes something outside of the reach of all but a few specialized firms.</p><p>Worse still, there is no reason to believe the results will be better than a fine-tuned version of a general-purpose model.</p><p>Fine-tuning leverages the pre-existing learning in a trained AI model, and it can learn to specialize from a remarkably small amount of additional domain-specific information. Fine-tuning a pre-trained model offers you every advantage over building new models from scratch: They take less computing time, demand less expensive hardware, and you need only a fraction of the training data while at the same time offering comparable or better outcomes.</p><p>Using Jina AI's Finetuner, all the problems of maintaining your own AI tech stack are eliminated, including the hardware if you use Jina AI Cloud. You can redeploy the savings to other parts of your business.</p><h3 id="securing-your-data">Securing your data</h3><p>Jina AI's Finetuner can run on your company's servers or in a secure, controlled sandbox on Jina AI's European-hosted cloud. Your sensitive data never has to leave your control, reducing the risk of unauthorized access and data breaches. This is a major advantage for businesses subject to strict data protection requirements.</p><p>Fine-tuning is essential to making the latest AI work for business, and it enables companies to develop innovative custom solutions that give them an edge in the market. With the right tools, you can quickly and cost-effectively integrate AI into your operations as a driver of growth.</p><p><a href="https://calendly.com/susana-guzman?ref=jina-ai-gmbh.ghost.io">Book a call with us</a> to discuss how we can make AI work for you.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffine-tuning-unlocking-the-full-potential-of-ai-for-businesses%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 50%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; 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Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Fine-tuning: Unlocking the full potential of AI for businesses</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Fine-tuning is a way of "tweaking" an AI model, like how a musician can fine-tune an instrument, and in the case of AI models, it can make an enormous difference.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 66.6875%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/WhatsApp-Image-2022-12-06-at-15.46.39.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Susana Guzmán</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 17, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Developments in artificial intelligence are moving fast, and it feels like there's something new going on with large AI models almost every day. These breakthroughs have opened up a world of possibilities for various industries. But to make the most of AI-powered processes and tools, it is essential to adapt them to your specific business and use case. That's where <strong><strong><strong><strong><strong><em>fine-tuning</em></strong></strong></strong></strong></strong> comes in.</p><p>In this blog post, we'll look at the concept of fine-tuning and why it's crucial for businesses to unlock the full potential of AI.</p><h2 id="what-is-fine-tuning">What is fine-tuning?</h2><p>Fine-tuning is the process of taking a pre-trained AI model and further training it to perform specific tasks or operate within a particular domain or scope of activity. This can mean either:</p><ul><li>Taking an unspecialized AI model, like GPT-4, and further training it to specialize.</li><li>Taking an AI model specialized for one task or domain and further training it to specialize in a different but related domain.</li></ul><p>This requires additional data specific to the task or domain. Fine-tuning takes advantage of everything the pre-trained AI model already knows, then refocuses it on the kind of work you are interested in using it for. It's a way of "tweaking" the model, like how a musician can fine-tune an instrument, and in the case of AI models, it can make an enormous difference.</p><h2 id="why-should-you-fine-tune">Why should you fine-tune?</h2><p>Large AI models are often pretty good out of the box. But don't let first impressions fool you. When you hire a new employee, no matter how impressive their resumé is, they will not be at their best until they know and understand your business processes and their role. In the same way, AI models with general-purpose training may seem impressively human, but like humans, they make mistakes, misunderstand, and sometimes go completely off the rails.</p><p>Fine-tuning is an AI analog of employee training and apprenticeship. It reduces error and inaccuracy.</p><p><a href="https://finetunerplus.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI's Finetuner</a> can unlock the full potential of large AI models for your company by:</p><h3 id="enhancing-accuracy-and-performance-through-customization">Enhancing accuracy and performance through customization</h3><p>You can't just download AI models that know your business and processes from the internet. Having state-of-the-art high-performance AI, producing high-quality results specialized for your use case, gives you a competitive advantage. Once it is in place, it can open the door to further innovation, improved customer satisfaction, and higher rates of return.</p><h3 id="costing-less">Costing less</h3><p>Developing a new AI model from scratch, competitive with the state-of-the-art, is a daunting expense. Hiring the technical expertise and maintaining the computer hardware needed for such a task is difficult enough. Add to that the truly enormous quantities of data required to train it, and it becomes something outside of the reach of all but a few specialized firms.</p><p>Worse still, there is no reason to believe the results will be better than a fine-tuned version of a general-purpose model.</p><p>Fine-tuning leverages the pre-existing learning in a trained AI model, and it can learn to specialize from a remarkably small amount of additional domain-specific information. Fine-tuning a pre-trained model offers you every advantage over building new models from scratch: They take less computing time, demand less expensive hardware, and you need only a fraction of the training data while at the same time offering comparable or better outcomes.</p><p>Using Jina AI's Finetuner, all the problems of maintaining your own AI tech stack are eliminated, including the hardware if you use Jina AI Cloud. You can redeploy the savings to other parts of your business.</p><h3 id="securing-your-data">Securing your data</h3><p>Jina AI's Finetuner can run on your company's servers or in a secure, controlled sandbox on Jina AI's European-hosted cloud. Your sensitive data never has to leave your control, reducing the risk of unauthorized access and data breaches. This is a major advantage for businesses subject to strict data protection requirements.</p><p>Fine-tuning is essential to making the latest AI work for business, and it enables companies to develop innovative custom solutions that give them an edge in the market. With the right tools, you can quickly and cost-effectively integrate AI into your operations as a driver of growth.</p><p><a href="https://calendly.com/susana-guzman?ref=jina-ai-gmbh.ghost.io">Book a call with us</a> to discuss how we can make AI work for you.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffine-tuning-unlocking-the-full-potential-of-ai-for-businesses%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Fine-tuning with Low Budget and High Expectations</title><meta charset="utf-8"><meta name="title" content="Fine-tuning with Low Budget and High Expectations"><meta name="description" content="Fine-tuning is highly effective, economical, and eco-friendly; or at least that's what all the deep learning tweets will tell you. Exactly how much data &amp; time do you need to get a good result?"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/fine-tuning-with-low-budget-and-high-expectations"><meta property="og:title" content="Fine-tuning with Low Budget and High Expectations"><meta property="og:description" content="Fine-tuning is highly effective, economical, and eco-friendly; or at least that's what all the deep learning tweets will tell you. Exactly how much data &amp; time do you need to get a good result?"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--53-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/fine-tuning-with-low-budget-and-high-expectations"><meta property="twitter:title" content="Fine-tuning with Low Budget and High Expectations"><meta property="twitter:description" content="Fine-tuning is highly effective, economical, and eco-friendly; or at least that's what all the deep learning tweets will tell you. Exactly how much data &amp; time do you need to get a good result?"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--53-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Fine-tuning with Low Budget and High Expectations</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Fine-tuning is highly effective, economical, and eco-friendly; or at least that's what all the deep learning tweets will tell you. Exactly how much data &amp; time do you need to get a good result?</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 80px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 93.2813%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/4B483B29-E306-402B-8635-64866C458406.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Bo Wang, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 01, 2022 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Fine-tuning is a transfer learning technique developed as part of the Deep Learning revolution in artificial intelligence. Instead of learning a new task from scratch, fine-tuning takes a pre-trained model, trained on a related task, and then further trains it for the new task. Alternately, it can mean taking a model pre-trained for an open domain task, and further training it for a domain-specific one.</p><p>Compared to training from scratch, fine-tuning is a much more cost-efficient solution whenever it is feasible. It requires:</p><ul><li><strong>less labeled data, </strong>as there is no need to learn everything all over again. All the training is devoted to acquiring domain-specific knowledge.</li><li><strong>less time to train, </strong>since the number of variables is much smaller and most layers in the deep neural network freeze during fine-tuning.</li></ul><p>Leveraging and transferring pre-existing training to new problems is one of the major practical developments of the Deep Learning revolution. It is highly effective, economical, and environmentally friendly. This is especially true for small businesses and individuals that hope to take advantage of new AI technologies.</p><p>Or at least that's what all the deep learning tweets will tell you.</p><p>But if you think about it, or try to use fine-tuning in a real world use-case, you will quickly find out that the promise comes with a lot of caveats:</p><ul><li><strong>Exactly <em>how much data</em> do you</strong><em><strong> </strong></em><strong>need to get a good result? </strong>One labeled data point? Ten? One thousand? Ten thousand?</li><li><strong>Exactly <em>how much time</em> do you need to get good results? </strong>One minute of fine-tuning? An hour? A day? A week?</li></ul><p>These are not trivial questions, even for large enterprises, but they are especially critical to SME's and individuals who have limited resources to invest in AI. Domain-specific data is neither free nor error-free and requires costly human labor to generate. Top of the line GPU pipelines are frighteningly expensive to buy and maintain, with most enterprises renting time on a cloud service. An unplanned AWS bill in the thousands of euros is unwelcome at the best of times.</p><p>This article will give you a <strong>quantitative answer</strong> to these questions, using the Jina AI Finetuner. This tool is designed to improve the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a><figcaption>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.&nbsp;</figcaption></figure><h2 id="experiment-design">Experiment design </h2><p>We designed two experiments to quantitatively study how <strong>labeled data</strong> and <strong>training time</strong> affect fine-tuning performance. For each experiment, we construct three multimodal search tasks by fine-tuning three deep neural networks. We chose seven datasets, two of which are non-domain-specific public datasets, to ensure the generality of our experiment. </p><p>We measure the performance of fine-tuned models by evaluating their ability to perform search tasks, as measured by <a href="https://en.wikipedia.org/wiki/Mean_reciprocal_rank?ref=jina-ai-gmbh.ghost.io">Mean Reciprocal Rank</a> (mRR), Recall, and <a href="https://stats.stackexchange.com/questions/127041/mean-average-precision-vs-mean-reciprocal-rank?ref=jina-ai-gmbh.ghost.io">Mean Average Precision</a> (mAP). These metrics are calculated using the top 20 results of each search in the validation subset held out from each dataset. </p><p>The table below summarizes the tasks, models and datasets used in our experiments, as well their performance metrics without any fine-tuning.</p><table>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Fine-tuning with Low Budget and High Expectations</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Fine-tuning is highly effective, economical, and eco-friendly; or at least that's what all the deep learning tweets will tell you. Exactly how much data &amp; time do you need to get a good result?</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 80px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 93.2813%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/4B483B29-E306-402B-8635-64866C458406.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Bo Wang, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 01, 2022 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Fine-tuning is a transfer learning technique developed as part of the Deep Learning revolution in artificial intelligence. Instead of learning a new task from scratch, fine-tuning takes a pre-trained model, trained on a related task, and then further trains it for the new task. Alternately, it can mean taking a model pre-trained for an open domain task, and further training it for a domain-specific one.</p><p>Compared to training from scratch, fine-tuning is a much more cost-efficient solution whenever it is feasible. It requires:</p><ul><li><strong>less labeled data, </strong>as there is no need to learn everything all over again. All the training is devoted to acquiring domain-specific knowledge.</li><li><strong>less time to train, </strong>since the number of variables is much smaller and most layers in the deep neural network freeze during fine-tuning.</li></ul><p>Leveraging and transferring pre-existing training to new problems is one of the major practical developments of the Deep Learning revolution. It is highly effective, economical, and environmentally friendly. This is especially true for small businesses and individuals that hope to take advantage of new AI technologies.</p><p>Or at least that's what all the deep learning tweets will tell you.</p><p>But if you think about it, or try to use fine-tuning in a real world use-case, you will quickly find out that the promise comes with a lot of caveats:</p><ul><li><strong>Exactly <em>how much data</em> do you</strong><em><strong> </strong></em><strong>need to get a good result? </strong>One labeled data point? Ten? One thousand? Ten thousand?</li><li><strong>Exactly <em>how much time</em> do you need to get good results? </strong>One minute of fine-tuning? An hour? A day? A week?</li></ul><p>These are not trivial questions, even for large enterprises, but they are especially critical to SME's and individuals who have limited resources to invest in AI. Domain-specific data is neither free nor error-free and requires costly human labor to generate. Top of the line GPU pipelines are frighteningly expensive to buy and maintain, with most enterprises renting time on a cloud service. An unplanned AWS bill in the thousands of euros is unwelcome at the best of times.</p><p>This article will give you a <strong>quantitative answer</strong> to these questions, using the Jina AI Finetuner. This tool is designed to improve the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a><figcaption>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.&nbsp;</figcaption></figure><h2 id="experiment-design">Experiment design </h2><p>We designed two experiments to quantitatively study how <strong>labeled data</strong> and <strong>training time</strong> affect fine-tuning performance. For each experiment, we construct three multimodal search tasks by fine-tuning three deep neural networks. We chose seven datasets, two of which are non-domain-specific public datasets, to ensure the generality of our experiment. </p><p>We measure the performance of fine-tuned models by evaluating their ability to perform search tasks, as measured by <a href="https://en.wikipedia.org/wiki/Mean_reciprocal_rank?ref=jina-ai-gmbh.ghost.io">Mean Reciprocal Rank</a> (mRR), Recall, and <a href="https://stats.stackexchange.com/questions/127041/mean-average-precision-vs-mean-reciprocal-rank?ref=jina-ai-gmbh.ghost.io">Mean Average Precision</a> (mAP). These metrics are calculated using the top 20 results of each search in the validation subset held out from each dataset. </p><p>The table below summarizes the tasks, models and datasets used in our experiments, as well their performance metrics without any fine-tuning.</p><table>
 <thead>
   <tr>
     <th>Task</th>
diff --git a/news/finetuner-0-6-3-update/index.html b/news/finetuner-0-6-3-update/index.html
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 GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Tas"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-0-6-3-update"><meta property="twitter:title" content="Finetuner 0.6.3 Update"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.
 
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+GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Tas"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.
 
 GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Tas</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 13, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers <a href="https://github.com/jina-ai/finetuner/releases/tag/v0.6.3?ref=jina-ai-gmbh.ghost.io">Finetuner version 0.6.3</a>, including dependencies finetuner-api 0.4.2 and finetuner-core 0.10.4.</p>
 <p>It contains 2 new features, 2 bug fixes, and 1 documentation improvement.</p>
@@ -28,13 +28,13 @@ <h3 id="allocate-more-gpu-memory-in-gpu-environments">Allocate more GPU memory i
 <h3 id="add-wise-ft-to-clip-finetuning-571">Add WiSE-FT to CLIP finetuning (#571)</h3>
 <p><a href="https://arxiv.org/abs/2109.01903?ref=jina-ai-gmbh.ghost.io">WiSE-FT</a> is a recent development that has proven to be an effective way to fine-tune models with a strong zero-shot capability, such as CLIP. We have added it to Finetuner along with <a href="https://finetuner.jina.ai/tasks/text-to-image/?ref=jina-ai-gmbh.ghost.io#advanced-wise-ft">documentation on its use</a>.</p>
 <p>Finetuner allows you to apply WiSE-FT easily using <code>WiSEFTCallback</code>. Finetuner will trigger the callback when the fine-tuning job is finished and merge the weights between the pre-trained model and the fine-tuned model:</p>
-<pre><code class="language-python">from finetuner.callbacks import WiSEFTCallback
+<pre><code class="language-python hljs"><span class="hljs-keyword">from</span> finetuner.callbacks <span class="hljs-keyword">import</span> WiSEFTCallback
 
 run = finetuner.fit(
-    model='ViT-B-32#openai',
+    model=<span class="hljs-string">'ViT-B-32#openai'</span>,
     ...,
-    loss='CLIPLoss',
-    callbacks=[WiSEFTCallback(alpha=0.5)],
+    loss=<span class="hljs-string">'CLIPLoss'</span>,
+    callbacks=[WiSEFTCallback(alpha=<span class="hljs-number">0.5</span>)],
 )
 </code></pre>
 <p>See the <a href="https://finetuner.jina.ai/tasks/text-to-image/?ref=jina-ai-gmbh.ghost.io#advanced-wise-ft">documentation</a> for advice on how to set alpha.</p>
@@ -57,4 +57,4 @@ <h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2>
 <li>Michael Günther (@guenthermi)</li>
 <li>George Mastrapas (@gmastrapas)</li>
 </ul>
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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; 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 Release v0.6.4 · jina-ai/finetunerRelease Note Finetuner 0.6.4This release contains 6 new features, 1 bug fix and 1 documentation improvement.🆕 FeaturesUser-friendly login from Python notebooks "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-0-6-4"><meta property="twitter:title" content="Finetuner 0.6.4 Update"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.
 
-Release v0.6.4 · jina-ai/finetunerRelease Note Finetuner 0.6.4This release contains 6 new features, 1 bug fix and 1 documentation improvement.🆕 FeaturesUser-friendly login from Python notebooks "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+Release v0.6.4 · jina-ai/finetunerRelease Note Finetuner 0.6.4This release contains 6 new features, 1 bug fix and 1 documentation improvement.🆕 FeaturesUser-friendly login from Python notebooks "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.
 
 Release v0.6.4 · jina-ai/finetunerRelease Note Finetuner 0.6.4This release contains 6 new features, 1 bug fix and 1 documentation improvement.🆕 FeaturesUser-friendly login from Python notebooks </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 27, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.6.4?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.6.4 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.6.4This release contains 6 new features, 1 bug fix and 1 documentation improvement.🆕 FeaturesUser-friendly login from Python notebooks (#576)We’ve added the method fine...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/29dd42398645ff3c697fa97e7419abadcadd0b8bfeb48959157cdaa1f38a38bb/jina-ai/finetuner/releases/tag/v0.6.4" alt=""></div></a></figure><p>This release covers <a href="https://github.com/jina-ai/finetuner/releases/tag/v0.6.4?ref=jina-ai-gmbh.ghost.io">Finetuner version 0.6.4</a>, including dependencies finetuner-api 0.4.4 and finetuner-core 0.11.0.</p><p>This release contains 6 new features, 1 bug fix and 1 documentation improvement.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="user-friendly-login-from-python-notebooks-576">User-friendly login from Python notebooks (<a href="https://github.com/jina-ai/finetuner/pull/576?ref=jina-ai-gmbh.ghost.io">#576</a>)</h3><p>We've added the method <code>finetuner.notebook_login()</code> as a new method for logging in from notebooks like <a href="https://jupyter.org/?ref=jina-ai-gmbh.ghost.io">Jupyter</a> in a more user-friendly way.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/196168124-d10390fd-d7ad-40f8-b965-71ed298fabb1.png" class="kg-image" alt="" width="2000" height="482" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/196168124-d10390fd-d7ad-40f8-b965-71ed298fabb1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/196168124-d10390fd-d7ad-40f8-b965-71ed298fabb1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/196168124-d10390fd-d7ad-40f8-b965-71ed298fabb1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/196168124-d10390fd-d7ad-40f8-b965-71ed298fabb1.png 2056w" sizes="(min-width: 720px) 720px"><figcaption>Notebook login</figcaption></figure><h3 id="change-device-specification-argument-in-finetunerfit-577">Change device specification argument in <code>finetuner.fit()</code> (<a href="https://github.com/jina-ai/finetuner/pull/577?ref=jina-ai-gmbh.ghost.io">#577</a>)<br></h3><p>We've deprecated the <code>cpu</code>argument to the <code>finetuner.fit()</code>method, replacing it with the <code>device</code>argument.<br><br>Instead of specifying <code>cpu=False</code>, for a GPU run, you should now use <code>device='cuda'</code>; and for a CPU run, instead of <code>cpu=True</code>, use <code>device='cpu'</code>.<br><br>The default is equivalent to <code>device='cuda'</code>. Unless you're certain that your Finetuner job will run quickly on a CPU, you should use the default argument.<br><br>We expect to remove the <code>cpu</code> argument entirely in version 0.7, which will break any old code still using it.</p><h3 id="validate-finetuner-run-arguments-on-the-client-side-579">Validate Finetuner run arguments on the client side (<a href="https://github.com/jina-ai/finetuner/pull/579?ref=jina-ai-gmbh.ghost.io">#579</a>)</h3><p>The Finetuner client now checks that the arguments to Finetuner runs are coherent and at least partially valid, before transmitting them to the cloud infrastructure. Not all arguments can be validated on the client-side, but the Finetuner client now checks all the ones that can.</p><h3 id="update-names-of-openclip-models-580">Update names of OpenCLIP models (<a href="https://github.com/jina-ai/finetuner/pull/580?ref=jina-ai-gmbh.ghost.io">#580</a>)</h3><p>We have changed the names of open-access CLIP models available via Finetuner to be compatible with <a href="https://clip-as-service.jina.ai/?ref=jina-ai-gmbh.ghost.io">CLIP-as-Service</a>. For example, the model previously referenced as <code>ViT-B-16#openai</code> is now <code>ViT-B-16::openai</code>.</p><h3 id="add-method-finetunerbuildmodel-to-load-pre-trained-models-without-fine-tuning-584">Add method <code>finetuner.build_model()</code> to load pre-trained models without fine-tuning (<a href="https://github.com/jina-ai/finetuner/pull/584?ref=jina-ai-gmbh.ghost.io">#584</a>)</h3><p>Previously, it was not possible to load a pre-trained model via Finetuner without performing some retraining or 'fine-tuning' on it. Now it is possible to get a pre-trained model, <em>as is</em>, and use it via Finetuner immediately.<br><br>For example, to use a BERT model in the finetuner without any fine-tuning:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> finetuner
 <span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document, DocumentArray
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner 0.7.7 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 24, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/0.7.7?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.7.7 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.7.7This release covers Finetuner version 0.7.7, including dependencies finetuner-api 0.5.9 and finetuner-core 0.13.5.This release contains 2 new features, 2 refactorings,…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/9d54ee74fbecd9e5d31578ccfd1998fd004b809ec941f849e4f1efe1f77264a6/jina-ai/finetuner/releases/tag/0.7.7" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.7, including dependencies finetuner-api 0.5.9 and finetuner-core 0.13.5.</p><p>This release contains 2 new features, 2 refactorings, 3 bug fixes, and 1 documentation improvement.</p><h2 id="%F0%9F%86%95-features"><strong>🆕 Features</strong></h2><h3 id="training-data-synthesis-715"><strong>Training data synthesis (<a href="https://github.com/jina-ai/finetuner/pull/715?ref=jina-ai-gmbh.ghost.io">#715</a>)</strong></h3><p>In this release of Finetuner, we have introduced a training data synthesis feature. This feature is particularly useful for users in the e-commerce domain, who may have difficulty obtaining enough labeled training data.</p><p>This feature allows you to use historical queries collected from your search system, along with your articles, to generate training data:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> finetuner
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner 0.7.7 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 24, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/0.7.7?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.7.7 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.7.7This release covers Finetuner version 0.7.7, including dependencies finetuner-api 0.5.9 and finetuner-core 0.13.5.This release contains 2 new features, 2 refactorings,…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/9d54ee74fbecd9e5d31578ccfd1998fd004b809ec941f849e4f1efe1f77264a6/jina-ai/finetuner/releases/tag/0.7.7" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.7, including dependencies finetuner-api 0.5.9 and finetuner-core 0.13.5.</p><p>This release contains 2 new features, 2 refactorings, 3 bug fixes, and 1 documentation improvement.</p><h2 id="%F0%9F%86%95-features"><strong>🆕 Features</strong></h2><h3 id="training-data-synthesis-715"><strong>Training data synthesis (<a href="https://github.com/jina-ai/finetuner/pull/715?ref=jina-ai-gmbh.ghost.io">#715</a>)</strong></h3><p>In this release of Finetuner, we have introduced a training data synthesis feature. This feature is particularly useful for users in the e-commerce domain, who may have difficulty obtaining enough labeled training data.</p><p>This feature allows you to use historical queries collected from your search system, along with your articles, to generate training data:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> finetuner
 <span class="hljs-keyword">from</span> finetuner.model <span class="hljs-keyword">import</span> synthesis_model_en
 
 synthesis_run = finetuner.synthesize(
@@ -44,4 +44,4 @@
         ),
     ]
 )
-</code></pre><h2 id="%E2%9A%99-refactoring"><strong>⚙ Refactoring</strong></h2><h3 id="display-small-loss-values-with-higher-precision"><strong>Display small loss values with higher precision.</strong></h3><p>To avoid displaying "0.000" for very small loss values, the display precision has been increased.</p><h3 id="filter-pil-debugging-messages-from-logging-stack"><strong>Filter PIL debugging messages from logging stack.</strong></h3><p>In order to enhance the readability of the logs, we have excluded debugging messages generated by the PIL package.</p><h2 id="%F0%9F%90%9E-bug-fixes"><strong>🐞 Bug Fixes</strong></h2><h3 id="no-longer-overestimate-the-batchsize-for-text-models"><strong>No longer overestimate the <code>batch_size</code> for text models.</strong></h3><p>This pull request resolves a bug where the batch size finder would incorrectly overestimate the maximum usable batch size for text models like BERT. This is likely to happen when users fine-tune the <code>bert-base-en</code> model without specifying <code>batch_size</code>.</p><h3 id="fix-division-by-none-error-in-evaluationcallback"><strong>Fix division by <code>None</code> error in <code>EvaluationCallback</code>.</strong></h3><p>Runs set up with automatic batch-size configuration and automatic evaluation callback previously passed the value <code>None</code> to <code>EvaluationCallback</code> as <code>batch_size</code>. This resulted in a division by <code>None</code> error.</p><h3 id="filter-out-queries-that-do-not-have-any-matches-in-evaluationcallback"><strong>Filter out queries that do not have any matches in <code>EvaluationCallback</code>.</strong></h3><p>When there are queries in the evaluation data which do not have any matches, Finetuner was previously unable to calculate any metrics, which leads to division by zero errors. It has been fixed in this release.</p><h2 id="%F0%9F%93%97-documentation-improvements"><strong>📗 Documentation Improvements</strong></h2><h3 id="add-a-tutorial-for-data-synthesis-745"><strong>Add a tutorial for data synthesis (<a href="https://github.com/jina-ai/finetuner/pull/745?ref=jina-ai-gmbh.ghost.io">#745</a>)</strong></h3><p>We have provided a tutorial for the new data synthesis module.</p><h2 id="%F0%9F%A4%9F-contributors"><strong>🤟 Contributors</strong></h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-0-7-7-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
+</code></pre><h2 id="%E2%9A%99-refactoring"><strong>⚙ Refactoring</strong></h2><h3 id="display-small-loss-values-with-higher-precision"><strong>Display small loss values with higher precision.</strong></h3><p>To avoid displaying "0.000" for very small loss values, the display precision has been increased.</p><h3 id="filter-pil-debugging-messages-from-logging-stack"><strong>Filter PIL debugging messages from logging stack.</strong></h3><p>In order to enhance the readability of the logs, we have excluded debugging messages generated by the PIL package.</p><h2 id="%F0%9F%90%9E-bug-fixes"><strong>🐞 Bug Fixes</strong></h2><h3 id="no-longer-overestimate-the-batchsize-for-text-models"><strong>No longer overestimate the <code>batch_size</code> for text models.</strong></h3><p>This pull request resolves a bug where the batch size finder would incorrectly overestimate the maximum usable batch size for text models like BERT. This is likely to happen when users fine-tune the <code>bert-base-en</code> model without specifying <code>batch_size</code>.</p><h3 id="fix-division-by-none-error-in-evaluationcallback"><strong>Fix division by <code>None</code> error in <code>EvaluationCallback</code>.</strong></h3><p>Runs set up with automatic batch-size configuration and automatic evaluation callback previously passed the value <code>None</code> to <code>EvaluationCallback</code> as <code>batch_size</code>. This resulted in a division by <code>None</code> error.</p><h3 id="filter-out-queries-that-do-not-have-any-matches-in-evaluationcallback"><strong>Filter out queries that do not have any matches in <code>EvaluationCallback</code>.</strong></h3><p>When there are queries in the evaluation data which do not have any matches, Finetuner was previously unable to calculate any metrics, which leads to division by zero errors. It has been fixed in this release.</p><h2 id="%F0%9F%93%97-documentation-improvements"><strong>📗 Documentation Improvements</strong></h2><h3 id="add-a-tutorial-for-data-synthesis-745"><strong>Add a tutorial for data synthesis (<a href="https://github.com/jina-ai/finetuner/pull/745?ref=jina-ai-gmbh.ghost.io">#745</a>)</strong></h3><p>We have provided a tutorial for the new data synthesis module.</p><h2 id="%F0%9F%A4%9F-contributors"><strong>🤟 Contributors</strong></h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-0-7-7-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. All rights reserved.</div></div></div></div><footer class="q-footer q-layout__section--marginal fixed-bottom lock-blur bg-transparent print-hide"><div class="row"><div class="q-btn-group row no-wrap q-btn-group--flat inline col-12 col-md-6 justify-center"><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://discord.jina.ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-discord" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://github.com/jina-ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-github" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://huggingface.co/jinaai" target="_blank" style="font-size: 10px; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner 0.7.8 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 08, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.7.8?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.7.8 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.7.8This release covers Finetuner version 0.7.8, including dependencies finetuner-api 0.5.10 and finetuner-core 0.13.7.This release contains 4 new features, 1 performance…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/bb41b435bfba0584c97c6832421d4a0ed9422bb9ef8f619171a3979f6255bddc/jina-ai/finetuner/releases/tag/v0.7.8" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.8, including dependencies finetuner-api 0.5.10 and finetuner-core 0.13.7.</p><p>This release contains 4 new features, 1 performance improvement, 1 refactoring, 2 bug fixes, and 1 documentation improvement.</p><h2 id="%F0%9F%86%95-features"><strong>🆕 Features</strong></h2><h3 id="add-multilingual-text-encoder-models"><strong>Add multilingual text encoder models</strong></h3><p>We have added support for the multilingual embedding model <code>distiluse-base-multi</code> (a copy of <a href="https://huggingface.co/sentence-transformers/distiluse-base-multilingual-cased-v1?ref=jina-ai-gmbh.ghost.io"><code>distiluse-base-multilingual-cased-v1</code></a>). It supports semantic search in Arabic, Chinese, Dutch, English, French, German, Italian, Korean, Polish, Portuguese, Russian, Spanish, and Turkish.</p><h3 id="add-multilingual-model-for-training-data-synthesis-jobs-750"><strong>Add multilingual model for training data synthesis jobs (<a href="https://github.com/jina-ai/finetuner/pull/750?ref=jina-ai-gmbh.ghost.io">#750</a>)</strong></h3><p>We now support data synthesis for datasets in languages other than English, specifically the ones supported by <code>distiluse-base-multi</code> (see above). To use them you need to add the synthesis model <code>synthesis_model_multi</code> as the <code>models</code> parameter to the <code>finetuner.synthesis</code> function:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> finetuner.model <span class="hljs-keyword">import</span> synthesis_model_multi
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner 0.7.8 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 08, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.7.8?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.7.8 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.7.8This release covers Finetuner version 0.7.8, including dependencies finetuner-api 0.5.10 and finetuner-core 0.13.7.This release contains 4 new features, 1 performance…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/bb41b435bfba0584c97c6832421d4a0ed9422bb9ef8f619171a3979f6255bddc/jina-ai/finetuner/releases/tag/v0.7.8" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.8, including dependencies finetuner-api 0.5.10 and finetuner-core 0.13.7.</p><p>This release contains 4 new features, 1 performance improvement, 1 refactoring, 2 bug fixes, and 1 documentation improvement.</p><h2 id="%F0%9F%86%95-features"><strong>🆕 Features</strong></h2><h3 id="add-multilingual-text-encoder-models"><strong>Add multilingual text encoder models</strong></h3><p>We have added support for the multilingual embedding model <code>distiluse-base-multi</code> (a copy of <a href="https://huggingface.co/sentence-transformers/distiluse-base-multilingual-cased-v1?ref=jina-ai-gmbh.ghost.io"><code>distiluse-base-multilingual-cased-v1</code></a>). It supports semantic search in Arabic, Chinese, Dutch, English, French, German, Italian, Korean, Polish, Portuguese, Russian, Spanish, and Turkish.</p><h3 id="add-multilingual-model-for-training-data-synthesis-jobs-750"><strong>Add multilingual model for training data synthesis jobs (<a href="https://github.com/jina-ai/finetuner/pull/750?ref=jina-ai-gmbh.ghost.io">#750</a>)</strong></h3><p>We now support data synthesis for datasets in languages other than English, specifically the ones supported by <code>distiluse-base-multi</code> (see above). To use them you need to add the synthesis model <code>synthesis_model_multi</code> as the <code>models</code> parameter to the <code>finetuner.synthesis</code> function:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> finetuner.model <span class="hljs-keyword">import</span> synthesis_model_multi
 
 synthesis_run = finetuner.synthesize(
     ...
@@ -21,4 +21,4 @@
 
 model = finetuner.get_model(<span class="hljs-string">'jinaai/ecommerce-sbert-model'</span>)
 e1, e2 = finetuner.encode(model, [<span class="hljs-string">'XBox'</span>, <span class="hljs-string">'Xbox One Console 500GB - Black (2015)'</span>])
-</code></pre><h3 id="add-an-option-to-the-tracking-callback-to-include-zero-shot-metrics-in-logging"><strong>Add an option to the tracking callback to include zero-shot metrics in logging.</strong></h3><p>Previously, tracking callbacks like <code>WandBLogger</code> did not consider the evaluation results of the model before fine-tuning, because they only start the tracking when the actual model tuning starts. Now, we add an option <code>log_zero_shot</code> to those callbacks (which is <code>True</code> by default). When enabled, this makes Finetuner send evaluation metrics calculated before training to the tracking service used during training.</p><h2 id="%F0%9F%9A%80-performance"><strong>🚀 Performance</strong></h2><h3 id="reduce-memory-consumption-during-data-synthesis-and-make-the-resulting-dataset-more-compact"><strong>Reduce memory consumption during data synthesis and make the resulting dataset more compact</strong></h3><p>We optimized data synthesis to reduce its memory consumption, which enables synthesis jobs to run on larger datasets and reduces the run-time of fine-tuning jobs using synthesized training data.</p><h2 id="%E2%9A%99-refactoring"><strong>⚙ Refactoring</strong></h2><h3 id="increase-the-default-numrelations-from-3-to-10-for-data-synthesis-jobs-750"><strong>Increase the default <code>num_relations</code> from 3 to 10 for data synthesis jobs. (<a href="https://github.com/jina-ai/finetuner/pull/750?ref=jina-ai-gmbh.ghost.io">#750</a>)</strong></h3><p>Data synthesis jobs are more effective if a large amount of training data is generated from small and medium-sized query datasets. Therefore, we have increased the default number of triplets generated for each query from 3 to 10. If you run data synthesis jobs with a large number of queries (&gt;1M), you should consider resetting the <code>num_relations</code> parameter to a lower number.</p><h2 id="%F0%9F%90%9E-bug-fixes"><strong>🐞 Bug Fixes</strong></h2><h3 id="change-the-english-cross-encoder-model-from-multi-lingual-to-an-actual-english-model"><strong>Change the English cross-encoder model from multi-lingual to an actual English model.</strong></h3><p>The English cross-encoder model which we used was actually a multi-lingual one. By using an English one instead, we produce higher-quality synthetic training data and the resulting embedding models achieve better evaluation results.</p><h3 id="fix-create-synthesis-run-not-accepting-documentarray-as-input-type-748"><strong>Fix create synthesis run not accepting DocumentArray as input type. (<a href="https://github.com/jina-ai/finetuner/pull/748?ref=jina-ai-gmbh.ghost.io">#748</a>)</strong></h3><p>We noticed that data synthesis jobs can accept either a named <code>DocumentArray</code> object stored on Jina AI Cloud or a list of text values. However, passing file paths to locally stored DocumentArray datasets failed. This bug is fixed by this release.</p><h2 id="%F0%9F%93%97-documentation-improvements"><strong>📗 Documentation Improvements</strong></h2><h3 id="update-data-synthesis-tutorial-including-english-and-multilingual-models-750"><strong>Update data synthesis tutorial including English and multilingual models. (<a href="https://github.com/jina-ai/finetuner/pull/750?ref=jina-ai-gmbh.ghost.io">#750</a>)</strong></h3><p>We have added documentation on how to apply data synthesis to datasets that include materials in languages other than English.</p><h2 id="%F0%9F%A4%9F-contributors"><strong>🤟 Contributors</strong></h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li><li>Jonathan Geuter (<a href="https://github.com/j-geuter?ref=jina-ai-gmbh.ghost.io">@j-geuter</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-0-7-8-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; 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+</code></pre><h3 id="add-an-option-to-the-tracking-callback-to-include-zero-shot-metrics-in-logging"><strong>Add an option to the tracking callback to include zero-shot metrics in logging.</strong></h3><p>Previously, tracking callbacks like <code>WandBLogger</code> did not consider the evaluation results of the model before fine-tuning, because they only start the tracking when the actual model tuning starts. Now, we add an option <code>log_zero_shot</code> to those callbacks (which is <code>True</code> by default). When enabled, this makes Finetuner send evaluation metrics calculated before training to the tracking service used during training.</p><h2 id="%F0%9F%9A%80-performance"><strong>🚀 Performance</strong></h2><h3 id="reduce-memory-consumption-during-data-synthesis-and-make-the-resulting-dataset-more-compact"><strong>Reduce memory consumption during data synthesis and make the resulting dataset more compact</strong></h3><p>We optimized data synthesis to reduce its memory consumption, which enables synthesis jobs to run on larger datasets and reduces the run-time of fine-tuning jobs using synthesized training data.</p><h2 id="%E2%9A%99-refactoring"><strong>⚙ Refactoring</strong></h2><h3 id="increase-the-default-numrelations-from-3-to-10-for-data-synthesis-jobs-750"><strong>Increase the default <code>num_relations</code> from 3 to 10 for data synthesis jobs. (<a href="https://github.com/jina-ai/finetuner/pull/750?ref=jina-ai-gmbh.ghost.io">#750</a>)</strong></h3><p>Data synthesis jobs are more effective if a large amount of training data is generated from small and medium-sized query datasets. Therefore, we have increased the default number of triplets generated for each query from 3 to 10. If you run data synthesis jobs with a large number of queries (&gt;1M), you should consider resetting the <code>num_relations</code> parameter to a lower number.</p><h2 id="%F0%9F%90%9E-bug-fixes"><strong>🐞 Bug Fixes</strong></h2><h3 id="change-the-english-cross-encoder-model-from-multi-lingual-to-an-actual-english-model"><strong>Change the English cross-encoder model from multi-lingual to an actual English model.</strong></h3><p>The English cross-encoder model which we used was actually a multi-lingual one. By using an English one instead, we produce higher-quality synthetic training data and the resulting embedding models achieve better evaluation results.</p><h3 id="fix-create-synthesis-run-not-accepting-documentarray-as-input-type-748"><strong>Fix create synthesis run not accepting DocumentArray as input type. (<a href="https://github.com/jina-ai/finetuner/pull/748?ref=jina-ai-gmbh.ghost.io">#748</a>)</strong></h3><p>We noticed that data synthesis jobs can accept either a named <code>DocumentArray</code> object stored on Jina AI Cloud or a list of text values. However, passing file paths to locally stored DocumentArray datasets failed. This bug is fixed by this release.</p><h2 id="%F0%9F%93%97-documentation-improvements"><strong>📗 Documentation Improvements</strong></h2><h3 id="update-data-synthesis-tutorial-including-english-and-multilingual-models-750"><strong>Update data synthesis tutorial including English and multilingual models. (<a href="https://github.com/jina-ai/finetuner/pull/750?ref=jina-ai-gmbh.ghost.io">#750</a>)</strong></h3><p>We have added documentation on how to apply data synthesis to datasets that include materials in languages other than English.</p><h2 id="%F0%9F%A4%9F-contributors"><strong>🤟 Contributors</strong></h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li><li>Jonathan Geuter (<a href="https://github.com/j-geuter?ref=jina-ai-gmbh.ghost.io">@j-geuter</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-0-7-8-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner 0.7 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 18, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, you can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.7.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.7.0 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.7.0This release covers Finetuner version 0.7.0, including dependencies finetuner-api 0.4.10 and finetuner-core 0.12.3.This release contains 4 new features, 4 bug fixes, a...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/b8d56ba2c85cf1fd9f4d3c9aff112f028bae95a5e70f7c96c772375e33173f1a/jina-ai/finetuner/releases/tag/v0.7.0" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.0, including dependencies finetuner-api 0.4.10 and finetuner-core 0.12.3.</p><p>This release contains 4 new features, 4 refactorings, 4 bug fixes, and 4 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="allow-fine-tuning-for-pointnet-models-638">Allow Fine-Tuning for PointNet++ Models (<a href="https://github.com/jina-ai/finetuner/pull/638?ref=jina-ai-gmbh.ghost.io">#638</a>)</h3><p>We have added a new embedding model based on the <a href="https://proceedings.neurips.cc/paper/2017/file/d8bf84be3800d12f74d8b05e9b89836f-Paper.pdf?ref=jina-ai-gmbh.ghost.io" rel="nofollow">PointNet++ model</a>. You can use this model for 3D-mesh applications. To fine-tune it, set the <code>model</code> parameter of the <code>fit</code> function to <code>pointnet++</code>:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> finetuner
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 18, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, you can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.7.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.7.0 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.7.0This release covers Finetuner version 0.7.0, including dependencies finetuner-api 0.4.10 and finetuner-core 0.12.3.This release contains 4 new features, 4 bug fixes, a...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/b8d56ba2c85cf1fd9f4d3c9aff112f028bae95a5e70f7c96c772375e33173f1a/jina-ai/finetuner/releases/tag/v0.7.0" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.0, including dependencies finetuner-api 0.4.10 and finetuner-core 0.12.3.</p><p>This release contains 4 new features, 4 refactorings, 4 bug fixes, and 4 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="allow-fine-tuning-for-pointnet-models-638">Allow Fine-Tuning for PointNet++ Models (<a href="https://github.com/jina-ai/finetuner/pull/638?ref=jina-ai-gmbh.ghost.io">#638</a>)</h3><p>We have added a new embedding model based on the <a href="https://proceedings.neurips.cc/paper/2017/file/d8bf84be3800d12f74d8b05e9b89836f-Paper.pdf?ref=jina-ai-gmbh.ghost.io" rel="nofollow">PointNet++ model</a>. You can use this model for 3D-mesh applications. To fine-tune it, set the <code>model</code> parameter of the <code>fit</code> function to <code>pointnet++</code>:</p><pre><code class="language-python">import finetuner
 
 finetuner.login()
 
 run = finetuner.fit(
-    model=<span class="hljs-string">'pointnet++'</span>,
-    train_data=<span class="hljs-string">'finetuner/modelnet40-train'</span>,
-    epochs=<span class="hljs-number">10</span>,
-    batch_size=<span class="hljs-number">64</span>,
-    learning_rate=<span class="hljs-number">5e-4</span>,
-    loss=<span class="hljs-string">'TripletMarginLoss'</span>,
-    device=<span class="hljs-string">'cuda'</span>,
-)</code></pre><p>We have also prepared a <a href="https://colab.research.google.com/drive/1lIMDFkUVsWMshU-akJ_hwzBfJ37zLFzU?usp=sharing&amp;ref=jina-ai-gmbh.ghost.io" rel="nofollow">tutorial</a> with detailed information about how to use the model and prepare 3D mesh data for Finetuner.</p><h3 id="add-valsplit-to-fit-interface-624">Add <code>val_split</code> to fit interface (<a href="https://github.com/jina-ai/finetuner/pull/624?ref=jina-ai-gmbh.ghost.io">#624</a>)</h3><p>To make it easier to evaluate models, we have added the <code>val_split</code> parameter to the fit function. Using this parameter automatically splits the training data into a training dataset and a validation dataset, used to calculate the validation loss. For example, the following call will automatically hold out 20% of the data for validation:</p><pre><code class="language-python hljs">run = finetuner.fit(
-    model=<span class="hljs-string">'efficientnet_b0'</span>,
+    model='pointnet++',
+    train_data='finetuner/modelnet40-train',
+    epochs=10,
+    batch_size=64,
+    learning_rate=5e-4,
+    loss='TripletMarginLoss',
+    device='cuda',
+)</code></pre><p>We have also prepared a <a href="https://colab.research.google.com/drive/1lIMDFkUVsWMshU-akJ_hwzBfJ37zLFzU?usp=sharing&amp;ref=jina-ai-gmbh.ghost.io" rel="nofollow">tutorial</a> with detailed information about how to use the model and prepare 3D mesh data for Finetuner.</p><h3 id="add-valsplit-to-fit-interface-624">Add <code>val_split</code> to fit interface (<a href="https://github.com/jina-ai/finetuner/pull/624?ref=jina-ai-gmbh.ghost.io">#624</a>)</h3><p>To make it easier to evaluate models, we have added the <code>val_split</code> parameter to the fit function. Using this parameter automatically splits the training data into a training dataset and a validation dataset, used to calculate the validation loss. For example, the following call will automatically hold out 20% of the data for validation:</p><pre><code class="language-python">run = finetuner.fit(
+    model='efficientnet_b0',
     train_data=train_data,
-    val_split=<span class="hljs-number">0.2</span>
-)</code></pre><h3 id="add-recall-and-f1-score-to-evaluation-metrics">Add recall and F1 score to evaluation metrics</h3><p>If you are using the evaluation callback, evaluation results now include two new metrics: <code>recall_at_k</code> and <code>f1_score_at_k</code>.</p><h3 id="evaluation-callback-evaluates-zero-shot-models-and-reports-this-in-the-logs">Evaluation callback evaluates zero-shot models and reports this in the logs</h3><p>Previously, the evaluation callback only evaluated models after each fine-tuning epoch. Now, evaluation metrics are also calculated before any fine-tuning and the log displays the metrics after each epoch, together with the pre-fine-tuning (i.e. zero-shot) evaluation results:</p><pre><code class="language-text hljs language-plaintext">DEBUG    Finetuning took 0 days, 0 hours 5 minutes and 39 seconds                                         __main__.py:197
+    val_split=0.2
+)</code></pre><h3 id="add-recall-and-f1-score-to-evaluation-metrics">Add recall and F1 score to evaluation metrics</h3><p>If you are using the evaluation callback, evaluation results now include two new metrics: <code>recall_at_k</code> and <code>f1_score_at_k</code>.</p><h3 id="evaluation-callback-evaluates-zero-shot-models-and-reports-this-in-the-logs">Evaluation callback evaluates zero-shot models and reports this in the logs</h3><p>Previously, the evaluation callback only evaluated models after each fine-tuning epoch. Now, evaluation metrics are also calculated before any fine-tuning and the log displays the metrics after each epoch, together with the pre-fine-tuning (i.e. zero-shot) evaluation results:</p><pre><code class="language-text">DEBUG    Finetuning took 0 days, 0 hours 5 minutes and 39 seconds                                         __main__.py:197
 INFO     Metric: 'pointnet++_precision_at_k' before fine-tuning:  0.56533 after fine-tuning: 0.81100      __main__.py:210
 INFO     Metric: 'pointnet++_recall_at_k' before fine-tuning:  0.15467 after fine-tuning: 0.24175         __main__.py:210
 INFO     Metric: 'pointnet++_f1_score_at_k' before fine-tuning:  0.23209 after fine-tuning: 0.34774       __main__.py:210
 INFO     Metric: 'pointnet++_hit_at_k' before fine-tuning:  0.95667 after fine-tuning: 0.95333            __main__.py:210
 INFO     Metric: 'pointnet++_average_precision' before fine-tuning:  0.71027 after fine-tuning: 0.85515   __main__.py:210
 INFO     Metric: 'pointnet++_reciprocal_rank' before fine-tuning:  0.79103 after fine-tuning: 0.89103     __main__.py:210
-INFO     Metric: 'pointnet++_dcg_at_k' before fine-tuning:  4.71826 after fine-tuning: 6.41999 </code></pre><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="drop-support-for-python-version-37">Drop support for Python version 3.7</h3><p>Due to a new dependency in the stubs package of finetuner-core that is not supported by Python 3.7, Finetuner now requires Python 3.8 or higher.</p><h3 id="change-default-experimentname-from-current-working-dir-to-default-637">Change default <code>experiment_name</code> from current working dir to default (<a href="https://github.com/jina-ai/finetuner/pull/637?ref=jina-ai-gmbh.ghost.io">#637</a>)</h3><p>Previously, Finetuner named experiments after the current folder, if no other name was provided. Now, the generic name <code>default</code> is used instead. Please note, that you can not create two runs with the same name in the same experiment, and we recommend always giving experiments explicit names.</p><h3 id="add-page-and-size-parameters-to-listruns-and-listexperiments-functions-637">Add <code>page</code> and <code>size</code> parameters to <code>list_runs</code> and <code>list_experiments</code> functions (<a href="https://github.com/jina-ai/finetuner/pull/637?ref=jina-ai-gmbh.ghost.io">#637</a>)</h3><p>We have added two new optional arguments to the <code>list_runs</code> and <code>list_experiments</code> functions: <code>page</code> and <code>size</code>. You can set <code>size</code> so that you retrieve no more than a specific number of runs or experiments. To retrieve more, set the <code>page</code> argument to progressively higher values. You can use these parameters to paginate the list of runs and experiments, which can become quite long.</p><h3 id="deprecate-cpu-parameter-and-notebooklogin-function-631">Deprecate <code>cpu</code> parameter and <code>notebook_login</code> function (<a href="https://github.com/jina-ai/finetuner/pull/631?ref=jina-ai-gmbh.ghost.io">#631</a>)</h3><p>The <code>cpu</code> parameter of the <code>fit</code> function is deprecated. Instead, use the <code>device</code> parameter which can be set to <code>cuda</code> or <code>cpu</code>:</p><pre><code class="language-diff hljs">run = finetuner.fit(
+INFO     Metric: 'pointnet++_dcg_at_k' before fine-tuning:  4.71826 after fine-tuning: 6.41999 </code></pre><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="drop-support-for-python-version-37">Drop support for Python version 3.7</h3><p>Due to a new dependency in the stubs package of finetuner-core that is not supported by Python 3.7, Finetuner now requires Python 3.8 or higher.</p><h3 id="change-default-experimentname-from-current-working-dir-to-default-637">Change default <code>experiment_name</code> from current working dir to default (<a href="https://github.com/jina-ai/finetuner/pull/637?ref=jina-ai-gmbh.ghost.io">#637</a>)</h3><p>Previously, Finetuner named experiments after the current folder, if no other name was provided. Now, the generic name <code>default</code> is used instead. Please note, that you can not create two runs with the same name in the same experiment, and we recommend always giving experiments explicit names.</p><h3 id="add-page-and-size-parameters-to-listruns-and-listexperiments-functions-637">Add <code>page</code> and <code>size</code> parameters to <code>list_runs</code> and <code>list_experiments</code> functions (<a href="https://github.com/jina-ai/finetuner/pull/637?ref=jina-ai-gmbh.ghost.io">#637</a>)</h3><p>We have added two new optional arguments to the <code>list_runs</code> and <code>list_experiments</code> functions: <code>page</code> and <code>size</code>. You can set <code>size</code> so that you retrieve no more than a specific number of runs or experiments. To retrieve more, set the <code>page</code> argument to progressively higher values. You can use these parameters to paginate the list of runs and experiments, which can become quite long.</p><h3 id="deprecate-cpu-parameter-and-notebooklogin-function-631">Deprecate <code>cpu</code> parameter and <code>notebook_login</code> function (<a href="https://github.com/jina-ai/finetuner/pull/631?ref=jina-ai-gmbh.ghost.io">#631</a>)</h3><p>The <code>cpu</code> parameter of the <code>fit</code> function is deprecated. Instead, use the <code>device</code> parameter which can be set to <code>cuda</code> or <code>cpu</code>:</p><pre><code class="language-diff">run = finetuner.fit(
     model='efficientnet_b0',
     train_data=train_data,
-<span class="hljs-deletion">-   cpu=False</span>
-<span class="hljs-addition">+   device='cuda'</span>
-)</code></pre><p>Additionally, we have deprecated the <code>notebook_login()</code> function. This was necessary to specifically support Jupyter notebooks, but <code>login()</code> now works correctly in notebooks by itself. We have removed the <code>notebook_login()</code> function and you must update any code that calls it.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-buildencodingdataset-623">Fix <code>build_encoding_dataset</code> (<a href="https://github.com/jina-ai/finetuner/pull/623?ref=jina-ai-gmbh.ghost.io">#623</a>)</h3><p>Previously, when fine-tuning a CLIP model, if you passed Finetuner a list of strings to encode, it would fail because it was unable to determine if this was a list of texts or a list of URIs to images or other objects. You would need to explicitly state the type in a <code>DocumentArray</code> object. Finetuner can now automatically detect the data type and handle it correctly.</p><pre><code class="language-python hljs">finetuner.encode(clip_text_model, [<span class="hljs-string">'some text to encode'</span>])</code></pre><h3 id="adjust-numitemsperclass-if-necessary">Adjust <code>num_items_per_class</code> if necessary</h3><p>The <code>finetuner.fit</code> function has a <code>num_items_per_class</code> parameter which determines how many items per class should be put into a batch during training. Unfortunately, it is not possible to freely set this parameter for every <code>batch_size</code> and every dataset, which could lead to errors during the training. Finetuner will now automatically adjust <code>num_items_per_class</code> if the one provided by the user is not compatible with the rest of the configuration.</p><p>Finetuner will try to find a parameter value close to the one you provided. You will only receive a warning that the parameter has been adjusted, and training will continue.</p><h3 id="set-default-freeze-to-false">Set default <code>freeze</code> to <code>False</code></h3><p>Until now, the <code>build_model</code> function would automatically set the parameter <code>freeze=True</code> when constructing a CNN model. Finetuner would also add a projection head to the function. To avoid this, <code>freeze</code> is now set to <code>False</code> by default.</p><h3 id="log-messages-in-evaluation-callback">Log messages in evaluation callback</h3><p>Previously, some logging messages from the evaluation callback were overwritten by progress bars in some cases. This should no longer occur.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><h3 id="rewrite-the-readme-638-643">Rewrite the README (<a href="https://github.com/jina-ai/finetuner/pull/638?ref=jina-ai-gmbh.ghost.io">#638</a>, <a href="https://github.com/jina-ai/finetuner/pull/643?ref=jina-ai-gmbh.ghost.io">#643</a>)</h3><p>We have rewritten the README file to be more concise and to include results from PointNet++ fine-tuning</p><h3 id="rewrite-the-m-clip-notebook-to-use-the-german-fashion12k-dataset-643">Rewrite the M-CLIP notebook to use the German Fashion12k dataset (<a href="https://github.com/jina-ai/finetuner/pull/643?ref=jina-ai-gmbh.ghost.io">#643</a>)</h3><p>Our M-CLIP tutorial now uses the <a href="https://jina.ai/news/improving-search-quality-non-english-queries-fine-tuned-multilingual-clip-models/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">German Fashion12k dataset</a>, which represents a more realistic application scenario.</p><h3 id="add-before-and-after-examples-in-the-tutorials-622">Add before and after examples in the tutorials (<a href="https://github.com/jina-ai/finetuner/pull/622?ref=jina-ai-gmbh.ghost.io">#622</a>)</h3><p>In our tutorials, we now include some examples that let you compare results before and after fine-tuning.</p><h3 id="restructuring-and-enriching-our-documentation-as-a-whole-643">Restructuring and enriching our documentation as a whole (<a href="https://github.com/jina-ai/finetuner/pull/643?ref=jina-ai-gmbh.ghost.io">#643</a>)</h3><p>We have performed a substantial re-write of our documentation pages. This includes new advanced topics like <em>Negative Mining</em> and more comprehensive information about inference in the <em>Walkthrough </em>section. We also improved the developer reference.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-0-7-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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\ No newline at end of file
+-   cpu=False
++   device='cuda'
+)</code></pre><p>Additionally, we have deprecated the <code>notebook_login()</code> function. This was necessary to specifically support Jupyter notebooks, but <code>login()</code> now works correctly in notebooks by itself. We have removed the <code>notebook_login()</code> function and you must update any code that calls it.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-buildencodingdataset-623">Fix <code>build_encoding_dataset</code> (<a href="https://github.com/jina-ai/finetuner/pull/623?ref=jina-ai-gmbh.ghost.io">#623</a>)</h3><p>Previously, when fine-tuning a CLIP model, if you passed Finetuner a list of strings to encode, it would fail because it was unable to determine if this was a list of texts or a list of URIs to images or other objects. You would need to explicitly state the type in a <code>DocumentArray</code> object. Finetuner can now automatically detect the data type and handle it correctly.</p><pre><code class="language-python">finetuner.encode(clip_text_model, ['some text to encode'])</code></pre><h3 id="adjust-numitemsperclass-if-necessary">Adjust <code>num_items_per_class</code> if necessary</h3><p>The <code>finetuner.fit</code> function has a <code>num_items_per_class</code> parameter which determines how many items per class should be put into a batch during training. Unfortunately, it is not possible to freely set this parameter for every <code>batch_size</code> and every dataset, which could lead to errors during the training. Finetuner will now automatically adjust <code>num_items_per_class</code> if the one provided by the user is not compatible with the rest of the configuration.</p><p>Finetuner will try to find a parameter value close to the one you provided. You will only receive a warning that the parameter has been adjusted, and training will continue.</p><h3 id="set-default-freeze-to-false">Set default <code>freeze</code> to <code>False</code></h3><p>Until now, the <code>build_model</code> function would automatically set the parameter <code>freeze=True</code> when constructing a CNN model. Finetuner would also add a projection head to the function. To avoid this, <code>freeze</code> is now set to <code>False</code> by default.</p><h3 id="log-messages-in-evaluation-callback">Log messages in evaluation callback</h3><p>Previously, some logging messages from the evaluation callback were overwritten by progress bars in some cases. This should no longer occur.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><h3 id="rewrite-the-readme-638-643">Rewrite the README (<a href="https://github.com/jina-ai/finetuner/pull/638?ref=jina-ai-gmbh.ghost.io">#638</a>, <a href="https://github.com/jina-ai/finetuner/pull/643?ref=jina-ai-gmbh.ghost.io">#643</a>)</h3><p>We have rewritten the README file to be more concise and to include results from PointNet++ fine-tuning</p><h3 id="rewrite-the-m-clip-notebook-to-use-the-german-fashion12k-dataset-643">Rewrite the M-CLIP notebook to use the German Fashion12k dataset (<a href="https://github.com/jina-ai/finetuner/pull/643?ref=jina-ai-gmbh.ghost.io">#643</a>)</h3><p>Our M-CLIP tutorial now uses the <a href="https://jina.ai/news/improving-search-quality-non-english-queries-fine-tuned-multilingual-clip-models/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">German Fashion12k dataset</a>, which represents a more realistic application scenario.</p><h3 id="add-before-and-after-examples-in-the-tutorials-622">Add before and after examples in the tutorials (<a href="https://github.com/jina-ai/finetuner/pull/622?ref=jina-ai-gmbh.ghost.io">#622</a>)</h3><p>In our tutorials, we now include some examples that let you compare results before and after fine-tuning.</p><h3 id="restructuring-and-enriching-our-documentation-as-a-whole-643">Restructuring and enriching our documentation as a whole (<a href="https://github.com/jina-ai/finetuner/pull/643?ref=jina-ai-gmbh.ghost.io">#643</a>)</h3><p>We have performed a substantial re-write of our documentation pages. This includes new advanced topics like <em>Negative Mining</em> and more comprehensive information about inference in the <em>Walkthrough </em>section. We also improved the developer reference.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-0-7-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
diff --git a/news/finetuner-release-note-0-6-2/index.html b/news/finetuner-release-note-0-6-2/index.html
index dbb99718923..1c59c3bf291 100644
--- a/news/finetuner-release-note-0-6-2/index.html
+++ b/news/finetuner-release-note-0-6-2/index.html
@@ -4,9 +4,9 @@
 
 GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Tas"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-release-note-0-6-2"><meta property="twitter:title" content="Finetuner 0.6.2 Update"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.
 
-GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Tas"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Tas"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.
 
-GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Tas</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 29, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers <a href="https://github.com/jina-ai/finetuner/releases/tag/v0.6.2?ref=jina-ai-gmbh.ghost.io">Finetuner version 0.6.2</a>, including dependencies finetuner-api 0.4.1 and finetuner-core 0.10.2. <br><br>It contains 3 new features and 1 bug fix.</p><h2 id="%F0%9F%86%95-features"> 🆕 Features</h2><h3 id="finetuner-can-now-produce-pytorch-models">Finetuner can now produce PyTorch models</h3><p>Previously, Finetuner only produced <a href="https://onnx.ai/?ref=jina-ai-gmbh.ghost.io">ONNX models</a>. Users can now choose between ONNX and <a href="https://pytorch.org/?ref=jina-ai-gmbh.ghost.io">PyTorch models</a>.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">PyTorch is now the <strong>default format</strong> for Finetuner output.</div></div><p>To select ONNX you must add the <code>to_onnx</code> flag to calls to <code>finetuner.fit()</code>:</p><pre><code class="language-Python hljs">run = finetuner.fit(
+GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Tas</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 29, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers <a href="https://github.com/jina-ai/finetuner/releases/tag/v0.6.2?ref=jina-ai-gmbh.ghost.io">Finetuner version 0.6.2</a>, including dependencies finetuner-api 0.4.1 and finetuner-core 0.10.2. <br><br>It contains 3 new features and 1 bug fix.</p><h2 id="%F0%9F%86%95-features"> 🆕 Features</h2><h3 id="finetuner-can-now-produce-pytorch-models">Finetuner can now produce PyTorch models</h3><p>Previously, Finetuner only produced <a href="https://onnx.ai/?ref=jina-ai-gmbh.ghost.io">ONNX models</a>. Users can now choose between ONNX and <a href="https://pytorch.org/?ref=jina-ai-gmbh.ghost.io">PyTorch models</a>.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">PyTorch is now the <strong>default format</strong> for Finetuner output.</div></div><p>To select ONNX you must add the <code>to_onnx</code> flag to calls to <code>finetuner.fit()</code>:</p><pre><code class="language-Python">run = finetuner.fit(
     ...,
-    to_onnx=<span class="hljs-literal">True</span>,
-)</code></pre><p>You must also add the flag to calls to <code>finetuner.get_model()</code> to use an ONNX model directly with <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray</a>:</p><pre><code class="language-Python hljs"> model = finetuner.get_model(..., is_onnx=<span class="hljs-literal">True</span>)</code></pre><p>To use an ONNX model inside a <a href="https://docs.jina.ai/fundamentals/flow/index.html?ref=jina-ai-gmbh.ghost.io">Jina Flow</a>:</p><pre><code class="language-Python hljs">f = Flow().add(
-    uses=<span class="hljs-string">'jinahub+docker://FinetunerExecutor/v0.10.2'</span>,
-    uses_with={<span class="hljs-string">'is_onnx'</span>: <span class="hljs-literal">True</span>},
-)</code></pre><h3 id="resubmit-jobs-automatically">Resubmit jobs automatically</h3><p>Previously, when submitting a request for Finetuner to use cloud computing resources, if the request failed, the job would fail and the user would have to resubmit it. Now, the job will be resubmitted automatically up to five times, before failing completely.</p><h3 id="concise-and-more-readable-log-messages">Concise and more readable log messages</h3><p>We have improved the logging in Finetuner to provide fewer and more readable messages for users.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="require-onnx-runtime-version-1111">Require ONNX runtime version &gt; 1.11.1</h3><ul><li>This bug was causing version incompatibility errors for users of Python 3.10.</li><li>The new version fixes the bug and makes Finetuner fully compatible with the latest Python releases.</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release: </p><ul><li>Michael Günther (@guenthermi)</li><li>Zhaofeng Miao (@mapleeit) </li><li>George Mastrapas (@gmastrapas) </li><li>Wang Bo (@bwanglzu) <br></li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-release-note-0-6-2%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
+    to_onnx=True,
+)</code></pre><p>You must also add the flag to calls to <code>finetuner.get_model()</code> to use an ONNX model directly with <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray</a>:</p><pre><code class="language-Python"> model = finetuner.get_model(..., is_onnx=True)</code></pre><p>To use an ONNX model inside a <a href="https://docs.jina.ai/fundamentals/flow/index.html?ref=jina-ai-gmbh.ghost.io">Jina Flow</a>:</p><pre><code class="language-Python">f = Flow().add(
+    uses='jinahub+docker://FinetunerExecutor/v0.10.2',
+    uses_with={'is_onnx': True},
+)</code></pre><h3 id="resubmit-jobs-automatically">Resubmit jobs automatically</h3><p>Previously, when submitting a request for Finetuner to use cloud computing resources, if the request failed, the job would fail and the user would have to resubmit it. Now, the job will be resubmitted automatically up to five times, before failing completely.</p><h3 id="concise-and-more-readable-log-messages">Concise and more readable log messages</h3><p>We have improved the logging in Finetuner to provide fewer and more readable messages for users.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="require-onnx-runtime-version-1111">Require ONNX runtime version &gt; 1.11.1</h3><ul><li>This bug was causing version incompatibility errors for users of Python 3.10.</li><li>The new version fixes the bug and makes Finetuner fully compatible with the latest Python releases.</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release: </p><ul><li>Michael Günther (@guenthermi)</li><li>Zhaofeng Miao (@mapleeit) </li><li>George Mastrapas (@gmastrapas) </li><li>Wang Bo (@bwanglzu) <br></li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-release-note-0-6-2%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Security Update to Finetuner 0.6.1</title><meta charset="utf-8"><meta name="title" content="Security Update to Finetuner 0.6.1"><meta name="description" content="Between 2022.09.23 and 2022.09.25, the Finetuner database was hacked and metadata from Finetuner runs was compromised. Training data and models were not compromised."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/finetuner-security-update-2022-28"><meta property="og:title" content="Security Update to Finetuner 0.6.1"><meta property="og:description" content="Between 2022.09.23 and 2022.09.25, the Finetuner database was hacked and metadata from Finetuner runs was compromised. Training data and models were not compromised."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/Blue-Pink-Gradient-Fashion-Banner--30---15-in---1-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-security-update-2022-28"><meta property="twitter:title" content="Security Update to Finetuner 0.6.1"><meta property="twitter:description" content="Between 2022.09.23 and 2022.09.25, the Finetuner database was hacked and metadata from Finetuner runs was compromised. Training data and models were not compromised."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/Blue-Pink-Gradient-Fashion-Banner--30---15-in---1-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Security Update to Finetuner 0.6.1</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Between 2022.09.23 and 2022.09.25, the Finetuner database was hacked and metadata from Finetuner runs was compromised. Training data and models were not compromised.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 28, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes fine-tuning easier, faster and performant by streamlining the workflow and handling all complexity and infrastructure on the cloud. With Finetuner, one can easily uplift pre-trained models to be more performant and production ready.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>Between 2022.09.23 and 2022.09.25, the Finetuner database was hacked and metadata from Finetuner runs was compromised. Training data and models were <strong>not</strong> compromised.</p><p>User privacy and security are essential for maintaining trust, and we want to remain as transparent as possible about events like these. Jina AI itself was not compromised and experienced no data breach from this event.</p><p>Read the rest of this note for more complete information.</p><h3 id="what-happened">What happened?</h3><p>On 2022.09.25, we received a bug report from a user that Finetuner login had failed. While inspecting the error logs, we discovered that an anonymous user had logged in to the Finetuner database and deleted all tables.</p><h3 id="who-was-impacted">Who was impacted?</h3><p>Finetuner is a machine learning training platform, and its internal databases do not store personal information. Only a user identifier string is stored. We have recently refactored our datastore and are now using an entirely different system from the one that was compromised.<br><br>We have database backups up to 2022.09.23. If you started a Finetuner job between 2022.09.23 and 2022.09.25 inclusive, we are sorry to inform you that we cannot recover your data. For jobs from before 2022.09.23, we will recover your data from backups at your request.</p><h3 id="what-information-was-involved">What information was involved?</h3><ul><li>The data being leaked has no personal information except a user identifier. All personal user information is stored in other information systems that have not been compromised.</li><li>Compromised data includes metadata for Finetuner jobs, such as <code>status</code>, <code>run_name</code>, <code>experiment_name</code>, &nbsp;<code>device</code>, <code>finetuner_version</code>, <code>creation_time</code>, <code>finish_time</code>.</li><li>Compromised data includes machine learning hyper-parameters for Finetuner jobs, such as <code>learning_rate</code>, <code>batch_size</code>, <code>loss_function</code>, <code>model</code>, etc.</li></ul><p>Compromised data <strong>does not include</strong>:</p><ul><li>Personal or company data about users.</li><li>Training data used in Finetuner.</li><li>Models used or produced in Finetuner runs.</li></ul><h3 id="what-should-i-do">What should I do?</h3><ul><li>If you want to recover a Finetuner run that was created <strong>before 2022.09.23</strong>, please reach out to <a href="mailto:team-finetuner@jina.ai">team-finetuner@jina.ai</a> and we will restore your data from backups.</li><li>If you have lost a Finetuner run created <strong>between 2022.09.23 and 2022.09.25</strong>, we suggest you rerun the job. Please update Finetuner to version 0.6.1.</li><li>Please let Jina AI know if you have any further issues in relation to this event. We are available to answer questions via <a href="mailto:team-finetuner@jina.ai">team-finetuner@jina.ai</a> .</li></ul><p>The security of your data is important to us, and we apologize for any problems caused by this breach.<br><br></p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-security-update-2022-28%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Security Update to Finetuner 0.6.1</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Between 2022.09.23 and 2022.09.25, the Finetuner database was hacked and metadata from Finetuner runs was compromised. Training data and models were not compromised.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 28, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes fine-tuning easier, faster and performant by streamlining the workflow and handling all complexity and infrastructure on the cloud. With Finetuner, one can easily uplift pre-trained models to be more performant and production ready.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>Between 2022.09.23 and 2022.09.25, the Finetuner database was hacked and metadata from Finetuner runs was compromised. Training data and models were <strong>not</strong> compromised.</p><p>User privacy and security are essential for maintaining trust, and we want to remain as transparent as possible about events like these. Jina AI itself was not compromised and experienced no data breach from this event.</p><p>Read the rest of this note for more complete information.</p><h3 id="what-happened">What happened?</h3><p>On 2022.09.25, we received a bug report from a user that Finetuner login had failed. While inspecting the error logs, we discovered that an anonymous user had logged in to the Finetuner database and deleted all tables.</p><h3 id="who-was-impacted">Who was impacted?</h3><p>Finetuner is a machine learning training platform, and its internal databases do not store personal information. Only a user identifier string is stored. We have recently refactored our datastore and are now using an entirely different system from the one that was compromised.<br><br>We have database backups up to 2022.09.23. If you started a Finetuner job between 2022.09.23 and 2022.09.25 inclusive, we are sorry to inform you that we cannot recover your data. For jobs from before 2022.09.23, we will recover your data from backups at your request.</p><h3 id="what-information-was-involved">What information was involved?</h3><ul><li>The data being leaked has no personal information except a user identifier. All personal user information is stored in other information systems that have not been compromised.</li><li>Compromised data includes metadata for Finetuner jobs, such as <code>status</code>, <code>run_name</code>, <code>experiment_name</code>, &nbsp;<code>device</code>, <code>finetuner_version</code>, <code>creation_time</code>, <code>finish_time</code>.</li><li>Compromised data includes machine learning hyper-parameters for Finetuner jobs, such as <code>learning_rate</code>, <code>batch_size</code>, <code>loss_function</code>, <code>model</code>, etc.</li></ul><p>Compromised data <strong>does not include</strong>:</p><ul><li>Personal or company data about users.</li><li>Training data used in Finetuner.</li><li>Models used or produced in Finetuner runs.</li></ul><h3 id="what-should-i-do">What should I do?</h3><ul><li>If you want to recover a Finetuner run that was created <strong>before 2022.09.23</strong>, please reach out to <a href="mailto:team-finetuner@jina.ai">team-finetuner@jina.ai</a> and we will restore your data from backups.</li><li>If you have lost a Finetuner run created <strong>between 2022.09.23 and 2022.09.25</strong>, we suggest you rerun the job. Please update Finetuner to version 0.6.1.</li><li>Please let Jina AI know if you have any further issues in relation to this event. We are available to answer questions via <a href="mailto:team-finetuner@jina.ai">team-finetuner@jina.ai</a> .</li></ul><p>The security of your data is important to us, and we apologize for any problems caused by this breach.<br><br></p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-security-update-2022-28%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Finetuner Update 0.6.5</title><meta charset="utf-8"><meta name="title" content="Finetuner Update 0.6.5"><meta name="description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/finetuner-update-0-6-5"><meta property="og:title" content="Finetuner Update 0.6.5"><meta property="og:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-update-0-6-5"><meta property="twitter:title" content="Finetuner Update 0.6.5"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner Update 0.6.5</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 11, 2022 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers <a href="https://github.com/jina-ai/finetuner/releases/tag/v0.6.5?ref=jina-ai-gmbh.ghost.io">Finetuner version 0.6.5</a>, including dependencies finetuner-api 0.4.7 and finetuner-core 0.11.4.</p><p>This release contains 6 new features, 1 bug fix, 2 refactorings, and 2 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="support-loading-training-data-and-evaluation-data-from-csv-files-592">Support loading training data and evaluation data from CSV files (<a href="https://github.com/jina-ai/finetuner/pull/592?ref=jina-ai-gmbh.ghost.io">#592</a>)</h3><p>We now support CSV files in the <code>finetuner.fit()</code>method. This simplifies training because it is no longer necessary to construct a <code>DocumentArray</code> object to contain training data. Instead, you can use a CSV file that contains the training data or pointers (i.e. URIs) to the relevant data objects.</p><pre><code class="language-python hljs">train_data = <span class="hljs-string">'path/to/some/data.csv'</span>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner Update 0.6.5</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 11, 2022 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers <a href="https://github.com/jina-ai/finetuner/releases/tag/v0.6.5?ref=jina-ai-gmbh.ghost.io">Finetuner version 0.6.5</a>, including dependencies finetuner-api 0.4.7 and finetuner-core 0.11.4.</p><p>This release contains 6 new features, 1 bug fix, 2 refactorings, and 2 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="support-loading-training-data-and-evaluation-data-from-csv-files-592">Support loading training data and evaluation data from CSV files (<a href="https://github.com/jina-ai/finetuner/pull/592?ref=jina-ai-gmbh.ghost.io">#592</a>)</h3><p>We now support CSV files in the <code>finetuner.fit()</code>method. This simplifies training because it is no longer necessary to construct a <code>DocumentArray</code> object to contain training data. Instead, you can use a CSV file that contains the training data or pointers (i.e. URIs) to the relevant data objects.</p><pre><code class="language-python hljs">train_data = <span class="hljs-string">'path/to/some/data.csv'</span>
 
 run = finetuner.fit(
     model=<span class="hljs-string">'efficientnet_b0'</span>,
@@ -36,4 +36,4 @@
 <span class="hljs-section">wandb:  View run at https://wandb.ai/anony-mouse-279369/[YOUR-RUN-URL]</span>
 </code></pre><p>See the <a href="https://finetuner.jina.ai/walkthrough/using-callbacks/?ref=jina-ai-gmbh.ghost.io#wandblogger">Finetuner documentation page on callbacks</a> for more information.</p><h3 id="support-for-image-blobs">Support for image blobs</h3><p>We now support <code>DocumentArray</code> image blobs in Finetuner. It is no longer necessary to directly convert images into tensors before sending them to the cloud.</p><p>You can convert image filepaths or URIs to blobs with the <code>Document.load_uri_to_blob()</code> method.</p><p>This saves a lot of memory and bandwidth since blobs are stored in their native, typically compressed format. Blobs are usually as small as 10% of the size of their corresponding tensor.</p><pre><code class="language-python hljs">d = Document(uri=<span class="hljs-string">'tests/resources/lena.png'</span>)
 d.load_uri_to_blob()
-</code></pre><p>If you use CSV to input local image files to Finetuner, this conversion happens automatically by default.</p><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="bump-hubble-sdk-version-to-0233-594">Bump Hubble SDK version to 0.23.3 (<a href="https://github.com/jina-ai/finetuner/pull/594?ref=jina-ai-gmbh.ghost.io">#594</a>)</h3><p>We have updated Finetuner to the latest version of Hubble, improving functionality and particularly improving access from code running in notebooks.</p><p>We will deprecate the method<code>finetuner.notebook_login()</code>starting from version 0.7 of Finetuner. Inside notebooks,<code>finetuner.login()</code>will now detect the environment automatically.</p><h3 id="remove-connect-function-596">Remove connect function (<a href="https://github.com/jina-ai/finetuner/pull/596?ref=jina-ai-gmbh.ghost.io">#596</a>)</h3><p>We have removed the <code>finetuner.connect()</code> method, since Finetuner no longer requires you to log in to Jina again if you are already logged in.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-executor-finetuner-import">Fix executor <code>_finetuner</code> import</h3><p>This bug caused the Finetuner executor to fail to start, and we have fixed the underlying issue.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><h3 id="document-the-force-argument-to-finetunerlogin-596">Document the <code>force</code> argument to <code>finetuner.login()</code> (<a href="https://github.com/jina-ai/finetuner/pull/596?ref=jina-ai-gmbh.ghost.io">#596</a>)</h3><p>We have documented the <code>force</code> parameter to <code>finetuner.login()</code>, which forces users to log in to Jina again, even if already logged in.</p><h3 id="update-image-to-image-example-599">Update Image-to-Image example (<a href="https://github.com/jina-ai/finetuner/pull/599?ref=jina-ai-gmbh.ghost.io">#599</a>)</h3><p>We have changed the configuration and training sets in the examples in the <a href="https://finetuner.jina.ai/notebooks/image_to_image/?ref=jina-ai-gmbh.ghost.io">Image-to-Image Search via ResNet50</a> documentation page.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Isabelle Mohr (<a href="https://github.com/violenil?ref=jina-ai-gmbh.ghost.io">@violenil</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-6-5%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; 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\ No newline at end of file
+</code></pre><p>If you use CSV to input local image files to Finetuner, this conversion happens automatically by default.</p><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="bump-hubble-sdk-version-to-0233-594">Bump Hubble SDK version to 0.23.3 (<a href="https://github.com/jina-ai/finetuner/pull/594?ref=jina-ai-gmbh.ghost.io">#594</a>)</h3><p>We have updated Finetuner to the latest version of Hubble, improving functionality and particularly improving access from code running in notebooks.</p><p>We will deprecate the method<code>finetuner.notebook_login()</code>starting from version 0.7 of Finetuner. Inside notebooks,<code>finetuner.login()</code>will now detect the environment automatically.</p><h3 id="remove-connect-function-596">Remove connect function (<a href="https://github.com/jina-ai/finetuner/pull/596?ref=jina-ai-gmbh.ghost.io">#596</a>)</h3><p>We have removed the <code>finetuner.connect()</code> method, since Finetuner no longer requires you to log in to Jina again if you are already logged in.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-executor-finetuner-import">Fix executor <code>_finetuner</code> import</h3><p>This bug caused the Finetuner executor to fail to start, and we have fixed the underlying issue.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><h3 id="document-the-force-argument-to-finetunerlogin-596">Document the <code>force</code> argument to <code>finetuner.login()</code> (<a href="https://github.com/jina-ai/finetuner/pull/596?ref=jina-ai-gmbh.ghost.io">#596</a>)</h3><p>We have documented the <code>force</code> parameter to <code>finetuner.login()</code>, which forces users to log in to Jina again, even if already logged in.</p><h3 id="update-image-to-image-example-599">Update Image-to-Image example (<a href="https://github.com/jina-ai/finetuner/pull/599?ref=jina-ai-gmbh.ghost.io">#599</a>)</h3><p>We have changed the configuration and training sets in the examples in the <a href="https://finetuner.jina.ai/notebooks/image_to_image/?ref=jina-ai-gmbh.ghost.io">Image-to-Image Search via ResNet50</a> documentation page.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Isabelle Mohr (<a href="https://github.com/violenil?ref=jina-ai-gmbh.ghost.io">@violenil</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-6-5%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Finetuner Update 0.6.7</title><meta charset="utf-8"><meta name="title" content="Finetuner Update 0.6.7"><meta name="description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/finetuner-update-0-6-6"><meta property="og:title" content="Finetuner Update 0.6.7"><meta property="og:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-update-0-6-6"><meta property="twitter:title" content="Finetuner Update 0.6.7"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f103304c-80ee-4091-8f7c-08916c1b5e34" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f103304c-80ee-4091-8f7c-08916c1b5e34" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner Update 0.6.7</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 24, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware. </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers <a href="https://github.com/jina-ai/finetuner/releases/tag/v0.6.7?ref=jina-ai-gmbh.ghost.io">Finetuner version 0.6.7</a>, including dependencies finetuner-api 0.4.8 and and finetuner-core 0.11.4.</p><p>This release contains 4 new features.</p><h2 id="%F0%9F%86%95-features"><strong>🆕 Features</strong></h2><h3 id="add-support-for-cross-modal-evaluation-in-the-evaluationcallback-615"><strong>Add support for cross-modal evaluation in the <code>EvaluationCallback</code> (<a href="https://github.com/jina-ai/finetuner/pull/615?ref=jina-ai-gmbh.ghost.io">#615</a>)</strong></h3><p>In previous versions of Finetuner, when using the <code>EvaluationCallback</code> to calculate IR metrics, you could only use a single model to encode both the query and the index data. This means that for training multiple models at the same time, like in CLIP fine-tuning, you could only use one encoder for evaluation. It is now possible to do cross-modal evaluation, where you use one model for encoding the query data and a second model for encoding the index data. This is useful in multi-modal tasks like <code>text-to-image</code>.</p><p>For doing the cross-modal evaluation, all you need to do is specify the <code>model</code> and <code>index_model</code> arguments in the <code>EvaluationCallback</code>, like so:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> finetuner
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 24, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware. </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers <a href="https://github.com/jina-ai/finetuner/releases/tag/v0.6.7?ref=jina-ai-gmbh.ghost.io">Finetuner version 0.6.7</a>, including dependencies finetuner-api 0.4.8 and and finetuner-core 0.11.4.</p><p>This release contains 4 new features.</p><h2 id="%F0%9F%86%95-features"><strong>🆕 Features</strong></h2><h3 id="add-support-for-cross-modal-evaluation-in-the-evaluationcallback-615"><strong>Add support for cross-modal evaluation in the <code>EvaluationCallback</code> (<a href="https://github.com/jina-ai/finetuner/pull/615?ref=jina-ai-gmbh.ghost.io">#615</a>)</strong></h3><p>In previous versions of Finetuner, when using the <code>EvaluationCallback</code> to calculate IR metrics, you could only use a single model to encode both the query and the index data. This means that for training multiple models at the same time, like in CLIP fine-tuning, you could only use one encoder for evaluation. It is now possible to do cross-modal evaluation, where you use one model for encoding the query data and a second model for encoding the index data. This is useful in multi-modal tasks like <code>text-to-image</code>.</p><p>For doing the cross-modal evaluation, all you need to do is specify the <code>model</code> and <code>index_model</code> arguments in the <code>EvaluationCallback</code>, like so:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> finetuner
 <span class="hljs-keyword">from</span> finetuner.callback <span class="hljs-keyword">import</span> EvaluationCallback
 
 run = finetuner.fit(
@@ -50,4 +50,4 @@
     batch_size=<span class="hljs-number">128</span>,
     num_items_per_class=<span class="hljs-number">8</span>,
 )
-</code></pre><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">The batch size needs to be a multiple of the number of items per class, in other words <code>batch_size % num_items_per_class == 0</code>. Otherwise Finetuner cannot respect the given <code>num_items_per_class</code> and throws an error.</div></div><h2 id="%F0%9F%A4%9F-contributors"><strong>🤟 Contributors</strong></h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-6-6%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
+</code></pre><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">The batch size needs to be a multiple of the number of items per class, in other words <code>batch_size % num_items_per_class == 0</code>. Otherwise Finetuner cannot respect the given <code>num_items_per_class</code> and throws an error.</div></div><h2 id="%F0%9F%A4%9F-contributors"><strong>🤟 Contributors</strong></h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-6-6%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Finetuner Update 0.7.1</title><meta charset="utf-8"><meta name="title" content="Finetuner Update 0.7.1"><meta name="description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/finetuner-update-0-7-1"><meta property="og:title" content="Finetuner Update 0.7.1"><meta property="og:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-update-0-7-1"><meta property="twitter:title" content="Finetuner Update 0.7.1"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner Update 0.7.1</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 15, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.1, including dependencies finetuner-api 0.5.0 and finetuner-core 0.12.6.</p><p>This release contains 2 new features, 3 refactorings, 3 bug fixes, and 4 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="support-sphereface-loss-functions-664">Support SphereFace Loss Functions (<a href="https://github.com/jina-ai/finetuner/pull/664?ref=jina-ai-gmbh.ghost.io">#664</a>)</h3><p>SphereFace loss functions were first formulated for computer vision, specifically face recognition, tasks. Finetuner supports two variations of this loss function, <code>ArcFaceLoss</code>, and <code>CosFaceLoss</code>. Instead of attempting to minimize the distance between positive pairs and maximize the distance between negative pairs, the SphereFace loss functions compare each sample with an estimate of the center point of each class's embeddings.</p><p>Like all supported loss functions, you can use them by specifying their name in the <code>loss</code> attribute of the <code>fit</code> function.</p><pre><code class="language-python hljs">run = finetuner.fit(
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner Update 0.7.1</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 15, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.1, including dependencies finetuner-api 0.5.0 and finetuner-core 0.12.6.</p><p>This release contains 2 new features, 3 refactorings, 3 bug fixes, and 4 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="support-sphereface-loss-functions-664">Support SphereFace Loss Functions (<a href="https://github.com/jina-ai/finetuner/pull/664?ref=jina-ai-gmbh.ghost.io">#664</a>)</h3><p>SphereFace loss functions were first formulated for computer vision, specifically face recognition, tasks. Finetuner supports two variations of this loss function, <code>ArcFaceLoss</code>, and <code>CosFaceLoss</code>. Instead of attempting to minimize the distance between positive pairs and maximize the distance between negative pairs, the SphereFace loss functions compare each sample with an estimate of the center point of each class's embeddings.</p><p>Like all supported loss functions, you can use them by specifying their name in the <code>loss</code> attribute of the <code>fit</code> function.</p><pre><code class="language-python hljs">run = finetuner.fit(
     ...,
     loss=<span class="hljs-string">'ArcFaceLoss'</span>,
     ...
@@ -25,4 +25,4 @@
     model=<span class="hljs-string">'efficientnet_b0'</span>,
     train_data=train_data,
     model_artifact=previous_run.artifact_id,
-)</code></pre><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="removing-resnet-based-clip-models-662">Removing ResNet-based CLIP Models (<a href="https://github.com/jina-ai/finetuner/pull/662?ref=jina-ai-gmbh.ghost.io">#662</a>)</h3><p>Due to low usage, we removed CLIP models which are based on ResNet.</p><h3 id="add-the-efficientnet-b7-model-662">Add the EfficientNet B7 Model (<a href="https://github.com/jina-ai/finetuner/pull/662?ref=jina-ai-gmbh.ghost.io">#662</a>)</h3><p>For image-to-image search, we now support EfficientNet B7 as a backbone model.</p><h3 id="increase-upload-size-of-csv-files-for-cloudjinaai">Increase Upload Size of CSV Files for cloud.jina.ai</h3><p>For <a href="https://cloud.jina.ai/user/finetuner-api?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Web UI</a> users, we have increased the upload file size from 1MB to 32MB. Python client users have always been able to upload much larger datasets and are unaffected by this change.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="solve-dependency-problem-in-mlflow-callback">Solve Dependency Problem in MLFlow Callback</h3><p>A new SQLAlchemy release caused the MLFlow callback to behave incorrectly in some cases. This release fixes the problem.</p><h3 id="prevent-errors-caused-by-wrong-numitemsperclass-parameter">Prevent Errors caused by wrong <code>num_items_per_class</code> Parameter</h3><p>Some loss functions do not use the <code>num_items_per_class</code> parameter. In some cases, it is possible for users to set this parameter in a way that is incompatible with the rest of the configuration and cause Finetuner to fail. Now the parameter is only validated if it is actually used, and for loss functions that do not use it, it is completely ignored.</p><h3 id="solve-problems-with-the-login-function-in-jupyter-notebooks-672">Solve Problems with the Login Function in Jupyter Notebooks (<a href="https://github.com/jina-ai/finetuner/pull/672?ref=jina-ai-gmbh.ghost.io">#672</a> )</h3><p>Sometimes, when calling <code>finetuner.login()</code> in a Jupyter notebook, login would appear successful, but Finetuner might not always behave correctly. Previously, users had to call <code>finetuner.login(force=True)</code> to be sure they were correctly logged in. This problem has been resolved, and <code>finetuner.login()</code> works correctly without the <code>force</code> flag.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><h3 id="add-a-documentation-page-for-loss-functions-and-pooling-664">Add a Documentation Page for Loss Functions and Pooling (<a href="https://github.com/jina-ai/finetuner/pull/664?ref=jina-ai-gmbh.ghost.io">#664</a>)</h3><p>We add a <a href="https://finetuner.jina.ai/advanced-topics/advanced-losses-optimizers-poolers/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">new page</a> to our documentation which explains several loss functions and the pooling options in more detail.</p><h3 id="add-a-section-about-finetuner-articles-669">Add a Section about Finetuner Articles (<a href="https://github.com/jina-ai/finetuner/pull/669?ref=jina-ai-gmbh.ghost.io">#669</a>)</h3><p>We add a list with articles to our README that make use of Finetuner and provide more insights for using Finetuner in practice.</p><h3 id="add-a-folder-for-example-csv-files-663">Add a Folder for Example CSV files (<a href="https://github.com/jina-ai/finetuner/pull/663?ref=jina-ai-gmbh.ghost.io">#663</a>)</h3><p>If you need example training datasets that have already been prepared for use in Finetuner, you can look at the <a href="https://github.com/jina-ai/finetuner/tree/main/datasets?ref=jina-ai-gmbh.ghost.io">dataset folder in our repository</a>.</p><h3 id="proofread-the-documentation-as-a-whole-to-fix-typos-and-broken-links-661-666">Proofread the documentation as a whole to fix typos and broken links (<a href="https://github.com/jina-ai/finetuner/pull/661?ref=jina-ai-gmbh.ghost.io">#661</a>, <a href="https://github.com/jina-ai/finetuner/pull/666?ref=jina-ai-gmbh.ghost.io">#666</a>)</h3><p>We repaired broken links and fixed typos found in the Finetuner documentation.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>CatStark (<a href="https://github.com/CatStark?ref=jina-ai-gmbh.ghost.io">@CatStark</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-7-1%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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\ No newline at end of file
+)</code></pre><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="removing-resnet-based-clip-models-662">Removing ResNet-based CLIP Models (<a href="https://github.com/jina-ai/finetuner/pull/662?ref=jina-ai-gmbh.ghost.io">#662</a>)</h3><p>Due to low usage, we removed CLIP models which are based on ResNet.</p><h3 id="add-the-efficientnet-b7-model-662">Add the EfficientNet B7 Model (<a href="https://github.com/jina-ai/finetuner/pull/662?ref=jina-ai-gmbh.ghost.io">#662</a>)</h3><p>For image-to-image search, we now support EfficientNet B7 as a backbone model.</p><h3 id="increase-upload-size-of-csv-files-for-cloudjinaai">Increase Upload Size of CSV Files for cloud.jina.ai</h3><p>For <a href="https://cloud.jina.ai/user/finetuner-api?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Web UI</a> users, we have increased the upload file size from 1MB to 32MB. Python client users have always been able to upload much larger datasets and are unaffected by this change.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="solve-dependency-problem-in-mlflow-callback">Solve Dependency Problem in MLFlow Callback</h3><p>A new SQLAlchemy release caused the MLFlow callback to behave incorrectly in some cases. This release fixes the problem.</p><h3 id="prevent-errors-caused-by-wrong-numitemsperclass-parameter">Prevent Errors caused by wrong <code>num_items_per_class</code> Parameter</h3><p>Some loss functions do not use the <code>num_items_per_class</code> parameter. In some cases, it is possible for users to set this parameter in a way that is incompatible with the rest of the configuration and cause Finetuner to fail. Now the parameter is only validated if it is actually used, and for loss functions that do not use it, it is completely ignored.</p><h3 id="solve-problems-with-the-login-function-in-jupyter-notebooks-672">Solve Problems with the Login Function in Jupyter Notebooks (<a href="https://github.com/jina-ai/finetuner/pull/672?ref=jina-ai-gmbh.ghost.io">#672</a> )</h3><p>Sometimes, when calling <code>finetuner.login()</code> in a Jupyter notebook, login would appear successful, but Finetuner might not always behave correctly. Previously, users had to call <code>finetuner.login(force=True)</code> to be sure they were correctly logged in. This problem has been resolved, and <code>finetuner.login()</code> works correctly without the <code>force</code> flag.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><h3 id="add-a-documentation-page-for-loss-functions-and-pooling-664">Add a Documentation Page for Loss Functions and Pooling (<a href="https://github.com/jina-ai/finetuner/pull/664?ref=jina-ai-gmbh.ghost.io">#664</a>)</h3><p>We add a <a href="https://finetuner.jina.ai/advanced-topics/advanced-losses-optimizers-poolers/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">new page</a> to our documentation which explains several loss functions and the pooling options in more detail.</p><h3 id="add-a-section-about-finetuner-articles-669">Add a Section about Finetuner Articles (<a href="https://github.com/jina-ai/finetuner/pull/669?ref=jina-ai-gmbh.ghost.io">#669</a>)</h3><p>We add a list with articles to our README that make use of Finetuner and provide more insights for using Finetuner in practice.</p><h3 id="add-a-folder-for-example-csv-files-663">Add a Folder for Example CSV files (<a href="https://github.com/jina-ai/finetuner/pull/663?ref=jina-ai-gmbh.ghost.io">#663</a>)</h3><p>If you need example training datasets that have already been prepared for use in Finetuner, you can look at the <a href="https://github.com/jina-ai/finetuner/tree/main/datasets?ref=jina-ai-gmbh.ghost.io">dataset folder in our repository</a>.</p><h3 id="proofread-the-documentation-as-a-whole-to-fix-typos-and-broken-links-661-666">Proofread the documentation as a whole to fix typos and broken links (<a href="https://github.com/jina-ai/finetuner/pull/661?ref=jina-ai-gmbh.ghost.io">#661</a>, <a href="https://github.com/jina-ai/finetuner/pull/666?ref=jina-ai-gmbh.ghost.io">#666</a>)</h3><p>We repaired broken links and fixed typos found in the Finetuner documentation.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>CatStark (<a href="https://github.com/CatStark?ref=jina-ai-gmbh.ghost.io">@CatStark</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-7-1%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Finetuner Update 0.7.2</title><meta charset="utf-8"><meta name="title" content="Finetuner Update 0.7.2"><meta name="description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/finetuner-update-0-7-2"><meta property="og:title" content="Finetuner Update 0.7.2"><meta property="og:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-update-0-7-2"><meta property="twitter:title" content="Finetuner Update 0.7.2"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 02, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.2, including dependencies finetuner-api 0.5.2 and finetuner-core 0.12.7.</p><p>This release contains 2 new features, 4 refactorings, 1 bug fix, and 3 documentation improvements.</p><h2 id="%F0%9F%86%95-features"><strong>🆕 Features</strong></h2><h3 id="support-learning-rate-scheduler-679"><strong>Support learning rate scheduler (<a href="https://github.com/jina-ai/finetuner/pull/679?ref=jina-ai-gmbh.ghost.io">#679</a>)</strong></h3><p>This PR add supports for the learning rate scheduler. The scheduler is used to adjust the learning rate during training. We support 6 learning rate schedulers: <code>linear</code>, <code>cosine</code>, <code>cosine_with_restarts</code>, <code>polynomial</code>, <code>constant</code> and <code>constant_with_warmup</code>.</p><p>When a scheduler is configured, the learning rate is by default adjusted after each batch. Alternatively, you can set <code>scheduler_optons = {'scheduler_step': 'epoch'}</code> to adjust the learning rate after each epoch instead.</p><p>You can use them by specifying their name in the <code>scheduler</code> attribute of the <code>fit</code> function.</p><pre><code class="language-python">run = finetuner.fit(
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 02, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.2, including dependencies finetuner-api 0.5.2 and finetuner-core 0.12.7.</p><p>This release contains 2 new features, 4 refactorings, 1 bug fix, and 3 documentation improvements.</p><h2 id="%F0%9F%86%95-features"><strong>🆕 Features</strong></h2><h3 id="support-learning-rate-scheduler-679"><strong>Support learning rate scheduler (<a href="https://github.com/jina-ai/finetuner/pull/679?ref=jina-ai-gmbh.ghost.io">#679</a>)</strong></h3><p>This PR add supports for the learning rate scheduler. The scheduler is used to adjust the learning rate during training. We support 6 learning rate schedulers: <code>linear</code>, <code>cosine</code>, <code>cosine_with_restarts</code>, <code>polynomial</code>, <code>constant</code> and <code>constant_with_warmup</code>.</p><p>When a scheduler is configured, the learning rate is by default adjusted after each batch. Alternatively, you can set <code>scheduler_optons = {'scheduler_step': 'epoch'}</code> to adjust the learning rate after each epoch instead.</p><p>You can use them by specifying their name in the <code>scheduler</code> attribute of the <code>fit</code> function.</p><pre><code class="language-python hljs">run = finetuner.fit(
     ...,
-    scheduler='linear',
-    scheduler_options={'scheduler_step': 'batch'},
+    scheduler=<span class="hljs-string">'linear'</span>,
+    scheduler_options={<span class="hljs-string">'scheduler_step'</span>: <span class="hljs-string">'batch'</span>},
     ...
 )
-</code></pre><h3 id="support-stepsperinterval-in-evaluationcallback"><strong>Support <code>steps_per_interval</code> in <code>EvaluationCallback</code></strong></h3><p>When working with large datasets, you may want to perform evaluations multiple times during each epoch. This parameter allows to specify a number of batches after which an evaluation should be performed. If set to <code>None</code>, an evaluation is performed only at the end of each epoch.</p><pre><code class="language-python">run = finetuner.fit(
+</code></pre><h3 id="support-stepsperinterval-in-evaluationcallback"><strong>Support <code>steps_per_interval</code> in <code>EvaluationCallback</code></strong></h3><p>When working with large datasets, you may want to perform evaluations multiple times during each epoch. This parameter allows to specify a number of batches after which an evaluation should be performed. If set to <code>None</code>, an evaluation is performed only at the end of each epoch.</p><pre><code class="language-python hljs">run = finetuner.fit(
     ...,
     callbacks=[
         EvaluationCallback(
             query_data=...,
             index_data=...,
-            steps_per_interval=3, # evaluate every 3 batches.
+            steps_per_interval=<span class="hljs-number">3</span>, <span class="hljs-comment"># evaluate every 3 batches.</span>
         ),
     ],
     ...
 )
-</code></pre><h2 id="%E2%9A%99-refactoring"><strong>⚙ Refactoring</strong></h2><h3 id="schedulerstep-becomes-part-of-scheduleroptions-679"><strong><code>scheduler_step</code> becomes part of <code>scheduler_options</code> (<a href="https://github.com/jina-ai/finetuner/pull/679?ref=jina-ai-gmbh.ghost.io">#679</a>)</strong></h3><p>We removed the <code>scheduler_step</code> argument from the <code>fit</code> function, now it is part of the <code>scheduler_options</code>.</p><pre><code class="language-diff">run = finetuner.fit(
+</code></pre><h2 id="%E2%9A%99-refactoring"><strong>⚙ Refactoring</strong></h2><h3 id="schedulerstep-becomes-part-of-scheduleroptions-679"><strong><code>scheduler_step</code> becomes part of <code>scheduler_options</code> (<a href="https://github.com/jina-ai/finetuner/pull/679?ref=jina-ai-gmbh.ghost.io">#679</a>)</strong></h3><p>We removed the <code>scheduler_step</code> argument from the <code>fit</code> function, now it is part of the <code>scheduler_options</code>.</p><pre><code class="language-diff hljs">run = finetuner.fit(
     ...,
     scheduler='linear',
--   scheduler_step='batch',
-+   scheduler_options={'scheduler_step': 'batch'},
+<span class="hljs-deletion">-   scheduler_step='batch',</span>
+<span class="hljs-addition">+   scheduler_options={'scheduler_step': 'batch'},</span>
     ...
 )
-</code></pre><h3 id="change-the-default-epochs-and-batchsize-in-cloudjinaai"><strong>Change the default <code>epochs</code> and <code>batch_size</code> in cloud.jina.ai</strong></h3><p>For <a href="https://cloud.jina.ai/user/finetuner-api?ref=jina-ai-gmbh.ghost.io">Web UI</a> users, we have reduced the default <code>epochs</code> from 10 to 5, and reduced the default <code>batch_size</code> from 128 to 64 to avoid out-of-memory errors from 3D-mesh fine-tuning.</p><h3 id="improve-the-user-journey-in-cloudjinaai"><strong>Improve the user journey in cloud.jina.ai</strong></h3><p>Add more textual guidance on creating Finetuner runs in the <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a> UI.</p><h3 id="remove-duplicate-query-document-pairs-in-unlabeled-csvs-678"><strong>Remove duplicate query-document pairs in unlabeled CSVs (<a href="https://github.com/jina-ai/finetuner/pull/678?ref=jina-ai-gmbh.ghost.io">#678</a>)</strong></h3><p>Finetuner now groups query-document pairs by their queries, thereby eliminating duplicate queries, when parsing CSV files. This leads to more effective fine-tuning.</p><h2 id="%F0%9F%90%9E-bug-fixes"><strong>🐞 Bug Fixes</strong></h2><h3 id="remove-invalid-argument-from-gem-pooler"><strong>Remove invalid argument from <code>GeM</code> pooler.</strong></h3><p>This PR removes the <code>output_dim</code> argument from the <code>GeM</code> pooler's forward function. You can use <code>GeM</code> pooler together with <code>ArcFaceLoss</code> to deliever better visual embedding quality.</p><pre><code class="language-diff">run = finetuner.fit(
+</code></pre><h3 id="change-the-default-epochs-and-batchsize-in-cloudjinaai"><strong>Change the default <code>epochs</code> and <code>batch_size</code> in cloud.jina.ai</strong></h3><p>For <a href="https://cloud.jina.ai/user/finetuner-api?ref=jina-ai-gmbh.ghost.io">Web UI</a> users, we have reduced the default <code>epochs</code> from 10 to 5, and reduced the default <code>batch_size</code> from 128 to 64 to avoid out-of-memory errors from 3D-mesh fine-tuning.</p><h3 id="improve-the-user-journey-in-cloudjinaai"><strong>Improve the user journey in cloud.jina.ai</strong></h3><p>Add more textual guidance on creating Finetuner runs in the <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a> UI.</p><h3 id="remove-duplicate-query-document-pairs-in-unlabeled-csvs-678"><strong>Remove duplicate query-document pairs in unlabeled CSVs (<a href="https://github.com/jina-ai/finetuner/pull/678?ref=jina-ai-gmbh.ghost.io">#678</a>)</strong></h3><p>Finetuner now groups query-document pairs by their queries, thereby eliminating duplicate queries, when parsing CSV files. This leads to more effective fine-tuning.</p><h2 id="%F0%9F%90%9E-bug-fixes"><strong>🐞 Bug Fixes</strong></h2><h3 id="remove-invalid-argument-from-gem-pooler"><strong>Remove invalid argument from <code>GeM</code> pooler.</strong></h3><p>This PR removes the <code>output_dim</code> argument from the <code>GeM</code> pooler's forward function. You can use <code>GeM</code> pooler together with <code>ArcFaceLoss</code> to deliever better visual embedding quality.</p><pre><code class="language-diff hljs">run = finetuner.fit(
     ...,
     model_options = {
         ...
--       'output_dim': 512,
-+       'pooler': 'GeM',
-+       'pooler_options': {'p': 2.4, 'eps': 1e-5}
+<span class="hljs-deletion">-       'output_dim': 512,</span>
+<span class="hljs-addition">+       'pooler': 'GeM',</span>
+<span class="hljs-addition">+       'pooler_options': {'p': 2.4, 'eps': 1e-5}</span>
     }
 )
-</code></pre><h2 id="%F0%9F%93%97-documentation-improvements"><strong>📗 Documentation Improvements</strong></h2><h3 id="add-a-documentation-section-for-gem-pooling-684"><strong>Add a documentation section for <code>GeM</code> pooling (<a href="https://github.com/jina-ai/finetuner/pull/684?ref=jina-ai-gmbh.ghost.io">#684</a>)</strong></h3><p>We have added a <a href="https://finetuner.jina.ai/advanced-topics/advanced-losses-optimizers-poolers/?ref=jina-ai-gmbh.ghost.io">new section</a> to our documentation which explains the pooling options in more detail.</p><h3 id="add-a-documentation-page-and-notebook-for-arcfaceloss-680"><strong>Add a documentation page and notebook for <code>ArcFaceLoss</code> (<a href="https://github.com/jina-ai/finetuner/pull/680?ref=jina-ai-gmbh.ghost.io">#680</a>)</strong></h3><p>We have added a <a href="https://finetuner.jina.ai/notebooks/image-to-image-arcface/?ref=jina-ai-gmbh.ghost.io">new page</a> to our documentation which demonstrates <code>ArcFaceLoss</code> on the <a href="http://ai.stanford.edu/%7Ejkrause/cars/car_dataset.html?ref=jina-ai-gmbh.ghost.io">Stanford Cars</a> dataset.</p><h3 id="add-a-documentation-section-on-creating-query-document-pairs-as-data-678"><strong>Add a documentation section on creating query-document pairs as data (<a href="https://github.com/jina-ai/finetuner/pull/678?ref=jina-ai-gmbh.ghost.io">#678</a>)</strong></h3><p>We have added a <a href="https://finetuner.jina.ai/walkthrough/create-training-data/?ref=jina-ai-gmbh.ghost.io">new section</a> to our documentation explaining how to create training data made of query-document pairs instead of explicitly annotated and labeled data.</p><h2 id="%F0%9F%A4%9F-contributors"><strong>🤟 Contributors</strong></h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>CatStark (<a href="https://github.com/CatStark?ref=jina-ai-gmbh.ghost.io">@CatStark</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Martin Matousek (<a href="https://github.com/matousek-martin?ref=jina-ai-gmbh.ghost.io">@matousek-martin</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-7-2%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
+</code></pre><h2 id="%F0%9F%93%97-documentation-improvements"><strong>📗 Documentation Improvements</strong></h2><h3 id="add-a-documentation-section-for-gem-pooling-684"><strong>Add a documentation section for <code>GeM</code> pooling (<a href="https://github.com/jina-ai/finetuner/pull/684?ref=jina-ai-gmbh.ghost.io">#684</a>)</strong></h3><p>We have added a <a href="https://finetuner.jina.ai/advanced-topics/advanced-losses-optimizers-poolers/?ref=jina-ai-gmbh.ghost.io">new section</a> to our documentation which explains the pooling options in more detail.</p><h3 id="add-a-documentation-page-and-notebook-for-arcfaceloss-680"><strong>Add a documentation page and notebook for <code>ArcFaceLoss</code> (<a href="https://github.com/jina-ai/finetuner/pull/680?ref=jina-ai-gmbh.ghost.io">#680</a>)</strong></h3><p>We have added a <a href="https://finetuner.jina.ai/notebooks/image-to-image-arcface/?ref=jina-ai-gmbh.ghost.io">new page</a> to our documentation which demonstrates <code>ArcFaceLoss</code> on the <a href="http://ai.stanford.edu/%7Ejkrause/cars/car_dataset.html?ref=jina-ai-gmbh.ghost.io">Stanford Cars</a> dataset.</p><h3 id="add-a-documentation-section-on-creating-query-document-pairs-as-data-678"><strong>Add a documentation section on creating query-document pairs as data (<a href="https://github.com/jina-ai/finetuner/pull/678?ref=jina-ai-gmbh.ghost.io">#678</a>)</strong></h3><p>We have added a <a href="https://finetuner.jina.ai/walkthrough/create-training-data/?ref=jina-ai-gmbh.ghost.io">new section</a> to our documentation explaining how to create training data made of query-document pairs instead of explicitly annotated and labeled data.</p><h2 id="%F0%9F%A4%9F-contributors"><strong>🤟 Contributors</strong></h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>CatStark (<a href="https://github.com/CatStark?ref=jina-ai-gmbh.ghost.io">@CatStark</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Martin Matousek (<a href="https://github.com/matousek-martin?ref=jina-ai-gmbh.ghost.io">@matousek-martin</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-7-2%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Finetuner Update 0.7.3</title><meta charset="utf-8"><meta name="title" content="Finetuner Update 0.7.3"><meta name="description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/finetuner-update-0-7-3"><meta property="og:title" content="Finetuner Update 0.7.3"><meta property="og:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1-1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-update-0-7-3"><meta property="twitter:title" content="Finetuner Update 0.7.3"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1-1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner Update 0.7.3</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 16, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.3, including dependencies finetuner-api 0.5.4 and finetuner-core 0.12.9.</p><p>This release contains 4 new features, 1 refactoring, and 1 bug fix.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="automatic-batch-size-configuration-691">Automatic batch size configuration (<a href="https://github.com/jina-ai/finetuner/pull/691?ref=jina-ai-gmbh.ghost.io">#691</a>)</h3><p>It can be complicated to find a good batch size for the <code>finetuner.fit</code> function. If you choose a value that's too small, fine-tuning may not be very effective; if you choose a value that's too large, the job may run out of memory and fail. To make this easier, Finetuner now sets the batch size automatically if you leave out the <code>batch_size</code> parameter to <code>finetuner.fit</code> or set it to <code>None</code>. This will choose the largest batch size supported by the current CUDA device.</p><h3 id="retrieving-evaluation-metrics-687">Retrieving evaluation metrics (<a href="https://github.com/jina-ai/finetuner/pull/687?ref=jina-ai-gmbh.ghost.io">#687</a>)</h3><p>You no longer need to retrieve the logs of Finetuner runs or manually unpack fine-tuned models to get the evaluation metrics. Now, you can get the metrics directly from the <code>Run.metrics</code> function:</p><pre><code class="language-python hljs">run = finetuner.fit(...)
-metrics = run.metrics()</code></pre><p>To print nicely formatted evaluation metrics to the console, use the <code>Run.display_metrics()</code> function. This will print tables showing evaluation metrics before and after fine-tuning:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://user-images.githubusercontent.com/6599259/224283786-5803fb8e-6d40-4eb7-b1d2-ae91a24648e7.png" class="kg-image" alt="Metrics before and after fine-tuning"></figure><h3 id="calculating-example-results-687">Calculating example results (<a href="https://github.com/jina-ai/finetuner/pull/687?ref=jina-ai-gmbh.ghost.io">#687</a>)</h3><p>In addition to evaluation metrics, you may find it helpful to see actual query results. We have introduced a new parameter <code>gather_examples</code> to the evaluation callback to make this easy. If this parameter is set to <code>True</code>, the evaluation callback also tracks the Top-K results for some example queries samples from the query dataset:</p><pre><code class="language-python hljs">run = finetuner.fit(
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 16, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.3, including dependencies finetuner-api 0.5.4 and finetuner-core 0.12.9.</p><p>This release contains 4 new features, 1 refactoring, and 1 bug fix.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="automatic-batch-size-configuration-691">Automatic batch size configuration (<a href="https://github.com/jina-ai/finetuner/pull/691?ref=jina-ai-gmbh.ghost.io">#691</a>)</h3><p>It can be complicated to find a good batch size for the <code>finetuner.fit</code> function. If you choose a value that's too small, fine-tuning may not be very effective; if you choose a value that's too large, the job may run out of memory and fail. To make this easier, Finetuner now sets the batch size automatically if you leave out the <code>batch_size</code> parameter to <code>finetuner.fit</code> or set it to <code>None</code>. This will choose the largest batch size supported by the current CUDA device.</p><h3 id="retrieving-evaluation-metrics-687">Retrieving evaluation metrics (<a href="https://github.com/jina-ai/finetuner/pull/687?ref=jina-ai-gmbh.ghost.io">#687</a>)</h3><p>You no longer need to retrieve the logs of Finetuner runs or manually unpack fine-tuned models to get the evaluation metrics. Now, you can get the metrics directly from the <code>Run.metrics</code> function:</p><pre><code class="language-python">run = finetuner.fit(...)
+metrics = run.metrics()</code></pre><p>To print nicely formatted evaluation metrics to the console, use the <code>Run.display_metrics()</code> function. This will print tables showing evaluation metrics before and after fine-tuning:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://user-images.githubusercontent.com/6599259/224283786-5803fb8e-6d40-4eb7-b1d2-ae91a24648e7.png" class="kg-image" alt="Metrics before and after fine-tuning"></figure><h3 id="calculating-example-results-687">Calculating example results (<a href="https://github.com/jina-ai/finetuner/pull/687?ref=jina-ai-gmbh.ghost.io">#687</a>)</h3><p>In addition to evaluation metrics, you may find it helpful to see actual query results. We have introduced a new parameter <code>gather_examples</code> to the evaluation callback to make this easy. If this parameter is set to <code>True</code>, the evaluation callback also tracks the Top-K results for some example queries samples from the query dataset:</p><pre><code class="language-python">run = finetuner.fit(
     ...,
     callbacks=[
         EvaluationCallback(
-            query_data=<span class="hljs-string">'query-data-name'</span><span class="hljs-string">',
-            index_data='</span>index-data-name<span class="hljs-string">''</span>,
-            gather_examples=<span class="hljs-literal">True</span>,
+            query_data='query-data-name'',
+            index_data='index-data-name'',
+            gather_examples=True,
         )
     ],
     ...
-)</code></pre><p>Like the evaluation metrics, you can retrieve the query results, before and after fine-tuning, with the <code>Run.example_results</code> function, or print them on the console using <code>Run.display_examples</code>:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://user-images.githubusercontent.com/6599259/224284912-f3f6f547-8d75-4529-8df1-7f9904423239.png" class="kg-image" alt="Example Results before and after fine-tuning"></figure><h3 id="similarity-based-training-and-cosine-similarity-loss">Similarity-based training and Cosine Similarity Loss</h3><p>Finetuner now supports training with data that is not specifically labeled, but that has for each pair of training items, a numerical similarity score between 0.0 (totally dissimilar) and 1.0 (totally the same). This extends the potential scenarios for which Finetuner is applicable.</p><p>For example, you can now use DocArray to prepare data pairs with scores like this:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document, DocumentArray
+)</code></pre><p>Like the evaluation metrics, you can retrieve the query results, before and after fine-tuning, with the <code>Run.example_results</code> function, or print them on the console using <code>Run.display_examples</code>:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://user-images.githubusercontent.com/6599259/224284912-f3f6f547-8d75-4529-8df1-7f9904423239.png" class="kg-image" alt="Example Results before and after fine-tuning"></figure><h3 id="similarity-based-training-and-cosine-similarity-loss">Similarity-based training and Cosine Similarity Loss</h3><p>Finetuner now supports training with data that is not specifically labeled, but that has for each pair of training items, a numerical similarity score between 0.0 (totally dissimilar) and 1.0 (totally the same). This extends the potential scenarios for which Finetuner is applicable.</p><p>For example, you can now use DocArray to prepare data pairs with scores like this:</p><pre><code class="language-python">from docarray import Document, DocumentArray
 d1 = Document(
-    [Document(text=<span class="hljs-string">'I am driving to Los Angeles'</span>), Document(<span class="hljs-string">'I am driving to Hollywood'</span>)],
-    tags={<span class="hljs-string">'finetuner_score'</span>: <span class="hljs-number">0.9</span>},
+    [Document(text='I am driving to Los Angeles'), Document('I am driving to Hollywood')],
+    tags={'finetuner_score': 0.9},
 )
 d2 = Document(
-    [Document(text=<span class="hljs-string">'I am driving to Los Angeles'</span>), Document(<span class="hljs-string">'I am flying to New York'</span>)],
-    tags={<span class="hljs-string">'finetuner_score'</span>: <span class="hljs-number">0.3</span>},
+    [Document(text='I am driving to Los Angeles'), Document('I am flying to New York')],
+    tags={'finetuner_score': 0.3},
 )
 ...
-train_data = DocumentArray([d1, d2, ...])</code></pre><p>Then, use <code>CosineSimilarityLoss</code> as the loss function in the <code>finetuner.fit</code> function:</p><pre><code class="language-python hljs">finetuner.fit(
-  model=<span class="hljs-string">'sentence-transformers/msmarco-distilbert-base-v3'</span>,
+train_data = DocumentArray([d1, d2, ...])</code></pre><p>Then, use <code>CosineSimilarityLoss</code> as the loss function in the <code>finetuner.fit</code> function:</p><pre><code class="language-python">finetuner.fit(
+  model='sentence-transformers/msmarco-distilbert-base-v3',
   train_data=train_data,
-  loss=<span class="hljs-string">'CosineSimilarityLoss'</span>,
+  loss='CosineSimilarityLoss',
   ...
-) </code></pre><p>In the future, we will also support data with scores in CSV format.</p><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="remove-job-limit">Remove job limit</h3><p>Previously, users could only run three jobs in parallel. This limit has been removed.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="logs-become-unavailable-after-some-time">Logs become unavailable after some time</h3><p>After fine-tuning jobs finish, the logs were lost after some length of time. Now, logs will remain available indefinitely.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-7-3%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+) </code></pre><p>In the future, we will also support data with scores in CSV format.</p><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="remove-job-limit">Remove job limit</h3><p>Previously, users could only run three jobs in parallel. This limit has been removed.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="logs-become-unavailable-after-some-time">Logs become unavailable after some time</h3><p>After fine-tuning jobs finish, the logs were lost after some length of time. Now, logs will remain available indefinitely.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-7-3%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Finetuner Update 0.7.4</title><meta charset="utf-8"><meta name="title" content="Finetuner Update 0.7.4"><meta name="description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/finetuner-update-0-7-4"><meta property="og:title" content="Finetuner Update 0.7.4"><meta property="og:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina-AI-Website-Banners-Templates--16-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-update-0-7-4"><meta property="twitter:title" content="Finetuner Update 0.7.4"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina-AI-Website-Banners-Templates--16-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 29, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><p>This release covers Finetuner version 0.7.4, including dependencies finetuner-api 0.5.5 and finetuner-core 0.13.0.</p><p>This release contains 2 new features, 3 refactoring, 1 bug fix, and 3 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="layer-wise-learning-rate-decay-llrd-697">Layer-wise learning rate decay (LLRD) (#697)</h3><p>LLRD sets a large learning rate for the top (last) layer and uses a multiplicative decay rate to decrease the learning rate layer-by-layer from top (last) to bottom (first). With high learning rates, the features recognized by the top layers change more and adapt to new tasks more easily, while the bottom layers have low learning rates and more easily preserve the features learned during pre-training:</p><pre><code class="language-diff">import finetuner
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 29, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><p>This release covers Finetuner version 0.7.4, including dependencies finetuner-api 0.5.5 and finetuner-core 0.13.0.</p><p>This release contains 2 new features, 3 refactoring, 1 bug fix, and 3 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="layer-wise-learning-rate-decay-llrd-697">Layer-wise learning rate decay (LLRD) (#697)</h3><p>LLRD sets a large learning rate for the top (last) layer and uses a multiplicative decay rate to decrease the learning rate layer-by-layer from top (last) to bottom (first). With high learning rates, the features recognized by the top layers change more and adapt to new tasks more easily, while the bottom layers have low learning rates and more easily preserve the features learned during pre-training:</p><pre><code class="language-diff hljs">import finetuner
 run = finetuner.fit(
     ...,
     optimizer='Adam'
-+   optimizer_options={'layer_wise_lr_decay': 0.98},
+<span class="hljs-addition">+   optimizer_options={'layer_wise_lr_decay': 0.98},</span>
     ...,
 )</code></pre><h3 id="support-csv-for-similarity-based-training-696">Support CSV for similarity-based training (<a href="https://github.com/jina-ai/finetuner/pull/696?ref=jina-ai-gmbh.ghost.io">#696</a>)</h3><p>In the previous release, Finetuner added support for training with data that is not specifically labeled, but each pair of training items has a numerical similarity score between 0.0 (totally dissimilar) and 1.0 (totally the same). This extends the potential scenarios for which Finetuner is applicable.</p><p>Now, users can prepare training data with a CSV file like this:</p><pre><code class="language-csv">The weather is nice, The weather is beautiful, 0.9
-The weather is nice, The weather is bad, 0</code></pre><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="unify-supported-backbone-names-700">Unify supported backbone names (<a href="https://github.com/jina-ai/finetuner/pull/700?ref=jina-ai-gmbh.ghost.io">#700</a>)</h3><p>We unified backbone names into the <code>name-size-[lang]</code> format. Now model names are easier to understand and remember. For example: <code>bert-base-cased</code> becomes <code>bert-base-en</code>, <code>openai/clip-vit-base-patch32</code> becomes <code>clip-base-en</code>, <code>resnet152</code> becomes <code>resnet-large</code>. Users can see the support backbones with:</p><pre><code class="language-python">finetuner.describe_models(task='text-to-image')</code></pre><p>Note that you can keep using the old names, for example:</p><pre><code class="language-python"># build a zero-shot resnet embedding model
-model = finetuner.build_model('resnet50')
+The weather is nice, The weather is bad, 0</code></pre><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="unify-supported-backbone-names-700">Unify supported backbone names (<a href="https://github.com/jina-ai/finetuner/pull/700?ref=jina-ai-gmbh.ghost.io">#700</a>)</h3><p>We unified backbone names into the <code>name-size-[lang]</code> format. Now model names are easier to understand and remember. For example: <code>bert-base-cased</code> becomes <code>bert-base-en</code>, <code>openai/clip-vit-base-patch32</code> becomes <code>clip-base-en</code>, <code>resnet152</code> becomes <code>resnet-large</code>. Users can see the support backbones with:</p><pre><code class="language-python hljs">finetuner.describe_models(task=<span class="hljs-string">'text-to-image'</span>)</code></pre><p>Note that you can keep using the old names, for example:</p><pre><code class="language-python hljs"><span class="hljs-comment"># build a zero-shot resnet embedding model</span>
+model = finetuner.build_model(<span class="hljs-string">'resnet50'</span>)
 
-# this is identical to
-model = finetuner.build_model('resnet-base')</code></pre><h3 id="simplify-model-offerings-700">Simplify model offerings. (<a href="https://github.com/jina-ai/finetuner/pull/700?ref=jina-ai-gmbh.ghost.io">#700</a>)</h3><p>To simplify our offerings and create a more intuitive user experience, we have decreased the number of supported machine-learning models. By doing so, we hope to make it easier for our users to navigate our platform and find the models that best suit their needs.</p><h3 id="change-the-default-batchsize-for-evaluationcallback-from-8-to-32">Change the default <code>batch_size</code> for <code>EvaluationCallback</code> from 8 to 32.</h3><p>We recently implemented a change to our <code>EvaluationCallback</code> by increasing the batch size. This has resulted in a significant improvement in evaluation speed, which in turn has reduced the overall cost of evaluation. By processing data more efficiently, we can evaluate models more quickly and accurately, which ultimately benefits our users.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-indexerror-in-evaluationcallback-when-gatherexamples-is-enabled">Fix <code>IndexError</code> in <code>EvaluationCallback</code> when <code>gather_examples</code> is enabled.</h3><p>We resolved an issue in the <code>EvaluationCallback</code> where the 'list out of range' error was occurring when <code>gather_examples</code> was enabled. This fix ensures that the evaluation callback works correctly with <code>gather_examples</code> and enables users to gather evaluation examples without encountering errors.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Add section for layer-wise learning rate decay (LLRD) (<a href="https://github.com/jina-ai/finetuner/pull/697?ref=jina-ai-gmbh.ghost.io">#697</a>)</li><li>Add section for <code>CosineSimilarityLoss</code> (<a href="https://github.com/jina-ai/finetuner/pull/697?ref=jina-ai-gmbh.ghost.io">#697</a>)</li><li>Add section on creating query-document pairs as CSV (<a href="https://github.com/jina-ai/finetuner/pull/697?ref=jina-ai-gmbh.ghost.io">#697</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-7-4%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
+<span class="hljs-comment"># this is identical to</span>
+model = finetuner.build_model(<span class="hljs-string">'resnet-base'</span>)</code></pre><h3 id="simplify-model-offerings-700">Simplify model offerings. (<a href="https://github.com/jina-ai/finetuner/pull/700?ref=jina-ai-gmbh.ghost.io">#700</a>)</h3><p>To simplify our offerings and create a more intuitive user experience, we have decreased the number of supported machine-learning models. By doing so, we hope to make it easier for our users to navigate our platform and find the models that best suit their needs.</p><h3 id="change-the-default-batchsize-for-evaluationcallback-from-8-to-32">Change the default <code>batch_size</code> for <code>EvaluationCallback</code> from 8 to 32.</h3><p>We recently implemented a change to our <code>EvaluationCallback</code> by increasing the batch size. This has resulted in a significant improvement in evaluation speed, which in turn has reduced the overall cost of evaluation. By processing data more efficiently, we can evaluate models more quickly and accurately, which ultimately benefits our users.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-indexerror-in-evaluationcallback-when-gatherexamples-is-enabled">Fix <code>IndexError</code> in <code>EvaluationCallback</code> when <code>gather_examples</code> is enabled.</h3><p>We resolved an issue in the <code>EvaluationCallback</code> where the 'list out of range' error was occurring when <code>gather_examples</code> was enabled. This fix ensures that the evaluation callback works correctly with <code>gather_examples</code> and enables users to gather evaluation examples without encountering errors.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Add section for layer-wise learning rate decay (LLRD) (<a href="https://github.com/jina-ai/finetuner/pull/697?ref=jina-ai-gmbh.ghost.io">#697</a>)</li><li>Add section for <code>CosineSimilarityLoss</code> (<a href="https://github.com/jina-ai/finetuner/pull/697?ref=jina-ai-gmbh.ghost.io">#697</a>)</li><li>Add section on creating query-document pairs as CSV (<a href="https://github.com/jina-ai/finetuner/pull/697?ref=jina-ai-gmbh.ghost.io">#697</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-7-4%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Finetuner Update 0.7.5</title><meta charset="utf-8"><meta name="title" content="Finetuner Update 0.7.5"><meta name="description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/finetuner-update-0-7-5"><meta property="og:title" content="Finetuner Update 0.7.5"><meta property="og:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-update-0-7-5"><meta property="twitter:title" content="Finetuner Update 0.7.5"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner Update 0.7.5</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 14, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.7.5?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.7.5 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.7.5This release covers Finetuner version 0.7.5, including dependencies finetuner-api 0.5.6 and finetuner-core 0.13.3.This release contains 2 refactorings and 2 bug fixes.…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/05f504fab130db5e9336e637dc52e37d89196e7c57a8be626e2260dc5bd5fcbd/jina-ai/finetuner/releases/tag/v0.7.5" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.5, including dependencies finetuner-api 0.5.6 and finetuner-core 0.13.3.</p><p>This release contains 2 refactorings and 2 bug fixes.</p><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="downloading-pre-trained-weights-is-not-necessary-anymore">Downloading pre-trained weights is not necessary anymore</h3><p>Previously, when a fine-tuning job was completed and the <code>get_model</code> function was called, we would construct the model, load the pre-trained weights, and then overwrite them with fine-tuned weights. We have now disabled the downloading of pre-trained weights, which speeds up the <code>get_model</code> function and eliminates unneeded network traffic.</p><h3 id="provide-informative-error-messages-when-user-did-not-login-708">Provide informative error messages when user did not login (<a href="https://github.com/jina-ai/finetuner/pull/708?ref=jina-ai-gmbh.ghost.io">#708</a>)</h3><p>Before creating a <code>Run</code>, users are required to call <code>finetuner.login()</code> and use third-party authentication to log in. Previously, if they had not already done so, they would receive an error message that did not tell them to log in. We now display a more informative error message in the event that a user forgets to log in or their login attempt was unsuccessful.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-model-name-validation-error-using-the-model-display-name">Fix model name validation error using the model display name</h3><p>When users request a model by name, they use names with the format <code>name-size-lang</code>, for example: <code>bert-base-en</code>. However, these names were not included in our internal schema for validation and jobs would fail validation. This has now been rectified.</p><h3 id="fix-automatic-batch-size-selection-for-pointnet-models">Fix automatic batch size selection for PointNet models</h3><p>In the past, <code>BatchSizeFinder</code> was unable to properly select batch sizes for PointNet++ models. This has been fixed.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-7-5%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 14, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.7.5?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.7.5 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.7.5This release covers Finetuner version 0.7.5, including dependencies finetuner-api 0.5.6 and finetuner-core 0.13.3.This release contains 2 refactorings and 2 bug fixes.…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/05f504fab130db5e9336e637dc52e37d89196e7c57a8be626e2260dc5bd5fcbd/jina-ai/finetuner/releases/tag/v0.7.5" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.5, including dependencies finetuner-api 0.5.6 and finetuner-core 0.13.3.</p><p>This release contains 2 refactorings and 2 bug fixes.</p><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="downloading-pre-trained-weights-is-not-necessary-anymore">Downloading pre-trained weights is not necessary anymore</h3><p>Previously, when a fine-tuning job was completed and the <code>get_model</code> function was called, we would construct the model, load the pre-trained weights, and then overwrite them with fine-tuned weights. We have now disabled the downloading of pre-trained weights, which speeds up the <code>get_model</code> function and eliminates unneeded network traffic.</p><h3 id="provide-informative-error-messages-when-user-did-not-login-708">Provide informative error messages when user did not login (<a href="https://github.com/jina-ai/finetuner/pull/708?ref=jina-ai-gmbh.ghost.io">#708</a>)</h3><p>Before creating a <code>Run</code>, users are required to call <code>finetuner.login()</code> and use third-party authentication to log in. Previously, if they had not already done so, they would receive an error message that did not tell them to log in. We now display a more informative error message in the event that a user forgets to log in or their login attempt was unsuccessful.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-model-name-validation-error-using-the-model-display-name">Fix model name validation error using the model display name</h3><p>When users request a model by name, they use names with the format <code>name-size-lang</code>, for example: <code>bert-base-en</code>. However, these names were not included in our internal schema for validation and jobs would fail validation. This has now been rectified.</p><h3 id="fix-automatic-batch-size-selection-for-pointnet-models">Fix automatic batch size selection for PointNet models</h3><p>In the past, <code>BatchSizeFinder</code> was unable to properly select batch sizes for PointNet++ models. This has been fixed.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Louis Milliken (<a href="https://github.com/LMMilliken?ref=jina-ai-gmbh.ghost.io">@LMMilliken</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>George Mastrapas (<a href="https://github.com/gmastrapas?ref=jina-ai-gmbh.ghost.io">@gmastrapas</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-7-5%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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diff --git a/news/finetuner-update-0-7-6/index.html b/news/finetuner-update-0-7-6/index.html
index a66fecbdc13..351fd785305 100644
--- a/news/finetuner-update-0-7-6/index.html
+++ b/news/finetuner-update-0-7-6/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Finetuner Update 0.7.6</title><meta charset="utf-8"><meta name="title" content="Finetuner Update 0.7.6"><meta name="description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/finetuner-update-0-7-6"><meta property="og:title" content="Finetuner Update 0.7.6"><meta property="og:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-update-0-7-6"><meta property="twitter:title" content="Finetuner Update 0.7.6"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Finetuner Update 0.7.6</title><meta charset="utf-8"><meta name="title" content="Finetuner Update 0.7.6"><meta name="description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/finetuner-update-0-7-6"><meta property="og:title" content="Finetuner Update 0.7.6"><meta property="og:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/finetuner-update-0-7-6"><meta property="twitter:title" content="Finetuner Update 0.7.6"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner Update 0.7.6</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 18, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.7.6?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.7.6 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.7.6This release covers Finetuner version 0.7.6, including dependencies finetuner-api 0.5.6 and finetuner-core 0.13.4.This release contains 2 refactorings and 1 bug fix.…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/9b75a1bf10ea2b8388c8ead9019d1fab1740b597363bae0733280c77bad8999a/jina-ai/finetuner/releases/tag/v0.7.6" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.6, including dependencies finetuner-api 0.5.6 and finetuner-core 0.13.4.</p><p>This release contains 2 refactorings and 1 bug fix.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">Due to the release of DocArray v2, which is not yet compatible with Finetuner, all previous versions of Finetuner will break when they update DocArray automatically. <strong>It is <em>strongly</em> recommended that you upgrade to this release because previous versions will not work.</strong></div></div><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="do-not-display-pil-warning-messages">Do not display PIL warning messages.</h3><p>Beforehand, when fine-tuning with a vision backbone, the PIL package would generate numerous warning messages that contaminated Finetuner's logs. However, this issue has been resolved, and PIL warnings are filtered out.</p><h3 id="display-small-loss-values-with-higher-precision">Display small loss values with higher precision.</h3><p>Previously, the progress bar would display a loss value of 0 when it was too small. To address this issue, we now use a higher precision when the loss value is too small.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="the-docarray-version-is-set-to-a-value-lower-than-030">The DocArray version is set to a value lower than 0.3.0.</h3><p>Previously, Finetuner automatically installed the latest version of DocArray. However, Docarray v2 has now been released and is a breaking change that is incompatible with the current version of Finetuner. Finetuner only supports DocArray up to version 0.3.0. Please upgrade your Finetuner to the latest version to resolve this issue.</p><p>We will release a version of Finetuner compatible with DocArray v2 in the immediate future.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-7-6%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 18, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud. With Finetuner, one can easily enhance the performance of pre-trained models and make them production-ready without expensive hardware.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.7.6?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.7.6 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.7.6This release covers Finetuner version 0.7.6, including dependencies finetuner-api 0.5.6 and finetuner-core 0.13.4.This release contains 2 refactorings and 1 bug fix.…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/9b75a1bf10ea2b8388c8ead9019d1fab1740b597363bae0733280c77bad8999a/jina-ai/finetuner/releases/tag/v0.7.6" alt=""></div></a></figure><p>This release covers Finetuner version 0.7.6, including dependencies finetuner-api 0.5.6 and finetuner-core 0.13.4.</p><p>This release contains 2 refactorings and 1 bug fix.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">Due to the release of DocArray v2, which is not yet compatible with Finetuner, all previous versions of Finetuner will break when they update DocArray automatically. <strong>It is <em>strongly</em> recommended that you upgrade to this release because previous versions will not work.</strong></div></div><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="do-not-display-pil-warning-messages">Do not display PIL warning messages.</h3><p>Beforehand, when fine-tuning with a vision backbone, the PIL package would generate numerous warning messages that contaminated Finetuner's logs. However, this issue has been resolved, and PIL warnings are filtered out.</p><h3 id="display-small-loss-values-with-higher-precision">Display small loss values with higher precision.</h3><p>Previously, the progress bar would display a loss value of 0 when it was too small. To address this issue, we now use a higher precision when the loss value is too small.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="the-docarray-version-is-set-to-a-value-lower-than-030">The DocArray version is set to a value lower than 0.3.0.</h3><p>Previously, Finetuner automatically installed the latest version of DocArray. However, Docarray v2 has now been released and is a breaking change that is incompatible with the current version of Finetuner. Finetuner only supports DocArray up to version 0.3.0. Please upgrade your Finetuner to the latest version to resolve this issue.</p><p>We will release a version of Finetuner compatible with DocArray v2 in the immediate future.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Wang Bo (<a href="https://github.com/bwanglzu?ref=jina-ai-gmbh.ghost.io">@bwanglzu</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>Scott Martens (<a href="https://github.com/scott-martens?ref=jina-ai-gmbh.ghost.io">@scott-martens</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffinetuner-update-0-7-6%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>5 Most Trending Open Source MLOps Tools of 2022</title><meta charset="utf-8"><meta name="title" content="5 Most Trending Open Source MLOps Tools of 2022"><meta name="description" content="MLOps helps organizations better manage the complexities of ML in production. This article reviews the top-5 most trending open source MLOps tools listed on OSSInsight.io in 2022."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/five-most-trending-open-source-mlops-tools-of-2022"><meta property="og:title" content="5 Most Trending Open Source MLOps Tools of 2022"><meta property="og:description" content="MLOps helps organizations better manage the complexities of ML in production. This article reviews the top-5 most trending open source MLOps tools listed on OSSInsight.io in 2022."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--24-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/five-most-trending-open-source-mlops-tools-of-2022"><meta property="twitter:title" content="5 Most Trending Open Source MLOps Tools of 2022"><meta property="twitter:description" content="MLOps helps organizations better manage the complexities of ML in production. This article reviews the top-5 most trending open source MLOps tools listed on OSSInsight.io in 2022."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--24-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">5 Most Trending Open Source MLOps Tools of 2022</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">MLOps helps organizations better manage the complexities of ML in production. This article reviews the top-5 most trending open source MLOps tools listed on OSSInsight.io in 2022.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 07, 2022 • 14 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><br>MLOps, or DevOps for machine learning, is a set of practices that aim to automate and improve the collaboration between data scientists and software engineers. It helps organizations better manage the complexities of developing and deploying machine learning models in production. In this article, we will review the top-5 most trending open source MLOps tools listed on OSSInsight.io in 2022. </p><h2 id="benefits-of-mlops">Benefits of MLOps</h2><p>One of the biggest benefits of MLOps is that it allows data scientists and engineers to work more closely together. Data scientists can focus on developing models, while engineers can focus on operationalizing them. This collaboration helps to ensure that models are deployed quickly and efficiently and that they meet the needs of the business. </p><p>Another benefit of MLOps is that it helps to automate the process of model development and deployment. This means that data scientists can spend less time on repetitive tasks, and more time on developing new models. Automation also helps to ensure that models are deployed consistently and with high quality.</p><h2 id="common-practices-in-mlops">Common Practices in MLOps</h2><p>MLOps is still a relatively new field (as we shall see below, all five tools were first released in 2018), and there is no one-size-fits-all approach to implementing it. However, some common practices are often used. One common practice is to use pipelines. These pipelines help to automate the process of building, testing and deploying machine learning models. </p><p>Another common practice is to use containerization technologies, such as Docker, to package machine learning models. This allows models to be easily deployed in different environments. </p><p>Finally, many MLOps practitioners use monitoring and logging tools to keep track of the performance of machine learning models in production. This allows for the early detection of issues and can help to improve the overall quality of the models.</p><h2 id="best-5-mlops-tools-in-2022">Best 5 MLOps Tools in 2022</h2><p>Implementing MLOps can be a challenge, but the benefits are clear. Organizations that adopt MLOps practices can improve the quality of their machine learning models and speed up the development and deployment process. In this article, we select the top-5 most trending open source MLOps tools in 2022 listed on OSSInsight.io, namely Jina (No.1), MLFlow (No.2), NNI (No.3), Kubefliow (No.4) and Label Studio (No.5). The rank is based on the stars, pull requests, pull request creators, and issues on the Github in 2022. OSSInsight is a powerful insight tool that can help one analyze in depth any single GitHub repository/developers, compare any two repositories using the same metrics, and provide comprehensive, valuable, and trending open source insights.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://ossinsight.io/collections/ml-ops-tools/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/MLOps-Tools---Stars.png" class="kg-image" alt="" width="1868" height="1241" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/MLOps-Tools---Stars.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/MLOps-Tools---Stars.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/MLOps-Tools---Stars.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/MLOps-Tools---Stars.png 1868w" sizes="(min-width: 720px) 720px"></a><figcaption>The pipeline chart shows how repo rankings have changed year to year since 2011. Repos are ranked by stars, pull requests, pull request creators, and issues. The top 5 tools are Jina, MLFlow, NNI, KubeFlow, and Label Studio. Click to view the source.</figcaption></figure><h2 id="1-jina">1. Jina</h2><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps</div><div class="kg-bookmark-description">🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps - GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cl...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/6d66c5cb-b3e8-4bc2-b2ee-b01b9d90933d" alt=""></div></a></figure><table>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">MLOps helps organizations better manage the complexities of ML in production. This article reviews the top-5 most trending open source MLOps tools listed on OSSInsight.io in 2022.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 07, 2022 • 14 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><br>MLOps, or DevOps for machine learning, is a set of practices that aim to automate and improve the collaboration between data scientists and software engineers. It helps organizations better manage the complexities of developing and deploying machine learning models in production. In this article, we will review the top-5 most trending open source MLOps tools listed on OSSInsight.io in 2022. </p><h2 id="benefits-of-mlops">Benefits of MLOps</h2><p>One of the biggest benefits of MLOps is that it allows data scientists and engineers to work more closely together. Data scientists can focus on developing models, while engineers can focus on operationalizing them. This collaboration helps to ensure that models are deployed quickly and efficiently and that they meet the needs of the business. </p><p>Another benefit of MLOps is that it helps to automate the process of model development and deployment. This means that data scientists can spend less time on repetitive tasks, and more time on developing new models. Automation also helps to ensure that models are deployed consistently and with high quality.</p><h2 id="common-practices-in-mlops">Common Practices in MLOps</h2><p>MLOps is still a relatively new field (as we shall see below, all five tools were first released in 2018), and there is no one-size-fits-all approach to implementing it. However, some common practices are often used. One common practice is to use pipelines. These pipelines help to automate the process of building, testing and deploying machine learning models. </p><p>Another common practice is to use containerization technologies, such as Docker, to package machine learning models. This allows models to be easily deployed in different environments. </p><p>Finally, many MLOps practitioners use monitoring and logging tools to keep track of the performance of machine learning models in production. This allows for the early detection of issues and can help to improve the overall quality of the models.</p><h2 id="best-5-mlops-tools-in-2022">Best 5 MLOps Tools in 2022</h2><p>Implementing MLOps can be a challenge, but the benefits are clear. Organizations that adopt MLOps practices can improve the quality of their machine learning models and speed up the development and deployment process. In this article, we select the top-5 most trending open source MLOps tools in 2022 listed on OSSInsight.io, namely Jina (No.1), MLFlow (No.2), NNI (No.3), Kubefliow (No.4) and Label Studio (No.5). The rank is based on the stars, pull requests, pull request creators, and issues on the Github in 2022. OSSInsight is a powerful insight tool that can help one analyze in depth any single GitHub repository/developers, compare any two repositories using the same metrics, and provide comprehensive, valuable, and trending open source insights.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://ossinsight.io/collections/ml-ops-tools/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/MLOps-Tools---Stars.png" class="kg-image" alt="" width="1868" height="1241" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/MLOps-Tools---Stars.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/MLOps-Tools---Stars.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/MLOps-Tools---Stars.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/MLOps-Tools---Stars.png 1868w" sizes="(min-width: 720px) 720px"></a><figcaption>The pipeline chart shows how repo rankings have changed year to year since 2011. Repos are ranked by stars, pull requests, pull request creators, and issues. The top 5 tools are Jina, MLFlow, NNI, KubeFlow, and Label Studio. Click to view the source.</figcaption></figure><h2 id="1-jina">1. Jina</h2><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps</div><div class="kg-bookmark-description">🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps - GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cl...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/6d66c5cb-b3e8-4bc2-b2ee-b01b9d90933d" alt=""></div></a></figure><table>
 <thead>
 <tr>
 <th>First Release</th>
@@ -35,47 +35,47 @@
 </table>
 <p>Jina from <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI</a> is the top-1 most trending MLOps tool according to OSSInsight. Jina is an MLOps framework for multimodal AI. It eases the building of neural search and creative AI on the cloud. Jina uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-image-card kg-card-hascaption">
 <img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Unlock-the-Business-Value-of-Multimodal-Data--1-.svg" class="kg-image" alt="" width="100%">
-<figcaption>The full picture of Jina AI's MLOps visioning. It covers the full development journey from prototyping, server-zing, deploying, fine-tuning, monitoring, etc.</figcaption></figure><p>Despite the advanced cloud-native features that Jina offers, learning Jina is very straightforward. Document, Executor, and Flow are three fundamental concepts in Jina.</p><ul><li><strong><a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Document</a></strong> is the fundamental data structure. (This project is also an opensource project by the Linux Foundation)</li><li><a href="https://docs.jina.ai/fundamentals/executor/?ref=jina-ai-gmbh.ghost.io" rel="nofollow"><strong>Executor</strong></a> is a Python class with functions that use Documents as IO.</li><li><a href="https://docs.jina.ai/fundamentals/flow/?ref=jina-ai-gmbh.ghost.io" rel="nofollow"><strong>Flow</strong></a> ties Executors together into a pipeline and exposes it with an API gateway.</li></ul><p>With these three concepts, one can easily build a semantic text search with sharding technology in just 45 lines of code!</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> pprint <span class="hljs-keyword">import</span> pprint
-<span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Flow, requests, DocumentArray, Document, Executor
+<figcaption>The full picture of Jina AI's MLOps visioning. It covers the full development journey from prototyping, server-zing, deploying, fine-tuning, monitoring, etc.</figcaption></figure><p>Despite the advanced cloud-native features that Jina offers, learning Jina is very straightforward. Document, Executor, and Flow are three fundamental concepts in Jina.</p><ul><li><strong><a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Document</a></strong> is the fundamental data structure. (This project is also an opensource project by the Linux Foundation)</li><li><a href="https://docs.jina.ai/fundamentals/executor/?ref=jina-ai-gmbh.ghost.io" rel="nofollow"><strong>Executor</strong></a> is a Python class with functions that use Documents as IO.</li><li><a href="https://docs.jina.ai/fundamentals/flow/?ref=jina-ai-gmbh.ghost.io" rel="nofollow"><strong>Flow</strong></a> ties Executors together into a pipeline and exposes it with an API gateway.</li></ul><p>With these three concepts, one can easily build a semantic text search with sharding technology in just 45 lines of code!</p><pre><code class="language-python">from pprint import pprint
+from jina import Flow, requests, DocumentArray, Document, Executor
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyFeature</span>(<span class="hljs-title class_ inherited__">Executor</span>):
-<span class="hljs-meta">    @requests</span>
-    <span class="hljs-keyword">async</span> <span class="hljs-keyword">def</span> <span class="hljs-title function_">foo</span>(<span class="hljs-params">self, docs, **kwargs</span>):
+class MyFeature(Executor):
+    @requests
+    async def foo(self, docs, **kwargs):
         docs.apply(Document.embed_feature_hashing)
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDB</span>(<span class="hljs-title class_ inherited__">Executor</span>):
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">__init__</span>(<span class="hljs-params">self, *args, **kwargs</span>):
-        <span class="hljs-built_in">super</span>().__init__(*args, **kwargs)
+class MyDB(Executor):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
         self.db = DocumentArray()
 
-<span class="hljs-meta">    @requests(<span class="hljs-params">on=<span class="hljs-string">'/index'</span></span>)</span>
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">index</span>(<span class="hljs-params">self, docs, **kwargs</span>):
+    @requests(on='/index')
+    def index(self, docs, **kwargs):
         self.db.extend(docs)
 
-<span class="hljs-meta">    @requests(<span class="hljs-params">on=<span class="hljs-string">'/query'</span></span>)</span>
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">query</span>(<span class="hljs-params">self, docs, **kwargs</span>):
-        <span class="hljs-keyword">return</span> self.db.find(docs, metric=<span class="hljs-string">'jaccard'</span>, use_scipy=<span class="hljs-literal">True</span>)[<span class="hljs-number">0</span>][:<span class="hljs-number">3</span>]
+    @requests(on='/query')
+    def query(self, docs, **kwargs):
+        return self.db.find(docs, metric='jaccard', use_scipy=True)[0][:3]
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyRanker</span>(<span class="hljs-title class_ inherited__">Executor</span>):
-<span class="hljs-meta">    @requests(<span class="hljs-params">on=<span class="hljs-string">'/query'</span></span>)</span>
-    <span class="hljs-keyword">async</span> <span class="hljs-keyword">def</span> <span class="hljs-title function_">foo</span>(<span class="hljs-params">self, docs, **kwargs</span>):
-        <span class="hljs-keyword">return</span> DocumentArray(<span class="hljs-built_in">sorted</span>(docs, key=<span class="hljs-keyword">lambda</span> x: x.scores[<span class="hljs-string">'jaccard'</span>].value))
+class MyRanker(Executor):
+    @requests(on='/query')
+    async def foo(self, docs, **kwargs):
+        return DocumentArray(sorted(docs, key=lambda x: x.scores['jaccard'].value))
 
-d = Document(uri=<span class="hljs-string">'https://www.gutenberg.org/files/1342/1342-0.txt'</span>).load_uri_to_text()
-da = DocumentArray(Document(text=s.strip()) <span class="hljs-keyword">for</span> s <span class="hljs-keyword">in</span> d.text.split(<span class="hljs-string">'\n'</span>) <span class="hljs-keyword">if</span> s.strip())
+d = Document(uri='https://www.gutenberg.org/files/1342/1342-0.txt').load_uri_to_text()
+da = DocumentArray(Document(text=s.strip()) for s in d.text.split('\n') if s.strip())
 
-<span class="hljs-keyword">if</span> __name__ == <span class="hljs-string">'__main__'</span>:
+if __name__ == '__main__':
     f = (
         Flow()
         .add(uses=MyFeature)
-        .add(uses=MyDB, shards=<span class="hljs-number">3</span>, polling={<span class="hljs-string">'/query'</span>: <span class="hljs-string">'ALL'</span>, <span class="hljs-string">'/index'</span>: <span class="hljs-string">'ANY'</span>})
+        .add(uses=MyDB, shards=3, polling={'/query': 'ALL', '/index': 'ANY'})
         .add(uses=MyRanker)
     )
-    <span class="hljs-keyword">with</span> f:
-        f.post(<span class="hljs-string">'/index'</span>, da, show_progress=<span class="hljs-literal">True</span>)
+    with f:
+        f.post('/index', da, show_progress=True)
         pprint(
-            f.post(<span class="hljs-string">'/query'</span>, Document(text=<span class="hljs-string">'she smiled too much'</span>))[
-                :, (<span class="hljs-string">'text'</span>, <span class="hljs-string">'scores__jaccard__value'</span>)
+            f.post('/query', Document(text='she smiled too much'))[
+                :, ('text', 'scores__jaccard__value')
             ]
         )</code></pre><figure class="kg-card kg-image-card kg-card-hascaption">
 <img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/a.svg" class="kg-image" alt="" width="80%">
@@ -101,19 +101,19 @@
 <td>Python</td>
 </tr>
 </tbody>
-</table><p>MLflow is the No.2 on the trending board. Unlike Jina which specializes on the neural search and multimodal AI applications, MLflow is a more general platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. It offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). MLflow's current components are:</p><ul><li>MLflow Tracking: An API to log parameters, code, and results in machine learning experiments and compare them using an interactive UI.</li><li>MLflow Projects: A code packaging format for reproducible runs using Conda and Docker, so you can share your ML code with others.</li><li>MLflow Models: A model packaging format and tools that let you easily deploy the same model (from any ML library) to batch and real-time scoring on platforms such as Docker, Apache Spark, Azure ML and AWS SageMaker.</li><li>MLflow Model Registry: A centralized model store, set of APIs, and UI, to collaboratively manage the full lifecycle of MLflow Models. </li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-2.png" class="kg-image" alt="" width="1200" height="630" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-2.png 1200w" sizes="(min-width: 720px) 720px"><figcaption>Overview of the CI/CD tools, architecture and workflow of the MLflow centralized hub for model management.</figcaption></figure><p>MLflow Projects provide a standard format for packaging reusable data science code. Each project is simply a directory with code or a Git repository, and uses a descriptor file to specify its dependencies and how to run the code. A MLflow Project is defined by a simple YAML file called <code>MLproject</code>.</p><pre><code class="language-yaml hljs"><span class="hljs-attr">name:</span> <span class="hljs-string">My</span> <span class="hljs-string">Project</span>
-<span class="hljs-attr">conda_env:</span> <span class="hljs-string">conda.yaml</span>
-<span class="hljs-attr">entry_points:</span>
-  <span class="hljs-attr">main:</span>
-    <span class="hljs-attr">parameters:</span>
-      <span class="hljs-attr">data_file:</span> <span class="hljs-string">path</span>
-      <span class="hljs-attr">regularization:</span> {<span class="hljs-attr">type:</span> <span class="hljs-string">float</span>, <span class="hljs-attr">default:</span> <span class="hljs-number">0.1</span>}
-    <span class="hljs-attr">command:</span> <span class="hljs-string">"python train.py -r {regularization} {data_file}"</span>
-  <span class="hljs-attr">validate:</span>
-    <span class="hljs-attr">parameters:</span>
-      <span class="hljs-attr">data_file:</span> <span class="hljs-string">path</span>
-    <span class="hljs-attr">command:</span> <span class="hljs-string">"python validate.py {data_file}"</span>
-</code></pre><p>Projects can specify their dependencies through a Conda environment. A project may also have multiple entry points for invoking runs, with named parameters. You can run projects using the <code>mlflow run</code> command-line tool, either from local files or from a Git repository:</p><pre><code class="language-shell hljs">mlflow run example/project -P alpha=0.5
+</table><p>MLflow is the No.2 on the trending board. Unlike Jina which specializes on the neural search and multimodal AI applications, MLflow is a more general platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. It offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). MLflow's current components are:</p><ul><li>MLflow Tracking: An API to log parameters, code, and results in machine learning experiments and compare them using an interactive UI.</li><li>MLflow Projects: A code packaging format for reproducible runs using Conda and Docker, so you can share your ML code with others.</li><li>MLflow Models: A model packaging format and tools that let you easily deploy the same model (from any ML library) to batch and real-time scoring on platforms such as Docker, Apache Spark, Azure ML and AWS SageMaker.</li><li>MLflow Model Registry: A centralized model store, set of APIs, and UI, to collaboratively manage the full lifecycle of MLflow Models. </li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-2.png" class="kg-image" alt="" width="1200" height="630" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-2.png 1200w" sizes="(min-width: 720px) 720px"><figcaption>Overview of the CI/CD tools, architecture and workflow of the MLflow centralized hub for model management.</figcaption></figure><p>MLflow Projects provide a standard format for packaging reusable data science code. Each project is simply a directory with code or a Git repository, and uses a descriptor file to specify its dependencies and how to run the code. A MLflow Project is defined by a simple YAML file called <code>MLproject</code>.</p><pre><code class="language-yaml">name: My Project
+conda_env: conda.yaml
+entry_points:
+  main:
+    parameters:
+      data_file: path
+      regularization: {type: float, default: 0.1}
+    command: "python train.py -r {regularization} {data_file}"
+  validate:
+    parameters:
+      data_file: path
+    command: "python validate.py {data_file}"
+</code></pre><p>Projects can specify their dependencies through a Conda environment. A project may also have multiple entry points for invoking runs, with named parameters. You can run projects using the <code>mlflow run</code> command-line tool, either from local files or from a Git repository:</p><pre><code class="language-shell">mlflow run example/project -P alpha=0.5
 
 mlflow run git@github.com:databricks/mlflow-example.git -P alpha=0.5
 </code></pre><p>MLflow will automatically set up the right environment for the project and run it.</p><h2 id="3-nni">3. NNI</h2><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/microsoft/nni?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - microsoft/nni: An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.</div><div class="kg-bookmark-description">An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. - GitHub - microsoft/...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">microsoft</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/135673451/54115900-1459-11eb-9c3e-442f26ab5e00" alt=""></div></a></figure><table>
@@ -137,19 +137,19 @@
 <td>Python</td>
 </tr>
 </tbody>
-</table><p>Microsoft NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate feature engineering, neural architecture search, hyperparameter tuning, and model compression for deep learning. NNI eases the effort to scale and manage AutoML experiments.</p><p>Unlike Jina which focuses more on inference, NNI focuses on model training and experimenting. It provides powerful and easy-to-use APIs for facilitating advanced training such as AutoML. Automatic neural architecture search is playing an increasingly important role in finding better models. Recent research has proven the feasibility of automatic NAS and has led to models that beat many manually designed and tuned models. Representative works include <a href="https://arxiv.org/abs/1707.07012?ref=jina-ai-gmbh.ghost.io">NASNet</a>, <a href="https://arxiv.org/abs/1802.03268?ref=jina-ai-gmbh.ghost.io">ENAS</a>, <a href="https://arxiv.org/abs/1806.09055?ref=jina-ai-gmbh.ghost.io">DARTS</a>, <a href="https://arxiv.org/abs/1806.10282?ref=jina-ai-gmbh.ghost.io">Network Morphism</a>, and <a href="https://arxiv.org/abs/1703.01041?ref=jina-ai-gmbh.ghost.io">Evolution</a>. </p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-4.png" class="kg-image" alt="" width="1105" height="256" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-4.png 1105w" sizes="(min-width: 720px) 720px"><figcaption>The process of neural architecture search is similar to Hyperparameter Optimization, except that the target is the best architecture rather than the hyperparameter.</figcaption></figure><p>In general, neural architecture search typically consists of three tasks: search space design, search strategy selection, and performance evaluation. These tasks are non-trivial by individual, but can be easily solved in NNI:</p><pre><code class="language-python hljs"><span class="hljs-comment"># define model space</span>
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">Model</span>(nn.Module):
+</table><p>Microsoft NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate feature engineering, neural architecture search, hyperparameter tuning, and model compression for deep learning. NNI eases the effort to scale and manage AutoML experiments.</p><p>Unlike Jina which focuses more on inference, NNI focuses on model training and experimenting. It provides powerful and easy-to-use APIs for facilitating advanced training such as AutoML. Automatic neural architecture search is playing an increasingly important role in finding better models. Recent research has proven the feasibility of automatic NAS and has led to models that beat many manually designed and tuned models. Representative works include <a href="https://arxiv.org/abs/1707.07012?ref=jina-ai-gmbh.ghost.io">NASNet</a>, <a href="https://arxiv.org/abs/1802.03268?ref=jina-ai-gmbh.ghost.io">ENAS</a>, <a href="https://arxiv.org/abs/1806.09055?ref=jina-ai-gmbh.ghost.io">DARTS</a>, <a href="https://arxiv.org/abs/1806.10282?ref=jina-ai-gmbh.ghost.io">Network Morphism</a>, and <a href="https://arxiv.org/abs/1703.01041?ref=jina-ai-gmbh.ghost.io">Evolution</a>. </p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-4.png" class="kg-image" alt="" width="1105" height="256" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-4.png 1105w" sizes="(min-width: 720px) 720px"><figcaption>The process of neural architecture search is similar to Hyperparameter Optimization, except that the target is the best architecture rather than the hyperparameter.</figcaption></figure><p>In general, neural architecture search typically consists of three tasks: search space design, search strategy selection, and performance evaluation. These tasks are non-trivial by individual, but can be easily solved in NNI:</p><pre><code class="language-python"># define model space
+class Model(nn.Module):
     self.conv2 = nn.LayerChoice([
-        nn.Conv2d(<span class="hljs-number">32</span>, <span class="hljs-number">64</span>, <span class="hljs-number">3</span>, <span class="hljs-number">1</span>),
-        DepthwiseSeparableConv(<span class="hljs-number">32</span>, <span class="hljs-number">64</span>)
+        nn.Conv2d(32, 64, 3, 1),
+        DepthwiseSeparableConv(32, 64)
     ])
 model_space = Model()
-<span class="hljs-comment"># search strategy + evaluator</span>
+# search strategy + evaluator
 strategy = RegularizedEvolution()
 evaluator = FunctionalEvaluator(
     train_eval_fn)
 
-<span class="hljs-comment"># run experiment</span>
+# run experiment
 RetiariiExperiment(model_space,
     evaluator, strategy).run()</code></pre><h2 id="4-kubeflow">4. Kubeflow</h2><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/kubeflow/kubeflow?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - kubeflow/kubeflow: Machine Learning Toolkit for Kubernetes</div><div class="kg-bookmark-description">Machine Learning Toolkit for Kubernetes. Contribute to kubeflow/kubeflow development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">kubeflow</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/bc75327fc9937f457fa648f4d86f9cf67581a894f73598a0dccc6e268ecc7bc2/kubeflow/kubeflow" alt=""></div></a></figure><table>
 <thead>
@@ -193,25 +193,25 @@
 <td>Python + Go</td>
 </tr>
 </tbody>
-</table><p>Label Studio is an open source tool from Heartex that focuses on an early but important stage of the ML lifecycle: <strong>data annotation</strong>. </p><p>Data annotation is the process of adding labels to data sets so that they can be used to train machine learning models. There are a few reasons why data annotation is so important. First, it allows for better-quality data sets. If data sets are not labeled, they can be more difficult for machine learning models to learn from. Second, data annotation can help to speed up the training process. And third, data annotation can improve the results of machine learning models by making them more accurate. Data annotation is usually done by hand, which can be a time-consuming and expensive process. </p><p>Label Studio lets you label data types like audio, text, images, videos, and time series with a simple UI and export them to various model formats. It can be used to prepare raw data or improve existing training data to get more accurate ML models. </p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/annotation_examples.gif" class="kg-image" alt="" width="900" height="500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/annotation_examples.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/annotation_examples.gif 900w" sizes="(min-width: 720px) 720px"></figure><p>You can also integrate Label Studio with machine learning models to supply predictions for labels (pre-labels), or perform continuous active learning. The Label Studio ML backend is an SDK that lets you wrap your machine learning code and turn it into a web server. You can then connect that server to a Label Studio instance to perform 2 tasks:</p><ul><li>Dynamically pre-annotate data based on model inference results</li><li>Retrain or fine-tune a model based on recently annotated data</li></ul><p>For example, to initialize an ML backend based on an example script:</p><pre><code class="language-shell hljs">label-studio-ml init my_ml_backend --script label_studio_ml/examples/simple_text_classifier/simple_text_classifier.py
-label-studio-ml start my_ml_backend</code></pre><p>After you define the loaders, you can define two methods for your model: an inference call and a training call.</p><p>One can use an inference call to get pre-annotations from your model on-the-fly. You must update the existing <code>predict</code> method in the example ML backend scripts to make them work for your specific use case. </p><figure class="kg-card kg-code-card"><pre><code class="language-python hljs"><span class="hljs-keyword">def</span> <span class="hljs-title function_">predict</span>(<span class="hljs-params">self, tasks, **kwargs</span>):
+</table><p>Label Studio is an open source tool from Heartex that focuses on an early but important stage of the ML lifecycle: <strong>data annotation</strong>. </p><p>Data annotation is the process of adding labels to data sets so that they can be used to train machine learning models. There are a few reasons why data annotation is so important. First, it allows for better-quality data sets. If data sets are not labeled, they can be more difficult for machine learning models to learn from. Second, data annotation can help to speed up the training process. And third, data annotation can improve the results of machine learning models by making them more accurate. Data annotation is usually done by hand, which can be a time-consuming and expensive process. </p><p>Label Studio lets you label data types like audio, text, images, videos, and time series with a simple UI and export them to various model formats. It can be used to prepare raw data or improve existing training data to get more accurate ML models. </p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/annotation_examples.gif" class="kg-image" alt="" width="900" height="500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/annotation_examples.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/annotation_examples.gif 900w" sizes="(min-width: 720px) 720px"></figure><p>You can also integrate Label Studio with machine learning models to supply predictions for labels (pre-labels), or perform continuous active learning. The Label Studio ML backend is an SDK that lets you wrap your machine learning code and turn it into a web server. You can then connect that server to a Label Studio instance to perform 2 tasks:</p><ul><li>Dynamically pre-annotate data based on model inference results</li><li>Retrain or fine-tune a model based on recently annotated data</li></ul><p>For example, to initialize an ML backend based on an example script:</p><pre><code class="language-shell">label-studio-ml init my_ml_backend --script label_studio_ml/examples/simple_text_classifier/simple_text_classifier.py
+label-studio-ml start my_ml_backend</code></pre><p>After you define the loaders, you can define two methods for your model: an inference call and a training call.</p><p>One can use an inference call to get pre-annotations from your model on-the-fly. You must update the existing <code>predict</code> method in the example ML backend scripts to make them work for your specific use case. </p><figure class="kg-card kg-code-card"><pre><code class="language-python">def predict(self, tasks, **kwargs):
     predictions = []
-    <span class="hljs-comment"># Get annotation tag first, and extract from_name/to_name keys from the labeling config to make predictions</span>
-    from_name, schema = <span class="hljs-built_in">list</span>(self.parsed_label_config.items())[<span class="hljs-number">0</span>]
-    to_name = schema[<span class="hljs-string">'to_name'</span>][<span class="hljs-number">0</span>]
-    <span class="hljs-keyword">for</span> task <span class="hljs-keyword">in</span> tasks:
-        <span class="hljs-comment"># for each task, return classification results in the form of "choices" pre-annotations</span>
+    # Get annotation tag first, and extract from_name/to_name keys from the labeling config to make predictions
+    from_name, schema = list(self.parsed_label_config.items())[0]
+    to_name = schema['to_name'][0]
+    for task in tasks:
+        # for each task, return classification results in the form of "choices" pre-annotations
         predictions.append({
-            <span class="hljs-string">'result'</span>: [{
-                <span class="hljs-string">'from_name'</span>: from_name,
-                <span class="hljs-string">'to_name'</span>: to_name,
-                <span class="hljs-string">'type'</span>: <span class="hljs-string">'choices'</span>,
-                <span class="hljs-string">'value'</span>: {<span class="hljs-string">'choices'</span>: [<span class="hljs-string">'My Label'</span>]}
+            'result': [{
+                'from_name': from_name,
+                'to_name': to_name,
+                'type': 'choices',
+                'value': {'choices': ['My Label']}
             }],
-            <span class="hljs-comment"># optionally you can include prediction scores that you can use to sort the tasks and do active learning</span>
-            <span class="hljs-string">'score'</span>: <span class="hljs-number">0.987</span>
+            # optionally you can include prediction scores that you can use to sort the tasks and do active learning
+            'score': 0.987
         })
-    <span class="hljs-keyword">return</span> predictions</code></pre><figcaption>Write your own code to override the predict(tasks, **kwargs) method, which takes JSON-formatted Label Studio tasks and returns predictions in the format accepted by Label Studio.</figcaption></figure><p>Write your own training call to update your model with new annotations, by overriding the <code>fit(annotations, **kwargs)</code> method, which takes <a href="https://labelstud.io/guide/export.html?ref=jina-ai-gmbh.ghost.io#Raw-JSON-format-of-completed-labeled-tasks" rel="nofollow">JSON-formatted Label Studio annotations</a> and returns an arbitrary dict where some information about the created model can be stored.</p><figure class="kg-card kg-code-card"><pre><code class="language-python hljs"><span class="hljs-keyword">def</span> <span class="hljs-title function_">fit</span>(<span class="hljs-params">self, completions, workdir=<span class="hljs-literal">None</span>, **kwargs</span>):
-    <span class="hljs-comment"># ... do some heavy computations, get your model and store checkpoints and resources</span>
-    <span class="hljs-keyword">return</span> {<span class="hljs-string">'checkpoints'</span>: <span class="hljs-string">'my/model/checkpoints'</span>}  <span class="hljs-comment"># &lt;-- you can retrieve this dict as self.train_output in the subsequent calls</span>
-</code></pre><figcaption>You don't need to use this call in your code, for example if you just want to pre-annotate tasks without retraining the model. If you do want to retrain the model based on annotations from Label Studio, use this method.</figcaption></figure><p>After you wrap your model code with the class, define the loaders, and define the methods, you're ready to run your model as an ML backend with Label Studio.</p><p>Hard to deny that the success of any machine learning model depends heavily on the quality of the data it is trained on. This explains why Label Studio is trending in 2022 and playes a crucial role in MLOps. </p><h2 id="mlops-adoption-inside-companies">MLOps Adoption Inside Companies</h2><p>In the past year, we've seen a number of companies adopting MLOps practices, and the trend is only accelerating. We see more companies adopting MLOps practices and sharing their experiences. In particular, there are two main approaches to MLOps: the centralized approach and the decentralized approach.</p><p>The centralized approach is typified by companies like Google and Facebook, who have centralized teams that are responsible for developing and managing the entire ML pipeline. The decentralized approach is typified by companies like Amazon and Netflix, who have decentralized teams that each manage a part of the ML pipeline. </p><ul><li>The centralized approach has the advantage of being able to develop and manage the entire ML pipeline in-house, which allows for greater control and transparency. The disadvantage of the centralized approach is that it can be very siloed, with different teams working in isolation from each other. </li><li>The decentralized approach has the advantage of being able to move faster and be more agile since each team is only responsible for a part of the ML pipeline. The disadvantage of the decentralized approach is that it can be less transparent and more difficult to track down issues. </li></ul><p>In 2022, the best MLOps setups have a mix of both centralized and decentralized approaches, depending on the needs of the company. For example, a company might have a centralized team responsible for developing the ML algorithms, and a decentralized team responsible for training and deploying the models.</p><h2 id="moving-forward-to-2023">Moving Forward to 2023</h2><p>In 2023, we expect to see more companies adopting MLOps practices, and the benefits of MLOps will become even more apparent. Especially <strong>with the paradigm shift of multimodal AI</strong>, more text, image, video, or even 3D mesh data are available, we will see datasets becoming more complex, and the need for automated data pipelines and machine learning management processes will become more critical.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">The Paradigm Shift Towards Multimodal AI</div><div class="kg-bookmark-description">We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they’re right at the starting line of this paradigm shift, and build the applications of the future today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/7.png" alt=""></div></a></figure><p>In 2023, the most successful MLOps setups will be the ones that can strike the right balance between people, process, and tooling. We anticipate that the most popular open source MLOps tools will be those that provide easy-to-use interfaces and allow for customizations to fit specific needs. The tools and platforms mentioned in this article will continue to evolve and become more user-friendly, making them accessible to a wider range of users. We also expect to see new platforms emerge, as well as new features and capabilities being added to existing platforms. </p><p>In terms of specific tools, we think that version control tools will become increasingly important for managing ML code and models. Data annotation and labeling tools will also gain popularity, as the need for high-quality training data becomes more apparent. And finally, model management tools will become essential for managing the various machine learning models that are deployed in production. Overall, we expect the MLOps landscape to become more diverse, with a wider range of tools available to meet the needs of different organizations. </p><p>In 2023, MLOps will be an essential part of any company that wants to stay competitive in the ever-changing world of machine learning. So if you're thinking about adopting MLOps, now is the time to do it. The benefits are clear, and the future looks very bright for MLOps.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffive-most-trending-open-source-mlops-tools-of-2022%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+    return predictions</code></pre><figcaption>Write your own code to override the predict(tasks, **kwargs) method, which takes JSON-formatted Label Studio tasks and returns predictions in the format accepted by Label Studio.</figcaption></figure><p>Write your own training call to update your model with new annotations, by overriding the <code>fit(annotations, **kwargs)</code> method, which takes <a href="https://labelstud.io/guide/export.html?ref=jina-ai-gmbh.ghost.io#Raw-JSON-format-of-completed-labeled-tasks" rel="nofollow">JSON-formatted Label Studio annotations</a> and returns an arbitrary dict where some information about the created model can be stored.</p><figure class="kg-card kg-code-card"><pre><code class="language-python">def fit(self, completions, workdir=None, **kwargs):
+    # ... do some heavy computations, get your model and store checkpoints and resources
+    return {'checkpoints': 'my/model/checkpoints'}  # &lt;-- you can retrieve this dict as self.train_output in the subsequent calls
+</code></pre><figcaption>You don't need to use this call in your code, for example if you just want to pre-annotate tasks without retraining the model. If you do want to retrain the model based on annotations from Label Studio, use this method.</figcaption></figure><p>After you wrap your model code with the class, define the loaders, and define the methods, you're ready to run your model as an ML backend with Label Studio.</p><p>Hard to deny that the success of any machine learning model depends heavily on the quality of the data it is trained on. This explains why Label Studio is trending in 2022 and playes a crucial role in MLOps. </p><h2 id="mlops-adoption-inside-companies">MLOps Adoption Inside Companies</h2><p>In the past year, we've seen a number of companies adopting MLOps practices, and the trend is only accelerating. We see more companies adopting MLOps practices and sharing their experiences. In particular, there are two main approaches to MLOps: the centralized approach and the decentralized approach.</p><p>The centralized approach is typified by companies like Google and Facebook, who have centralized teams that are responsible for developing and managing the entire ML pipeline. The decentralized approach is typified by companies like Amazon and Netflix, who have decentralized teams that each manage a part of the ML pipeline. </p><ul><li>The centralized approach has the advantage of being able to develop and manage the entire ML pipeline in-house, which allows for greater control and transparency. The disadvantage of the centralized approach is that it can be very siloed, with different teams working in isolation from each other. </li><li>The decentralized approach has the advantage of being able to move faster and be more agile since each team is only responsible for a part of the ML pipeline. The disadvantage of the decentralized approach is that it can be less transparent and more difficult to track down issues. </li></ul><p>In 2022, the best MLOps setups have a mix of both centralized and decentralized approaches, depending on the needs of the company. For example, a company might have a centralized team responsible for developing the ML algorithms, and a decentralized team responsible for training and deploying the models.</p><h2 id="moving-forward-to-2023">Moving Forward to 2023</h2><p>In 2023, we expect to see more companies adopting MLOps practices, and the benefits of MLOps will become even more apparent. Especially <strong>with the paradigm shift of multimodal AI</strong>, more text, image, video, or even 3D mesh data are available, we will see datasets becoming more complex, and the need for automated data pipelines and machine learning management processes will become more critical.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">The Paradigm Shift Towards Multimodal AI</div><div class="kg-bookmark-description">We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they’re right at the starting line of this paradigm shift, and build the applications of the future today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/7.png" alt=""></div></a></figure><p>In 2023, the most successful MLOps setups will be the ones that can strike the right balance between people, process, and tooling. We anticipate that the most popular open source MLOps tools will be those that provide easy-to-use interfaces and allow for customizations to fit specific needs. The tools and platforms mentioned in this article will continue to evolve and become more user-friendly, making them accessible to a wider range of users. We also expect to see new platforms emerge, as well as new features and capabilities being added to existing platforms. </p><p>In terms of specific tools, we think that version control tools will become increasingly important for managing ML code and models. Data annotation and labeling tools will also gain popularity, as the need for high-quality training data becomes more apparent. And finally, model management tools will become essential for managing the various machine learning models that are deployed in production. Overall, we expect the MLOps landscape to become more diverse, with a wider range of tools available to meet the needs of different organizations. </p><p>In 2023, MLOps will be an essential part of any company that wants to stay competitive in the ever-changing world of machine learning. So if you're thinking about adopting MLOps, now is the time to do it. The benefits are clear, and the future looks very bright for MLOps.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffive-most-trending-open-source-mlops-tools-of-2022%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>From Words to Art: Create Your Dream Stickers with Stable Diffusion</title><meta charset="utf-8"><meta name="title" content="From Words to Art: Create Your Dream Stickers with Stable Diffusion"><meta name="description" content="Dive into the world of Stable Diffusion and Prompt Engineering by fine-tuning your own LoRA, converting your words into stunning art and bringing your dream stickers to life."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/from-words-to-art-create-your-dream-stickers-with-stable-diffusion"><meta property="og:title" content="From Words to Art: Create Your Dream Stickers with Stable Diffusion"><meta property="og:description" content="Dive into the world of Stable Diffusion and Prompt Engineering by fine-tuning your own LoRA, converting your words into stunning art and bringing your dream stickers to life."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Blog-images--11-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/from-words-to-art-create-your-dream-stickers-with-stable-diffusion"><meta property="twitter:title" content="From Words to Art: Create Your Dream Stickers with Stable Diffusion"><meta property="twitter:description" content="Dive into the world of Stable Diffusion and Prompt Engineering by fine-tuning your own LoRA, converting your words into stunning art and bringing your dream stickers to life."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Blog-images--11-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>From Words to Art: Create Your Dream Stickers with Stable Diffusion</title><meta charset="utf-8"><meta name="title" content="From Words to Art: Create Your Dream Stickers with Stable Diffusion"><meta name="description" content="Dive into the world of Stable Diffusion and Prompt Engineering by fine-tuning your own LoRA, converting your words into stunning art and bringing your dream stickers to life."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/from-words-to-art-create-your-dream-stickers-with-stable-diffusion"><meta property="og:title" content="From Words to Art: Create Your Dream Stickers with Stable Diffusion"><meta property="og:description" content="Dive into the world of Stable Diffusion and Prompt Engineering by fine-tuning your own LoRA, converting your words into stunning art and bringing your dream stickers to life."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Blog-images--11-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/from-words-to-art-create-your-dream-stickers-with-stable-diffusion"><meta property="twitter:title" content="From Words to Art: Create Your Dream Stickers with Stable Diffusion"><meta property="twitter:description" content="Dive into the world of Stable Diffusion and Prompt Engineering by fine-tuning your own LoRA, converting your words into stunning art and bringing your dream stickers to life."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Blog-images--11-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">From Words to Art: Create Your Dream Stickers with Stable Diffusion</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Dive into the world of Stable Diffusion and Prompt Engineering by fine-tuning your own LoRA, converting your words into stunning art and bringing your dream stickers to life.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 80px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 55.5%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Jack-Min---upper-mid.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 121.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/profile-option-2.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jack Min Ong, Alex C-G, Saahil Ognawala</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 07, 2023 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the ever-evolving landscape of technology and creativity, artificial intelligence has emerged as a powerful tool capable of producing awe-inspiring works of art with relative ease, making artistic expression accessible to a wider audience.</p><p>As AI algorithms continue to push the boundaries of what is creatively achievable, some artists find themselves torn between marveling at the breathtaking beauty of AI-generated masterpieces and grappling with concerns about its impact on the traditional artistic landscape. While a <a href="https://www.reuters.com/legal/litigation/us-judge-finds-flaws-artists-lawsuit-against-ai-companies-2023-07-19/?ref=jina-ai-gmbh.ghost.io">recent legal case</a> [1] highlighted certain flaws in artists' attempts to hold AI companies accountable, their concern indicates the undeniable brilliance of the current state of AI-generated art and the implications on the future of the artistic process.</p><p>However, while the technology is impressive at generating realistic images and recreating the art styles of famous artists, it often falls short in generating images with the precise style we desire right out of the box. To bridge this gap and teach the model about our unique artistic style, fine-tuning becomes essential. In this blog post, we will explore finetuning Stable Diffusion to generate WhatsApp stickers.</p><h2 id="preparing-the-data"><strong>Preparing the Data</strong></h2><p>Before we embark on our sticker-generating journey, we must first gather the necessary data to train our model. You can use your own sticker packs or pick from the vast collection available on sites like <a href="https://getstickerpack.com/stickers?ref=jina-ai-gmbh.ghost.io">Sticker Maker</a>. For this blog post, we will be using the <a href="https://getstickerpack.com/stickers/vitavitacat?ref=jina-ai-gmbh.ghost.io">Vitavitacat sticker pack</a>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/dirty_grid.png" class="kg-image" alt="" width="2000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/dirty_grid.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/dirty_grid.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/dirty_grid.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/dirty_grid.png 2048w" sizes="(min-width: 720px) 720px"><figcaption>Sample images from vitavitacat stickerpack</figcaption></figure><p>Before we can use the stickers for training, we must first do some cleaning.</p><p>As of writing in August 2023, the Stable Diffusion models have a hard time generating text. If we leave the text in the images, our trained model will generate gibberish text which we will have to clean out in post-processing.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--32-.png" class="kg-image" alt="" width="1024" height="1020" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled--32-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Untitled--32-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--32-.png 1024w" sizes="(min-width: 720px) 720px"><figcaption>When you train on images that contain text, the model will generate gibberish text in the images</figcaption></figure><p>To prevent this, we need to remove the text in the image. To do this, just load your images into your favorite photo editing tool and erase the text:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/dirty_grid--1-.png" class="kg-image" alt="" width="2000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/dirty_grid--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/dirty_grid--1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/dirty_grid--1-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/dirty_grid--1-.png 2048w" sizes="(min-width: 720px) 720px"><figcaption>Raw images from vitavitacat stickerpack</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/clean_grid.png" class="kg-image" alt="" width="2000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/clean_grid.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/clean_grid.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/clean_grid.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/clean_grid.png 2048w" sizes="(min-width: 720px) 720px"><figcaption>Cleaned images without the text</figcaption></figure><p>Save all your cleaned images into a folder on your machine. Before we get to training, let’s take a brief detour to talk about how we would evaluate our model.</p><h2 id="evaluation-clip-score"><strong>Evaluation: CLIP score</strong></h2><p>To evaluate how well our model has learned our sticker style, we can use a CLIP (Contrastive Language-Image Pretraining) score. <a href="https://arxiv.org/pdf/2103.00020.pdf?ref=jina-ai-gmbh.ghost.io">CLIP</a> [5] is a model that was trained for image and text similarity. The <a href="https://huggingface.co/openai/clip-vit-base-patch32?ref=jina-ai-gmbh.ghost.io">CLIP model</a> [6] can be used to calculate a similarity metric between a pair of images or text which lies between 0 and 1, where 0 indicates that the pair are very different and 1 indicates that the pair are exactly the same.</p><p>We will calculate two types of CLIP Score to measure how well our model is doing:</p><h3 id="style-alignment">Style Alignment</h3><p>In order to measure how well our model has learned the overall style of our images, we will generate images using our trained model and compare their similarity with the images we prepared in our training dataset.</p><h3 id="text-image-alignment">Text-Image Alignment</h3><p>We also want to know how well our model is following the text prompts during generation. To do this, we will generate images using our trained model and compare their similarity with a set of prompts that we provide.</p><p>The CLIP score serves as a useful baseline evaluation metric and can be used as an indicator of how well your model is learning the style. However, it is not perfectly correlated with human preferences [2].</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--33-.png" class="kg-image" alt="" width="990" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled--33-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--33-.png 990w" sizes="(min-width: 720px) 720px"><figcaption>Correlation between Elo ratings of real users and Elo ratings by Zero-shot CLIP-H on human preferences from work done by Kirstain et al [2].</figcaption></figure><p>It will also not penalize the model for generating distortions which may occur when the model is trained for too long.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/distorted.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/distorted.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/distorted.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/distorted.png 1024w" sizes="(min-width: 720px) 720px"><figcaption>Distorted images from overt-raining</figcaption></figure><p>Thus, manual inspection and fine-tuning based on human judgment are still necessary for evaluating the model outputs.</p><h2 id="dreambooth"><strong>Dreambooth</strong></h2><p><a href="https://arxiv.org/pdf/2208.12242.pdf?ref=jina-ai-gmbh.ghost.io">Dreambooth</a> [3] was originally a method developed at Google for finetuning diffusion models to generate photos of a particular subject. However, in the Stable Diffusion community, it has come to mean any method that trains the full model. This is different from a training method that only trains on a part of the model, which is what we will describe in the rest of this article.</p><h2 id="colab-notebook">Colab Notebook</h2><p>To follow along with our fine-tuning story, use this <a href="https://colab.research.google.com/drive/16wFff7M3ttqqNg2qy3ZNMzygTL2XN-gx?usp=sharing&amp;ref=jina-ai-gmbh.ghost.io">Colab notebook</a> to start training your model with examples from this blog:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://colab.research.google.com/drive/16wFff7M3ttqqNg2qy3ZNMzygTL2XN-gx?usp=sharing&amp;ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Google Colaboratory</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ssl.gstatic.com/colaboratory-static/common/5dec30e9ccc134d01c1131623a7f1470/img/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://colab.research.google.com/img/colab_favicon_256px.png" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--34-.png" class="kg-image" alt="" width="2000" height="971" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled--34-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Untitled--34-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/Untitled--34-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/Untitled--34-.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Training metrics on Weights &amp; Biases from Colab notebook.</figcaption></figure><h2 id="loras">LoRAs</h2><p>Training the full model with Dreambooth is likely to yield the best results. However, this is resource intensive and requires a significant amount of VRAM (graphics card memory). This makes training impossible on some graphics cards. We can, however, lower the amount of VRAM required by using a method called Low-Rank Adaptation (<a href="https://arxiv.org/abs/2106.09685?ref=jina-ai-gmbh.ghost.io">LoRA</a>) [4]. When using LoRA, instead of training the full-weight matrices, we train two lower-ranked versions. This allows us to train with fewer parameters and reduce the amount of VRAM required.</p><h2 id="generating-images"><strong>Generating Images</strong></h2><p>With our Stable Diffusion model fine-tuned and ready to work its magic, we can now easily generate stickers directly within a notebook. If you uploaded your model, you can find the code snippet in the model card to generate images.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--35-.png" class="kg-image" alt="" width="1512" height="1212" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled--35-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Untitled--35-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--35-.png 1512w" sizes="(min-width: 720px) 720px"><figcaption>Code snippet to generate images with a trained model that was exported to the hub</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--36-.png" class="kg-image" alt="" width="2000" height="1157" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled--36-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Untitled--36-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/Untitled--36-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--36-.png 2050w" sizes="(min-width: 720px) 720px"><figcaption>Using the code snippet to generate images in a Colab notebook. Kung Fu cat has three tails for ULTIMATE BALANCE, obviously.</figcaption></figure><p>If you did not upload your model, you can instead download it directly in your Colab session using this link - <code>/content/output/pytorch_lora_weights.safetensors</code>. You can then use the path to the downloaded weights to initialize your model.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">From Words to Art: Create Your Dream Stickers with Stable Diffusion</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Dive into the world of Stable Diffusion and Prompt Engineering by fine-tuning your own LoRA, converting your words into stunning art and bringing your dream stickers to life.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 80px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 55.5%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Jack-Min---upper-mid.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 121.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/profile-option-2.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jack Min Ong, Alex C-G, Saahil Ognawala</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 07, 2023 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the ever-evolving landscape of technology and creativity, artificial intelligence has emerged as a powerful tool capable of producing awe-inspiring works of art with relative ease, making artistic expression accessible to a wider audience.</p><p>As AI algorithms continue to push the boundaries of what is creatively achievable, some artists find themselves torn between marveling at the breathtaking beauty of AI-generated masterpieces and grappling with concerns about its impact on the traditional artistic landscape. While a <a href="https://www.reuters.com/legal/litigation/us-judge-finds-flaws-artists-lawsuit-against-ai-companies-2023-07-19/?ref=jina-ai-gmbh.ghost.io">recent legal case</a> [1] highlighted certain flaws in artists' attempts to hold AI companies accountable, their concern indicates the undeniable brilliance of the current state of AI-generated art and the implications on the future of the artistic process.</p><p>However, while the technology is impressive at generating realistic images and recreating the art styles of famous artists, it often falls short in generating images with the precise style we desire right out of the box. To bridge this gap and teach the model about our unique artistic style, fine-tuning becomes essential. In this blog post, we will explore finetuning Stable Diffusion to generate WhatsApp stickers.</p><h2 id="preparing-the-data"><strong>Preparing the Data</strong></h2><p>Before we embark on our sticker-generating journey, we must first gather the necessary data to train our model. You can use your own sticker packs or pick from the vast collection available on sites like <a href="https://getstickerpack.com/stickers?ref=jina-ai-gmbh.ghost.io">Sticker Maker</a>. For this blog post, we will be using the <a href="https://getstickerpack.com/stickers/vitavitacat?ref=jina-ai-gmbh.ghost.io">Vitavitacat sticker pack</a>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/dirty_grid.png" class="kg-image" alt="" width="2000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/dirty_grid.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/dirty_grid.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/dirty_grid.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/dirty_grid.png 2048w" sizes="(min-width: 720px) 720px"><figcaption>Sample images from vitavitacat stickerpack</figcaption></figure><p>Before we can use the stickers for training, we must first do some cleaning.</p><p>As of writing in August 2023, the Stable Diffusion models have a hard time generating text. If we leave the text in the images, our trained model will generate gibberish text which we will have to clean out in post-processing.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--32-.png" class="kg-image" alt="" width="1024" height="1020" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled--32-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Untitled--32-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--32-.png 1024w" sizes="(min-width: 720px) 720px"><figcaption>When you train on images that contain text, the model will generate gibberish text in the images</figcaption></figure><p>To prevent this, we need to remove the text in the image. To do this, just load your images into your favorite photo editing tool and erase the text:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/dirty_grid--1-.png" class="kg-image" alt="" width="2000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/dirty_grid--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/dirty_grid--1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/dirty_grid--1-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/dirty_grid--1-.png 2048w" sizes="(min-width: 720px) 720px"><figcaption>Raw images from vitavitacat stickerpack</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/clean_grid.png" class="kg-image" alt="" width="2000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/clean_grid.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/clean_grid.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/clean_grid.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/clean_grid.png 2048w" sizes="(min-width: 720px) 720px"><figcaption>Cleaned images without the text</figcaption></figure><p>Save all your cleaned images into a folder on your machine. Before we get to training, let’s take a brief detour to talk about how we would evaluate our model.</p><h2 id="evaluation-clip-score"><strong>Evaluation: CLIP score</strong></h2><p>To evaluate how well our model has learned our sticker style, we can use a CLIP (Contrastive Language-Image Pretraining) score. <a href="https://arxiv.org/pdf/2103.00020.pdf?ref=jina-ai-gmbh.ghost.io">CLIP</a> [5] is a model that was trained for image and text similarity. The <a href="https://huggingface.co/openai/clip-vit-base-patch32?ref=jina-ai-gmbh.ghost.io">CLIP model</a> [6] can be used to calculate a similarity metric between a pair of images or text which lies between 0 and 1, where 0 indicates that the pair are very different and 1 indicates that the pair are exactly the same.</p><p>We will calculate two types of CLIP Score to measure how well our model is doing:</p><h3 id="style-alignment">Style Alignment</h3><p>In order to measure how well our model has learned the overall style of our images, we will generate images using our trained model and compare their similarity with the images we prepared in our training dataset.</p><h3 id="text-image-alignment">Text-Image Alignment</h3><p>We also want to know how well our model is following the text prompts during generation. To do this, we will generate images using our trained model and compare their similarity with a set of prompts that we provide.</p><p>The CLIP score serves as a useful baseline evaluation metric and can be used as an indicator of how well your model is learning the style. However, it is not perfectly correlated with human preferences [2].</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--33-.png" class="kg-image" alt="" width="990" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled--33-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--33-.png 990w" sizes="(min-width: 720px) 720px"><figcaption>Correlation between Elo ratings of real users and Elo ratings by Zero-shot CLIP-H on human preferences from work done by Kirstain et al [2].</figcaption></figure><p>It will also not penalize the model for generating distortions which may occur when the model is trained for too long.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/distorted.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/distorted.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/distorted.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/distorted.png 1024w" sizes="(min-width: 720px) 720px"><figcaption>Distorted images from overt-raining</figcaption></figure><p>Thus, manual inspection and fine-tuning based on human judgment are still necessary for evaluating the model outputs.</p><h2 id="dreambooth"><strong>Dreambooth</strong></h2><p><a href="https://arxiv.org/pdf/2208.12242.pdf?ref=jina-ai-gmbh.ghost.io">Dreambooth</a> [3] was originally a method developed at Google for finetuning diffusion models to generate photos of a particular subject. However, in the Stable Diffusion community, it has come to mean any method that trains the full model. This is different from a training method that only trains on a part of the model, which is what we will describe in the rest of this article.</p><h2 id="colab-notebook">Colab Notebook</h2><p>To follow along with our fine-tuning story, use this <a href="https://colab.research.google.com/drive/16wFff7M3ttqqNg2qy3ZNMzygTL2XN-gx?usp=sharing&amp;ref=jina-ai-gmbh.ghost.io">Colab notebook</a> to start training your model with examples from this blog:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://colab.research.google.com/drive/16wFff7M3ttqqNg2qy3ZNMzygTL2XN-gx?usp=sharing&amp;ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Google Colaboratory</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ssl.gstatic.com/colaboratory-static/common/5dec30e9ccc134d01c1131623a7f1470/img/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://colab.research.google.com/img/colab_favicon_256px.png" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--34-.png" class="kg-image" alt="" width="2000" height="971" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled--34-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Untitled--34-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/Untitled--34-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/Untitled--34-.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Training metrics on Weights &amp; Biases from Colab notebook.</figcaption></figure><h2 id="loras">LoRAs</h2><p>Training the full model with Dreambooth is likely to yield the best results. However, this is resource intensive and requires a significant amount of VRAM (graphics card memory). This makes training impossible on some graphics cards. We can, however, lower the amount of VRAM required by using a method called Low-Rank Adaptation (<a href="https://arxiv.org/abs/2106.09685?ref=jina-ai-gmbh.ghost.io">LoRA</a>) [4]. When using LoRA, instead of training the full-weight matrices, we train two lower-ranked versions. This allows us to train with fewer parameters and reduce the amount of VRAM required.</p><h2 id="generating-images"><strong>Generating Images</strong></h2><p>With our Stable Diffusion model fine-tuned and ready to work its magic, we can now easily generate stickers directly within a notebook. If you uploaded your model, you can find the code snippet in the model card to generate images.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--35-.png" class="kg-image" alt="" width="1512" height="1212" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled--35-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Untitled--35-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--35-.png 1512w" sizes="(min-width: 720px) 720px"><figcaption>Code snippet to generate images with a trained model that was exported to the hub</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--36-.png" class="kg-image" alt="" width="2000" height="1157" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled--36-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Untitled--36-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/Untitled--36-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled--36-.png 2050w" sizes="(min-width: 720px) 720px"><figcaption>Using the code snippet to generate images in a Colab notebook. Kung Fu cat has three tails for ULTIMATE BALANCE, obviously.</figcaption></figure><p>If you did not upload your model, you can instead download it directly in your Colab session using this link - <code>/content/output/pytorch_lora_weights.safetensors</code>. You can then use the path to the downloaded weights to initialize your model.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline
 <span class="hljs-keyword">import</span> torch
 
 device = torch.device(<span class="hljs-string">'cuda:0'</span> <span class="hljs-keyword">if</span> torch.cuda.is_available() <span class="hljs-keyword">else</span> <span class="hljs-string">'cpu'</span>)
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">New Community Reward Program is Coming!</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">We are excited to introduce a new Reward Plan to recognize active community members! You can gain credits by engaging with the community. How? Read on! </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 24, 2022 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>When you join an open-source community, there are many ways in which you can get involved. For example, <a href="https://github.com/fissoreg?ref=jina-ai-gmbh.ghost.io">Giancarlo Fissore</a>, a Ph.D. student in statistical physics and machine learning, started as a contributor and built a <a href="https://github.com/fissoreg/protein_search?ref=jina-ai-gmbh.ghost.io">protein search with Jina</a>. </p><p>Giancarlo’s journey in our community hasn't stopped there. His deep involvement has led him to become our community hero. He has guided new members in their onboarding journey, supported the community via doubt resolution, and joined our <a href="https://www.youtube.com/watch?v=clzHl1sIqrs&amp;ref=jina-ai-gmbh.ghost.io">community panel talk</a>. His impact as a passionate, open-source citizen was recognized. Also, he extended his global social networking by participating in the first cohort of the <a href="https://twitter.com/JinaAI_/status/1550108399249293312?ref=jina-ai-gmbh.ghost.io">Jina Community Advocates Panel (JCAP)</a>. Our US team members welcomed him when he traveled to San Francisco. </p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://lh5.googleusercontent.com/nHp8BTyaMSzSMTikZCcOqTeQDMy5IsGknqV_efW3ZJLIiNWWAgqpaMRA4fs47XfPqpY3bzJcOsx4-6-4U4FoBcrkimTI-8HFjUgsEccWj-0VdtKXj3FBxPSSyrZCfaZwwEHL8Ym6oww2y9S8lr-_sJhlHrBqt-1hlcnpzOx_hsrX6S-fHu-ju6ApcA" class="kg-image" alt="" width="277" height="248"><figcaption>Jina AI team members met Giancarlo in San Francisco</figcaption></figure><p>As a panelist of the first cohort, he took the initiative to introduce Jina to more developers. JCAP also provided mentorship programs for advocates like Giancarlo to improve their knowledge of the Jina ecosystem, craft their technical writing skills, get career development suggestions, and a variety of other developer community activities. With his active engagement and all the love from the Jina AI community, he is truly a community hero. After the ten weeks program, he was declared the first JCaptain this September. We officially announced the exciting news in Sep. Of course, he also received awesome swag! </p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh3.googleusercontent.com/TzzwewB8w93G0ahKvzkSuEI6I-2LTbzPKNOzVp7pnKHJ0LhZjBftiaPWHw4YoI-hKEZ9o_btJIaryA6XxYjP6AqBQgoNdHiLiLQD2kUA9PcBG8ngOxKrTSfsD1fUIiORwZAgFUYsx5JqpDu-hBpeL2QvYGRk3lSF9XONBGDErEavesjq0QiQF-BSZA" class="kg-image" alt="" width="624" height="351"></figure><p>The whole community always loves our swag. We also have some great items for our other community contributors. This journey could be yours in our open-source community. How? Read on!</p><p><strong>Jina AI Community Reward Plan For Active Members</strong><br>From Giancarlo's story, we know that coding is not the only way to engage with an open-source community, and the first step to being a community hero is to be active. Being an active community member, grants exposure, and provides personal impact, friendships, career development opportunities, and more. Several Jina AI team members have come directly from our developer community. A vibrant and supportive community can bring value to all developers. As a part of our community, we hope you will contribute to building the community you would like to see.</p><p><strong>We are excited to introduce a new Reward Plan to recognize active members! </strong>This new program will provide newly designed Jina AI swag. Stunning Jina AI items are designed for our community members and displayed through a swag portal. You can gain credits by engaging with the community, then redeem those credits for any swag you want. There is no limit on how many credits one can earn! Curious about what cool swag is offered? Check out <a href="https://store.covver.io/jina-ai/collections/swag-store?ref=jina-ai-gmbh.ghost.io">Jina AI Swag Store</a> here. In addition to all the amazing swag in the portal, be on the lookout for upcoming seasonal items!</p><p></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/all-over-print-tote-black-15-x15-mockup-62f4acaf9c567--1--1.png" width="1000" height="1000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/all-over-print-tote-black-15-x15-mockup-62f4acaf9c567--1--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/all-over-print-tote-black-15-x15-mockup-62f4acaf9c567--1--1.png 1000w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/1470203720be6cd52fed874-f7f974532.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/1470203720be6cd52fed874-f7f974532.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/1470203720be6cd52fed874-f7f974532.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/1470203720be6cd52fed874-f7f974532.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/a7c56a21c7a8f8ab22ff3eacc--20cd569--1--1.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/a7c56a21c7a8f8ab22ff3eacc--20cd569--1--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/a7c56a21c7a8f8ab22ff3eacc--20cd569--1--1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/a7c56a21c7a8f8ab22ff3eacc--20cd569--1--1.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>🏆<strong> 10 Luckiest New Members</strong><br>On the first day you join our community, don't forget to do a self-introduction on the #introduction channel, and join the survey to tell us your expectations! Every month, 10 new members who finish the two tasks will get 10 credits with a randomizer.</p><p><strong>🏆 Top 10 Monthly Active Messengers</strong><br>If you have any issues or cool ideas about using the Jina ecosystem, don't hesitate to post them on our public channels! Please also feel free to share your comments, give recognition, and answer questions. Each of the top 10 active messengers will receive 10 credits every month. All messages in public channels are counted, no matter whether you post or reply.</p><p><strong>🏆 Community Advocates Award</strong><br>We hope to see more advocates from our community. If you manage to make more developers know about the Jina ecosystem, you will be awarded 20 credits each time! And don't forget to post whatever you have done at our #showcase channel to redeem your credits! There are various ways to make it happen:<br>1️⃣ Post the project you make with Jina on your social media<br>2️⃣ Write technical blogs about Jina and share them with public<br>3️⃣Give a speech about the Jina ecosystem at any events you are in<br>4️⃣Host a local Jina advocates meetup<br>5️⃣Apply to be the speaker at our community event</p><p>Also, we are happy to provide you support to help you to give a successful speech or host a local meetup. Please get in touch with us on <a href="https://jina.ai/slack/?ref=jina-ai-gmbh.ghost.io">Slack</a> to let us know if you have any good ideas about it. <strong>Meanwhile, we are looking for passionate members to join our JCAP program to make yourself a community hero sooner! </strong>Please fulfill the <a href="https://forms.gle/fPCv1qChWUXuEr5u9?ref=jina-ai-gmbh.ghost.io">JCAP application form</a> and we will contact you after.</p><p>Joining our community today itself will give you a chance to win credits! So, what are you waiting for? We welcome everyone and look forward to rewarding you for your efforts. Please note this announcement implies that we are retiring our previous swag distribution criteria and closing our swag form. The new reward system is effective from Oct. 24th, 2022.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ffrom-zero-to-hero-at-jina-ai-community%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">We are excited to introduce a new Reward Plan to recognize active community members! You can gain credits by engaging with the community. How? Read on! </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 24, 2022 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>When you join an open-source community, there are many ways in which you can get involved. For example, <a href="https://github.com/fissoreg?ref=jina-ai-gmbh.ghost.io">Giancarlo Fissore</a>, a Ph.D. student in statistical physics and machine learning, started as a contributor and built a <a href="https://github.com/fissoreg/protein_search?ref=jina-ai-gmbh.ghost.io">protein search with Jina</a>. </p><p>Giancarlo’s journey in our community hasn't stopped there. His deep involvement has led him to become our community hero. He has guided new members in their onboarding journey, supported the community via doubt resolution, and joined our <a href="https://www.youtube.com/watch?v=clzHl1sIqrs&amp;ref=jina-ai-gmbh.ghost.io">community panel talk</a>. His impact as a passionate, open-source citizen was recognized. Also, he extended his global social networking by participating in the first cohort of the <a href="https://twitter.com/JinaAI_/status/1550108399249293312?ref=jina-ai-gmbh.ghost.io">Jina Community Advocates Panel (JCAP)</a>. Our US team members welcomed him when he traveled to San Francisco. </p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://lh5.googleusercontent.com/nHp8BTyaMSzSMTikZCcOqTeQDMy5IsGknqV_efW3ZJLIiNWWAgqpaMRA4fs47XfPqpY3bzJcOsx4-6-4U4FoBcrkimTI-8HFjUgsEccWj-0VdtKXj3FBxPSSyrZCfaZwwEHL8Ym6oww2y9S8lr-_sJhlHrBqt-1hlcnpzOx_hsrX6S-fHu-ju6ApcA" class="kg-image" alt="" width="277" height="248"><figcaption>Jina AI team members met Giancarlo in San Francisco</figcaption></figure><p>As a panelist of the first cohort, he took the initiative to introduce Jina to more developers. JCAP also provided mentorship programs for advocates like Giancarlo to improve their knowledge of the Jina ecosystem, craft their technical writing skills, get career development suggestions, and a variety of other developer community activities. With his active engagement and all the love from the Jina AI community, he is truly a community hero. After the ten weeks program, he was declared the first JCaptain this September. We officially announced the exciting news in Sep. Of course, he also received awesome swag! </p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh3.googleusercontent.com/TzzwewB8w93G0ahKvzkSuEI6I-2LTbzPKNOzVp7pnKHJ0LhZjBftiaPWHw4YoI-hKEZ9o_btJIaryA6XxYjP6AqBQgoNdHiLiLQD2kUA9PcBG8ngOxKrTSfsD1fUIiORwZAgFUYsx5JqpDu-hBpeL2QvYGRk3lSF9XONBGDErEavesjq0QiQF-BSZA" class="kg-image" alt="" width="624" height="351"></figure><p>The whole community always loves our swag. We also have some great items for our other community contributors. This journey could be yours in our open-source community. How? Read on!</p><p><strong>Jina AI Community Reward Plan For Active Members</strong><br>From Giancarlo's story, we know that coding is not the only way to engage with an open-source community, and the first step to being a community hero is to be active. Being an active community member, grants exposure, and provides personal impact, friendships, career development opportunities, and more. Several Jina AI team members have come directly from our developer community. A vibrant and supportive community can bring value to all developers. As a part of our community, we hope you will contribute to building the community you would like to see.</p><p><strong>We are excited to introduce a new Reward Plan to recognize active members! </strong>This new program will provide newly designed Jina AI swag. Stunning Jina AI items are designed for our community members and displayed through a swag portal. You can gain credits by engaging with the community, then redeem those credits for any swag you want. There is no limit on how many credits one can earn! Curious about what cool swag is offered? Check out <a href="https://store.covver.io/jina-ai/collections/swag-store?ref=jina-ai-gmbh.ghost.io">Jina AI Swag Store</a> here. In addition to all the amazing swag in the portal, be on the lookout for upcoming seasonal items!</p><p></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/all-over-print-tote-black-15-x15-mockup-62f4acaf9c567--1--1.png" width="1000" height="1000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/all-over-print-tote-black-15-x15-mockup-62f4acaf9c567--1--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/all-over-print-tote-black-15-x15-mockup-62f4acaf9c567--1--1.png 1000w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/1470203720be6cd52fed874-f7f974532.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/1470203720be6cd52fed874-f7f974532.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/1470203720be6cd52fed874-f7f974532.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/1470203720be6cd52fed874-f7f974532.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/a7c56a21c7a8f8ab22ff3eacc--20cd569--1--1.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/a7c56a21c7a8f8ab22ff3eacc--20cd569--1--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/a7c56a21c7a8f8ab22ff3eacc--20cd569--1--1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/a7c56a21c7a8f8ab22ff3eacc--20cd569--1--1.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>🏆<strong> 10 Luckiest New Members</strong><br>On the first day you join our community, don't forget to do a self-introduction on the #introduction channel, and join the survey to tell us your expectations! Every month, 10 new members who finish the two tasks will get 10 credits with a randomizer.</p><p><strong>🏆 Top 10 Monthly Active Messengers</strong><br>If you have any issues or cool ideas about using the Jina ecosystem, don't hesitate to post them on our public channels! Please also feel free to share your comments, give recognition, and answer questions. Each of the top 10 active messengers will receive 10 credits every month. All messages in public channels are counted, no matter whether you post or reply.</p><p><strong>🏆 Community Advocates Award</strong><br>We hope to see more advocates from our community. If you manage to make more developers know about the Jina ecosystem, you will be awarded 20 credits each time! And don't forget to post whatever you have done at our #showcase channel to redeem your credits! There are various ways to make it happen:<br>1️⃣ Post the project you make with Jina on your social media<br>2️⃣ Write technical blogs about Jina and share them with public<br>3️⃣Give a speech about the Jina ecosystem at any events you are in<br>4️⃣Host a local Jina advocates meetup<br>5️⃣Apply to be the speaker at our community event</p><p>Also, we are happy to provide you support to help you to give a successful speech or host a local meetup. Please get in touch with us on <a href="https://jina.ai/slack/?ref=jina-ai-gmbh.ghost.io">Slack</a> to let us know if you have any good ideas about it. <strong>Meanwhile, we are looking for passionate members to join our JCAP program to make yourself a community hero sooner! </strong>Please fulfill the <a href="https://forms.gle/fPCv1qChWUXuEr5u9?ref=jina-ai-gmbh.ghost.io">JCAP application form</a> and we will contact you after.</p><p>Joining our community today itself will give you a chance to win credits! So, what are you waiting for? We welcome everyone and look forward to rewarding you for your efforts. Please note this announcement implies that we are retiring our previous swag distribution criteria and closing our swag form. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Full-stack RAG with Jina Embeddings v2 and LlamaIndex</title><meta charset="utf-8"><meta name="title" content="Full-stack RAG with Jina Embeddings v2 and LlamaIndex"><meta name="description" content="You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex"><meta property="og:title" content="Full-stack RAG with Jina Embeddings v2 and LlamaIndex"><meta property="og:description" content="You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex"><meta property="twitter:title" content="Full-stack RAG with Jina Embeddings v2 and LlamaIndex"><meta property="twitter:description" content="You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 22, 2023 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>LLMs are cool, but their input context windows are always so small. They’re getting bigger, but they’ll never be big enough for, say, a whole book, much less an encyclopedia, unless there is some breakthrough in AI model architectures.</p><p>RAG (<a href="https://blogs.nvidia.com/blog/what-is-retrieval-augmented-generation/?ref=jina-ai-gmbh.ghost.io">Retrieval Augmented Generation</a>) is a strategy that can compensate for this limitation, letting you use LLMs to respond to questions with answers that draw on relevant parts of documents or whole repositories of documents that are far too large to put entirely into the model’s input.</p><p>This article will show you how to use LlamaIndex, Jina Embeddings, and the <code>Mixtral-8x7B-Instruct-v0.1</code> language model (<a href="https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1?ref=jina-ai-gmbh.ghost.io">hosted on HuggingFace</a>) to build a complete RAG system. For more information on the Mixtral language model, see the <a href="https://mistral.ai/news/mixtral-of-experts/?ref=jina-ai-gmbh.ghost.io">Mistral AI website</a> or the <a href="https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1?ref=jina-ai-gmbh.ghost.io">model card on HuggingFace</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.llamaindex.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">LlamaIndex - Data Framework for LLM Applications</div><div class="kg-bookmark-description">LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models (LLMs).</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://assets-global.website-files.com/6459a0e3f348e9e898b7df80/645ad8c999ba34bf0713622b_LlamaBrowserTab.png" alt=""><span class="kg-bookmark-author">Data Framework for LLM Applications</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://assets-global.website-files.com/6459a0e3f348e9e898b7df80/6462e6a26afc95b84a8db9dc_LlamaLogo%20White.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Embedding API</div><div class="kg-bookmark-description">Top-performing, 8192-token length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/banner-embedding-api.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://mistral.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Mistral AI | Open source models</div><div class="kg-bookmark-description">Frontier AI in your hands</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://mistral.ai/images/favicon/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">Open source models</span><span class="kg-bookmark-publisher">Mistral AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://mistral.ai/images/mistral-social-banner.jpg" alt=""></div></a></figure><p>You can also <a href="https://raw.githubusercontent.com/jina-ai/workshops/article/LlamaIndex/notebooks/llamaindex/RAGwithJinaLlamaIndex.ipynb?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">download a Jupyter Notebook with all the code in this article from GitHub</a>, or <a href="https://colab.research.google.com/github/jina-ai/workshops/blob/article%2FLlamaIndex/notebooks/llamaindex/RAGwithJinaLlamaIndex.ipynb?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">run it directly on Colab</a>.</p><p>You will need:</p><ol><li>A <a href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io">Jina Embeddings API key</a>.</li><li>A <a href="https://huggingface.co/settings/tokens?ref=jina-ai-gmbh.ghost.io">HuggingFace account and token</a>.</li></ol><p>Since both the Jina Embeddings model and Mixtral are running remotely and are accessed via a web API, you won’t need any special hardware. You will need to install Python and meet the <a href="https://docs.llamaindex.ai/en/stable/getting_started/installation.html?ref=jina-ai-gmbh.ghost.io">system requirements for LlamaIndex</a>.</p><h2 id="what-is-rag-and-how-does-it-work">What is RAG and How Does it Work?</h2><p>Retrieval Augmented Generation is a strategy that merges search with language generation. The way it works is that it uses an external information retrieval system to find documents that are likely to inform the answer to a user query. It then passes them, with the user’s request, to a text-generating language model, which produces a natural language response.</p><p>This allows you to use an LLM to answer questions and use information from documents and sets of documents that are much larger than its input context window. The LLM only sees a few pertinent parts of the document when responding to prompts. This also has the advantage of reducing (although not eliminating) inexplicable hallucinations.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Untitled--24-.png" class="kg-image" alt="" width="1600" height="750" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Untitled--24-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/Untitled--24-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/Untitled--24-.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>This strategy has some limitations:</p><ol><li>It is sensitive to the input context size supported by the LLM. The larger the context size, the more information you can give the LLM, yielding better and richer responses.</li><li>It is sensitive to the quality of the results of the initial information retrieval. If your search engine gives it irrelevant or inaccurate results, the LLM may paste them together as best it can and give you garbage output. This can be caused by bad data (as the saying goes <a href="https://en.wikipedia.org/wiki/Garbage_in,_garbage_out?ref=jina-ai-gmbh.ghost.io"><em>garbage in, garbage out</em></a>) but can also be caused by a search system that does not return the most useful matches or does not rank them highly enough in the results.</li></ol><p>High-quality embeddings are key to making RAG work because they reduce the impact of these limitations.</p><p>First, a small context size for an LLM means it’s extra important to find the most relevant information, because you cannot add very much to the user’s prompt. Second, how informative the answer is depends on how informative the input is. If the search results displayed to the LLM are irrelevant or poorly informative, that will be reflected in the result.</p><p>AI-generated embeddings are, on the whole, the best way to find and rank query results in general.</p><h2 id="build-a-full-rag-chatbot">Build a Full RAG Chatbot</h2><p>We will create and install a full RAG system using the <a href="https://www.llamaindex.ai/?ref=jina-ai-gmbh.ghost.io">LlamaIndex framework</a> for working with LLMs. This system uses Jina Embeddings to index document elements and store them in LlamaIndex’ built-in vector store and search engine. Then, it uses the newly released <a href="https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1?ref=jina-ai-gmbh.ghost.io">Mixtral Instruct</a> model to construct natural language answers.</p><p>The approach in the article will also work with OpenAI’s GPT models and Meta’s Llama2, with some adaptation of the code and possibly the prompt. For more details, read the <a href="https://docs.llamaindex.ai/en/stable/?ref=jina-ai-gmbh.ghost.io">LlamaIndex documentation</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docs.llamaindex.ai/en/stable/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">LlamaIndex 🦙 0.9.19</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docs.llamaindex.ai/favicon.ico" alt=""><span class="kg-bookmark-author">LlamaIndex 🦙 0.9.19</span></div></div></a></figure><p>This section involves a lot of code to copy and paste, and it will only get a very high-level explanation. You may prefer to <a href="https://raw.githubusercontent.com/jina-ai/workshops/article/LlamaIndex/notebooks/llamaindex/RAGwithJinaLlamaIndex.ipynb?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">download the accompanying notebook</a> or <a href="https://colab.research.google.com/github/jina-ai/workshops/blob/article%2FLlamaIndex/notebooks/llamaindex/RAGwithJinaLlamaIndex.ipynb?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">run this code on Google Colab</a>.</p><h3 id="getting-started">Getting Started</h3><p>First, install LlamaIndex:</p><pre><code class="language-bash hljs">pip install llama-index
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 22, 2023 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>LLMs are cool, but their input context windows are always so small. They’re getting bigger, but they’ll never be big enough for, say, a whole book, much less an encyclopedia, unless there is some breakthrough in AI model architectures.</p><p>RAG (<a href="https://blogs.nvidia.com/blog/what-is-retrieval-augmented-generation/?ref=jina-ai-gmbh.ghost.io">Retrieval Augmented Generation</a>) is a strategy that can compensate for this limitation, letting you use LLMs to respond to questions with answers that draw on relevant parts of documents or whole repositories of documents that are far too large to put entirely into the model’s input.</p><p>This article will show you how to use LlamaIndex, Jina Embeddings, and the <code>Mixtral-8x7B-Instruct-v0.1</code> language model (<a href="https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1?ref=jina-ai-gmbh.ghost.io">hosted on HuggingFace</a>) to build a complete RAG system. For more information on the Mixtral language model, see the <a href="https://mistral.ai/news/mixtral-of-experts/?ref=jina-ai-gmbh.ghost.io">Mistral AI website</a> or the <a href="https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1?ref=jina-ai-gmbh.ghost.io">model card on HuggingFace</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.llamaindex.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">LlamaIndex - Data Framework for LLM Applications</div><div class="kg-bookmark-description">LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models (LLMs).</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://assets-global.website-files.com/6459a0e3f348e9e898b7df80/645ad8c999ba34bf0713622b_LlamaBrowserTab.png" alt=""><span class="kg-bookmark-author">Data Framework for LLM Applications</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://assets-global.website-files.com/6459a0e3f348e9e898b7df80/6462e6a26afc95b84a8db9dc_LlamaLogo%20White.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Embedding API</div><div class="kg-bookmark-description">Top-performing, 8192-token length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/banner-embedding-api.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://mistral.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Mistral AI | Open source models</div><div class="kg-bookmark-description">Frontier AI in your hands</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://mistral.ai/images/favicon/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">Open source models</span><span class="kg-bookmark-publisher">Mistral AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://mistral.ai/images/mistral-social-banner.jpg" alt=""></div></a></figure><p>You can also <a href="https://raw.githubusercontent.com/jina-ai/workshops/article/LlamaIndex/notebooks/llamaindex/RAGwithJinaLlamaIndex.ipynb?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">download a Jupyter Notebook with all the code in this article from GitHub</a>, or <a href="https://colab.research.google.com/github/jina-ai/workshops/blob/article%2FLlamaIndex/notebooks/llamaindex/RAGwithJinaLlamaIndex.ipynb?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">run it directly on Colab</a>.</p><p>You will need:</p><ol><li>A <a href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io">Jina Embeddings API key</a>.</li><li>A <a href="https://huggingface.co/settings/tokens?ref=jina-ai-gmbh.ghost.io">HuggingFace account and token</a>.</li></ol><p>Since both the Jina Embeddings model and Mixtral are running remotely and are accessed via a web API, you won’t need any special hardware. You will need to install Python and meet the <a href="https://docs.llamaindex.ai/en/stable/getting_started/installation.html?ref=jina-ai-gmbh.ghost.io">system requirements for LlamaIndex</a>.</p><h2 id="what-is-rag-and-how-does-it-work">What is RAG and How Does it Work?</h2><p>Retrieval Augmented Generation is a strategy that merges search with language generation. The way it works is that it uses an external information retrieval system to find documents that are likely to inform the answer to a user query. It then passes them, with the user’s request, to a text-generating language model, which produces a natural language response.</p><p>This allows you to use an LLM to answer questions and use information from documents and sets of documents that are much larger than its input context window. The LLM only sees a few pertinent parts of the document when responding to prompts. This also has the advantage of reducing (although not eliminating) inexplicable hallucinations.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Untitled--24-.png" class="kg-image" alt="" width="1600" height="750" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Untitled--24-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/12/Untitled--24-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/Untitled--24-.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>This strategy has some limitations:</p><ol><li>It is sensitive to the input context size supported by the LLM. The larger the context size, the more information you can give the LLM, yielding better and richer responses.</li><li>It is sensitive to the quality of the results of the initial information retrieval. If your search engine gives it irrelevant or inaccurate results, the LLM may paste them together as best it can and give you garbage output. This can be caused by bad data (as the saying goes <a href="https://en.wikipedia.org/wiki/Garbage_in,_garbage_out?ref=jina-ai-gmbh.ghost.io"><em>garbage in, garbage out</em></a>) but can also be caused by a search system that does not return the most useful matches or does not rank them highly enough in the results.</li></ol><p>High-quality embeddings are key to making RAG work because they reduce the impact of these limitations.</p><p>First, a small context size for an LLM means it’s extra important to find the most relevant information, because you cannot add very much to the user’s prompt. Second, how informative the answer is depends on how informative the input is. If the search results displayed to the LLM are irrelevant or poorly informative, that will be reflected in the result.</p><p>AI-generated embeddings are, on the whole, the best way to find and rank query results in general.</p><h2 id="build-a-full-rag-chatbot">Build a Full RAG Chatbot</h2><p>We will create and install a full RAG system using the <a href="https://www.llamaindex.ai/?ref=jina-ai-gmbh.ghost.io">LlamaIndex framework</a> for working with LLMs. This system uses Jina Embeddings to index document elements and store them in LlamaIndex’ built-in vector store and search engine. Then, it uses the newly released <a href="https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1?ref=jina-ai-gmbh.ghost.io">Mixtral Instruct</a> model to construct natural language answers.</p><p>The approach in the article will also work with OpenAI’s GPT models and Meta’s Llama2, with some adaptation of the code and possibly the prompt. For more details, read the <a href="https://docs.llamaindex.ai/en/stable/?ref=jina-ai-gmbh.ghost.io">LlamaIndex documentation</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docs.llamaindex.ai/en/stable/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">LlamaIndex 🦙 0.9.19</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docs.llamaindex.ai/favicon.ico" alt=""><span class="kg-bookmark-author">LlamaIndex 🦙 0.9.19</span></div></div></a></figure><p>This section involves a lot of code to copy and paste, and it will only get a very high-level explanation. You may prefer to <a href="https://raw.githubusercontent.com/jina-ai/workshops/article/LlamaIndex/notebooks/llamaindex/RAGwithJinaLlamaIndex.ipynb?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">download the accompanying notebook</a> or <a href="https://colab.research.google.com/github/jina-ai/workshops/blob/article%2FLlamaIndex/notebooks/llamaindex/RAGwithJinaLlamaIndex.ipynb?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">run this code on Google Colab</a>.</p><h3 id="getting-started">Getting Started</h3><p>First, install LlamaIndex:</p><pre><code class="language-bash hljs">pip install llama-index
 </code></pre><p>Next, make sure that you have a <a href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io">Jina API key</a> and a <a href="https://huggingface.co/settings/tokens?ref=jina-ai-gmbh.ghost.io">HuggingFace Inference API token</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Embedding API</div><div class="kg-bookmark-description">Top-performing, 8192-token length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/banner-embedding-api.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/settings/tokens?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Hugging Face – The AI community building the future.</div><div class="kg-bookmark-description">We’re on a journey to advance and democratize artificial intelligence through open source and open science.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://huggingface.co/front/thumbnails/v2-2.png" alt=""></div></a></figure><p>In Python, set up your secret key values like this:</p><pre><code class="language-Python hljs">jinaai_api_key = <span class="hljs-string">"&lt;your Jina Embeddings API key&gt;"</span>
 hf_inference_api_key: <span class="hljs-built_in">str</span> = <span class="hljs-string">'&lt;your HuggingFace Inference API token&gt;'</span>
 </code></pre><h3 id="connect-jina-embeddings">Connect Jina Embeddings</h3><p>LlamaIndex provides built-in support for the Jina Embeddings API. To use it, you only need to initialize the <code>JinaEmbedding</code> object with your API key and model name. For this example, we will use <code>jina-embeddings-v2-base-en</code>.</p><pre><code class="language-Python hljs"><span class="hljs-keyword">from</span> llama_index.embeddings.jinaai <span class="hljs-keyword">import</span> JinaEmbedding
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>The Battle over Copyright in the Age of AI</title><meta charset="utf-8"><meta name="title" content="The Battle over Copyright in the Age of AI"><meta name="description" content="New Generative AI technologies have important consequences for IP regulatory law, and how they are ultimately handled will strongly affect the development of this sector."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/generative-ai-as-ip"><meta property="og:title" content="The Battle over Copyright in the Age of AI"><meta property="og:description" content="New Generative AI technologies have important consequences for IP regulatory law, and how they are ultimately handled will strongly affect the development of this sector."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/AI-Copyright.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/generative-ai-as-ip"><meta property="twitter:title" content="The Battle over Copyright in the Age of AI"><meta property="twitter:description" content="New Generative AI technologies have important consequences for IP regulatory law, and how they are ultimately handled will strongly affect the development of this sector."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/AI-Copyright.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">The Battle over Copyright in the Age of AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">New Generative AI technologies have important consequences for IP regulatory law, and how they are ultimately handled will strongly affect the development of this sector.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 14, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Originally published in German translation as <em><a href="https://background.tagesspiegel.de/digitalisierung/wie-mit-den-urheberrechtsdebatten-um-ki-umgegangen-werden-koennte?ref=jina-ai-gmbh.ghost.io">Wie mit den Urheberrechtsdebatten um KI umgegangen werden könnte</a></em> in <em>Tagesspiegel Background</em></div></div><p>In the last few years, Generative AI models have begun to produce strikingly fluent language, polished images, and appealing music from within themselves, arguably demonstrating autonomous creativity. Names like ChatGPT and Stable Diffusion are in the news. Jina AI is part an emerging German 'AI sector', encompassing a growing collection of startups that provide AI-centered software and services. New Generative AI technologies have important consequences for intellectual property (IP) law, and how they are ultimately handled will strongly affect the development of this sector.</p><p>There is some debate about whether AI output can be IP at all. There is little clear law on this subject. Copyright requires works to reflect <em>human</em> creativity, but in practice creating works using AI models requires significant human involvement. Humans construct textual "prompts" to stimulate image production, then modify those prompts based on the result, and select among multiple productions. AI-generated texts and music follow much the same pattern. This is comparable to the way a photographer takes a picture, and that has clear IP protections.</p><p>A bigger problem is the way Generative AI models are made. Large AI models are expensive to produce and come primarily from a few sources, particularly OpenAI (which is mostly controlled by Microsoft), Meta (Facebook/Instagram), and Alphabet (Google/DeepMind). Jina AI and other start-ups are highly dependent on access to them.</p><p>These models are trained to produce their outputs using large quantities of human-made written text, images, music, etc. and the most useful ones have all been trained using data taken from the Internet without the consent of their owners. Writers and musicians have not responded very strongly to this unauthorized use, but it has evoked strong reactions from visual artists. “AI art is theft” <a href="https://www.artstation.com/artwork/nEaqd4?ref=jina-ai-gmbh.ghost.io">has become a viral slogan</a>.</p><p>There are lawsuits challenging Generative AI underway in <a href="https://stablediffusionlitigation.com/?ref=jina-ai-gmbh.ghost.io">California</a> and the <a href="https://www.theverge.com/2023/1/17/23558516/ai-art-copyright-stable-diffusion-getty-images-lawsuit?ref=jina-ai-gmbh.ghost.io">UK</a>, and we can assume that there will be cases under EU law. These suits argue that Generative AI models are derivative works infringing on IP rights in their training data. Furthermore, they allege that anything created using those models is equally an infringing work, because neural network models merely store and then “recombine” the works of others. AI advocates challenge that characterization.</p><p>Under the laws of the US, UK, and countries inheriting their legal traditions, principles of “fair use” or “fair dealing” create broad but ambiguous exceptions to copyright, which might apply to AI training. But “fair use” has no equivalent in European and German law. Allowed exceptions to copyright are listed in <a href="https://lexparency.de/eu/32001L0029/ART_5/?ref=jina-ai-gmbh.ghost.io">Article 5 of the EU Copyright and Information Society Directive</a>, and contain nothing to help AI models. Since the 2013 <a href="https://hudoc.echr.coe.int/eng?ref=jina-ai-gmbh.ghost.io#%7B%22itemid%22:[%22001-115845%22]%7D">Ashby decision by the ECHR</a>, European courts have begun to find an implicit “fair use” doctrine in the European Convention’s guarantee of freedom of expression, but this is unlikely to apply to for-profit software.</p><p>We cannot predict the future, but it is possible, perhaps likely, that European courts will find that models trained with unlicensed data infringe copyright. There is a good chance that US courts will also reject claims of "fair use". Whatever the outcome, this will impact the entire field. Copyrighted works are in the training data of <em>all</em> major Generative AI models, including ChatGPT and AI models that generate music, not just the ones that make images.</p><p>Nonetheless, even if legal claims fail, there is a strong moral case that Generative AI profits from the work of uncompensated IP owners. Regulatory law might attempt to compensate them.</p><p>One possible regulatory solution is a compulsory licensing regime akin to the ones in the music industry. The music industry is already comfortable with them. The publishing industry is unafraid of AI and authors might readily accept such a scheme. Visual artists, however, might resist.</p><p>An alternative would be for the AI industry to fund a common training dataset and pay creators directly for the use of their work. This would completely eliminate IP claims against Generative AI models, and would create a locus for action over other concerns with AI. It would also put at least a little bit of money in the pockets of creators, who are rarely well compensated for their work.</p><p>Although such a body raises concerns about unfair barriers to market entry, it has benefits. An industry association can self-regulate in ways that governments cannot. For example, objectionable imagery may be legally protected from state action as free speech, but an industry body can forbid training AI models to produce pornography or graphic violence, and can restrict consumers' usage though the terms in their software licenses.</p><p>Furthermore, Generative AI models consume <a href="https://www.forbes.com/sites/robtoews/2020/06/17/deep-learnings-climate-change-problem/?ref=jina-ai-gmbh.ghost.io">an extraordinary amount of electricity to train</a>. An industry body can verify the environmental conduct of its members, and eliminate the temptation to train models in places where energy is cheap but environmentally unfriendly.</p><p>We want the emerging German AI sector to prosper and we need a stable, competitive, well-regulated environment. Uncertainty about these IP issues risks undermining our open source tech stacks and overturning our infant industry, causing an exodus to less scrupulous countries. Using these kinds of tools to take control of Generative AI's training data has promising prospects for regulating the industry in a way that continues to encourage German and European growth in the AI sector, relieving smaller firms like Jina AI of uncertainty while retaining a highly-competitive market environment.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Insights</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fgenerative-ai-as-ip%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. Navigating enterprise mazes &amp; startup vibes. Where's search headed next?</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">September 01, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/generativejina_mad_men_tv_serie_a_girl_is_looking_at_a_selectio_42a73443-5825-4394-a7ef-9c08294d29b6.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/fine-tuning-gpt-3-5-turbo-a-costly-mirage" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 25, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_modern_geometric_abstract_pattern_featuring_pu_24e4060e-dc76-4186-afb7-94d18d266b41.png" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">The Battle over Copyright in the Age of AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">New Generative AI technologies have important consequences for IP regulatory law, and how they are ultimately handled will strongly affect the development of this sector.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 14, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Originally published in German translation as <em><a href="https://background.tagesspiegel.de/digitalisierung/wie-mit-den-urheberrechtsdebatten-um-ki-umgegangen-werden-koennte?ref=jina-ai-gmbh.ghost.io">Wie mit den Urheberrechtsdebatten um KI umgegangen werden könnte</a></em> in <em>Tagesspiegel Background</em></div></div><p>In the last few years, Generative AI models have begun to produce strikingly fluent language, polished images, and appealing music from within themselves, arguably demonstrating autonomous creativity. Names like ChatGPT and Stable Diffusion are in the news. Jina AI is part an emerging German 'AI sector', encompassing a growing collection of startups that provide AI-centered software and services. New Generative AI technologies have important consequences for intellectual property (IP) law, and how they are ultimately handled will strongly affect the development of this sector.</p><p>There is some debate about whether AI output can be IP at all. There is little clear law on this subject. Copyright requires works to reflect <em>human</em> creativity, but in practice creating works using AI models requires significant human involvement. Humans construct textual "prompts" to stimulate image production, then modify those prompts based on the result, and select among multiple productions. AI-generated texts and music follow much the same pattern. This is comparable to the way a photographer takes a picture, and that has clear IP protections.</p><p>A bigger problem is the way Generative AI models are made. Large AI models are expensive to produce and come primarily from a few sources, particularly OpenAI (which is mostly controlled by Microsoft), Meta (Facebook/Instagram), and Alphabet (Google/DeepMind). Jina AI and other start-ups are highly dependent on access to them.</p><p>These models are trained to produce their outputs using large quantities of human-made written text, images, music, etc. and the most useful ones have all been trained using data taken from the Internet without the consent of their owners. Writers and musicians have not responded very strongly to this unauthorized use, but it has evoked strong reactions from visual artists. “AI art is theft” <a href="https://www.artstation.com/artwork/nEaqd4?ref=jina-ai-gmbh.ghost.io">has become a viral slogan</a>.</p><p>There are lawsuits challenging Generative AI underway in <a href="https://stablediffusionlitigation.com/?ref=jina-ai-gmbh.ghost.io">California</a> and the <a href="https://www.theverge.com/2023/1/17/23558516/ai-art-copyright-stable-diffusion-getty-images-lawsuit?ref=jina-ai-gmbh.ghost.io">UK</a>, and we can assume that there will be cases under EU law. These suits argue that Generative AI models are derivative works infringing on IP rights in their training data. Furthermore, they allege that anything created using those models is equally an infringing work, because neural network models merely store and then “recombine” the works of others. AI advocates challenge that characterization.</p><p>Under the laws of the US, UK, and countries inheriting their legal traditions, principles of “fair use” or “fair dealing” create broad but ambiguous exceptions to copyright, which might apply to AI training. But “fair use” has no equivalent in European and German law. Allowed exceptions to copyright are listed in <a href="https://lexparency.de/eu/32001L0029/ART_5/?ref=jina-ai-gmbh.ghost.io">Article 5 of the EU Copyright and Information Society Directive</a>, and contain nothing to help AI models. Since the 2013 <a href="https://hudoc.echr.coe.int/eng?ref=jina-ai-gmbh.ghost.io#%7B%22itemid%22:[%22001-115845%22]%7D">Ashby decision by the ECHR</a>, European courts have begun to find an implicit “fair use” doctrine in the European Convention’s guarantee of freedom of expression, but this is unlikely to apply to for-profit software.</p><p>We cannot predict the future, but it is possible, perhaps likely, that European courts will find that models trained with unlicensed data infringe copyright. There is a good chance that US courts will also reject claims of "fair use". Whatever the outcome, this will impact the entire field. Copyrighted works are in the training data of <em>all</em> major Generative AI models, including ChatGPT and AI models that generate music, not just the ones that make images.</p><p>Nonetheless, even if legal claims fail, there is a strong moral case that Generative AI profits from the work of uncompensated IP owners. Regulatory law might attempt to compensate them.</p><p>One possible regulatory solution is a compulsory licensing regime akin to the ones in the music industry. The music industry is already comfortable with them. The publishing industry is unafraid of AI and authors might readily accept such a scheme. Visual artists, however, might resist.</p><p>An alternative would be for the AI industry to fund a common training dataset and pay creators directly for the use of their work. This would completely eliminate IP claims against Generative AI models, and would create a locus for action over other concerns with AI. It would also put at least a little bit of money in the pockets of creators, who are rarely well compensated for their work.</p><p>Although such a body raises concerns about unfair barriers to market entry, it has benefits. An industry association can self-regulate in ways that governments cannot. For example, objectionable imagery may be legally protected from state action as free speech, but an industry body can forbid training AI models to produce pornography or graphic violence, and can restrict consumers' usage though the terms in their software licenses.</p><p>Furthermore, Generative AI models consume <a href="https://www.forbes.com/sites/robtoews/2020/06/17/deep-learnings-climate-change-problem/?ref=jina-ai-gmbh.ghost.io">an extraordinary amount of electricity to train</a>. An industry body can verify the environmental conduct of its members, and eliminate the temptation to train models in places where energy is cheap but environmentally unfriendly.</p><p>We want the emerging German AI sector to prosper and we need a stable, competitive, well-regulated environment. Uncertainty about these IP issues risks undermining our open source tech stacks and overturning our infant industry, causing an exodus to less scrupulous countries. Using these kinds of tools to take control of Generative AI's training data has promising prospects for regulating the industry in a way that continues to encourage German and European growth in the AI sector, relieving smaller firms like Jina AI of uncertainty while retaining a highly-competitive market environment.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Insights</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fgenerative-ai-as-ip%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. Navigating enterprise mazes &amp; startup vibes. Where's search headed next?</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">September 01, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/generativejina_mad_men_tv_serie_a_girl_is_looking_at_a_selectio_42a73443-5825-4394-a7ef-9c08294d29b6.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/fine-tuning-gpt-3-5-turbo-a-costly-mirage" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 25, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_modern_geometric_abstract_pattern_featuring_pu_24e4060e-dc76-4186-afb7-94d18d266b41.png" style="object-fit: cover; 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diff --git a/news/give-and-take-in-fdps-ai-geopolitics-panel/index.html b/news/give-and-take-in-fdps-ai-geopolitics-panel/index.html
index 27a40345e6e..3ec99e4978d 100644
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@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Give and Take in FDP's AI Geopolitics Panel</title><meta charset="utf-8"><meta name="title" content="Give and Take in FDP's AI Geopolitics Panel"><meta name="description" content="This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/give-and-take-in-fdps-ai-geopolitics-panel"><meta property="og:title" content="Give and Take in FDP's AI Geopolitics Panel"><meta property="og:description" content="This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/give-and-take-in-fdps-ai-geopolitics-panel"><meta property="twitter:title" content="Give and Take in FDP's AI Geopolitics Panel"><meta property="twitter:description" content="This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Give and Take in FDP's AI Geopolitics Panel</title><meta charset="utf-8"><meta name="title" content="Give and Take in FDP's AI Geopolitics Panel"><meta name="description" content="This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/give-and-take-in-fdps-ai-geopolitics-panel"><meta property="og:title" content="Give and Take in FDP's AI Geopolitics Panel"><meta property="og:description" content="This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/give-and-take-in-fdps-ai-geopolitics-panel"><meta property="twitter:title" content="Give and Take in FDP's AI Geopolitics Panel"><meta property="twitter:description" content="This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Give and Take in FDP's AI Geopolitics Panel</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 29, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The crisp air of Berlin in late November carried a unique vibrancy, especially in the bustling district of Prenzlauer Berg. As I weaved through the lively Christmas market outside the <a href="https://palais-kulturbrauerei.de/?ref=jina-ai-gmbh.ghost.io">Palais der Kulturbrauerei</a>, the scene was a microcosm of Berlin itself. Stalls adorned with twinkling lights offered an array of handmade trinkets and steaming treats, drawing in a crowd that was as diverse as the city's own character. Artists, both emerging and established, mingled with locals and tourists, their conversations a blend of German and a myriad of other languages, creating a tapestry of global influence and local charm. </p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/2831701259388_.pic.jpg" class="kg-image" alt="" width="1702" height="1276" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/2831701259388_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/2831701259388_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/2831701259388_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/2831701259388_.pic.jpg 1702w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Xmas market at Kulturbrauerei, a symbol of Berlin's industrial past and its cultural renaissance, was more than just a festive gathering. It was a reflection of the city's unique ethos - not striving to compete with the grandeur of Paris or the pace of Shanghai, but instead carving out its own identity, one that embraced its history while boldly facing the future.</span></figcaption></figure><p>As I approached the Palais, the sounds of the market slowly gave way to a more subdued atmosphere. Inside, the venue buzzed with the energy of intellectuals and policymakers, all gathered to dissect and debate the future of EU's AI. </p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://crm.fdpbt.de/termin/ai-revolution-wie-kuenstliche-intelligenz-unsere-welt-veraendert?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Zustimmung zu Cookies | FDP-Fraktion im Bundestag</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://crm.fdpbt.de/themes/custom/uv_fdpbt_theme/favicon.ico" alt=""><span class="kg-bookmark-author">FDP-Fraktion im Bundestag</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://crm.fdpbt.de/termin/themes/custom/uv_fdpbt_theme/images/logo.svg" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">The full program of this FDP event is available </span><a href="https://crm.fdpbt.de/sites/default/files/2023-11/231128%20FDPBT%20KI%20Programm.pdf?ref=jina-ai-gmbh.ghost.io"><span style="white-space: pre-wrap;">here</span></a><span style="white-space: pre-wrap;">.</span></p></figcaption></figure><p>Despite my role as a panelist and my years of experience in AI, spanning from Tencent AI to my own AI startups, I couldn't shake a sense of skepticism. Was my presence here truly impactful? Would the discussions tonight resonate beyond these walls? </p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/2851701259389_.pic.jpg" class="kg-image" alt="" width="1702" height="1276" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/2851701259389_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/2851701259389_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/2851701259389_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/2851701259389_.pic.jpg 1702w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">As the conversation unfolded, my thoughts turned towards what I would share with the audience. My answers, crafted from years of navigating the complex landscapes of AI in two very different worlds, were ready.</span></figcaption></figure><p>The air was thick with expectations as the panelists, including myself, took our seats. I was curious to hear the perspectives of my fellow speakers and the FDP's stance on these pressing issues. While I harbored doubts about the overall impact of such events, a part of me remained hopeful. Perhaps, through these discussions, we could foster a deeper understanding between Europe and China, bridging gaps in perception and strategy. </p><p>Below, you'll find my responses to the questions posed during the panel. Some answers have been expanded and further refined during my subsequent reflections.</p><h2 id="strategies-and-positions-of-major-powers">Strategies and positions of major powers</h2><h3 id="q-how-do-the-strategies-and-positions-of-the-us-china-and-the-eu-differ-in-achieving-global-leadership-in-ai">Q: How do the strategies and positions of the US, China and the EU differ in achieving global leadership in AI?</h3><p><strong>Han:</strong> In discussing how the strategies and positions of the US, China, and the EU differ in achieving global leadership in AI, I would start by highlighting that the US primarily drives innovation through the private sector with substantial funding and the robust Silicon Valley ecosystem. In contrast, China adopts a <strong>state-driven </strong>approach, utilizing <strong>large-scale</strong> data and focusing on <strong>rapid implementation</strong> of AI technologies. The EU, on the other hand, places a strong emphasis on ethical AI, developing regulatory frameworks, and maintaining a focus on human-centric AI.</p><p>Diving deeper into China's approach, we see ambitious state-driven initiatives, with the goal of becoming an AI world leader by 2030. This is rooted in a legacy of central planning and a national capitalism ethos. There's a significant emphasis on indigenous innovation, mirroring European approaches, but with a distinct focus on technological sovereignty. Talent development is also key, as evidenced by China's "Thousand Talents" plan, which aims to bolster AI expertise.</p><p>Large-scale data usage in China is a critical factor, with vast data repositories enhancing algorithm accuracy. This is supported by multidimensional datasets, particularly rich user data derived from diverse smartphone activities. When it comes to implementation, China has developed 79 large language models, each with over 1 billion parameters, showing remarkable progress. The focus here is on practical application, transitioning from discovery to a strong execution in "1 to n" innovation.</p><p>In contrast to the US, which focuses more on discovery, China excels in the implementation and application of AI technologies. This difference highlights a unique approach where China leverages its strengths in rapid development and practical application of AI solutions.</p><h2 id="cooperation-versus-regulation">Cooperation versus regulation</h2><h3 id="q-should-countries-limit-or-expand-their-collaborations-in-ai-research-due-to-geopolitical-rivalries">Q: Should countries limit or expand their collaborations in AI research due to geopolitical rivalries?</h3><p><strong>Han: </strong>When considering whether countries should limit or expand their collaborations in AI research due to geopolitical rivalries, it's tempting to adopt an old cold-war mindset. It's easy to see why the US might be hesitant to collaborate: they don't want to share their technological leadership, have security concerns, face economic competition, and grapple with ideological differences. In German, there's a saying "Wer oben ist, will oben bleiben," meaning "Those who are on top want to stay on top."</p><p>However, collaboration is the only rational way to accelerate AI development. The United States is known for its advanced AI algorithms and strong research capabilities, while China boasts vast data resources essential for training AI models.</p><p>The ideal scenario would involve collaboration between the US and China, specializing in AI excelling in efficiency and scalability, but we must be mindful of potential issues with global trust and acceptance due to weaker ethical and privacy safeguards. Similarly, collaboration between the US and the EU could yield technologically sophisticated, ethically compliant AI, but might struggle with data diversity and comprehensiveness. China and the EU could focus on ethically-grounded AI with rich data integration but might lag in incorporating the latest AI innovations. The best outcome would be a balanced AI, leading in innovation, ethics, and data scope, overcoming individual limitations.</p><p>A balanced approach is necessary, considering geopolitical tensions and concerns about data privacy, security, and ethical use of AI.</p><p>However, the reason China might be reluctant to open its arms fully to US AI is due to a focus on cultural and political autonomy. The Chinese emphasis on indigenous innovation is partly driven by concerns over cultural influences and values being exported through U.S.-dominated AI, especially in terms of political influence.</p><p>Information sovereignty is crucial for ensuring that AI development aligns with national values and interests, avoiding external cultural or political influences.</p><p>A true story illustrates this point: Post-WWII, Japan was heavily influenced by American ideas, including the notion that a bread diet was superior to rice for health. This belief, supported by some Japanese scholars and the government, led to significant changes in dietary habits in Japan, decreasing the country's self-sufficiency in food and increasing reliance on imports from the United States. This example shows how foreign influence can profoundly impact national culture and practices.</p><h3 id="q-should-the-eu-work-even-more-closely-with-strategic-partners-like-the-us">Q: Should the EU work even more closely with strategic partners like the US?</h3><p><strong>Han: </strong>Understanding the EU's inclination to collaborate with the US in AI is straightforward, as the US is a leader in AI innovation, which can complement the EU's strengths in regulatory frameworks. Additionally, the EU and US often share common values such as democracy, human rights, and privacy, aligning closely in AI development.</p><p>However, working with China also presents significant advantages. China ranks in the top 3 globally for AI vibrancy, as per the Stanford AI Index. Its AI market is projected to exceed $26.7 billion by 2026, offering the largest real-world testing ground for AI innovations, invaluable for global scalability. The sector diversity in China, with strong AI adoption in finance, retail, and high tech, and leadership in consumer AI apps, is noteworthy. Additionally, the automotive AI potential in China, being the world's largest auto market, presents significant opportunities, especially in autonomous vehicles and fleet management, with an estimated $380 billion economic value by 2030.</p><h2 id="challenges-and-opportunities-for-the-eu">Challenges and opportunities for the EU</h2><h3 id="q-compared-to-individual-state-actors-such-as-the-us-and-china-how-can-the-eu-maintain-its-competitiveness">Q: Compared to individual state actors such as the US and China, how can the EU maintain its competitiveness?</h3><p><strong>Han: </strong>The EU faces significant challenges in maintaining competitiveness with individual technological powerhouses like the US and China. One of the main hurdles is technological lag, with European companies generally underperforming compared to their US counterparts, especially in terms of growth and R&amp;D investment. This is reflective of Europe's lag in the last technology revolution, notably in ICT and disruptive innovations.</p><p>Moreover, there are stark investment disparities in key future technologies such as quantum computing, 5G, and AI. For instance, in AI, Europe only captured about 12% of external funding between 2015 and 2020, compared to 40% by the US and 32% by Asia, including China. This gap in investment is a significant factor contributing to the EU's challenges in maintaining technological competitiveness.</p><h3 id="q-does-the-eu-offer-any-specific-advantages">Q: Does the EU offer any specific advantages?</h3><p><strong>Han: </strong>The EU indeed offers specific advantages in the realm of AI. Europe boasts a rich talent pool and a strong tradition in theoretical AI research and mathematics. Notable European AI researchers include Yoshua Bengio from France/Canada, a leader in deep learning, Jürgen Schmidhuber from Germany, known for his work on neural networks, and Max Welling, a Dutch computer scientist recognized for his contributions in machine learning and AI. Esteemed institutions like the Max Planck Institutes in Germany and INRIA in France have been at the forefront of significant AI advancements.</p><p>Europe is often seen as the 'Switzerland of AI politics,' maintaining a neutral position amid US-China tech tensions. This neutrality is strategic, enabling Europe to focus on ethical AI development and collaborate innovatively without getting entangled in geopolitical struggles.</p><p>The EU's approach is characterized by the motto, "In Europe, we don't just have history in our museums; we also make history in our AI labs." This reflects Europe's unique position in observing and learning from the technological race between the 'eagles' (US) and 'dragons' (China), emphasizing the importance of foresight in addition to speed.</p><p>In conclusion, AI is a transformative force comparable to the Industrial Revolution. Europe's stance encourages teamwork, openness, and curiosity. If not leveraged, there's a risk of turning this revolutionary era into a missed opportunity, relegating Europe to a spectator's role in this global race.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fgive-and-take-in-fdps-ai-geopolitics-panel%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-ap-virtual-ticket-giveaway-for-pycon-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina AI Virtual Ticket Giveaway for PyCon 2023 Online</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina AI's giving away PyCon US Online passes. Deadline April 10.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/avatar.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jocelyn Matthews</div><div class="q-item__label q-item__label--caption text-caption">April 03, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/virtual-ticket-promo.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 29, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The crisp air of Berlin in late November carried a unique vibrancy, especially in the bustling district of Prenzlauer Berg. As I weaved through the lively Christmas market outside the <a href="https://palais-kulturbrauerei.de/?ref=jina-ai-gmbh.ghost.io">Palais der Kulturbrauerei</a>, the scene was a microcosm of Berlin itself. Stalls adorned with twinkling lights offered an array of handmade trinkets and steaming treats, drawing in a crowd that was as diverse as the city's own character. Artists, both emerging and established, mingled with locals and tourists, their conversations a blend of German and a myriad of other languages, creating a tapestry of global influence and local charm. </p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/2831701259388_.pic.jpg" class="kg-image" alt="" width="1702" height="1276" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/2831701259388_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/2831701259388_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/2831701259388_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/2831701259388_.pic.jpg 1702w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Xmas market at Kulturbrauerei, a symbol of Berlin's industrial past and its cultural renaissance, was more than just a festive gathering. It was a reflection of the city's unique ethos - not striving to compete with the grandeur of Paris or the pace of Shanghai, but instead carving out its own identity, one that embraced its history while boldly facing the future.</span></figcaption></figure><p>As I approached the Palais, the sounds of the market slowly gave way to a more subdued atmosphere. Inside, the venue buzzed with the energy of intellectuals and policymakers, all gathered to dissect and debate the future of EU's AI. </p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://crm.fdpbt.de/termin/ai-revolution-wie-kuenstliche-intelligenz-unsere-welt-veraendert?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Zustimmung zu Cookies | FDP-Fraktion im Bundestag</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://crm.fdpbt.de/themes/custom/uv_fdpbt_theme/favicon.ico" alt=""><span class="kg-bookmark-author">FDP-Fraktion im Bundestag</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://crm.fdpbt.de/termin/themes/custom/uv_fdpbt_theme/images/logo.svg" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">The full program of this FDP event is available </span><a href="https://crm.fdpbt.de/sites/default/files/2023-11/231128%20FDPBT%20KI%20Programm.pdf?ref=jina-ai-gmbh.ghost.io"><span style="white-space: pre-wrap;">here</span></a><span style="white-space: pre-wrap;">.</span></p></figcaption></figure><p>Despite my role as a panelist and my years of experience in AI, spanning from Tencent AI to my own AI startups, I couldn't shake a sense of skepticism. Was my presence here truly impactful? Would the discussions tonight resonate beyond these walls? </p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/2851701259389_.pic.jpg" class="kg-image" alt="" width="1702" height="1276" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/2851701259389_.pic.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/2851701259389_.pic.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/2851701259389_.pic.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/2851701259389_.pic.jpg 1702w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">As the conversation unfolded, my thoughts turned towards what I would share with the audience. My answers, crafted from years of navigating the complex landscapes of AI in two very different worlds, were ready.</span></figcaption></figure><p>The air was thick with expectations as the panelists, including myself, took our seats. I was curious to hear the perspectives of my fellow speakers and the FDP's stance on these pressing issues. While I harbored doubts about the overall impact of such events, a part of me remained hopeful. Perhaps, through these discussions, we could foster a deeper understanding between Europe and China, bridging gaps in perception and strategy. </p><p>Below, you'll find my responses to the questions posed during the panel. Some answers have been expanded and further refined during my subsequent reflections.</p><h2 id="strategies-and-positions-of-major-powers">Strategies and positions of major powers</h2><h3 id="q-how-do-the-strategies-and-positions-of-the-us-china-and-the-eu-differ-in-achieving-global-leadership-in-ai">Q: How do the strategies and positions of the US, China and the EU differ in achieving global leadership in AI?</h3><p><strong>Han:</strong> In discussing how the strategies and positions of the US, China, and the EU differ in achieving global leadership in AI, I would start by highlighting that the US primarily drives innovation through the private sector with substantial funding and the robust Silicon Valley ecosystem. In contrast, China adopts a <strong>state-driven </strong>approach, utilizing <strong>large-scale</strong> data and focusing on <strong>rapid implementation</strong> of AI technologies. The EU, on the other hand, places a strong emphasis on ethical AI, developing regulatory frameworks, and maintaining a focus on human-centric AI.</p><p>Diving deeper into China's approach, we see ambitious state-driven initiatives, with the goal of becoming an AI world leader by 2030. This is rooted in a legacy of central planning and a national capitalism ethos. There's a significant emphasis on indigenous innovation, mirroring European approaches, but with a distinct focus on technological sovereignty. Talent development is also key, as evidenced by China's "Thousand Talents" plan, which aims to bolster AI expertise.</p><p>Large-scale data usage in China is a critical factor, with vast data repositories enhancing algorithm accuracy. This is supported by multidimensional datasets, particularly rich user data derived from diverse smartphone activities. When it comes to implementation, China has developed 79 large language models, each with over 1 billion parameters, showing remarkable progress. The focus here is on practical application, transitioning from discovery to a strong execution in "1 to n" innovation.</p><p>In contrast to the US, which focuses more on discovery, China excels in the implementation and application of AI technologies. This difference highlights a unique approach where China leverages its strengths in rapid development and practical application of AI solutions.</p><h2 id="cooperation-versus-regulation">Cooperation versus regulation</h2><h3 id="q-should-countries-limit-or-expand-their-collaborations-in-ai-research-due-to-geopolitical-rivalries">Q: Should countries limit or expand their collaborations in AI research due to geopolitical rivalries?</h3><p><strong>Han: </strong>When considering whether countries should limit or expand their collaborations in AI research due to geopolitical rivalries, it's tempting to adopt an old cold-war mindset. It's easy to see why the US might be hesitant to collaborate: they don't want to share their technological leadership, have security concerns, face economic competition, and grapple with ideological differences. In German, there's a saying "Wer oben ist, will oben bleiben," meaning "Those who are on top want to stay on top."</p><p>However, collaboration is the only rational way to accelerate AI development. The United States is known for its advanced AI algorithms and strong research capabilities, while China boasts vast data resources essential for training AI models.</p><p>The ideal scenario would involve collaboration between the US and China, specializing in AI excelling in efficiency and scalability, but we must be mindful of potential issues with global trust and acceptance due to weaker ethical and privacy safeguards. Similarly, collaboration between the US and the EU could yield technologically sophisticated, ethically compliant AI, but might struggle with data diversity and comprehensiveness. China and the EU could focus on ethically-grounded AI with rich data integration but might lag in incorporating the latest AI innovations. The best outcome would be a balanced AI, leading in innovation, ethics, and data scope, overcoming individual limitations.</p><p>A balanced approach is necessary, considering geopolitical tensions and concerns about data privacy, security, and ethical use of AI.</p><p>However, the reason China might be reluctant to open its arms fully to US AI is due to a focus on cultural and political autonomy. The Chinese emphasis on indigenous innovation is partly driven by concerns over cultural influences and values being exported through U.S.-dominated AI, especially in terms of political influence.</p><p>Information sovereignty is crucial for ensuring that AI development aligns with national values and interests, avoiding external cultural or political influences.</p><p>A true story illustrates this point: Post-WWII, Japan was heavily influenced by American ideas, including the notion that a bread diet was superior to rice for health. This belief, supported by some Japanese scholars and the government, led to significant changes in dietary habits in Japan, decreasing the country's self-sufficiency in food and increasing reliance on imports from the United States. This example shows how foreign influence can profoundly impact national culture and practices.</p><h3 id="q-should-the-eu-work-even-more-closely-with-strategic-partners-like-the-us">Q: Should the EU work even more closely with strategic partners like the US?</h3><p><strong>Han: </strong>Understanding the EU's inclination to collaborate with the US in AI is straightforward, as the US is a leader in AI innovation, which can complement the EU's strengths in regulatory frameworks. Additionally, the EU and US often share common values such as democracy, human rights, and privacy, aligning closely in AI development.</p><p>However, working with China also presents significant advantages. China ranks in the top 3 globally for AI vibrancy, as per the Stanford AI Index. Its AI market is projected to exceed $26.7 billion by 2026, offering the largest real-world testing ground for AI innovations, invaluable for global scalability. The sector diversity in China, with strong AI adoption in finance, retail, and high tech, and leadership in consumer AI apps, is noteworthy. Additionally, the automotive AI potential in China, being the world's largest auto market, presents significant opportunities, especially in autonomous vehicles and fleet management, with an estimated $380 billion economic value by 2030.</p><h2 id="challenges-and-opportunities-for-the-eu">Challenges and opportunities for the EU</h2><h3 id="q-compared-to-individual-state-actors-such-as-the-us-and-china-how-can-the-eu-maintain-its-competitiveness">Q: Compared to individual state actors such as the US and China, how can the EU maintain its competitiveness?</h3><p><strong>Han: </strong>The EU faces significant challenges in maintaining competitiveness with individual technological powerhouses like the US and China. One of the main hurdles is technological lag, with European companies generally underperforming compared to their US counterparts, especially in terms of growth and R&amp;D investment. This is reflective of Europe's lag in the last technology revolution, notably in ICT and disruptive innovations.</p><p>Moreover, there are stark investment disparities in key future technologies such as quantum computing, 5G, and AI. For instance, in AI, Europe only captured about 12% of external funding between 2015 and 2020, compared to 40% by the US and 32% by Asia, including China. This gap in investment is a significant factor contributing to the EU's challenges in maintaining technological competitiveness.</p><h3 id="q-does-the-eu-offer-any-specific-advantages">Q: Does the EU offer any specific advantages?</h3><p><strong>Han: </strong>The EU indeed offers specific advantages in the realm of AI. Europe boasts a rich talent pool and a strong tradition in theoretical AI research and mathematics. Notable European AI researchers include Yoshua Bengio from France/Canada, a leader in deep learning, Jürgen Schmidhuber from Germany, known for his work on neural networks, and Max Welling, a Dutch computer scientist recognized for his contributions in machine learning and AI. Esteemed institutions like the Max Planck Institutes in Germany and INRIA in France have been at the forefront of significant AI advancements.</p><p>Europe is often seen as the 'Switzerland of AI politics,' maintaining a neutral position amid US-China tech tensions. This neutrality is strategic, enabling Europe to focus on ethical AI development and collaborate innovatively without getting entangled in geopolitical struggles.</p><p>The EU's approach is characterized by the motto, "In Europe, we don't just have history in our museums; we also make history in our AI labs." This reflects Europe's unique position in observing and learning from the technological race between the 'eagles' (US) and 'dragons' (China), emphasizing the importance of foresight in addition to speed.</p><p>In conclusion, AI is a transformative force comparable to the Industrial Revolution. Europe's stance encourages teamwork, openness, and curiosity. If not leveraged, there's a risk of turning this revolutionary era into a missed opportunity, relegating Europe to a spectator's role in this global race.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fgive-and-take-in-fdps-ai-geopolitics-panel%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Gold Retriever: Let ChatGPT talk to your data</title><meta charset="utf-8"><meta name="title" content="Gold Retriever: Let ChatGPT talk to your data"><meta name="description" content="With Gold Retriever, you can easily enable ChatGPT to store, retrieve, and reason with your data in just a few steps"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/gold-retriever-let-chatgpt-talk-to-your-data"><meta property="og:title" content="Gold Retriever: Let ChatGPT talk to your data"><meta property="og:description" content="With Gold Retriever, you can easily enable ChatGPT to store, retrieve, and reason with your data in just a few steps"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Blog-images--7--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/gold-retriever-let-chatgpt-talk-to-your-data"><meta property="twitter:title" content="Gold Retriever: Let ChatGPT talk to your data"><meta property="twitter:description" content="With Gold Retriever, you can easily enable ChatGPT to store, retrieve, and reason with your data in just a few steps"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Blog-images--7--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Gold Retriever: Let ChatGPT talk to your data</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With Gold Retriever, you can easily enable ChatGPT to store, retrieve, and reason with your data in just a few steps</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 75.6836%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/IMG-1054.PNG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Saba Sturua, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 23, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the realm of AI, language models like ChatGPT have revolutionized how we interact with machines. However, as efficient as these models are, they encounter certain limitations. One key hurdle is their inability to seamlessly integrate and reason with new, personalized, or up-to-date data, which is often critical for users.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/image-6.png" class="kg-image" alt="" width="932" height="587" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/image-6.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/image-6.png 932w" sizes="(min-width: 720px) 720px"><figcaption>Out-of-date data</figcaption></figure><p>Language models have a knowledge cut-off, beyond which they aren't informed about new world events, scientific discoveries, or technological breakthroughs. They may also lack depth in specific knowledge domains, struggle with real-time data, and produce outputs that might need fact-checking for accuracy. Additionally, users desire AI interactions tailored to their profiles and control over their data, which requires the AI to access user-specific data.</p><p>Enter "Gold Retriever", a powerful open-source tool powered by <a href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io">Jina</a> and <a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io">DocArray</a>, that addresses these very needs.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/GoldRetriever?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/GoldRetriever: Create and host retrieval plugins for ChatGPT in one click</div><div class="kg-bookmark-description">Create and host retrieval plugins for ChatGPT in one click - GitHub - jina-ai/GoldRetriever: Create and host retrieval plugins for ChatGPT in one click</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/621363017/b2bbcea2-ccf0-4597-ae30-0b168212a9fb" alt=""></div></a></figure><p>It equips users to create custom plugins that enable ChatGPT to interact with their data, overcoming inherent limitations. Gold Retriever acts as a bridge linking ChatGPT with the vast and dynamic world of data, making AI interactions more meaningful, accurate, and personal.</p><h3 id="gold-retriever-in-action-study-assistant">Gold Retriever in Action: Study Assistant</h3><p>To better illustrate how Gold Retriever works, let's consider a practical scenario. Imagine you're a student seeking assistance from ChatGPT with your coursework. However, your course materials exceed ChatGPT's prompt limit, preventing you from getting the help you need. That's exactly where Gold Retriever comes in handy.</p><p>In this example, we'll use resources from MIT's open course - <a href="https://ocw.mit.edu/courses/1-018j-ecology-i-the-earth-system-fall-2009/?ref=jina-ai-gmbh.ghost.io">Ecology I: The Earth System</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://ocw.mit.edu/courses/1-018j-ecology-i-the-earth-system-fall-2009/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Ecology I: The Earth System | Civil and Environmental Engineering | MIT OpenCourseWare</div><div class="kg-bookmark-description">We will cover fundamentals of ecology, considering Earth as an integrated dynamic system. Topics include coevolution of the biosphere, geosphere, atmosphere and oceans; photosynthesis and respiration; the hydrologic, carbon and nitrogen cycles. We will examine the flow of energy and materials throug…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ocw.mit.edu/favicon.ico" alt=""><span class="kg-bookmark-author">MIT OpenCourseWare</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://ocw.mit.edu/courses/1-018j-ecology-i-the-earth-system-fall-2009/6fb954a330c3fe950f2305df362b755a_1-018jf09.jpg" alt=""></div></a></figure><p>The first step is to gather all relevant text files in one directory, which will serve as your data source. Next, you'll need to create a Gold Retriever plugin. Here's how:</p><p>Install Gold Retriever via pip with the command:</p><pre><code class="language-shell hljs">pip install goldretriever</code></pre><p>Now, deploy a plugin providing your OpenAI key:</p><pre><code class="language-shell hljs">goldretriever deploy --key &lt;your openai key&gt;</code></pre><p>After deployment, make a note of the "Gateway (HTTP)" URL and the Bearer token, as you'll need them to incorporate the plugin into ChatGPT.</p><pre><code class="language-shell hljs">╭──────────────────────── 🎉 Flow is available! ────────────────────────╮
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Gold Retriever: Let ChatGPT talk to your data</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With Gold Retriever, you can easily enable ChatGPT to store, retrieve, and reason with your data in just a few steps</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 75.6836%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/IMG-1054.PNG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Saba Sturua, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 23, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the realm of AI, language models like ChatGPT have revolutionized how we interact with machines. However, as efficient as these models are, they encounter certain limitations. One key hurdle is their inability to seamlessly integrate and reason with new, personalized, or up-to-date data, which is often critical for users.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/image-6.png" class="kg-image" alt="" width="932" height="587" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/image-6.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/image-6.png 932w" sizes="(min-width: 720px) 720px"><figcaption>Out-of-date data</figcaption></figure><p>Language models have a knowledge cut-off, beyond which they aren't informed about new world events, scientific discoveries, or technological breakthroughs. They may also lack depth in specific knowledge domains, struggle with real-time data, and produce outputs that might need fact-checking for accuracy. Additionally, users desire AI interactions tailored to their profiles and control over their data, which requires the AI to access user-specific data.</p><p>Enter "Gold Retriever", a powerful open-source tool powered by <a href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io">Jina</a> and <a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io">DocArray</a>, that addresses these very needs.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/GoldRetriever?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/GoldRetriever: Create and host retrieval plugins for ChatGPT in one click</div><div class="kg-bookmark-description">Create and host retrieval plugins for ChatGPT in one click - GitHub - jina-ai/GoldRetriever: Create and host retrieval plugins for ChatGPT in one click</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/621363017/b2bbcea2-ccf0-4597-ae30-0b168212a9fb" alt=""></div></a></figure><p>It equips users to create custom plugins that enable ChatGPT to interact with their data, overcoming inherent limitations. Gold Retriever acts as a bridge linking ChatGPT with the vast and dynamic world of data, making AI interactions more meaningful, accurate, and personal.</p><h3 id="gold-retriever-in-action-study-assistant">Gold Retriever in Action: Study Assistant</h3><p>To better illustrate how Gold Retriever works, let's consider a practical scenario. Imagine you're a student seeking assistance from ChatGPT with your coursework. However, your course materials exceed ChatGPT's prompt limit, preventing you from getting the help you need. That's exactly where Gold Retriever comes in handy.</p><p>In this example, we'll use resources from MIT's open course - <a href="https://ocw.mit.edu/courses/1-018j-ecology-i-the-earth-system-fall-2009/?ref=jina-ai-gmbh.ghost.io">Ecology I: The Earth System</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://ocw.mit.edu/courses/1-018j-ecology-i-the-earth-system-fall-2009/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Ecology I: The Earth System | Civil and Environmental Engineering | MIT OpenCourseWare</div><div class="kg-bookmark-description">We will cover fundamentals of ecology, considering Earth as an integrated dynamic system. Topics include coevolution of the biosphere, geosphere, atmosphere and oceans; photosynthesis and respiration; the hydrologic, carbon and nitrogen cycles. We will examine the flow of energy and materials throug…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ocw.mit.edu/favicon.ico" alt=""><span class="kg-bookmark-author">MIT OpenCourseWare</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://ocw.mit.edu/courses/1-018j-ecology-i-the-earth-system-fall-2009/6fb954a330c3fe950f2305df362b755a_1-018jf09.jpg" alt=""></div></a></figure><p>The first step is to gather all relevant text files in one directory, which will serve as your data source. Next, you'll need to create a Gold Retriever plugin. Here's how:</p><p>Install Gold Retriever via pip with the command:</p><pre><code class="language-shell hljs">pip install goldretriever</code></pre><p>Now, deploy a plugin providing your OpenAI key:</p><pre><code class="language-shell hljs">goldretriever deploy --key &lt;your openai key&gt;</code></pre><p>After deployment, make a note of the "Gateway (HTTP)" URL and the Bearer token, as you'll need them to incorporate the plugin into ChatGPT.</p><pre><code class="language-shell hljs">╭──────────────────────── 🎉 Flow is available! ────────────────────────╮
 │                                                                       │
 │   ID               retrieval-plugin-&lt;plugin id&gt;                       │
 │   Gateway (Http)   https://retrieval-plugin-&lt;plugin id&gt;.wolf.jina.ai  │
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@@ -4,9 +4,9 @@
 
 Now graph embeddings vectorize nodes. Distill graphs into geometry. Embeddings work magic. AI devours graphs."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_purple_and_green_network_graphs_on_purple_backgr_8f3f4431-5317-4b2e-a2b7-44e206c14b26.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/graph-embedding-101-unraveling-the-magic-of-relational-data"><meta property="twitter:title" content="Graph Embedding 101: Unraveling the Magic of Relational Data"><meta property="twitter:description" content="Graphs → everywhere. Social. Knowledge. Molecular. Critical infrastructure. Complex hairy ball visuals. Hard for machines.
 
-Now graph embeddings vectorize nodes. Distill graphs into geometry. Embeddings work magic. AI devours graphs."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_purple_and_green_network_graphs_on_purple_backgr_8f3f4431-5317-4b2e-a2b7-44e206c14b26.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+Now graph embeddings vectorize nodes. Distill graphs into geometry. Embeddings work magic. AI devours graphs."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_purple_and_green_network_graphs_on_purple_backgr_8f3f4431-5317-4b2e-a2b7-44e206c14b26.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Graphs → everywhere. Social. Knowledge. Molecular. Critical infrastructure. Complex hairy ball visuals. Hard for machines.
 
-Now graph embeddings vectorize nodes. Distill graphs into geometry. Embeddings work magic. AI devours graphs.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 29, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Graphs are everywhere, from the intricate web of neurons in our brains to the sprawling networks of social media platforms. But how do we translate these complex structures into a language that AI models can understand? </p><p>In this post, we'll delve deep into the world of graph embeddings, drawing parallels with familiar concepts, and exploring the challenges and potential of this transformative technique.</p><h2 id="what-is-graph-embedding">What is Graph Embedding?</h2><p>In short, <strong>graph embedding vectorizes nodes.</strong></p><p>Imagine a vast, sprawling city - a tangled web of streets and junctions. Each intersection is a point of interest, and each road between them is a connection. Now picture looking down on this city from above - you see a complex mess of intersections and streets spreading out in all directions.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail.png" class="kg-image" alt="" width="1280" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail.png 1280w" sizes="(min-width: 720px) 720px"></figure><p>This city is like a graph - a set of nodes (the junctions) and edges between them (the streets). Handling very large, complex graphs tends to be computationally demanding, just as navigating a vast city can be overwhelming.</p><p>This is where graph embedding comes in - it takes this vast graph and simplifies it down into a simpler space as if we squeeze all the myriad streets and intersections down into basic proximity on a 2D map. Nodes highly interconnected end up clustered together, just as related city sights group together on a tourist map. Each node gets converted into a single point on a map, represented by coordinates in a lower-dimensional space. Nearby nodes in the original graph end up close together on the map. Far away nodes end up far apart.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail--1-.png" class="kg-image" alt="" width="1280" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail--1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail--1-.png 1280w" sizes="(min-width: 720px) 720px"></figure><p>So in summary, graph embedding takes a hairball graph and simplifies it down into a tidy map - a vector space that preserves the structure and relationships from the original graph. This is mathematically equivalent to <a href="https://arxiv.org/abs/2307.11224?ref=jina-ai-gmbh.ghost.io">sentence embeddings</a> applied to graphs instead of sentences. In essence, <strong>graph embedding vectorizes nodes like sentence embeddings vectorize sentences.</strong> It massages graphs into a format friendly for machine learning models.</p><h2 id="formal-definition-of-graph-embeddings">Formal Definition of Graph Embeddings</h2><p>Formally, a graph $G = (V, E)$ is a representation of relationships using nodes $V$ and edges $E$. Now, navigating a city can be overwhelming due to its vastness. Similarly, handling large graphs can be computationally challenging. Enter graph embedding.</p><p>Graph embedding is the art of translating this city (or graph) into a simplified map, where each point of interest (or node) is represented by a coordinate in a lower-dimensional space. Mathematically, it's about learning a function $f: v_i → y_i ∈ R^d$ that maps each node $v_i$ to a vector $y_i$ in a space $R^d$ where $d$ is much smaller than $|V|$.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-15.png" class="kg-image" alt="" width="557" height="326"><figcaption>Source: TigerGraph - Graph Embedding: Understanding Graph Embedding AlgorithmsS</figcaption></figure><h2 id="why-is-graph-embedding-a-game-changer">Why is Graph Embedding a Game-Changer?</h2><p>From predicting potential friendships on social media to visualizing intricate datasets, graph embeddings are proving invaluable. They're pivotal in node classification tasks, link predictions, and even in clustering nodes with similar properties. Moreover, as we venture into the realm of multimodal AI, where different types of data converge, graph embeddings can serve as a bridge, connecting structured data with unstructured data.</p><ol><li><strong>Machine Learning Compatibility</strong>: Traditional ML models, from linear regressors to deep neural networks, thrive on numerical data. Graph embeddings translate the intricate relationships of a graph into a numerical format, making them digestible for these models.</li><li><strong>Preserving Topology and Features</strong>: A well-crafted graph embedding retains the original graph's structure and node features. <a href="https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/40839.pdf?ref=jina-ai-gmbh.ghost.io">This dual preservation is a challenge that many earlier methods struggled with</a>.</li><li><strong>Dimensionality Reduction</strong>: Instead of grappling with a dimension for every node, we can now work in a much-reduced space, often just 50-1000 dimensions. This simplification is a boon for computational efficiency.</li><li><strong>Unearthing Latent Patterns</strong>: Beyond the explicit, graph embeddings can tease out hidden relationships, offering insights that might not be immediately apparent in the original graph.</li></ol><h2 id="how-to-compute-graph-embeddings">How to Compute Graph Embeddings?</h2><p>Graph embedding techniques are as diverse as the graphs they seek to represent. However, most can be bucketed into a few broad categories:</p><ul><li><strong>Matrix Factorization</strong>: Techniques like HOPE and Laplacian Eigenmaps revolve around factorizing the graph's adjacency matrix <code>A</code>. For instance, HOPE employs a generalized SVD to approximate <code>A</code> as <code>Y_s Y_t^T</code>, extracting the embedding <code>Y</code> in the process.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://zw-zhang.github.io/publication/2016-08-Asymmetric-Transitivity-Preserving-Graph-Embedding?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Asymmetric Transitivity Preserving Graph Embedding</div><div class="kg-bookmark-description">Key words: graph embedding, asymmetric transitivity, Generalized SVD (GSVD)</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://zw-zhang.github.io/images/android-chrome-192x192.png?v=M44lzPylqQ" alt=""><span class="kg-bookmark-author">Ziwei Zhang</span><span class="kg-bookmark-publisher">Email</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://zw-zhang.github.io/images/profile-photo.jpg" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://proceedings.neurips.cc/paper_files/paper/2001/hash/f106b7f99d2cb30c3db1c3cc0fde9ccb-Abstract.html?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://proceedings.neurips.cc/favicon.ico" alt=""><span class="kg-bookmark-author">NeurIPS Proceedings</span></div></div></a></figure><ul><li><strong>Random Walks</strong>: Picture a drunken walk through our earlier city analogy, meandering through landmarks. Methods like DeepWalk and node2vec use such random walks to capture the essence of a graph. These walks are then fed to models akin to Word2Vec to derive the embeddings.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/1403.6652?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">DeepWalk: Online Learning of Social Representations</div><div class="kg-bookmark-description">We present DeepWalk, a novel approach for learning latent representations ofvertices in a network. These latent representations encode social relations ina continuous vector space, which is easily exploited by statistical models.DeepWalk generalizes recent advancements in language modeling and un…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Bryan Perozzi</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/1607.00653?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">node2vec: Scalable Feature Learning for Networks</div><div class="kg-bookmark-description">Prediction tasks over nodes and edges in networks require careful effort inengineering features used by learning algorithms. Recent research in thebroader field of representation learning has led to significant progress inautomating prediction by learning the features themselves. However, present…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Aditya Grover</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><ul><li><strong>Neural Networks</strong>: The neural revolution hasn't spared graph embeddings. Approaches like GraphSAGE and GCNs employ neural encoders, which, when applied to a node's local neighborhood, distill both the graph's topology and node features into the embeddings.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/1706.02216?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Inductive Representation Learning on Large Graphs</div><div class="kg-bookmark-description">Low-dimensional embeddings of nodes in large graphs have proved extremelyuseful in a variety of prediction tasks, from content recommendation toidentifying protein functions. However, most existing approaches require thatall nodes in the graph are present during training of the embeddings; these…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">William L. Hamilton</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/1609.02907?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Semi-Supervised Classification with Graph Convolutional Networks</div><div class="kg-bookmark-description">We present a scalable approach for semi-supervised learning ongraph-structured data that is based on an efficient variant of convolutionalneural networks which operate directly on graphs. We motivate the choice of ourconvolutional architecture via a localized first-order approximation ofspectral…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Thomas N. Kipf</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><h2 id="a-toy-implementation-of-graph-embeddings">A Toy Implementation of Graph Embeddings</h2><p>Implementing graph embedding techniques from scratch can be challenging. The algorithm below shows a simple way to generate graph embeddings. It takes an adjacency matrix as input, which represents the connections in a graph. Each row and column corresponds to a node, and a 1 indicates an edge between those nodes.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> typing <span class="hljs-keyword">import</span> <span class="hljs-type">List</span> 
-<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
+Now graph embeddings vectorize nodes. Distill graphs into geometry. Embeddings work magic. AI devours graphs.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 29, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Graphs are everywhere, from the intricate web of neurons in our brains to the sprawling networks of social media platforms. But how do we translate these complex structures into a language that AI models can understand? </p><p>In this post, we'll delve deep into the world of graph embeddings, drawing parallels with familiar concepts, and exploring the challenges and potential of this transformative technique.</p><h2 id="what-is-graph-embedding">What is Graph Embedding?</h2><p>In short, <strong>graph embedding vectorizes nodes.</strong></p><p>Imagine a vast, sprawling city - a tangled web of streets and junctions. Each intersection is a point of interest, and each road between them is a connection. Now picture looking down on this city from above - you see a complex mess of intersections and streets spreading out in all directions.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail.png" class="kg-image" alt="" width="1280" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail.png 1280w" sizes="(min-width: 720px) 720px"></figure><p>This city is like a graph - a set of nodes (the junctions) and edges between them (the streets). Handling very large, complex graphs tends to be computationally demanding, just as navigating a vast city can be overwhelming.</p><p>This is where graph embedding comes in - it takes this vast graph and simplifies it down into a simpler space as if we squeeze all the myriad streets and intersections down into basic proximity on a 2D map. Nodes highly interconnected end up clustered together, just as related city sights group together on a tourist map. Each node gets converted into a single point on a map, represented by coordinates in a lower-dimensional space. Nearby nodes in the original graph end up close together on the map. Far away nodes end up far apart.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail--1-.png" class="kg-image" alt="" width="1280" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail--1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Dark-Modern-Elegant-Singer-New-Song-YouTube-Thumbnail--1-.png 1280w" sizes="(min-width: 720px) 720px"></figure><p>So in summary, graph embedding takes a hairball graph and simplifies it down into a tidy map - a vector space that preserves the structure and relationships from the original graph. This is mathematically equivalent to <a href="https://arxiv.org/abs/2307.11224?ref=jina-ai-gmbh.ghost.io">sentence embeddings</a> applied to graphs instead of sentences. In essence, <strong>graph embedding vectorizes nodes like sentence embeddings vectorize sentences.</strong> It massages graphs into a format friendly for machine learning models.</p><h2 id="formal-definition-of-graph-embeddings">Formal Definition of Graph Embeddings</h2><p>Formally, a graph $G = (V, E)$ is a representation of relationships using nodes $V$ and edges $E$. Now, navigating a city can be overwhelming due to its vastness. Similarly, handling large graphs can be computationally challenging. Enter graph embedding.</p><p>Graph embedding is the art of translating this city (or graph) into a simplified map, where each point of interest (or node) is represented by a coordinate in a lower-dimensional space. Mathematically, it's about learning a function $f: v_i → y_i ∈ R^d$ that maps each node $v_i$ to a vector $y_i$ in a space $R^d$ where $d$ is much smaller than $|V|$.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-15.png" class="kg-image" alt="" width="557" height="326"><figcaption>Source: TigerGraph - Graph Embedding: Understanding Graph Embedding AlgorithmsS</figcaption></figure><h2 id="why-is-graph-embedding-a-game-changer">Why is Graph Embedding a Game-Changer?</h2><p>From predicting potential friendships on social media to visualizing intricate datasets, graph embeddings are proving invaluable. They're pivotal in node classification tasks, link predictions, and even in clustering nodes with similar properties. Moreover, as we venture into the realm of multimodal AI, where different types of data converge, graph embeddings can serve as a bridge, connecting structured data with unstructured data.</p><ol><li><strong>Machine Learning Compatibility</strong>: Traditional ML models, from linear regressors to deep neural networks, thrive on numerical data. Graph embeddings translate the intricate relationships of a graph into a numerical format, making them digestible for these models.</li><li><strong>Preserving Topology and Features</strong>: A well-crafted graph embedding retains the original graph's structure and node features. <a href="https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/40839.pdf?ref=jina-ai-gmbh.ghost.io">This dual preservation is a challenge that many earlier methods struggled with</a>.</li><li><strong>Dimensionality Reduction</strong>: Instead of grappling with a dimension for every node, we can now work in a much-reduced space, often just 50-1000 dimensions. This simplification is a boon for computational efficiency.</li><li><strong>Unearthing Latent Patterns</strong>: Beyond the explicit, graph embeddings can tease out hidden relationships, offering insights that might not be immediately apparent in the original graph.</li></ol><h2 id="how-to-compute-graph-embeddings">How to Compute Graph Embeddings?</h2><p>Graph embedding techniques are as diverse as the graphs they seek to represent. However, most can be bucketed into a few broad categories:</p><ul><li><strong>Matrix Factorization</strong>: Techniques like HOPE and Laplacian Eigenmaps revolve around factorizing the graph's adjacency matrix <code>A</code>. For instance, HOPE employs a generalized SVD to approximate <code>A</code> as <code>Y_s Y_t^T</code>, extracting the embedding <code>Y</code> in the process.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://zw-zhang.github.io/publication/2016-08-Asymmetric-Transitivity-Preserving-Graph-Embedding?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Asymmetric Transitivity Preserving Graph Embedding</div><div class="kg-bookmark-description">Key words: graph embedding, asymmetric transitivity, Generalized SVD (GSVD)</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://zw-zhang.github.io/images/android-chrome-192x192.png?v=M44lzPylqQ" alt=""><span class="kg-bookmark-author">Ziwei Zhang</span><span class="kg-bookmark-publisher">Email</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://zw-zhang.github.io/images/profile-photo.jpg" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://proceedings.neurips.cc/paper_files/paper/2001/hash/f106b7f99d2cb30c3db1c3cc0fde9ccb-Abstract.html?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://proceedings.neurips.cc/favicon.ico" alt=""><span class="kg-bookmark-author">NeurIPS Proceedings</span></div></div></a></figure><ul><li><strong>Random Walks</strong>: Picture a drunken walk through our earlier city analogy, meandering through landmarks. Methods like DeepWalk and node2vec use such random walks to capture the essence of a graph. These walks are then fed to models akin to Word2Vec to derive the embeddings.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/1403.6652?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">DeepWalk: Online Learning of Social Representations</div><div class="kg-bookmark-description">We present DeepWalk, a novel approach for learning latent representations ofvertices in a network. These latent representations encode social relations ina continuous vector space, which is easily exploited by statistical models.DeepWalk generalizes recent advancements in language modeling and un…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Bryan Perozzi</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/1607.00653?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">node2vec: Scalable Feature Learning for Networks</div><div class="kg-bookmark-description">Prediction tasks over nodes and edges in networks require careful effort inengineering features used by learning algorithms. Recent research in thebroader field of representation learning has led to significant progress inautomating prediction by learning the features themselves. However, present…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Aditya Grover</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><ul><li><strong>Neural Networks</strong>: The neural revolution hasn't spared graph embeddings. Approaches like GraphSAGE and GCNs employ neural encoders, which, when applied to a node's local neighborhood, distill both the graph's topology and node features into the embeddings.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/1706.02216?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Inductive Representation Learning on Large Graphs</div><div class="kg-bookmark-description">Low-dimensional embeddings of nodes in large graphs have proved extremelyuseful in a variety of prediction tasks, from content recommendation toidentifying protein functions. However, most existing approaches require thatall nodes in the graph are present during training of the embeddings; these…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">William L. Hamilton</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/1609.02907?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Semi-Supervised Classification with Graph Convolutional Networks</div><div class="kg-bookmark-description">We present a scalable approach for semi-supervised learning ongraph-structured data that is based on an efficient variant of convolutionalneural networks which operate directly on graphs. We motivate the choice of ourconvolutional architecture via a localized first-order approximation ofspectral…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Thomas N. Kipf</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><h2 id="a-toy-implementation-of-graph-embeddings">A Toy Implementation of Graph Embeddings</h2><p>Implementing graph embedding techniques from scratch can be challenging. The algorithm below shows a simple way to generate graph embeddings. It takes an adjacency matrix as input, which represents the connections in a graph. Each row and column corresponds to a node, and a 1 indicates an edge between those nodes.</p><pre><code class="language-python">from typing import List 
+import numpy as np
 
-<span class="hljs-keyword">def</span> <span class="hljs-title function_">graph_embedding</span>(<span class="hljs-params">adj_matrix: <span class="hljs-type">List</span>[<span class="hljs-type">List</span>[<span class="hljs-built_in">int</span>]], emb_size: <span class="hljs-built_in">int</span> = <span class="hljs-number">16</span></span>) -&gt; <span class="hljs-type">List</span>[np.ndarray]:
-    <span class="hljs-string">"""Generate graph embedding
+def graph_embedding(adj_matrix: List[List[int]], emb_size: int = 16) -&gt; List[np.ndarray]:
+    """Generate graph embedding
     
     Args:
         adj_matrix: Adjacency matrix as nested list
@@ -31,20 +31,20 @@
         
     Returns:
         List of numpy arrays as node embeddings
-    """</span>
+    """
         
-    <span class="hljs-comment"># Initialize empty embeddings</span>
-    embeddings = [np.random.rand(emb_size) <span class="hljs-keyword">for</span> _ <span class="hljs-keyword">in</span> adj_matrix]
+    # Initialize empty embeddings
+    embeddings = [np.random.rand(emb_size) for _ in adj_matrix]
     
-    <span class="hljs-comment"># Train embedding -visualize nodes moving closer if connected</span>
-    <span class="hljs-keyword">for</span> _ <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">100</span>): 
-        <span class="hljs-keyword">for</span> v1, row <span class="hljs-keyword">in</span> <span class="hljs-built_in">enumerate</span>(adj_matrix):
-            <span class="hljs-keyword">for</span> v2, is_connected <span class="hljs-keyword">in</span> <span class="hljs-built_in">enumerate</span>(row):
-                <span class="hljs-keyword">if</span> is_connected:
-                    <span class="hljs-comment"># Move embeddings closer if nodes connected</span>
-                    embeddings[v1] -= <span class="hljs-number">0.1</span> * (embeddings[v1] - embeddings[v2])  
+    # Train embedding -visualize nodes moving closer if connected
+    for _ in range(100): 
+        for v1, row in enumerate(adj_matrix):
+            for v2, is_connected in enumerate(row):
+                if is_connected:
+                    # Move embeddings closer if nodes connected
+                    embeddings[v1] -= 0.1 * (embeddings[v1] - embeddings[v2])  
 
-    <span class="hljs-keyword">return</span> embeddings</code></pre><ul><li>It initializes an embedding vector of random values for each node. Then it <em>trains</em> these embeddings by iterating through the adjacency matrix to identify connected nodes.</li><li>For any pair of nodes that are connected, it moves their embedding vectors slightly closer together. This is done by subtracting a fraction of their vector difference from the first node's embedding.</li><li>Over multiple iterations, nodes that are tightly interconnected will have very similar embedding vectors, while disconnected nodes will remain far apart in the embedding space.</li><li>The <code>for _ in range(100)</code> loop controls the number of training iterations. More iterations allow the embeddings to converge closer to their optimal values for representing the graph structure.</li></ul><p>Finally, the embeddings are returned as a list of <code>numpy</code> arrays. Each array is the vector representation for a node.</p><h2 id="top-3-open-source-packages-for-graph-embeddings">Top 3 Open Source Packages for Graph Embeddings</h2><p>This algorithm above gives a simple illustrative example of how graph embeddings can capture topology, which is not recommended to use in production of course. Instead, there are several excellent open source packages available to make working with graph embeddings much easier. Here are 3 popular options:</p><h3 id="pytorch-geometric">PyTorch Geometric</h3><p><a href="https://pytorch-geometric.readthedocs.io/en/latest/?ref=jina-ai-gmbh.ghost.io">PyTorch Geometric</a> is a geometric deep learning extension library for PyTorch. It includes a wide range of graph embedding techniques including GCN, GAT, GraphSAGE, and more. The mini-batches and autograd support make PyTorch Geometric great for developing and training new graph embedding models.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://pytorch-geometric.readthedocs.io/en/latest/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PyG Documentation — pytorch_geometric documentation</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://raw.githubusercontent.com/pyg-team/pyg_sphinx_theme/master/pyg_sphinx_theme/static/img/favicon.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://raw.githubusercontent.com/pyg-team/pyg_sphinx_theme/master/pyg_sphinx_theme/static/img/pyg_logo.png" alt=""></div></a></figure><h3 id="deep-graph-library-dgl">Deep Graph Library (DGL)</h3><p><a href="https://www.dgl.ai/?ref=jina-ai-gmbh.ghost.io">DGL</a> is a Python package from AWS that provides building blocks optimized for deep learning on graphs. DGL supports inductive graph representation learning techniques like GraphSAGE and GAT out of the box. The flexible frameworks allow you to implement custom graph neural network architectures.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.dgl.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Deep Graph Library</div><div class="kg-bookmark-description">Library for deep learning on graphs</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.dgl.ai/assets/images/dgl-favicon.png" alt=""><span class="kg-bookmark-author">logo</span><span class="kg-bookmark-publisher">Themeix</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://www.dgl.ai/assets/images/logo.png" alt=""></div></a></figure><h3 id="stellargraph">StellarGraph</h3><p><a href="https://www.stellargraph.io/?ref=jina-ai-gmbh.ghost.io">StellarGraph</a> is a Python library for machine learning on network data. It has implementations of graph embedding algorithms including node2vec, DeepWalk, and GraphSAGE. StellarGraph integrates seamlessly with common ML frameworks like TensorFlow and Scikit-Learn.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.stellargraph.io/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">StellarGraph - Machine Learning on Graphs</div><div class="kg-bookmark-description">StellarGraph provides graph analytics software for machine learning on networks. Uncover insights with the next generation of data science tools.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.wixstatic.com/media/91c550_bf9afe8aa7dd463891bd08edcbc42191~mv2.png/v1/fill/w_32%2Ch_32%2Clg_1%2Cusm_0.66_1.00_0.01/91c550_bf9afe8aa7dd463891bd08edcbc42191~mv2.png" alt=""><span class="kg-bookmark-author">Stellar2</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.wixstatic.com/media/91c550_bf9afe8aa7dd463891bd08edcbc42191~mv2.png/v1/fill/w_512,h_512,al_c/91c550_bf9afe8aa7dd463891bd08edcbc42191~mv2.png" alt=""></div></a></figure><p>These libraries make it easy to leverage graph embeddings in your own projects. They handle low-level optimizations and provide pre-built models so you can focus on your application. Graph embeddings are now more accessible than ever for researchers and developers.</p><h2 id="graph-embeddings-vs-sentence-embeddings">Graph Embeddings vs. Sentence Embeddings</h2><p>Graph embeddings and sentence embeddings, both aim to distill intricate structures into compact vector forms, yet they cater to distinct data types and possess their own set of challenges and strengths. Let's embark on an expedition to discern their similarities, differences, and unique attributes.</p><h3 id="the-common-ground">The Common Ground</h3><ul><li><strong>Dimensionality Reduction</strong>: Both graph and sentence embeddings endeavor to encapsulate high-dimensional data within a more compact, lower-dimensional space. This transformation not only makes the data more tractable but also primes it for machine learning models.</li><li><strong>Preservation of Relationships</strong>: Be it the intricate ties between nodes in a graph or the semantic dance of words in a sentence, both embeddings are committed to ensuring that the spatial relationships in the original structure find their echo in the embedding space.</li><li><strong>Facilitating Machine Learning</strong>: By transmuting graphs and sentences into fixed-length vectors, both embeddings pave the way for the application of a plethora of machine learning algorithms, spanning from clustering to classification.</li></ul><h3 id="diving-into-the-differences">Diving into the Differences</h3><table>
+    return embeddings</code></pre><ul><li>It initializes an embedding vector of random values for each node. Then it <em>trains</em> these embeddings by iterating through the adjacency matrix to identify connected nodes.</li><li>For any pair of nodes that are connected, it moves their embedding vectors slightly closer together. This is done by subtracting a fraction of their vector difference from the first node's embedding.</li><li>Over multiple iterations, nodes that are tightly interconnected will have very similar embedding vectors, while disconnected nodes will remain far apart in the embedding space.</li><li>The <code>for _ in range(100)</code> loop controls the number of training iterations. More iterations allow the embeddings to converge closer to their optimal values for representing the graph structure.</li></ul><p>Finally, the embeddings are returned as a list of <code>numpy</code> arrays. Each array is the vector representation for a node.</p><h2 id="top-3-open-source-packages-for-graph-embeddings">Top 3 Open Source Packages for Graph Embeddings</h2><p>This algorithm above gives a simple illustrative example of how graph embeddings can capture topology, which is not recommended to use in production of course. Instead, there are several excellent open source packages available to make working with graph embeddings much easier. Here are 3 popular options:</p><h3 id="pytorch-geometric">PyTorch Geometric</h3><p><a href="https://pytorch-geometric.readthedocs.io/en/latest/?ref=jina-ai-gmbh.ghost.io">PyTorch Geometric</a> is a geometric deep learning extension library for PyTorch. It includes a wide range of graph embedding techniques including GCN, GAT, GraphSAGE, and more. The mini-batches and autograd support make PyTorch Geometric great for developing and training new graph embedding models.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://pytorch-geometric.readthedocs.io/en/latest/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PyG Documentation — pytorch_geometric documentation</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://raw.githubusercontent.com/pyg-team/pyg_sphinx_theme/master/pyg_sphinx_theme/static/img/favicon.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://raw.githubusercontent.com/pyg-team/pyg_sphinx_theme/master/pyg_sphinx_theme/static/img/pyg_logo.png" alt=""></div></a></figure><h3 id="deep-graph-library-dgl">Deep Graph Library (DGL)</h3><p><a href="https://www.dgl.ai/?ref=jina-ai-gmbh.ghost.io">DGL</a> is a Python package from AWS that provides building blocks optimized for deep learning on graphs. DGL supports inductive graph representation learning techniques like GraphSAGE and GAT out of the box. The flexible frameworks allow you to implement custom graph neural network architectures.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.dgl.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Deep Graph Library</div><div class="kg-bookmark-description">Library for deep learning on graphs</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.dgl.ai/assets/images/dgl-favicon.png" alt=""><span class="kg-bookmark-author">logo</span><span class="kg-bookmark-publisher">Themeix</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://www.dgl.ai/assets/images/logo.png" alt=""></div></a></figure><h3 id="stellargraph">StellarGraph</h3><p><a href="https://www.stellargraph.io/?ref=jina-ai-gmbh.ghost.io">StellarGraph</a> is a Python library for machine learning on network data. It has implementations of graph embedding algorithms including node2vec, DeepWalk, and GraphSAGE. StellarGraph integrates seamlessly with common ML frameworks like TensorFlow and Scikit-Learn.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.stellargraph.io/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">StellarGraph - Machine Learning on Graphs</div><div class="kg-bookmark-description">StellarGraph provides graph analytics software for machine learning on networks. Uncover insights with the next generation of data science tools.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.wixstatic.com/media/91c550_bf9afe8aa7dd463891bd08edcbc42191~mv2.png/v1/fill/w_32%2Ch_32%2Clg_1%2Cusm_0.66_1.00_0.01/91c550_bf9afe8aa7dd463891bd08edcbc42191~mv2.png" alt=""><span class="kg-bookmark-author">Stellar2</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.wixstatic.com/media/91c550_bf9afe8aa7dd463891bd08edcbc42191~mv2.png/v1/fill/w_512,h_512,al_c/91c550_bf9afe8aa7dd463891bd08edcbc42191~mv2.png" alt=""></div></a></figure><p>These libraries make it easy to leverage graph embeddings in your own projects. They handle low-level optimizations and provide pre-built models so you can focus on your application. Graph embeddings are now more accessible than ever for researchers and developers.</p><h2 id="graph-embeddings-vs-sentence-embeddings">Graph Embeddings vs. Sentence Embeddings</h2><p>Graph embeddings and sentence embeddings, both aim to distill intricate structures into compact vector forms, yet they cater to distinct data types and possess their own set of challenges and strengths. Let's embark on an expedition to discern their similarities, differences, and unique attributes.</p><h3 id="the-common-ground">The Common Ground</h3><ul><li><strong>Dimensionality Reduction</strong>: Both graph and sentence embeddings endeavor to encapsulate high-dimensional data within a more compact, lower-dimensional space. This transformation not only makes the data more tractable but also primes it for machine learning models.</li><li><strong>Preservation of Relationships</strong>: Be it the intricate ties between nodes in a graph or the semantic dance of words in a sentence, both embeddings are committed to ensuring that the spatial relationships in the original structure find their echo in the embedding space.</li><li><strong>Facilitating Machine Learning</strong>: By transmuting graphs and sentences into fixed-length vectors, both embeddings pave the way for the application of a plethora of machine learning algorithms, spanning from clustering to classification.</li></ul><h3 id="diving-into-the-differences">Diving into the Differences</h3><table>
 <thead>
 <tr>
 <th>Aspect</th>
@@ -74,4 +74,4 @@
 <td>Sentences, with their chameleon-like nature, can adopt multiple meanings based on context (polysemy). Grasping these nuances, especially in linguistically rich languages, is a formidable challenge.</td>
 </tr>
 </tbody>
-</table><h2 id="challenges-and-the-road-ahead">Challenges and the Road Ahead</h2><p>Graph embeddings, while transformative, are not without their challenges. Striking the right balance between preserving topology and node features is a tightrope walk. As graphs burgeon in size and intricacy, the specter of computational inefficiency looms large. However, as evidenced by initiatives like the RESTORE framework, the community is rallying together, pooling resources and expertise to surmount these challenges.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2308.14659?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">RESTORE: Graph Embedding Assessment Through Reconstruction</div><div class="kg-bookmark-description">Following the success of Word2Vec embeddings, graph embeddings (GEs) havegained substantial traction. GEs are commonly generated and evaluatedextrinsically on downstream applications, but intrinsic evaluations of theoriginal graph properties in terms of topological structure and semanticinformat…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Hong Yung Yip</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><p>In conclusion, graph embeddings are not just reshaping our understanding of relational data; they are laying the foundation for a future where data, irrespective of its form or source, can be seamlessly integrated and processed. As we continue our foray into the uncharted territories of machine learning, tools and techniques like graph embeddings will be the compass guiding our way. Stay tuned as we journey deeper into the mesmerizing realm of machine learning, uncovering treasures and charting new courses!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fgraph-embedding-101-unraveling-the-magic-of-relational-data%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+</table><h2 id="challenges-and-the-road-ahead">Challenges and the Road Ahead</h2><p>Graph embeddings, while transformative, are not without their challenges. Striking the right balance between preserving topology and node features is a tightrope walk. As graphs burgeon in size and intricacy, the specter of computational inefficiency looms large. However, as evidenced by initiatives like the RESTORE framework, the community is rallying together, pooling resources and expertise to surmount these challenges.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2308.14659?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">RESTORE: Graph Embedding Assessment Through Reconstruction</div><div class="kg-bookmark-description">Following the success of Word2Vec embeddings, graph embeddings (GEs) havegained substantial traction. GEs are commonly generated and evaluatedextrinsically on downstream applications, but intrinsic evaluations of theoriginal graph properties in terms of topological structure and semanticinformat…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Hong Yung Yip</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><p>In conclusion, graph embeddings are not just reshaping our understanding of relational data; they are laying the foundation for a future where data, irrespective of its form or source, can be seamlessly integrated and processed. As we continue our foray into the uncharted territories of machine learning, tools and techniques like graph embeddings will be the compass guiding our way. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">A Guide to Using OpenTelemetry in Jina for Monitoring and Tracing Applications</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">In Jina 3.12 tracing and monitoring become much easier with built-in OpenTelemetry integration, leading to a quicker response time and faster turnaround time for fixing issues.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 66.7188%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/HEM01345.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Girish Chandrashekar, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 29, 2022 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>As software (and the cloud) eats the world, more companies are using more microservice architectures, containerization, multi-cloud deployments and continuous deployment patterns. That means more points of failure. Failures, along with tight Service Level Objectives, stress out operations/SRE/DevOps teams, in turn increasing friction with development teams that want to deploy new features and launch new A/B tests as soon as possible.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.giphy.com/media/1Be4g2yeiJ1QfqaKvz/giphy.gif" class="kg-image" alt="Jina developers when we can’t deploy new features"><figcaption>Jina developers when we can’t deploy new features</figcaption></figure><p>CI/CD patterns have evolved a lot in the cloud era, helping teams to push improvements, fixes or new features to production almost instantaneously, giving users access to the latest goodies. One thing that enables this is the wide range of tools that both generate and collect information from running applications in real-time or near real-time. </p><p>This information is in the form of signals indicating an application's health, performance and conformity. You can observe and analyze signal anomalies to catch misbehaving applications or features that need to be patched or disabled until further analysis. If you do it properly, you can detect anomalies more quickly, meaning happier customers, prevention of major outages and fewer security leaks.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.giphy.com/media/J4JSpIwM6y3Q6xnHgg/giphy.gif" class="kg-image" alt="A disembodied hand coming from a screen like the girl from the Ring is another way to make customers happy"><figcaption>A disembodied hand coming from a screen like the girl from the Ring is another way to make customers happy</figcaption></figure><p>Back in the old days, signalling methods started as humble error/exception logging. They've now evolved to the latest OpenTelemetry standard.</p><p>In this post we’ll explore the <strong>new tracing and monitoring features introduced in Jina 3.12</strong>, and use Sentry to track what’s happening when indexing or searching.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://jina.ai/news/jina-3-12-update/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina 3.12 Update</div><div class="kg-bookmark-description">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--8-.png" alt=""></div></a><figcaption>You'll need Jina version ≥3.12.0 to use OpenTelemetry features.</figcaption></figure><h2 id="what-problems-can-monitoring-and-tracing-solve">What problems can monitoring and tracing solve?</h2><p>We're going to use a fake real-world person to help explore the monitoring and tracing landscape: Meet Pamela NoLastName: She started a website called <code>Pamazon</code> to help people buy products online. Let's walk through the evolution of <code>Pamazon</code>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-17.png" class="kg-image" alt="" width="2000" height="1143" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-17.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-17.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-17.png 2000w" sizes="(min-width: 720px) 720px"><figcaption>Pamazon front page</figcaption></figure><h3 id="pamazon-10-logs-as-stdout">Pamazon 1.0: Logs as <code>stdout</code></h3><p>As Pamela's site grows, she needs monitoring to generate, capture and analyze signals and improve site reliability. She starts with a pretty simple system:</p><ul><li>Application logs are stored on each local machine and rotated periodically to avoid using up all the available disk space. If Pamela wants a longer retention period, she has to export these logs.</li><li>If a customer or tester notices an anomaly like the search engine constantly timing out, they create a support ticket to complain.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-18.png" class="kg-image" alt="" width="2000" height="1143" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-18.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-18.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-18.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-18.png 2000w" sizes="(min-width: 720px) 720px"></figure><ul><li>Pamela checks the logs and matches the time and possible error that the customer saw.</li></ul><p>This is a cumbersome process, and root cause analysis doesn't target the customer’s actual experience. Pamela needs a better way to do things.</p><h3 id="pamazon-20-structured-and-persistent-logs">Pamazon 2.0: Structured and persistent logs</h3><p>Luckily for Pamela, application logging has evolved a lot with logging formats, structured logging (JSON) and better error messages. There are tools integrating code performance style measurements into running applications to measure near real-time performance of pieces of code at various layers (networking, disk, CPU) of the application stack. Pamela can capture, visualize and store these signals for a longer time. Big data processing frameworks let her aggregate and crunch data from different application landscapes (languages, architectures, device platforms) and deployment environments.</p><h3 id="pamazon-30-tracing-errors-with-logs">Pamazon 3.0: Tracing errors with logs </h3><p>Pamazon is becoming a big success. It has a cloud/hybrid deployment environment, dealing with millions of global users over multiple device types. This means Pamela needs a more nuanced approach for:</p><ul><li>Generating valuable signals.</li><li>Targeting likely root causes of issues.</li></ul><p>Take the users Alice and Bob for example:</p><ul><li>Alice is in the USA using up her data connection to shop for fancy earrings on the Pamazon Android app.</li><li>Bob is shopping for a black jacket from a Chilean research base on an Ubuntu PC.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-22.png" class="kg-image" alt="" width="2000" height="889" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-22.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-22.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-22.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-22.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>Will Alice and Bob have similar experiences? All answers point to no. Delivering localized search results to many different devices (not to mention different languages) worldwide is a complex and daunting endeavor. <strong>It requires precise ways to generate signals and target likely root causes of issues.</strong> More users and device types mean more and more ways for things to go wrong, and more root causes of issues.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-32.png" class="kg-image" alt="" width="1400" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-32.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-32.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-32.png 1400w" sizes="(min-width: 720px) 720px"><figcaption>Bob is starting to get angry at the constant errors. You won’t like him when he’s angry. Mostly because he mopes about it on Facebook ALL the time. Get out of my feed Bob!</figcaption></figure><p>In short, Pamela needs to up her game again.</p><h2 id="what-is-opentelemetry">What is OpenTelemetry?</h2><p><a href="https://opentelemetry.io/?ref=jina-ai-gmbh.ghost.io">OpenTelemetry</a> is a project incubated by <a href="https://www.cncf.io/?ref=jina-ai-gmbh.ghost.io">CNCF</a>. It brings distributed tracing and metrics. Pamela has brought us on to implement this telemetry into her Jina Flow. Before getting started we have to learn a few new terms:</p><ul><li><a href="https://en.wikipedia.org/wiki/Telemetry?ref=jina-ai-gmbh.ghost.io"><strong>Telemetry</strong></a> is on-site collection of measurements or other data at remote points and automatically sending them to receiving equipment for monitoring. Simply put, you can consider a log message or raw observation value of the error count during a request as a measurement.</li><li><strong>Instrumentation</strong> is the process of using instruments that record/collect raw observations that are transformed into signals and transmitted for monitoring purposes.</li><li><a href="https://en.wikipedia.org/wiki/Tracing_(software)?ref=jina-ai-gmbh.ghost.io"><strong>Tracing</strong></a> involves a specialized use of logging to record information about a program's execution.</li></ul><p>Bear these in mind, as Pamela has roped us into doing this.</p><h2 id="how-to-use-opentelemetry-integration-in-jina">How to use OpenTelemetry integration in Jina?</h2><p>Jina &gt;=3.12 comes with built-in OpenTelemetry integrations and features. Let's see how it works for Pamela. We now outline how to build a text-to-image search system using the following components:</p><ul><li><a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io">DocArray</a> to manipulate data and interact with the storage backend using <a href="https://docarray.jina.ai/advanced/document-store/?ref=jina-ai-gmbh.ghost.io">document store</a>.</li><li><a href="https://docs.jina.ai/fundamentals/flow/?ref=jina-ai-gmbh.ghost.io#flow">Jina Flow</a> to orchestrate microservices for data loading, encoding and storage.</li><li><a href="https://docs.jina.ai/fundamentals/executor/?ref=jina-ai-gmbh.ghost.io#executor">Jina Executor</a> as the base to implement microservices.</li><li><a href="https://github.com/open-telemetry/opentelemetry-collector-contrib?ref=jina-ai-gmbh.ghost.io">OpenTelemetry Collector Contrib</a> to collect traces from the microservices.</li><li><a href="https://github.com/getsentry/self-hosted?ref=jina-ai-gmbh.ghost.io">Sentry</a> to visualise operations reported by the microservices.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-24.png" class="kg-image" alt="" width="2000" height="1143" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-24.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-24.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-24.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-24.png 2000w" sizes="(min-width: 720px) 720px"></figure><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">In this post we’re just building out a backend, and not touching on a frontend. To build your own low-code backend+frontend neural search solution, check out <a href="https://now.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina NOW</a>.</div></div><h3 id="preparing-the-data">Preparing the data</h3><p>We derived the dataset by pre-processing the <a href="https://www.google.com/url?sa=t&amp;rct=j&amp;q=&amp;esrc=s&amp;source=web&amp;cd=&amp;cad=rja&amp;uact=8&amp;ved=2ahUKEwjD6J_lkbP7AhWigP0HHWLAAYgQFnoECBIQAQ&amp;url=https%3A%2F%2Fpaperswithcode.com%2Fdataset%2Fdeepfashion&amp;usg=AOvVaw18-D2R5xEfrptAFWZmhT0H">deepfashion</a> dataset using <a href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io">Finetuner</a>. The image label generated by Finetuner is extracted and formatted to produce the <code>text</code> attribute of each product.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-25.png" class="kg-image" alt="" width="2000" height="840" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-25.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-25.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-25.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-25.png 2000w" sizes="(min-width: 720px) 720px"></figure><h3 id="building-a-flow-with-tracing-enabled">Building a Flow with tracing enabled</h3><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">You'll need Jina version ≥3.12.0 to use OpenTelemetry features.</div></div><p>We use a Jina Flow as a pipeline to connect our microservices (a.k.a Executors) together. Since we don't care too much about the nitty-gritty details, we won't dive into <em>all</em> the code, but just give a high-level overview. After all, the telemetry is the thing. Let's define the following in Python:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Flow, DocumentArray, Document
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="33cc6371-fea0-4b54-80ff-1b7c539b1d03" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="33cc6371-fea0-4b54-80ff-1b7c539b1d03" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">A Guide to Using OpenTelemetry in Jina for Monitoring and Tracing Applications</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">In Jina 3.12 tracing and monitoring become much easier with built-in OpenTelemetry integration, leading to a quicker response time and faster turnaround time for fixing issues.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 66.7188%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/HEM01345.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Girish Chandrashekar, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 29, 2022 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>As software (and the cloud) eats the world, more companies are using more microservice architectures, containerization, multi-cloud deployments and continuous deployment patterns. That means more points of failure. Failures, along with tight Service Level Objectives, stress out operations/SRE/DevOps teams, in turn increasing friction with development teams that want to deploy new features and launch new A/B tests as soon as possible.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.giphy.com/media/1Be4g2yeiJ1QfqaKvz/giphy.gif" class="kg-image" alt="Jina developers when we can’t deploy new features"><figcaption>Jina developers when we can’t deploy new features</figcaption></figure><p>CI/CD patterns have evolved a lot in the cloud era, helping teams to push improvements, fixes or new features to production almost instantaneously, giving users access to the latest goodies. One thing that enables this is the wide range of tools that both generate and collect information from running applications in real-time or near real-time. </p><p>This information is in the form of signals indicating an application's health, performance and conformity. You can observe and analyze signal anomalies to catch misbehaving applications or features that need to be patched or disabled until further analysis. If you do it properly, you can detect anomalies more quickly, meaning happier customers, prevention of major outages and fewer security leaks.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.giphy.com/media/J4JSpIwM6y3Q6xnHgg/giphy.gif" class="kg-image" alt="A disembodied hand coming from a screen like the girl from the Ring is another way to make customers happy"><figcaption>A disembodied hand coming from a screen like the girl from the Ring is another way to make customers happy</figcaption></figure><p>Back in the old days, signalling methods started as humble error/exception logging. They've now evolved to the latest OpenTelemetry standard.</p><p>In this post we’ll explore the <strong>new tracing and monitoring features introduced in Jina 3.12</strong>, and use Sentry to track what’s happening when indexing or searching.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://jina.ai/news/jina-3-12-update/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina 3.12 Update</div><div class="kg-bookmark-description">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--8-.png" alt=""></div></a><figcaption>You'll need Jina version ≥3.12.0 to use OpenTelemetry features.</figcaption></figure><h2 id="what-problems-can-monitoring-and-tracing-solve">What problems can monitoring and tracing solve?</h2><p>We're going to use a fake real-world person to help explore the monitoring and tracing landscape: Meet Pamela NoLastName: She started a website called <code>Pamazon</code> to help people buy products online. Let's walk through the evolution of <code>Pamazon</code>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-17.png" class="kg-image" alt="" width="2000" height="1143" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-17.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-17.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-17.png 2000w" sizes="(min-width: 720px) 720px"><figcaption>Pamazon front page</figcaption></figure><h3 id="pamazon-10-logs-as-stdout">Pamazon 1.0: Logs as <code>stdout</code></h3><p>As Pamela's site grows, she needs monitoring to generate, capture and analyze signals and improve site reliability. She starts with a pretty simple system:</p><ul><li>Application logs are stored on each local machine and rotated periodically to avoid using up all the available disk space. If Pamela wants a longer retention period, she has to export these logs.</li><li>If a customer or tester notices an anomaly like the search engine constantly timing out, they create a support ticket to complain.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-18.png" class="kg-image" alt="" width="2000" height="1143" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-18.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-18.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-18.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-18.png 2000w" sizes="(min-width: 720px) 720px"></figure><ul><li>Pamela checks the logs and matches the time and possible error that the customer saw.</li></ul><p>This is a cumbersome process, and root cause analysis doesn't target the customer’s actual experience. Pamela needs a better way to do things.</p><h3 id="pamazon-20-structured-and-persistent-logs">Pamazon 2.0: Structured and persistent logs</h3><p>Luckily for Pamela, application logging has evolved a lot with logging formats, structured logging (JSON) and better error messages. There are tools integrating code performance style measurements into running applications to measure near real-time performance of pieces of code at various layers (networking, disk, CPU) of the application stack. Pamela can capture, visualize and store these signals for a longer time. Big data processing frameworks let her aggregate and crunch data from different application landscapes (languages, architectures, device platforms) and deployment environments.</p><h3 id="pamazon-30-tracing-errors-with-logs">Pamazon 3.0: Tracing errors with logs </h3><p>Pamazon is becoming a big success. It has a cloud/hybrid deployment environment, dealing with millions of global users over multiple device types. This means Pamela needs a more nuanced approach for:</p><ul><li>Generating valuable signals.</li><li>Targeting likely root causes of issues.</li></ul><p>Take the users Alice and Bob for example:</p><ul><li>Alice is in the USA using up her data connection to shop for fancy earrings on the Pamazon Android app.</li><li>Bob is shopping for a black jacket from a Chilean research base on an Ubuntu PC.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-22.png" class="kg-image" alt="" width="2000" height="889" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-22.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-22.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-22.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-22.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>Will Alice and Bob have similar experiences? All answers point to no. Delivering localized search results to many different devices (not to mention different languages) worldwide is a complex and daunting endeavor. <strong>It requires precise ways to generate signals and target likely root causes of issues.</strong> More users and device types mean more and more ways for things to go wrong, and more root causes of issues.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-32.png" class="kg-image" alt="" width="1400" height="800" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-32.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-32.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-32.png 1400w" sizes="(min-width: 720px) 720px"><figcaption>Bob is starting to get angry at the constant errors. You won’t like him when he’s angry. Mostly because he mopes about it on Facebook ALL the time. Get out of my feed Bob!</figcaption></figure><p>In short, Pamela needs to up her game again.</p><h2 id="what-is-opentelemetry">What is OpenTelemetry?</h2><p><a href="https://opentelemetry.io/?ref=jina-ai-gmbh.ghost.io">OpenTelemetry</a> is a project incubated by <a href="https://www.cncf.io/?ref=jina-ai-gmbh.ghost.io">CNCF</a>. It brings distributed tracing and metrics. Pamela has brought us on to implement this telemetry into her Jina Flow. Before getting started we have to learn a few new terms:</p><ul><li><a href="https://en.wikipedia.org/wiki/Telemetry?ref=jina-ai-gmbh.ghost.io"><strong>Telemetry</strong></a> is on-site collection of measurements or other data at remote points and automatically sending them to receiving equipment for monitoring. Simply put, you can consider a log message or raw observation value of the error count during a request as a measurement.</li><li><strong>Instrumentation</strong> is the process of using instruments that record/collect raw observations that are transformed into signals and transmitted for monitoring purposes.</li><li><a href="https://en.wikipedia.org/wiki/Tracing_(software)?ref=jina-ai-gmbh.ghost.io"><strong>Tracing</strong></a> involves a specialized use of logging to record information about a program's execution.</li></ul><p>Bear these in mind, as Pamela has roped us into doing this.</p><h2 id="how-to-use-opentelemetry-integration-in-jina">How to use OpenTelemetry integration in Jina?</h2><p>Jina &gt;=3.12 comes with built-in OpenTelemetry integrations and features. Let's see how it works for Pamela. We now outline how to build a text-to-image search system using the following components:</p><ul><li><a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io">DocArray</a> to manipulate data and interact with the storage backend using <a href="https://docarray.jina.ai/advanced/document-store/?ref=jina-ai-gmbh.ghost.io">document store</a>.</li><li><a href="https://docs.jina.ai/fundamentals/flow/?ref=jina-ai-gmbh.ghost.io#flow">Jina Flow</a> to orchestrate microservices for data loading, encoding and storage.</li><li><a href="https://docs.jina.ai/fundamentals/executor/?ref=jina-ai-gmbh.ghost.io#executor">Jina Executor</a> as the base to implement microservices.</li><li><a href="https://github.com/open-telemetry/opentelemetry-collector-contrib?ref=jina-ai-gmbh.ghost.io">OpenTelemetry Collector Contrib</a> to collect traces from the microservices.</li><li><a href="https://github.com/getsentry/self-hosted?ref=jina-ai-gmbh.ghost.io">Sentry</a> to visualise operations reported by the microservices.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-24.png" class="kg-image" alt="" width="2000" height="1143" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-24.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-24.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-24.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-24.png 2000w" sizes="(min-width: 720px) 720px"></figure><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">In this post we’re just building out a backend, and not touching on a frontend. To build your own low-code backend+frontend neural search solution, check out <a href="https://now.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina NOW</a>.</div></div><h3 id="preparing-the-data">Preparing the data</h3><p>We derived the dataset by pre-processing the <a href="https://www.google.com/url?sa=t&amp;rct=j&amp;q=&amp;esrc=s&amp;source=web&amp;cd=&amp;cad=rja&amp;uact=8&amp;ved=2ahUKEwjD6J_lkbP7AhWigP0HHWLAAYgQFnoECBIQAQ&amp;url=https%3A%2F%2Fpaperswithcode.com%2Fdataset%2Fdeepfashion&amp;usg=AOvVaw18-D2R5xEfrptAFWZmhT0H">deepfashion</a> dataset using <a href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io">Finetuner</a>. The image label generated by Finetuner is extracted and formatted to produce the <code>text</code> attribute of each product.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-25.png" class="kg-image" alt="" width="2000" height="840" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-25.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-25.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-25.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-25.png 2000w" sizes="(min-width: 720px) 720px"></figure><h3 id="building-a-flow-with-tracing-enabled">Building a Flow with tracing enabled</h3><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">You'll need Jina version ≥3.12.0 to use OpenTelemetry features.</div></div><p>We use a Jina Flow as a pipeline to connect our microservices (a.k.a Executors) together. Since we don't care too much about the nitty-gritty details, we won't dive into <em>all</em> the code, but just give a high-level overview. After all, the telemetry is the thing. Let's define the following in Python:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Flow, DocumentArray, Document
 
 flow = (
     Flow(
diff --git a/news/hackday-with-jina-ai/index.html b/news/hackday-with-jina-ai/index.html
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@@ -4,9 +4,9 @@
 
 The &quot;Beginning Vector Search&quot; group built their first Image-to-Text search engine in one day from the ground up, using Jina AI's neural search framework and cloud-based CLIP-as-Service. They were readily able to program a classifier that could distinguish pictures o"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Blue-Pink-Gradient-Fashion-Banner--30---15-in---4-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/hackday-with-jina-ai"><meta property="twitter:title" content="From Zero to Hero: Vector Search Hackday Summary"><meta property="twitter:description" content="On Wednesday, Jina AI hosted a Vector Search Hackday with the Haystack EU Community in our Berlin office. Participants were grouped by interests and background, from beginners in vector search to information retrieval professionals.
 
-The &quot;Beginning Vector Search&quot; group built their first Image-to-Text search engine in one day from the ground up, using Jina AI's neural search framework and cloud-based CLIP-as-Service. They were readily able to program a classifier that could distinguish pictures o"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Blue-Pink-Gradient-Fashion-Banner--30---15-in---4-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+The &quot;Beginning Vector Search&quot; group built their first Image-to-Text search engine in one day from the ground up, using Jina AI's neural search framework and cloud-based CLIP-as-Service. They were readily able to program a classifier that could distinguish pictures o"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Blue-Pink-Gradient-Fashion-Banner--30---15-in---4-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jerboa</div><div class="q-item__label q-item__label--caption text-caption">An experimental finetuner for open-source LLMs</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="5cb3b68d-dfa3-4166-9ce9-54b65b93782e" aria-label="Expand &quot;Company&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><span class="q-icon" aria-hidden="true" role="presentation"><img src="/J.svg"></span></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Company</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="5cb3b68d-dfa3-4166-9ce9-54b65b93782e" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/about-us"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">About us</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/contact-sales"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Contact sales</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/open-day"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Open day</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/internship"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Intern program</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://jobs.lever.co/jina-ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Join us</div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">open_in_new</i></div></div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div></div></div></div><div class="q-scrollarea__bar q-scrollarea__bar--v absolute-right q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__bar q-scrollarea__bar--h absolute-bottom q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--v absolute-right q-scrollarea__thumb--invisible" aria-hidden="true" style="top: 0px; height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Blue-Pink-Gradient-Fashion-Banner--30---15-in---4-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">On Wednesday, Jina AI hosted a Vector Search Hackday with the Haystack EU Community in our Berlin office. Participants were grouped by interests and background, from beginners in vector search to information retrieval professionals.
+    gtag('config', 'G-9T52NXDS9T');</script></head><body class="desktop no-touch body--dark"><div id="q-app" data-v-app class="hidden"><div class="q-layout q-layout--standard" tabindex="-1" style="min-height: 600px;"><header class="q-header q-layout__section--marginal fixed-top text-white lock-blur bg-transparent print-hide"><div class="q-toolbar row no-wrap items-center q-px-none" role="toolbar"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch" tabindex="0" type="button" style="padding: 24px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">reorder</i></span></button><hr class="q-separator q-separator--vertical q-separator--dark" aria-orientation="vertical"><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch" tabindex="0" href="/" style="font-size: 32px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="q-icon" aria-hidden="true" role="img"><img src="/Jina - Dark.svg"></span></span></a><div class="q-space"></div><label class="q-field row no-wrap items-start q-field--borderless q-select q-field--auto-height q-select--without-input q-select--without-chips q-select--single q-field--float q-field--dense q-field--dark" for="f_3b612272-b208-4029-97df-34e771f2cc37"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__prepend q-field__marginal row no-wrap items-center"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">language</i></div><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><div class="q-field__native row items-center"><span>English</span><input class="q-select__focus-target" id="f_3b612272-b208-4029-97df-34e771f2cc37" readonly="" tabindex="0" role="combobox" aria-readonly="false" aria-autocomplete="none" aria-expanded="false" aria-controls="f_3b612272-b208-4029-97df-34e771f2cc37_lb"></div></div><div class="q-field__append q-field__marginal row no-wrap items-center q-anchor--skip"><i class="q-icon fas fa-caret-down q-select__dropdown-icon" aria-hidden="true" role="presentation"> </i></div></div></div></label></div></header><div class="q-drawer-container"><div class="q-drawer__opener fixed-left" aria-hidden="true"></div><div class="fullscreen q-drawer__backdrop hidden" aria-hidden="true" style="background-color: rgba(0, 0, 0, 0);"></div><aside class="q-drawer q-drawer--left q-drawer--bordered q-drawer--dark q-dark q-layout--prevent-focus fixed q-drawer--on-top q-drawer--mobile q-drawer--top-padding" style="width: 300px; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">PromptPerfect</div><div class="q-item__label q-item__label--caption text-caption">Premier tool for prompt engineering</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://scenex.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://scenex.jina.ai/SceneX - Light.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">From Zero to Hero: Vector Search Hackday Summary</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">On Wednesday, Jina AI hosted a Vector Search Hackday with the Haystack EU Community in our Berlin office. Participants were grouped by interests and background, from beginners in vector search to information retrieval professionals.
 
-The "Beginning Vector Search" group built their first Image-to-Text search engine in one day from the ground up, using Jina AI's neural search framework and cloud-based CLIP-as-Service. They were readily able to program a classifier that could distinguish pictures o</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 04, 2022 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://www.meetup.com/jina-community-meetup/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/IMG_0209.jpg" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/09/IMG_0209.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/09/IMG_0209.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/09/IMG_0209.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/09/IMG_0209.jpg 2400w" sizes="(min-width: 720px) 720px"></a><figcaption>Hackday in Jina AI's Berlin Office, Sept 28th&nbsp;</figcaption></figure><p>On Wednesday, Jina AI hosted a Vector Search Hackday with the Haystack EU Community in our Berlin office. Participants were grouped by interests and background, from beginners in vector search to information retrieval professionals. </p><p>The "Beginning Vector Search" group built their first Image-to-Text search engine in one day from the ground up, using Jina AI's neural search framework and cloud-based CLIP-as-Service. They were readily able to program a classifier that could distinguish pictures of cats from dogs. After that, the team added a filter for specific dog and cat breeds. </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/clip-as-service?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/clip-as-service: 🏄 Embed/reason/rank images and sentences with CLIP models</div><div class="kg-bookmark-description">🏄 Embed/reason/rank images and sentences with CLIP models - GitHub - jina-ai/clip-as-service: 🏄 Embed/reason/rank images and sentences with CLIP models</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/157198623/4f792a2e-d529-4f08-80f1-61a55592d781" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/IMG_0203.jpg" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/09/IMG_0203.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/09/IMG_0203.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/09/IMG_0203.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/09/IMG_0203.jpg 2400w" sizes="(min-width: 720px) 720px"><figcaption>Show &amp; Tell by the "Beginning Vector Search" group</figcaption></figure><p>The "Fine-tuning Models" group explored the possibilities of Jina AI's Finetuner. Finetuner makes it easier and faster to optimize pre-trained neural networks for specific tasks. The team first explored the many features of Finetuner, and by the end of the event, they were fine-tuning a network for a specific task.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/IMG_0187.jpg" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/09/IMG_0187.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/09/IMG_0187.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/09/IMG_0187.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/09/IMG_0187.jpg 2400w" sizes="(min-width: 720px) 720px"><figcaption>Show &amp; Tell by the "Fine-tuning models" team</figcaption></figure><p>The "Combining TF/IDF &amp; Vector Search" group had a fully running project by the end of the event. For their trial use case, the team used a dataset of 1000 product photos and descriptions. First, they combined images and texts using CLIP-as-Service to get vector embeddings for both. Then, they implemented a comparison of three search algorithms: BM25, CLIP nearest-neighbor, and a hybrid of the first two. Results were promising, and they gained a lot of experience combining text relevance with neural search. </p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/IMG_0200.jpg" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/09/IMG_0200.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/09/IMG_0200.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/09/IMG_0200.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/09/IMG_0200.jpg 2400w" sizes="(min-width: 720px) 720px"><figcaption>Show&amp;Tell by the "Combining TF/IDF &amp; Vector Search" team&nbsp;</figcaption></figure><p>The "Vector Search to E-commerce" group built an end-to-end search engine and deployed it to JCloud. They constructed a <a href="https://docs.jina.ai/fundamentals/flow/index.html?ref=jina-ai-gmbh.ghost.io">Flow</a> with a <a href="https://yaml.org/?ref=jina-ai-gmbh.ghost.io">YAML</a> file and implemented an <a href="https://docs.jina.ai/fundamentals/architecture-overview/?ref=jina-ai-gmbh.ghost.io#term-Executor">Executor</a> in it. They were then able to deploy the Flow to JCloud with a one-line command. They were able to set up a monitoring dashboard and by the end of the day had indexed 5000 images with descriptions this way.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docs.jina.ai/fundamentals/jcloud/index.html?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">JCloud</div><div class="kg-bookmark-description">After building a Jina project, the next step is to deploy and host it on Cloud. JCloud simplifies deploying and hosting your Jina projects on Jina Cloud. It provides a simple CLI with five commands to manage the lifecycle of your Jina projects. Basic: Jina Cloud provides a CLI and you can use it ...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docs.jina.ai/_static/favicon.ico" alt=""><span class="kg-bookmark-author">Jina 3.10.1 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docs.jina.ai/_images/jcloud-banner.png" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/IMG_0204.jpg" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/09/IMG_0204.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/09/IMG_0204.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/09/IMG_0204.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/09/IMG_0204.jpg 2400w" sizes="(min-width: 720px) 720px"><figcaption>Show&amp;Tell by the "Vector Search to E-commerce" team</figcaption></figure><p>To participate in similar events, learn more about Jina AI and meet the team, please follow us on Meetup.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.meetup.com/jina-community-meetup/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina Community Meetup (Berlin, Germany)</div><div class="kg-bookmark-description">Gather people who are interested in the Jina search framework, open-source neural search, and related topics.No matter if you’re AI engineers, Python Engineers, Data Scientists, CTO, Machine Learning</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.meetup.com/mu_static/en-US/m_swarm_196x196.b5c9ccb2.png" alt=""><span class="kg-bookmark-author">Meetup</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://secure.meetupstatic.com/photos/event/a/1/3/6/600_497201270.jpeg" alt=""></div></a></figure><p>If you want to explore how to build programs like the ones mentioned above, please check out <a href="https://examples.jina.ai/?ref=jina-ai-gmbh.ghost.io">our tutorials</a> and <a href="https://docs.jina.ai/?ref=jina-ai-gmbh.ghost.io">docs</a>. </p><p>If you have questions about the Jina AI platform, feel free to join our Slack channel to get answers from our staff.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://slack.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Join our Slack Community</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fhackday-with-jina-ai%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; 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+The "Beginning Vector Search" group built their first Image-to-Text search engine in one day from the ground up, using Jina AI's neural search framework and cloud-based CLIP-as-Service. They were readily able to program a classifier that could distinguish pictures o</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 04, 2022 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://www.meetup.com/jina-community-meetup/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/IMG_0209.jpg" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/09/IMG_0209.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/09/IMG_0209.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/09/IMG_0209.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/09/IMG_0209.jpg 2400w" sizes="(min-width: 720px) 720px"></a><figcaption>Hackday in Jina AI's Berlin Office, Sept 28th&nbsp;</figcaption></figure><p>On Wednesday, Jina AI hosted a Vector Search Hackday with the Haystack EU Community in our Berlin office. Participants were grouped by interests and background, from beginners in vector search to information retrieval professionals. </p><p>The "Beginning Vector Search" group built their first Image-to-Text search engine in one day from the ground up, using Jina AI's neural search framework and cloud-based CLIP-as-Service. They were readily able to program a classifier that could distinguish pictures of cats from dogs. After that, the team added a filter for specific dog and cat breeds. </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/clip-as-service?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/clip-as-service: 🏄 Embed/reason/rank images and sentences with CLIP models</div><div class="kg-bookmark-description">🏄 Embed/reason/rank images and sentences with CLIP models - GitHub - jina-ai/clip-as-service: 🏄 Embed/reason/rank images and sentences with CLIP models</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/157198623/4f792a2e-d529-4f08-80f1-61a55592d781" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/IMG_0203.jpg" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/09/IMG_0203.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/09/IMG_0203.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/09/IMG_0203.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/09/IMG_0203.jpg 2400w" sizes="(min-width: 720px) 720px"><figcaption>Show &amp; Tell by the "Beginning Vector Search" group</figcaption></figure><p>The "Fine-tuning Models" group explored the possibilities of Jina AI's Finetuner. Finetuner makes it easier and faster to optimize pre-trained neural networks for specific tasks. The team first explored the many features of Finetuner, and by the end of the event, they were fine-tuning a network for a specific task.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/IMG_0187.jpg" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/09/IMG_0187.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/09/IMG_0187.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/09/IMG_0187.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/09/IMG_0187.jpg 2400w" sizes="(min-width: 720px) 720px"><figcaption>Show &amp; Tell by the "Fine-tuning models" team</figcaption></figure><p>The "Combining TF/IDF &amp; Vector Search" group had a fully running project by the end of the event. For their trial use case, the team used a dataset of 1000 product photos and descriptions. First, they combined images and texts using CLIP-as-Service to get vector embeddings for both. Then, they implemented a comparison of three search algorithms: BM25, CLIP nearest-neighbor, and a hybrid of the first two. Results were promising, and they gained a lot of experience combining text relevance with neural search. </p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/IMG_0200.jpg" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/09/IMG_0200.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/09/IMG_0200.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/09/IMG_0200.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/09/IMG_0200.jpg 2400w" sizes="(min-width: 720px) 720px"><figcaption>Show&amp;Tell by the "Combining TF/IDF &amp; Vector Search" team&nbsp;</figcaption></figure><p>The "Vector Search to E-commerce" group built an end-to-end search engine and deployed it to JCloud. They constructed a <a href="https://docs.jina.ai/fundamentals/flow/index.html?ref=jina-ai-gmbh.ghost.io">Flow</a> with a <a href="https://yaml.org/?ref=jina-ai-gmbh.ghost.io">YAML</a> file and implemented an <a href="https://docs.jina.ai/fundamentals/architecture-overview/?ref=jina-ai-gmbh.ghost.io#term-Executor">Executor</a> in it. They were then able to deploy the Flow to JCloud with a one-line command. They were able to set up a monitoring dashboard and by the end of the day had indexed 5000 images with descriptions this way.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docs.jina.ai/fundamentals/jcloud/index.html?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">JCloud</div><div class="kg-bookmark-description">After building a Jina project, the next step is to deploy and host it on Cloud. JCloud simplifies deploying and hosting your Jina projects on Jina Cloud. It provides a simple CLI with five commands to manage the lifecycle of your Jina projects. Basic: Jina Cloud provides a CLI and you can use it ...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docs.jina.ai/_static/favicon.ico" alt=""><span class="kg-bookmark-author">Jina 3.10.1 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docs.jina.ai/_images/jcloud-banner.png" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/IMG_0204.jpg" class="kg-image" alt="" width="2000" height="1500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/09/IMG_0204.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/09/IMG_0204.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/09/IMG_0204.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/09/IMG_0204.jpg 2400w" sizes="(min-width: 720px) 720px"><figcaption>Show&amp;Tell by the "Vector Search to E-commerce" team</figcaption></figure><p>To participate in similar events, learn more about Jina AI and meet the team, please follow us on Meetup.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.meetup.com/jina-community-meetup/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina Community Meetup (Berlin, Germany)</div><div class="kg-bookmark-description">Gather people who are interested in the Jina search framework, open-source neural search, and related topics.No matter if you’re AI engineers, Python Engineers, Data Scientists, CTO, Machine Learning</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.meetup.com/mu_static/en-US/m_swarm_196x196.b5c9ccb2.png" alt=""><span class="kg-bookmark-author">Meetup</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://secure.meetupstatic.com/photos/event/a/1/3/6/600_497201270.jpeg" alt=""></div></a></figure><p>If you want to explore how to build programs like the ones mentioned above, please check out <a href="https://examples.jina.ai/?ref=jina-ai-gmbh.ghost.io">our tutorials</a> and <a href="https://docs.jina.ai/?ref=jina-ai-gmbh.ghost.io">docs</a>. </p><p>If you have questions about the Jina AI platform, feel free to join our Slack channel to get answers from our staff.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://slack.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Join our Slack Community</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fhackday-with-jina-ai%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>How Embeddings Drive AI: A Comprehensive Presentation</title><meta charset="utf-8"><meta name="title" content="How Embeddings Drive AI: A Comprehensive Presentation"><meta name="description" content="Embeddings are a core concept and technology in AI, present in some form across the spectrum of AI applications. Properly understanding and mastering this technology positions you to leverage AI models to add the most value to your business."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/how-embeddings-drive-ai-a-guide"><meta property="og:title" content="How Embeddings Drive AI: A Comprehensive Presentation"><meta property="og:description" content="Embeddings are a core concept and technology in AI, present in some form across the spectrum of AI applications. Properly understanding and mastering this technology positions you to leverage AI models to add the most value to your business."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--19-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/how-embeddings-drive-ai-a-guide"><meta property="twitter:title" content="How Embeddings Drive AI: A Comprehensive Presentation"><meta property="twitter:description" content="Embeddings are a core concept and technology in AI, present in some form across the spectrum of AI applications. Properly understanding and mastering this technology positions you to leverage AI models to add the most value to your business."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--19-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How Embeddings Drive AI: A Comprehensive Presentation</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Embeddings are a core concept and technology in AI, present in some form across the spectrum of AI applications. Properly understanding and mastering this technology positions you to leverage AI models to add the most value to your business.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 19, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Embeddings are a core concept and technology in artificial intelligence, used in some form in practically all recent AI models, including ChatGPT and image generators like Stable Diffusion. It is one of the fundamental technologies behind the most visible and useful AI applications.</p><p>Embeddings are also important to less flashy applications, like search, visual face and object recognition, machine translation, recommenders, and many more.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text"><b><strong style="white-space: pre-wrap;">What is an embedding?</strong></b><br><br>An embedding is a <i><em class="italic" style="white-space: pre-wrap;">vector </em></i>that stands in for some other object (digital, physical, or abstract) such that some of the properties of the object it stands for are preserved as geometric properties of their corresponding vectors.</div></div><p>This post tries to explain what that means concretely.</p><h2 id="vectors">Vectors</h2><p>A vector is just a list of numbers that we can interpret as coordinates in a high-dimensional space.</p><p>Imagine a list of two numbers $(x,y)$. We could treat them as coordinates on an x-y graph, with each list corresponding to a point in a two-dimensional space:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/vec1-1-1.png" class="kg-image" alt="" width="1000" height="997" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/vec1-1-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/vec1-1-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><p>If we have three numbers $(x,y,z)$, then this corresponds to a point in a three-dimensional space:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/vec2-1.png" class="kg-image" alt="" width="1000" height="1162" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/vec2-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/vec2-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><p>We can readily extend this logic into more dimensions: four, five, a hundred, a thousand, even millions or billions. Drawing a space with a thousand dimensions is very hard, and imagining one is all but impossible, but mathematically, it’s trivial to manage.</p><h2 id="embeddings-as-vectors">Embeddings as Vectors</h2><p>For example, let’s say we had a way to assign a small vector — just two numbers long — to pictures of apples and oranges.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/apple_and_orange.png" class="kg-image" alt="" width="900" height="448" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/apple_and_orange.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/apple_and_orange.png 900w" sizes="(min-width: 720px) 720px"></figure><p>We can display vectors of just two numbers as points on an XY graph, so imagine we took pictures of apples and oranges and assigned each a random vector, then plotted them on a graph:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/graph1-2-1.png" class="kg-image" alt="" width="516" height="389"></figure><p>The apples and oranges are all mixed together, and nothing about how they’re placed on the graph tells us whether a picture is of an apple or an orange.</p><p>What we’d like to have is something like this:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/graph2-1-1.png" class="kg-image" alt="" width="515" height="389"></figure><p>If we had the means to assign vectors like these to pictures of apples and oranges, it would be trivial to write a program to tell them apart. All it would have to do is check which side of a line the vector fell on.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/graph3-1.png" class="kg-image" alt="" width="515" height="389"></figure><p>AI and neural networks provide a way to do exactly that.</p><p>Using machine learning, we can construct an AI model that takes images and then outputs vectors such that the oranges and apples are easily separated. These vectors typically have a lot more than two dimensions, so they aren’t easy to draw.</p><p>The property of the original object that we care about — whether it is an apple or an orange — is preserved in the geometry of the embedding vectors: The apples are all to one side and the oranges to the other, easily separated by what in high-dimensional geometry is called a <em>hyper-plane</em>, but is really just a simple way of splitting the embedding space.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/flow-1.png" class="kg-image" alt="" width="820" height="300" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/flow-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/flow-1.png 820w" sizes="(min-width: 720px) 720px"></figure><p>This example is very simple and concerns only one distinction: apples or oranges. Embeddings can capture a lot of information about many different aspects of the objects they represent. If we trained an AI model to distinguish apples from oranges, we would likely find that the embeddings encoded many of the characteristics that distinguish apples from oranges, like color and texture and the presence of a stem. We might additionally find that the green apples are clustered together, farther from the red ones, or that highly mottled apples had embeddings closer to the oranges.</p><h2 id="word-embeddings">Word Embeddings</h2><p>Embeddings emerge almost automatically from neural network-based AI models, as we will show in the next section, but they were first developed as a way to better encapsulate the semantics (i.e. meanings) of words for computers. You will still sometimes see people talk about "semantic embeddings" because of the role word embeddings have played in this technology, even though embeddings aren’t specifically about some kind of real-world meaning but about any useful property that an AI model can learn to recognize.</p><p>In natural language processing, embeddings have always been associated with an idea in linguistics called the <strong>distributional hypothesis</strong>, most frequently associated with the linguist J.R. Firth:</p><blockquote>You shall know a word by the company it keeps.<br><br>A Synopsis of Linguistic Theory, 1930-55.<br>(In Studies in Linguistic Analysis, 1957, pp. 1-31) </blockquote><p>The distributional hypothesis is the idea that the semantics — that is to say, the meaning — of a word is reflected in the contexts of its usage. We should expect that the more related the meanings of two words, the more we should see them in the same contexts.</p><p>For example, when two words are spelled or pronounced the same, we use context to figure out which word is intended:</p><ul><li>She took her <strong>bat</strong> to baseball practice.</li><li>She was chased away from the cave by a <strong>bat</strong>.</li></ul><p>It is clear from the surrounding context which meaning of the word <strong>bat</strong> is intended.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/bat_girl.png" class="kg-image" alt="" width="1456" height="816" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/bat_girl.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/bat_girl.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/bat_girl.png 1456w" sizes="(min-width: 720px) 720px"></figure><p>Similarly, we can often expect that words from the same semantic class, like <strong>tomato</strong>, <strong>carrot</strong>, and <strong>zucchini</strong>, appear in the same contexts:</p><ul><li>He grew <strong>tomatoes</strong> in his garden.</li><li>He grew <strong>carrots</strong> in his garden.</li><li>He grew <strong>zucchini</strong> in his garden.</li></ul><p>But not:</p><ul><li>He grew <strong>bicycles</strong> in his garden.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/bicycle_plant.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/bicycle_plant.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/bicycle_plant.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/bicycle_plant.png 1024w" sizes="(min-width: 720px) 720px"></figure><p>Words that can fill the blank in “He grew _____ in his garden” share a property that they do not share with bicycles, and we can build an AI model that encompasses this information, along with thousands of other contexts where some words can go and others can’t.</p><p>Word embeddings are a way to encapsulate this information in a vector space.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/graph4-1.png" class="kg-image" alt="" width="515" height="389"></figure><h2 id="image-recognition">Image Recognition</h2><p>We can even construct embeddings where we don’t explicitly say what features are relevant.</p><p>For example, an embedding for a face recognition system translates pictures of people into embedding vectors distributed in a high-dimensional space.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/faces_A-1.png" class="kg-image" alt="" width="1000" height="999" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/faces_A-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/faces_A-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><p>We might find that people whose faces have some common properties would be grouped together in some part of the embedding space. We might find, for example, that grey-haired people and bald people cluster together:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/faces_marked-1.png" class="kg-image" alt="" width="1000" height="999" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/faces_marked-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/faces_marked-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><p>But more importantly and usefully, we would expect that if we gave it two pictures of the same person, those two embeddings would be closer to each other than to any other person’s picture:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Wynona-1.png" class="kg-image" alt="" width="1000" height="728" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Wynona-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Wynona-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><p>Of course, it would also find people who just&nbsp;look&nbsp;similar, although we hope that they wouldn’t be as close together as two people who are actually the same:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Hobbit_dude-1.png" class="kg-image" alt="" width="1000" height="728" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Hobbit_dude-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Hobbit_dude-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><h2 id="multimodal-embeddings">Multimodal Embeddings</h2><p>Embedding spaces can also act as a bridge between different kinds of inputs.</p><p>For example, if we have a database of pictures with descriptive captions, we can co-train two embedding models — one for images and one for texts — to output vectors in the same embedding space. The result is that embeddings of descriptions of images and embeddings of the images themselves will be near each other.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/fruit-1.png" class="kg-image" alt="" width="1000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/fruit-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/fruit-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><h2 id="embeddings-everywhere">Embeddings Everywhere</h2><p>Embeddings provide a very generalized framework for making useful comparisons between things. They are so useful that they see applications all over AI and machine learning. Any application that requires similarity/dissimilarity evaluation, relies on hidden or non-obvious features, or requires implicit context-sensitive mappings between different inputs and outputs, likely uses embeddings in some form.</p><p>They are actively in use for:</p><ul><li>Search and information retrieval for all media types</li><li>Face and object recognition in machine vision</li><li>Question-answering systems</li><li>Recommender systems</li><li>Outlier detection (often as part of fraud detection)</li><li>Spellchecking and grammar correction</li><li>Natural language understanding</li><li>Machine translation</li></ul><p>This is a far from exhaustive list because nearly every AI application uses embeddings. In some scenarios, embeddings are used internally and are invisible to users and developers, but many AI applications hinge on the ability to use embeddings to identify and compare things in useful, human-like ways.</p><p>Jina AI is developing a collection of high-performance specialized embedding models that you can download or use via our public API, without any of the complexities of AI development. We are also preparing a suite of open-source tools in Python to help you integrate embedding models into your tech stack.</p><p>Jina AI is committed to providing you with tools and help for creating, optimizing, evaluating, and implementing embedding models for your enterprise. We’re here to help you navigate the new world of business AI. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How Embeddings Drive AI: A Comprehensive Presentation</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Embeddings are a core concept and technology in AI, present in some form across the spectrum of AI applications. Properly understanding and mastering this technology positions you to leverage AI models to add the most value to your business.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 19, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Embeddings are a core concept and technology in artificial intelligence, used in some form in practically all recent AI models, including ChatGPT and image generators like Stable Diffusion. It is one of the fundamental technologies behind the most visible and useful AI applications.</p><p>Embeddings are also important to less flashy applications, like search, visual face and object recognition, machine translation, recommenders, and many more.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text"><b><strong style="white-space: pre-wrap;">What is an embedding?</strong></b><br><br>An embedding is a <i><em class="italic" style="white-space: pre-wrap;">vector </em></i>that stands in for some other object (digital, physical, or abstract) such that some of the properties of the object it stands for are preserved as geometric properties of their corresponding vectors.</div></div><p>This post tries to explain what that means concretely.</p><h2 id="vectors">Vectors</h2><p>A vector is just a list of numbers that we can interpret as coordinates in a high-dimensional space.</p><p>Imagine a list of two numbers $(x,y)$. We could treat them as coordinates on an x-y graph, with each list corresponding to a point in a two-dimensional space:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/vec1-1-1.png" class="kg-image" alt="" width="1000" height="997" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/vec1-1-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/vec1-1-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><p>If we have three numbers $(x,y,z)$, then this corresponds to a point in a three-dimensional space:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/vec2-1.png" class="kg-image" alt="" width="1000" height="1162" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/vec2-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/vec2-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><p>We can readily extend this logic into more dimensions: four, five, a hundred, a thousand, even millions or billions. Drawing a space with a thousand dimensions is very hard, and imagining one is all but impossible, but mathematically, it’s trivial to manage.</p><h2 id="embeddings-as-vectors">Embeddings as Vectors</h2><p>For example, let’s say we had a way to assign a small vector — just two numbers long — to pictures of apples and oranges.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/apple_and_orange.png" class="kg-image" alt="" width="900" height="448" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/apple_and_orange.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/apple_and_orange.png 900w" sizes="(min-width: 720px) 720px"></figure><p>We can display vectors of just two numbers as points on an XY graph, so imagine we took pictures of apples and oranges and assigned each a random vector, then plotted them on a graph:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/graph1-2-1.png" class="kg-image" alt="" width="516" height="389"></figure><p>The apples and oranges are all mixed together, and nothing about how they’re placed on the graph tells us whether a picture is of an apple or an orange.</p><p>What we’d like to have is something like this:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/graph2-1-1.png" class="kg-image" alt="" width="515" height="389"></figure><p>If we had the means to assign vectors like these to pictures of apples and oranges, it would be trivial to write a program to tell them apart. All it would have to do is check which side of a line the vector fell on.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/graph3-1.png" class="kg-image" alt="" width="515" height="389"></figure><p>AI and neural networks provide a way to do exactly that.</p><p>Using machine learning, we can construct an AI model that takes images and then outputs vectors such that the oranges and apples are easily separated. These vectors typically have a lot more than two dimensions, so they aren’t easy to draw.</p><p>The property of the original object that we care about — whether it is an apple or an orange — is preserved in the geometry of the embedding vectors: The apples are all to one side and the oranges to the other, easily separated by what in high-dimensional geometry is called a <em>hyper-plane</em>, but is really just a simple way of splitting the embedding space.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/flow-1.png" class="kg-image" alt="" width="820" height="300" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/flow-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/flow-1.png 820w" sizes="(min-width: 720px) 720px"></figure><p>This example is very simple and concerns only one distinction: apples or oranges. Embeddings can capture a lot of information about many different aspects of the objects they represent. If we trained an AI model to distinguish apples from oranges, we would likely find that the embeddings encoded many of the characteristics that distinguish apples from oranges, like color and texture and the presence of a stem. We might additionally find that the green apples are clustered together, farther from the red ones, or that highly mottled apples had embeddings closer to the oranges.</p><h2 id="word-embeddings">Word Embeddings</h2><p>Embeddings emerge almost automatically from neural network-based AI models, as we will show in the next section, but they were first developed as a way to better encapsulate the semantics (i.e. meanings) of words for computers. You will still sometimes see people talk about "semantic embeddings" because of the role word embeddings have played in this technology, even though embeddings aren’t specifically about some kind of real-world meaning but about any useful property that an AI model can learn to recognize.</p><p>In natural language processing, embeddings have always been associated with an idea in linguistics called the <strong>distributional hypothesis</strong>, most frequently associated with the linguist J.R. Firth:</p><blockquote>You shall know a word by the company it keeps.<br><br>A Synopsis of Linguistic Theory, 1930-55.<br>(In Studies in Linguistic Analysis, 1957, pp. 1-31) </blockquote><p>The distributional hypothesis is the idea that the semantics — that is to say, the meaning — of a word is reflected in the contexts of its usage. We should expect that the more related the meanings of two words, the more we should see them in the same contexts.</p><p>For example, when two words are spelled or pronounced the same, we use context to figure out which word is intended:</p><ul><li>She took her <strong>bat</strong> to baseball practice.</li><li>She was chased away from the cave by a <strong>bat</strong>.</li></ul><p>It is clear from the surrounding context which meaning of the word <strong>bat</strong> is intended.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/bat_girl.png" class="kg-image" alt="" width="1456" height="816" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/bat_girl.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/bat_girl.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/bat_girl.png 1456w" sizes="(min-width: 720px) 720px"></figure><p>Similarly, we can often expect that words from the same semantic class, like <strong>tomato</strong>, <strong>carrot</strong>, and <strong>zucchini</strong>, appear in the same contexts:</p><ul><li>He grew <strong>tomatoes</strong> in his garden.</li><li>He grew <strong>carrots</strong> in his garden.</li><li>He grew <strong>zucchini</strong> in his garden.</li></ul><p>But not:</p><ul><li>He grew <strong>bicycles</strong> in his garden.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/bicycle_plant.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/bicycle_plant.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/bicycle_plant.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/bicycle_plant.png 1024w" sizes="(min-width: 720px) 720px"></figure><p>Words that can fill the blank in “He grew _____ in his garden” share a property that they do not share with bicycles, and we can build an AI model that encompasses this information, along with thousands of other contexts where some words can go and others can’t.</p><p>Word embeddings are a way to encapsulate this information in a vector space.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/graph4-1.png" class="kg-image" alt="" width="515" height="389"></figure><h2 id="image-recognition">Image Recognition</h2><p>We can even construct embeddings where we don’t explicitly say what features are relevant.</p><p>For example, an embedding for a face recognition system translates pictures of people into embedding vectors distributed in a high-dimensional space.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/faces_A-1.png" class="kg-image" alt="" width="1000" height="999" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/faces_A-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/faces_A-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><p>We might find that people whose faces have some common properties would be grouped together in some part of the embedding space. We might find, for example, that grey-haired people and bald people cluster together:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/faces_marked-1.png" class="kg-image" alt="" width="1000" height="999" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/faces_marked-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/faces_marked-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><p>But more importantly and usefully, we would expect that if we gave it two pictures of the same person, those two embeddings would be closer to each other than to any other person’s picture:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Wynona-1.png" class="kg-image" alt="" width="1000" height="728" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Wynona-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Wynona-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><p>Of course, it would also find people who just&nbsp;look&nbsp;similar, although we hope that they wouldn’t be as close together as two people who are actually the same:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Hobbit_dude-1.png" class="kg-image" alt="" width="1000" height="728" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Hobbit_dude-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Hobbit_dude-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><h2 id="multimodal-embeddings">Multimodal Embeddings</h2><p>Embedding spaces can also act as a bridge between different kinds of inputs.</p><p>For example, if we have a database of pictures with descriptive captions, we can co-train two embedding models — one for images and one for texts — to output vectors in the same embedding space. The result is that embeddings of descriptions of images and embeddings of the images themselves will be near each other.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/fruit-1.png" class="kg-image" alt="" width="1000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/fruit-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/fruit-1.png 1000w" sizes="(min-width: 720px) 720px"></figure><h2 id="embeddings-everywhere">Embeddings Everywhere</h2><p>Embeddings provide a very generalized framework for making useful comparisons between things. They are so useful that they see applications all over AI and machine learning. Any application that requires similarity/dissimilarity evaluation, relies on hidden or non-obvious features, or requires implicit context-sensitive mappings between different inputs and outputs, likely uses embeddings in some form.</p><p>They are actively in use for:</p><ul><li>Search and information retrieval for all media types</li><li>Face and object recognition in machine vision</li><li>Question-answering systems</li><li>Recommender systems</li><li>Outlier detection (often as part of fraud detection)</li><li>Spellchecking and grammar correction</li><li>Natural language understanding</li><li>Machine translation</li></ul><p>This is a far from exhaustive list because nearly every AI application uses embeddings. In some scenarios, embeddings are used internally and are invisible to users and developers, but many AI applications hinge on the ability to use embeddings to identify and compare things in useful, human-like ways.</p><p>Jina AI is developing a collection of high-performance specialized embedding models that you can download or use via our public API, without any of the complexities of AI development. We are also preparing a suite of open-source tools in Python to help you integrate embedding models into your tech stack.</p><p>Jina AI is committed to providing you with tools and help for creating, optimizing, evaluating, and implementing embedding models for your enterprise. We’re here to help you navigate the new world of business AI. Contact us via our&nbsp;<a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">website</a>&nbsp;or join our&nbsp;<a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">community on Discord</a>&nbsp;to get started.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI - Your Portal to Multimodal AI</div><div class="kg-bookmark-description">Jina AI offers powerful multimodal AI solutions for everyday users, developers, and scalable enterprise solutions. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How SceneXplain Solved Video-to-Text Comprehension</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Pushing the boundaries of video-to-text comprehension, SceneXplain unveils the Inception algorithm: decoding narratives, acknowledging challenges, and inviting firsthand exploration. Dive into the next frontier of video comprehension.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 30, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the modern digital age, the line between visuals and the stories they convey is becoming increasingly blurred. SceneXplain has consistently been at the forefront of this transformation, setting <a href="https://jina.ai/news/scenexplain-vs-minigpt4-a-comprehensive-benchmark-of-top-5-image-captioning-algorithms-for-understanding-complex-scenes/?ref=jina-ai-gmbh.ghost.io">new standards in visual comprehension</a>. Starting with innovations in image-to-text and <a href="https://jina.ai/news/beyond-pixels-to-prose-scenexplains-hearth-algorithm-breathes-audible-life-into-images/?ref=jina-ai-gmbh.ghost.io">image-to-audio</a> generations, we've now extended our expertise into the intricate realm of video-to-text! This natural progression marks our latest endeavor, the <code>Inception</code> algorithm.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image and video storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><p>The power of video, with its dynamic interplay of images and sequences, captures narratives that are often richer and deeper than static images. Yet, unlocking these narratives remains a challenge. Here's where SceneXplain steps in. By leveraging advanced multimodal AI techniques, our platform doesn't merely provide superficial descriptions; it delves deeper to unearth and articulate the stories that unfold within videos. Beyond mere captions, SceneXplain strives for contextual understanding, ensuring each narrative is captured with the depth it deserves.</p><p>Developers and enterprises alike will find value in our system. Not only does SceneXplain bring sophisticated video storytelling tools to the table, but its seamless interface and adaptable API ensure that integrating these tools into your platforms or systems is as smooth as possible.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-23.png" class="kg-image" alt="" width="2000" height="984" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-23.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-23.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-23.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/image-23.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Don't forget to select the "Inception" algorithm from the model list to activate it.</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/share?thread=EWJcZuS3FpcKJ9AyRq9i&amp;ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-17.png" class="kg-image" alt="" width="1028" height="1828" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-17.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-17.png 1028w" sizes="(min-width: 720px) 720px"></a><figcaption>Click to play the video and view the results on SceneXplain</figcaption></figure><p>Join us as we dive deeper into the inception of the "Inception" algorithm and explore how it’s setting new paradigms in the world of video comprehension.</p><h2 id="the-imperative-of-video-to-text-comprehension-in-a-visual-first-digital-age"><strong>The Imperative of Video-to-Text Comprehension in a Visual-First Digital Age</strong></h2><p>In our digital epoch, the proliferation of visual content has outpaced almost every other medium. Videos, in particular, have mushroomed into the bedrock of content consumption. From short-form social media clips to extensive webinars, the digital ecosystem is awash with moving pixels. And while the explosion of video content signals a seismic shift in how information is shared and consumed, it also presents an intricate challenge: the sheer volume of content and the immediacy of its consumption.</p><h3 id="the-search-dilemma-from-pixels-to-text"><strong><strong>The Search Dilemma: From Pixels to Text</strong></strong></h3><p>Think about it. Every video that gets uploaded is, in essence, a repository of information. But how do search engines understand them? Unlike text, videos don’t lend themselves easily to the parsing and indexing mechanisms that power the modern web. This is where video-to-text transcends from a luxury to a necessity. Translating videos into text allows search engines to index, categorize, and rank them, making content not just accessible but discoverable.</p><h3 id="the-skim-economy-catering-to-the-impatient-user"><strong><strong>The Skim Economy: Catering to the Impatient User</strong></strong></h3><p>Today’s user is not the reader of yesteryears; they're skimmers and scanners. Not everyone has the time (or inclination) to sit through a 30-minute video. A textual summary, however, can be skimmed in mere minutes. Video comprehension caters to this very demographic, ensuring content remains consumable for the fast-paced digital nomad.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.theguardian.com/commentisfree/2018/aug/25/skim-reading-new-normal-maryanne-wolf?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Skim reading is the new normal. The effect on society is profound | Maryanne Wolf</div><div class="kg-bookmark-description">When the reading brain skims texts, we don’t have time to grasp complexity, to understand another’s feelings or to perceive beauty. We need a new literacy for the digital age writes Maryanne Wolf, author of Reader, Come Home</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.guim.co.uk/images/favicon-32x32.ico" alt=""><span class="kg-bookmark-author">The Guardian</span><span class="kg-bookmark-publisher">Maryanne Wolf</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://i.guim.co.uk/img/media/f51170cfbfdcb69dd0adf127db5aa79dbe480751/0_0_6667_4000/master/6667.jpg?width=1200&amp;height=630&amp;quality=85&amp;auto=format&amp;fit=crop&amp;overlay-align=bottom%2Cleft&amp;overlay-width=100p&amp;overlay-base64=L2ltZy9zdGF0aWMvb3ZlcmxheXMvdGctb3BpbmlvbnMtYWdlLTIwMTgucG5n&amp;enable=upscale&amp;s=6293bd1a0ebd769f7ddbf98255a729aa" alt=""></div></a></figure><h3 id="accessibility-bridging-the-gap"><strong><strong>Accessibility: Bridging the Gap</strong></strong></h3><p>A core tenet of the modern web is inclusivity. While videos are an excellent medium for many, they inadvertently sideline those with visual or auditory impairments. Converting videos to text ensures that content is universally accessible, not just to a select few. Interested readers are strongly recommended to follow our efforts in using SceneXplain to improve digital accessibility in the EU. </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</div><div class="kg-bookmark-description">Explore SceneXplain’s impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">World Health Organization</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png" alt=""></div></a></figure><h3 id="the-content-overload-making-sense-of-the-digital-deluge"><strong><strong>The Content Overload: Making Sense of the Digital Deluge</strong></strong></h3><p>Every minute, 500 hours of video are uploaded to platforms like YouTube. In this sea of content, how does one discern value? Automatic video comprehension can help platforms curate and recommend, ensuring users find not just any content, but relevant content.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-16.png" class="kg-image" alt="" width="566" height="562"><figcaption>Source: <a href="https://www.convinceandconvert.com/content-marketing/video-marketing-statistics/?ref=jina-ai-gmbh.ghost.io">12 Video Marketing Statistics You Need to Know in 2020&nbsp;</a></figcaption></figure><p>The pressing need for video comprehension or video-to-text techniques is not just about keeping pace with technological advancements; it's about shaping the future of content consumption. In an increasingly visual-first digital realm, understanding and articulating the stories within videos isn't just desirable — it's imperative.</p><h2 id="delving-into-the-mathematics-of-video-comprehension">Delving into the Mathematics of Video Comprehension</h2>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How SceneXplain Solved Video-to-Text Comprehension</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Pushing the boundaries of video-to-text comprehension, SceneXplain unveils the Inception algorithm: decoding narratives, acknowledging challenges, and inviting firsthand exploration. Dive into the next frontier of video comprehension.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 30, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the modern digital age, the line between visuals and the stories they convey is becoming increasingly blurred. SceneXplain has consistently been at the forefront of this transformation, setting <a href="https://jina.ai/news/scenexplain-vs-minigpt4-a-comprehensive-benchmark-of-top-5-image-captioning-algorithms-for-understanding-complex-scenes/?ref=jina-ai-gmbh.ghost.io">new standards in visual comprehension</a>. Starting with innovations in image-to-text and <a href="https://jina.ai/news/beyond-pixels-to-prose-scenexplains-hearth-algorithm-breathes-audible-life-into-images/?ref=jina-ai-gmbh.ghost.io">image-to-audio</a> generations, we've now extended our expertise into the intricate realm of video-to-text! This natural progression marks our latest endeavor, the <code>Inception</code> algorithm.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image and video storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><p>The power of video, with its dynamic interplay of images and sequences, captures narratives that are often richer and deeper than static images. Yet, unlocking these narratives remains a challenge. Here's where SceneXplain steps in. By leveraging advanced multimodal AI techniques, our platform doesn't merely provide superficial descriptions; it delves deeper to unearth and articulate the stories that unfold within videos. Beyond mere captions, SceneXplain strives for contextual understanding, ensuring each narrative is captured with the depth it deserves.</p><p>Developers and enterprises alike will find value in our system. Not only does SceneXplain bring sophisticated video storytelling tools to the table, but its seamless interface and adaptable API ensure that integrating these tools into your platforms or systems is as smooth as possible.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-23.png" class="kg-image" alt="" width="2000" height="984" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-23.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-23.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-23.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/image-23.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Don't forget to select the "Inception" algorithm from the model list to activate it.</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/share?thread=EWJcZuS3FpcKJ9AyRq9i&amp;ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-17.png" class="kg-image" alt="" width="1028" height="1828" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-17.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-17.png 1028w" sizes="(min-width: 720px) 720px"></a><figcaption>Click to play the video and view the results on SceneXplain</figcaption></figure><p>Join us as we dive deeper into the inception of the "Inception" algorithm and explore how it’s setting new paradigms in the world of video comprehension.</p><h2 id="the-imperative-of-video-to-text-comprehension-in-a-visual-first-digital-age"><strong>The Imperative of Video-to-Text Comprehension in a Visual-First Digital Age</strong></h2><p>In our digital epoch, the proliferation of visual content has outpaced almost every other medium. Videos, in particular, have mushroomed into the bedrock of content consumption. From short-form social media clips to extensive webinars, the digital ecosystem is awash with moving pixels. And while the explosion of video content signals a seismic shift in how information is shared and consumed, it also presents an intricate challenge: the sheer volume of content and the immediacy of its consumption.</p><h3 id="the-search-dilemma-from-pixels-to-text"><strong><strong>The Search Dilemma: From Pixels to Text</strong></strong></h3><p>Think about it. Every video that gets uploaded is, in essence, a repository of information. But how do search engines understand them? Unlike text, videos don’t lend themselves easily to the parsing and indexing mechanisms that power the modern web. This is where video-to-text transcends from a luxury to a necessity. Translating videos into text allows search engines to index, categorize, and rank them, making content not just accessible but discoverable.</p><h3 id="the-skim-economy-catering-to-the-impatient-user"><strong><strong>The Skim Economy: Catering to the Impatient User</strong></strong></h3><p>Today’s user is not the reader of yesteryears; they're skimmers and scanners. Not everyone has the time (or inclination) to sit through a 30-minute video. A textual summary, however, can be skimmed in mere minutes. Video comprehension caters to this very demographic, ensuring content remains consumable for the fast-paced digital nomad.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.theguardian.com/commentisfree/2018/aug/25/skim-reading-new-normal-maryanne-wolf?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Skim reading is the new normal. The effect on society is profound | Maryanne Wolf</div><div class="kg-bookmark-description">When the reading brain skims texts, we don’t have time to grasp complexity, to understand another’s feelings or to perceive beauty. We need a new literacy for the digital age writes Maryanne Wolf, author of Reader, Come Home</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.guim.co.uk/images/favicon-32x32.ico" alt=""><span class="kg-bookmark-author">The Guardian</span><span class="kg-bookmark-publisher">Maryanne Wolf</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://i.guim.co.uk/img/media/f51170cfbfdcb69dd0adf127db5aa79dbe480751/0_0_6667_4000/master/6667.jpg?width=1200&amp;height=630&amp;quality=85&amp;auto=format&amp;fit=crop&amp;overlay-align=bottom%2Cleft&amp;overlay-width=100p&amp;overlay-base64=L2ltZy9zdGF0aWMvb3ZlcmxheXMvdGctb3BpbmlvbnMtYWdlLTIwMTgucG5n&amp;enable=upscale&amp;s=6293bd1a0ebd769f7ddbf98255a729aa" alt=""></div></a></figure><h3 id="accessibility-bridging-the-gap"><strong><strong>Accessibility: Bridging the Gap</strong></strong></h3><p>A core tenet of the modern web is inclusivity. While videos are an excellent medium for many, they inadvertently sideline those with visual or auditory impairments. Converting videos to text ensures that content is universally accessible, not just to a select few. Interested readers are strongly recommended to follow our efforts in using SceneXplain to improve digital accessibility in the EU. </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</div><div class="kg-bookmark-description">Explore SceneXplain’s impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">World Health Organization</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png" alt=""></div></a></figure><h3 id="the-content-overload-making-sense-of-the-digital-deluge"><strong><strong>The Content Overload: Making Sense of the Digital Deluge</strong></strong></h3><p>Every minute, 500 hours of video are uploaded to platforms like YouTube. In this sea of content, how does one discern value? Automatic video comprehension can help platforms curate and recommend, ensuring users find not just any content, but relevant content.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-16.png" class="kg-image" alt="" width="566" height="562"><figcaption>Source: <a href="https://www.convinceandconvert.com/content-marketing/video-marketing-statistics/?ref=jina-ai-gmbh.ghost.io">12 Video Marketing Statistics You Need to Know in 2020&nbsp;</a></figcaption></figure><p>The pressing need for video comprehension or video-to-text techniques is not just about keeping pace with technological advancements; it's about shaping the future of content consumption. In an increasingly visual-first digital realm, understanding and articulating the stories within videos isn't just desirable — it's imperative.</p><h2 id="delving-into-the-mathematics-of-video-comprehension">Delving into the Mathematics of Video Comprehension</h2>
 <p>The modern quest to elucidate video content's narrative essence can be likened to the pursuit of converting a rich tapestry of visual sequences into coherent textual symphonies. To embark on this journey, we must first define our problem in a precise mathematical manner.</p>
 <p>Given a video $V$, comprising a series of frames ${f_1, f_2, ... f_n}$, our aim is to transform it into a series of textual descriptions or a summary $S$, such that $S = {s_1, s_2, ... s_k}$ where $k \leq n$.</p>
 <p>At the heart of this transformation lies the relationship between each frame $f_i$ and its corresponding summary statement $s_j$. Using Bayesian probabilistic notation, we can express this relationship as the conditional probability $P(s_j | f_i)$. However, given the sequential nature of videos, it's often the case that a summary statement $s_j$ is conditioned on a sequence of frames rather than an individual frame.</p>
@@ -22,4 +22,4 @@
 <p><span><span class="katex-display"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block"><semantics><mrow><munder><mrow><mi>max</mi><mo>⁡</mo></mrow><mi>S</mi></munder><munderover><mo>∏</mo><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>k</mi></munderover><mi>P</mi><mo stretchy="false">(</mo><msub><mi>s</mi><mi>j</mi></msub><mi mathvariant="normal">∣</mi><msub><mi>f</mi><mi>i</mi></msub><mo separator="true">,</mo><msub><mi>f</mi><mrow><mi>i</mi><mo>−</mo><mn>1</mn></mrow></msub><mo separator="true">,</mo><mi mathvariant="normal">.</mi><mi mathvariant="normal">.</mi><mi mathvariant="normal">.</mi><msub><mi>f</mi><mrow><mi>i</mi><mo>−</mo><mi>l</mi></mrow></msub><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex"> \max_{S} \prod_{j=1}^{k} P(s_j | f_i, f_{i-1}, ... f_{i-l}) </annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height: 3.2499em; vertical-align: -1.4138em;"></span><span class="mop op-limits"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height: 0.4306em;"><span class="" style="top: -2.3557em; margin-left: 0em;"><span class="pstrut" style="height: 3em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight" style="margin-right: 0.0576em;">S</span></span></span></span><span class="" style="top: -3em;"><span class="pstrut" style="height: 3em;"></span><span class=""><span class="mop">max</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height: 0.7443em;"><span class=""></span></span></span></span></span><span class="mspace" style="margin-right: 0.1667em;"></span><span class="mop op-limits"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height: 1.8361em;"><span class="" style="top: -1.8723em; margin-left: 0em;"><span class="pstrut" style="height: 3.05em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight" style="margin-right: 0.0572em;">j</span><span class="mrel mtight">=</span><span class="mord mtight">1</span></span></span></span><span class="" style="top: -3.05em;"><span class="pstrut" style="height: 3.05em;"></span><span class=""><span class="mop op-symbol large-op">∏</span></span></span><span class="" style="top: -4.3em; margin-left: 0em;"><span class="pstrut" style="height: 3.05em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight" style="margin-right: 0.0315em;">k</span></span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height: 1.4138em;"><span class=""></span></span></span></span></span><span class="mspace" style="margin-right: 0.1667em;"></span><span class="mord mathnormal" style="margin-right: 0.1389em;">P</span><span class="mopen">(</span><span class="mord"><span class="mord mathnormal">s</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height: 0.3117em;"><span class="" style="top: -2.55em; margin-left: 0em; margin-right: 0.05em;"><span class="pstrut" style="height: 2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight" style="margin-right: 0.0572em;">j</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height: 0.2861em;"><span class=""></span></span></span></span></span></span><span class="mord">∣</span><span class="mord"><span class="mord mathnormal" style="margin-right: 0.1076em;">f</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height: 0.3117em;"><span class="" style="top: -2.55em; margin-left: -0.1076em; margin-right: 0.05em;"><span class="pstrut" style="height: 2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight">i</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height: 0.15em;"><span class=""></span></span></span></span></span></span><span class="mpunct">,</span><span class="mspace" style="margin-right: 0.1667em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right: 0.1076em;">f</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height: 0.3117em;"><span class="" style="top: -2.55em; margin-left: -0.1076em; margin-right: 0.05em;"><span class="pstrut" style="height: 2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">i</span><span class="mbin mtight">−</span><span class="mord mtight">1</span></span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height: 0.2083em;"><span class=""></span></span></span></span></span></span><span class="mpunct">,</span><span class="mspace" style="margin-right: 0.1667em;"></span><span class="mord">...</span><span class="mord"><span class="mord mathnormal" style="margin-right: 0.1076em;">f</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height: 0.3361em;"><span class="" style="top: -2.55em; margin-left: -0.1076em; margin-right: 0.05em;"><span class="pstrut" style="height: 2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">i</span><span class="mbin mtight">−</span><span class="mord mathnormal mtight" style="margin-right: 0.0197em;">l</span></span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height: 0.2083em;"><span class=""></span></span></span></span></span></span><span class="mclose">)</span></span></span></span></span></span></p>
 <p>This formulation elegantly captures the essence of video comprehension — weaving a textual narrative from a series of interlinked visual frames, while also accounting for the inherent continuity and interdependence of video content.</p>
 <p>In this probablistic framework, our task not only becomes clearer but also lays the foundation for the development of algorithms, like Inception, that can effectively tackle the intricate nuances of the video-to-text conversion process.</p>
-<h2 id="tackling-the-challenges-keyframes-context-and-coherence"><strong>Tackling the Challenges: Keyframes, Context, and Coherence</strong></h2><p>In our earlier discussion on the mathematical framework of video comprehension, we highlighted the importance of a narrative continuum and the sequential dependence of frames. This context is vital in comprehending how we approach keyframe insights and descriptions.</p><h3 id="the-keyframe-conundrum-coherence-over-quantity"><strong><strong>The Keyframe Conundrum: Coherence Over Quantity</strong></strong></h3><p>A consistent series of keyframe insights ensures that the video's narrative essence remains undistorted. However, inconsistency in keyframes' details introduces fragmentation, leading to a disjunctive understanding where the context is lost. Instead of a clear narrative thread, you're left with disconnected vignettes, robbing the video of its richness and continuity.</p><p>The most direct approach would be to ascertain the "optimal" number of keyframes, capturing the essence without diluting the narrative. But what's optimal for a fast-paced action clip might differ from an introspective documentary. Additionally, the descriptions for each keyframe should be succinct yet sufficiently detailed to relay the frame's narrative weight.</p><h3 id="towards-an-adaptive-framework-balancing-details-and-density"><strong><strong>Towards an Adaptive Framework: Balancing Details and Density</strong></strong></h3><p>Defining the "right" balance of keyframes and the granularity of their descriptions is a nuanced challenge, with variances across video genres and styles. Taking a probabilistic stance, as per our Bayesian framework, the challenge boils down to maximizing the likelihood of our summarized content given the original video, while maintaining a controlled description density.</p><p>SceneXplain's base video summarization algorithm pragmatically navigates this challenge. Built on the principle that "<em>overloading with details can be more detrimental than being minimally informative,</em>" we've capped the keyframes to a maximum of 6 per minute and limited caption lengths to 20 words. This ensures clarity without overburdening the viewer, offering a distilled yet coherent narrative.</p><h3 id="the-road-ahead-dynamic-adaptations"><strong><strong>The Road Ahead: Dynamic Adaptations</strong></strong></h3><p>Recognizing the dynamic nature of videos and their myriad styles, SceneXplain is also committed to evolving its constraints. Future iterations are primed to make these metrics tunable, adapting to the unique requirements of different content, thus maintaining the Bayesian foundation of context and sequence.</p><h2 id="demonstrating-scenexplain-a-deep-dive-into-inceptions-excellence"><strong>Demonstrating SceneXplain: A Deep Dive into Inception's Excellence</strong></h2><p>As we transition from the theoretical framework and the challenges we navigated to bring SceneXplain to life, it's time to dive into its practical performance. Words, equations, and design philosophies can only convey so much — it's in the real-world application that an algorithm truly proves its mettle. And our Inception algorithm stands tall when subjected to the rigorous tests of Topicality, Details, and Factuality.</p><h3 id="details-not-just-what-meets-the-eye"><strong><strong>Details: Not Just What Meets the Eye</strong></strong></h3><p>Every frame of a video carries an expansive depth of information — from the nuanced expressions of a character to the intricate patterns on a distant artifact. Inception's prowess lies in not merely recognizing these myriad details but artfully weaving them into coherent and engaging narratives. Our demo showcases scenes replete with complexity and depth, and Inception's ability to encapsulate each facet, validating its unparalleled performance in capturing intricate visual information.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/share?thread=RuXPznfRGNtqdKJuJVQl&amp;ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-19.png" class="kg-image" alt="" width="1022" height="1826" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-19.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-19.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-19.png 1022w" sizes="(min-width: 720px) 720px"></a><figcaption>Click to play the video and view the results on SceneXplain</figcaption></figure><h3 id="topicality-finger-on-the-pulse"><strong><strong>Topicality: Finger on the Pulse</strong></strong></h3><p>In an age where information flows at breakneck speed and cultural contexts evolve almost daily, it's paramount for an algorithm to remain current and contextual. SceneXplain, powered by Inception, goes beyond just visually describing content. Whether it's referencing a recent global event, alluding to a trending meme, or identifying a breakout celebrity, our algorithm ensures that the generated captions resonate with what's topical, relevant, and engaging. Dive into our demos, and witness how Inception connects the visual narratives with the contemporary cultural zeitgeist.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/share?thread=EWJcZuS3FpcKJ9AyRq9i&amp;ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-20.png" class="kg-image" alt="" width="1018" height="1842" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-20.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-20.png 1018w" sizes="(min-width: 720px) 720px"></a><figcaption>Click to play the video and view the results on SceneXplain</figcaption></figure><h3 id="factuality-the-bedrock-of-trust"><strong><strong>Factuality: The Bedrock of Trust</strong></strong></h3><p>While creativity and engagement are crucial, they should never come at the expense of truthfulness. A tool like SceneXplain holds immense responsibility in ensuring the information it disseminates is accurate. Inception has been crafted with an unwavering commitment to factuality. Every caption it produces is meticulously vetted for accuracy, minimizing hallucinations and misinformation. Our demonstrations will highlight scenes where it's tempting for algorithms to falter, to extrapolate beyond what's present — but Inception stands firm, delivering trustworthy descriptions consistently.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/share?thread=rw3NJMGKiM2N9sEWB2TC&amp;ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-18.png" class="kg-image" alt="" width="1022" height="1822" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-18.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-18.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-18.png 1022w" sizes="(min-width: 720px) 720px"></a><figcaption>Click to play the video and view the results on SceneXplain</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/share?thread=3oq0bZmkGezlPThLGyM8&amp;ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-21.png" class="kg-image" alt="" width="1014" height="1716" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-21.png 1014w" sizes="(min-width: 720px) 720px"></a><figcaption>Click to play the video and view the results on SceneXplain</figcaption></figure><p>More examples can be found below:</p><ul><li><a href="https://scenex.jina.ai/share?thread=mFme4ygBpTOkSzpGEDBT&amp;ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">https://scenex.jina.ai/share?thread=mFme4ygBpTOkSzpGEDBT</a></li><li><a href="https://scenex.jina.ai/share?thread=RuXPznfRGNtqdKJuJVQl&amp;ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">https://scenex.jina.ai/share?thread=RuXPznfRGNtqdKJuJVQl</a></li><li><a href="https://scenex.jina.ai/share?thread=EWJcZuS3FpcKJ9AyRq9i&amp;ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">https://scenex.jina.ai/share?thread=EWJcZuS3FpcKJ9AyRq9i</a></li></ul><h2 id="known-limitations-of-the-inception-algorithm-embracing-transparency-and-ethical-responsibility"><strong>Known Limitations of the Inception Algorithm: Embracing Transparency and Ethical Responsibility</strong></h2><p>In the era of machine learning, it's tempting to herald algorithms as faultless, all-seeing entities. At SceneXplain, however, we firmly believe that recognizing and addressing an algorithm's limitations is just as important as celebrating its capabilities. As stewards of technology with potential societal impact, we bear the ethical responsibility of being transparent about the bounds of our creations. Here, we outline some of the known limitations of the Inception algorithm, allowing users to deploy it with a complete understanding of its scope.</p><h3 id="challenges-with-keyframe-detection"><strong><strong>Challenges with Keyframe Detection</strong></strong></h3><ul><li><strong>Small Region Of Interest (ROI)</strong>: In videos taken from a considerable distance without significant movement, the ROI is minimal. This can trip up similarity detection algorithms, causing them to perceive all frames as alike. A potential consequence? A 5-minute video might yield just 1 or 2 keyframes, translating to significant content loss.</li><li><strong>Proliferation of Scenes</strong>: Videos with rapid scene changes, like movie trailers, pose unique challenges. A sub-3-minute trailer could contain over a hundred disparate scenes, leading to a glut of keyframes. This not only increases the computational burden but also risks omitting crucial scenes when we apply a "max keyframe ratio per minute" filter.</li><li><strong>Artistic Interpretations</strong>: Videos with specific artistic styles, such as macro shots, time-lapses, or drone footage, defy conventional detection paradigms. Depending on zoom levels and playback speed, these could either produce an overabundance of keyframes or too few.</li></ul><h3 id="nuances-in-keyframe-captioning"><strong><strong>Nuances in Keyframe Captioning</strong></strong></h3><ul><li><strong>Contextually Dependent Frames</strong>: Frames that are abstract or hinge on an external context can confound the algorithm. This leads to captions that range from slightly off-kilter to downright nonsensical. Computationally generated images, extreme zoom-ins, or artistic interpretations are classic culprits.</li><li><strong>Detecting Subtly Erroneous Captions</strong>: If a caption, while incorrect, aligns with the general context of the video, spotting such errors becomes challenging.</li><li><strong>Detail Disproportionality</strong>: A minor video element that's densely detailed might be accorded undue prominence over the main subject if it's relatively simpler. This can skew the narrative thread.</li><li><strong>Insufficient Details, Incorrect Associations</strong>: A recurring element across several keyframes, if not detailed enough, might be misinterpreted. For instance, the same individual appearing across multiple frames could be erroneously recognized as multiple people.</li></ul><p>Our commitment to transparency and continual improvement means we're always working on these challenges. However, we believe that only by acknowledging these limitations can we truly leverage the Inception algorithm ethically and responsibly.</p><h2 id="in-conclusion-the-journey-and-the-invitation">In Conclusion: The Journey and the Invitation</h2><p>The landscape of video comprehension has been evolving at a dizzying pace, and at SceneXplain, we're excited to be at the forefront of this revolution with our Inception algorithm. From understanding the nuances of complex narratives to grappling with the intricacies of contemporary culture, Inception promises a transformative experience in video-to-text translation.</p><p>However, as with all pioneering technologies, it's not without its challenges. We've approached these not as setbacks, but as opportunities for growth and refinement. Our transparency in sharing these challenges stems from a commitment to ethical and responsible AI development.</p><p>But, words can only convey so much. The true power and potential of Inception is best experienced firsthand. We invite you to try SceneXplain's Inception algorithm for yourself. Dive deep into its capabilities, test its boundaries, and witness how it can redefine your understanding of visual narratives.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image and video storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><p>The future of video comprehension beckons, and with SceneXplain's Inception, you're not just a spectator – you're a part of the narrative. 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+<h2 id="tackling-the-challenges-keyframes-context-and-coherence"><strong>Tackling the Challenges: Keyframes, Context, and Coherence</strong></h2><p>In our earlier discussion on the mathematical framework of video comprehension, we highlighted the importance of a narrative continuum and the sequential dependence of frames. This context is vital in comprehending how we approach keyframe insights and descriptions.</p><h3 id="the-keyframe-conundrum-coherence-over-quantity"><strong><strong>The Keyframe Conundrum: Coherence Over Quantity</strong></strong></h3><p>A consistent series of keyframe insights ensures that the video's narrative essence remains undistorted. However, inconsistency in keyframes' details introduces fragmentation, leading to a disjunctive understanding where the context is lost. Instead of a clear narrative thread, you're left with disconnected vignettes, robbing the video of its richness and continuity.</p><p>The most direct approach would be to ascertain the "optimal" number of keyframes, capturing the essence without diluting the narrative. But what's optimal for a fast-paced action clip might differ from an introspective documentary. Additionally, the descriptions for each keyframe should be succinct yet sufficiently detailed to relay the frame's narrative weight.</p><h3 id="towards-an-adaptive-framework-balancing-details-and-density"><strong><strong>Towards an Adaptive Framework: Balancing Details and Density</strong></strong></h3><p>Defining the "right" balance of keyframes and the granularity of their descriptions is a nuanced challenge, with variances across video genres and styles. Taking a probabilistic stance, as per our Bayesian framework, the challenge boils down to maximizing the likelihood of our summarized content given the original video, while maintaining a controlled description density.</p><p>SceneXplain's base video summarization algorithm pragmatically navigates this challenge. Built on the principle that "<em>overloading with details can be more detrimental than being minimally informative,</em>" we've capped the keyframes to a maximum of 6 per minute and limited caption lengths to 20 words. This ensures clarity without overburdening the viewer, offering a distilled yet coherent narrative.</p><h3 id="the-road-ahead-dynamic-adaptations"><strong><strong>The Road Ahead: Dynamic Adaptations</strong></strong></h3><p>Recognizing the dynamic nature of videos and their myriad styles, SceneXplain is also committed to evolving its constraints. Future iterations are primed to make these metrics tunable, adapting to the unique requirements of different content, thus maintaining the Bayesian foundation of context and sequence.</p><h2 id="demonstrating-scenexplain-a-deep-dive-into-inceptions-excellence"><strong>Demonstrating SceneXplain: A Deep Dive into Inception's Excellence</strong></h2><p>As we transition from the theoretical framework and the challenges we navigated to bring SceneXplain to life, it's time to dive into its practical performance. Words, equations, and design philosophies can only convey so much — it's in the real-world application that an algorithm truly proves its mettle. And our Inception algorithm stands tall when subjected to the rigorous tests of Topicality, Details, and Factuality.</p><h3 id="details-not-just-what-meets-the-eye"><strong><strong>Details: Not Just What Meets the Eye</strong></strong></h3><p>Every frame of a video carries an expansive depth of information — from the nuanced expressions of a character to the intricate patterns on a distant artifact. Inception's prowess lies in not merely recognizing these myriad details but artfully weaving them into coherent and engaging narratives. Our demo showcases scenes replete with complexity and depth, and Inception's ability to encapsulate each facet, validating its unparalleled performance in capturing intricate visual information.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/share?thread=RuXPznfRGNtqdKJuJVQl&amp;ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-19.png" class="kg-image" alt="" width="1022" height="1826" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-19.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-19.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-19.png 1022w" sizes="(min-width: 720px) 720px"></a><figcaption>Click to play the video and view the results on SceneXplain</figcaption></figure><h3 id="topicality-finger-on-the-pulse"><strong><strong>Topicality: Finger on the Pulse</strong></strong></h3><p>In an age where information flows at breakneck speed and cultural contexts evolve almost daily, it's paramount for an algorithm to remain current and contextual. SceneXplain, powered by Inception, goes beyond just visually describing content. Whether it's referencing a recent global event, alluding to a trending meme, or identifying a breakout celebrity, our algorithm ensures that the generated captions resonate with what's topical, relevant, and engaging. Dive into our demos, and witness how Inception connects the visual narratives with the contemporary cultural zeitgeist.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/share?thread=EWJcZuS3FpcKJ9AyRq9i&amp;ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-20.png" class="kg-image" alt="" width="1018" height="1842" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-20.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-20.png 1018w" sizes="(min-width: 720px) 720px"></a><figcaption>Click to play the video and view the results on SceneXplain</figcaption></figure><h3 id="factuality-the-bedrock-of-trust"><strong><strong>Factuality: The Bedrock of Trust</strong></strong></h3><p>While creativity and engagement are crucial, they should never come at the expense of truthfulness. A tool like SceneXplain holds immense responsibility in ensuring the information it disseminates is accurate. Inception has been crafted with an unwavering commitment to factuality. Every caption it produces is meticulously vetted for accuracy, minimizing hallucinations and misinformation. Our demonstrations will highlight scenes where it's tempting for algorithms to falter, to extrapolate beyond what's present — but Inception stands firm, delivering trustworthy descriptions consistently.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/share?thread=rw3NJMGKiM2N9sEWB2TC&amp;ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-18.png" class="kg-image" alt="" width="1022" height="1822" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-18.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-18.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-18.png 1022w" sizes="(min-width: 720px) 720px"></a><figcaption>Click to play the video and view the results on SceneXplain</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/share?thread=3oq0bZmkGezlPThLGyM8&amp;ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-21.png" class="kg-image" alt="" width="1014" height="1716" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-21.png 1014w" sizes="(min-width: 720px) 720px"></a><figcaption>Click to play the video and view the results on SceneXplain</figcaption></figure><p>More examples can be found below:</p><ul><li><a href="https://scenex.jina.ai/share?thread=mFme4ygBpTOkSzpGEDBT&amp;ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">https://scenex.jina.ai/share?thread=mFme4ygBpTOkSzpGEDBT</a></li><li><a href="https://scenex.jina.ai/share?thread=RuXPznfRGNtqdKJuJVQl&amp;ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">https://scenex.jina.ai/share?thread=RuXPznfRGNtqdKJuJVQl</a></li><li><a href="https://scenex.jina.ai/share?thread=EWJcZuS3FpcKJ9AyRq9i&amp;ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">https://scenex.jina.ai/share?thread=EWJcZuS3FpcKJ9AyRq9i</a></li></ul><h2 id="known-limitations-of-the-inception-algorithm-embracing-transparency-and-ethical-responsibility"><strong>Known Limitations of the Inception Algorithm: Embracing Transparency and Ethical Responsibility</strong></h2><p>In the era of machine learning, it's tempting to herald algorithms as faultless, all-seeing entities. At SceneXplain, however, we firmly believe that recognizing and addressing an algorithm's limitations is just as important as celebrating its capabilities. As stewards of technology with potential societal impact, we bear the ethical responsibility of being transparent about the bounds of our creations. Here, we outline some of the known limitations of the Inception algorithm, allowing users to deploy it with a complete understanding of its scope.</p><h3 id="challenges-with-keyframe-detection"><strong><strong>Challenges with Keyframe Detection</strong></strong></h3><ul><li><strong>Small Region Of Interest (ROI)</strong>: In videos taken from a considerable distance without significant movement, the ROI is minimal. This can trip up similarity detection algorithms, causing them to perceive all frames as alike. A potential consequence? A 5-minute video might yield just 1 or 2 keyframes, translating to significant content loss.</li><li><strong>Proliferation of Scenes</strong>: Videos with rapid scene changes, like movie trailers, pose unique challenges. A sub-3-minute trailer could contain over a hundred disparate scenes, leading to a glut of keyframes. This not only increases the computational burden but also risks omitting crucial scenes when we apply a "max keyframe ratio per minute" filter.</li><li><strong>Artistic Interpretations</strong>: Videos with specific artistic styles, such as macro shots, time-lapses, or drone footage, defy conventional detection paradigms. Depending on zoom levels and playback speed, these could either produce an overabundance of keyframes or too few.</li></ul><h3 id="nuances-in-keyframe-captioning"><strong><strong>Nuances in Keyframe Captioning</strong></strong></h3><ul><li><strong>Contextually Dependent Frames</strong>: Frames that are abstract or hinge on an external context can confound the algorithm. This leads to captions that range from slightly off-kilter to downright nonsensical. Computationally generated images, extreme zoom-ins, or artistic interpretations are classic culprits.</li><li><strong>Detecting Subtly Erroneous Captions</strong>: If a caption, while incorrect, aligns with the general context of the video, spotting such errors becomes challenging.</li><li><strong>Detail Disproportionality</strong>: A minor video element that's densely detailed might be accorded undue prominence over the main subject if it's relatively simpler. This can skew the narrative thread.</li><li><strong>Insufficient Details, Incorrect Associations</strong>: A recurring element across several keyframes, if not detailed enough, might be misinterpreted. For instance, the same individual appearing across multiple frames could be erroneously recognized as multiple people.</li></ul><p>Our commitment to transparency and continual improvement means we're always working on these challenges. However, we believe that only by acknowledging these limitations can we truly leverage the Inception algorithm ethically and responsibly.</p><h2 id="in-conclusion-the-journey-and-the-invitation">In Conclusion: The Journey and the Invitation</h2><p>The landscape of video comprehension has been evolving at a dizzying pace, and at SceneXplain, we're excited to be at the forefront of this revolution with our Inception algorithm. From understanding the nuances of complex narratives to grappling with the intricacies of contemporary culture, Inception promises a transformative experience in video-to-text translation.</p><p>However, as with all pioneering technologies, it's not without its challenges. We've approached these not as setbacks, but as opportunities for growth and refinement. Our transparency in sharing these challenges stems from a commitment to ethical and responsible AI development.</p><p>But, words can only convey so much. The true power and potential of Inception is best experienced firsthand. We invite you to try SceneXplain's Inception algorithm for yourself. Dive deep into its capabilities, test its boundaries, and witness how it can redefine your understanding of visual narratives.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image and video storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><p>The future of video comprehension beckons, and with SceneXplain's Inception, you're not just a spectator – you're a part of the narrative. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>How to Caption Image Segments with SceneXplain: Introducing Crop'n Explain</title><meta charset="utf-8"><meta name="title" content="How to Caption Image Segments with SceneXplain: Introducing Crop'n Explain"><meta name="description" content="SceneXplain: Precise image insights, webcam uploads, multi-API keys, and more user-friendly updates."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/how-to-caption-image-segments-with-scenexplain-introducing-cropn-explain"><meta property="og:title" content="How to Caption Image Segments with SceneXplain: Introducing Crop'n Explain"><meta property="og:description" content="SceneXplain: Precise image insights, webcam uploads, multi-API keys, and more user-friendly updates."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels--14-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/how-to-caption-image-segments-with-scenexplain-introducing-cropn-explain"><meta property="twitter:title" content="How to Caption Image Segments with SceneXplain: Introducing Crop'n Explain"><meta property="twitter:description" content="SceneXplain: Precise image insights, webcam uploads, multi-API keys, and more user-friendly updates."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels--14-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How to Caption Image Segments with SceneXplain: Introducing Crop'n Explain</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">SceneXplain: Precise image insights, webcam uploads, multi-API keys, and more user-friendly updates.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Miruna Nedelcu</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 27, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>We're excited to introduce some exciting updates to SceneXplain 0.16.5, your reliable platform for uncovering the hidden stories within your images.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Try The New Features Now</span></p></figcaption></figure><p>Let's dive right in and explore these improvements!</p><h2 id="focus-on-what-matters-most-in-your-images-with-cropn-explain">Focus On What Matters Most in Your Images with Crop'n Explain</h2><p>With Crop'n Explain, you can extract insights and descriptions for the elements that most matter to you. </p><p>It's as simple as uploading an image and selecting your area of interest. Our advanced computer vision algorithm then springs into action, automatically generating accurate and detailed captions for it. </p><p>Whether you're a content creator, media professional, SEO expert, or part of an e-commerce enterprise, Crop'n Explain provides the ultimate tool for making sense of the visual world.</p><figure class="kg-card kg-video-card kg-width-regular kg-card-hascaption" data-kg-thumbnail="https://jina-ai-gmbh.ghost.io/content/media/2023/10/Blogpost_thumb.jpg" data-kg-custom-thumbnail="">
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How to Caption Image Segments with SceneXplain: Introducing Crop'n Explain</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">SceneXplain: Precise image insights, webcam uploads, multi-API keys, and more user-friendly updates.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Miruna Nedelcu</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 27, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>We're excited to introduce some exciting updates to SceneXplain 0.16.5, your reliable platform for uncovering the hidden stories within your images.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Try The New Features Now</span></p></figcaption></figure><p>Let's dive right in and explore these improvements!</p><h2 id="focus-on-what-matters-most-in-your-images-with-cropn-explain">Focus On What Matters Most in Your Images with Crop'n Explain</h2><p>With Crop'n Explain, you can extract insights and descriptions for the elements that most matter to you. </p><p>It's as simple as uploading an image and selecting your area of interest. Our advanced computer vision algorithm then springs into action, automatically generating accurate and detailed captions for it. </p><p>Whether you're a content creator, media professional, SEO expert, or part of an e-commerce enterprise, Crop'n Explain provides the ultimate tool for making sense of the visual world.</p><figure class="kg-card kg-video-card kg-width-regular kg-card-hascaption" data-kg-thumbnail="https://jina-ai-gmbh.ghost.io/content/media/2023/10/Blogpost_thumb.jpg" data-kg-custom-thumbnail="">
             <div class="kg-video-container">
                 <video src="https://jina-ai-gmbh.ghost.io/content/media/2023/10/Blogpost.mp4" poster="https://img.spacergif.org/v1/1924x1080/0a/spacer.png" width="1924" height="1080" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/media/2023/10/Blogpost_thumb.jpg') 50% 50% / cover no-repeat;"></video>
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             <figcaption><p><span style="white-space: pre-wrap;">See Multi API Key Management In Action</span></p></figcaption>
-        </figure><p>Whether your focus is on image captioning or any other project aspect, these unique API keys offer flexibility and improve workflow coordination.</p><p>Stay tuned for more updates, your feedback continually drives our commitment to improving SceneXplain. </p><p>Happy exploring! </p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fhow-to-caption-image-segments-with-scenexplain-introducing-cropn-explain%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+        </figure><p>Whether your focus is on image captioning or any other project aspect, these unique API keys offer flexibility and improve workflow coordination.</p><p>Stay tuned for more updates, your feedback continually drives our commitment to improving SceneXplain. </p><p>Happy exploring! </p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fhow-to-caption-image-segments-with-scenexplain-introducing-cropn-explain%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>How to Manage Jina Resources with Namespace</title><meta charset="utf-8"><meta name="title" content="How to Manage Jina Resources with Namespace"><meta name="description" content="With Jina AI Cloud's user namespaces, all users can have their own DocumentArrays and Executors with the same name, with no fear of naming conflicts."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/how-to-manage-jina-resources-with-namespaces"><meta property="og:title" content="How to Manage Jina Resources with Namespace"><meta property="og:description" content="With Jina AI Cloud's user namespaces, all users can have their own DocumentArrays and Executors with the same name, with no fear of naming conflicts."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--35-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/how-to-manage-jina-resources-with-namespaces"><meta property="twitter:title" content="How to Manage Jina Resources with Namespace"><meta property="twitter:description" content="With Jina AI Cloud's user namespaces, all users can have their own DocumentArrays and Executors with the same name, with no fear of naming conflicts."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--35-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How to Manage Jina Resources with Namespace</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With Jina AI Cloud's user namespaces, all users can have their own DocumentArrays and Executors with the same name, with no fear of naming conflicts.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/492616.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Degi</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 16, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Over the past year, we’ve been rapidly expanding Jina AI Cloud, starting with our <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Executor Hub</a>, and now encompassing <a href="https://docarray.jina.ai/fundamentals/cloud-support/data/?ref=jina-ai-gmbh.ghost.io">DocumentArray storage</a>, <a href="https://docs.jina.ai/fundamentals/jcloud/?ref=jina-ai-gmbh.ghost.io">hosted Flows</a> and <a href="https://now.jina.ai/?ref=jina-ai-gmbh.ghost.io">cloud apps</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">The most advanced MLOps platform for multimodal AI, neural search and creative AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a></figure><p>That’s a lot of stuff to manage! We’re introducing <strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong>user namespaces</strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong> to make things easier for all our users.</p><h2 id="namespace">Namespace</h2><p>Previously, if Alice and Bob both wanted to push a DocumentArray called <code>fashion-mnist</code>, whoever pushed first would get the name. That means Bob might have to go with <code>fashion-mnist2</code> or similar. With more people using Jina AI Cloud, naming conflicts could become commonplace.</p><p>With user namespaces, both Alice and Bob can have their own <code>fashion_mnist</code> DocumentArrays (or Executors with the same name) with no fear of naming conflicts.</p><p>The new namespace apply to two important resources inside Jina AI ecosystem: <strong>DocumentArray</strong> and <strong>Executor</strong>. </p><h3 id="schema">Schema</h3><p>Moving forwards, names for DocumentArrays and Hub Executors will follow the new schema, <code>namespace/resource</code>:</p><table>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="9450dfa8-ea0c-4ef7-8a76-e6c7aa5cdacd" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="9450dfa8-ea0c-4ef7-8a76-e6c7aa5cdacd" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How to Manage Jina Resources with Namespace</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With Jina AI Cloud's user namespaces, all users can have their own DocumentArrays and Executors with the same name, with no fear of naming conflicts.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/492616.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Degi</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 16, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Over the past year, we’ve been rapidly expanding Jina AI Cloud, starting with our <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Executor Hub</a>, and now encompassing <a href="https://docarray.jina.ai/fundamentals/cloud-support/data/?ref=jina-ai-gmbh.ghost.io">DocumentArray storage</a>, <a href="https://docs.jina.ai/fundamentals/jcloud/?ref=jina-ai-gmbh.ghost.io">hosted Flows</a> and <a href="https://now.jina.ai/?ref=jina-ai-gmbh.ghost.io">cloud apps</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">The most advanced MLOps platform for multimodal AI, neural search and creative AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a></figure><p>That’s a lot of stuff to manage! We’re introducing <strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong>user namespaces</strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong> to make things easier for all our users.</p><h2 id="namespace">Namespace</h2><p>Previously, if Alice and Bob both wanted to push a DocumentArray called <code>fashion-mnist</code>, whoever pushed first would get the name. That means Bob might have to go with <code>fashion-mnist2</code> or similar. With more people using Jina AI Cloud, naming conflicts could become commonplace.</p><p>With user namespaces, both Alice and Bob can have their own <code>fashion_mnist</code> DocumentArrays (or Executors with the same name) with no fear of naming conflicts.</p><p>The new namespace apply to two important resources inside Jina AI ecosystem: <strong>DocumentArray</strong> and <strong>Executor</strong>. </p><h3 id="schema">Schema</h3><p>Moving forwards, names for DocumentArrays and Hub Executors will follow the new schema, <code>namespace/resource</code>:</p><table>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How to Personalize Stable Diffusion for ALL the Things</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI's BIG metamodel lets you fine-tune Stable Diffusion to the next level, creating images of multiple subjects in any style you want</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 108.35%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/IMG_2227-5-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Joschka Braun, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 30, 2023 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/BIG_eq.png" class="kg-image" alt="" width="900" height="300" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/BIG_eq.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/BIG_eq.png 900w" sizes="(min-width: 720px) 720px"></figure><p>Jina AI is really into generative AI. It started out with <a href="https://github.com/jina-ai/dalle-flow?ref=jina-ai-gmbh.ghost.io">DALL·E Flow</a>, swiftly followed by <a href="https://colab.research.google.com/github/jina-ai/discoart/blob/main/discoart.ipynb?ref=jina-ai-gmbh.ghost.io">DiscoArt</a>. And then…<strong>🦗🦗</strong><em><strong>&lt;</strong>cricket sounds<strong>&gt;</strong></em><strong>🦗🦗</strong>. At least for a while…</p><p>That while has ended. We’re Back In the Game, baby. Big time, with our new <a href="https://github.com/jina-ai/big_creative_ai?ref=jina-ai-gmbh.ghost.io">BIG metamodel</a>. You might be wondering: What’s so meta about it? Before you needed multiple Stable Diffusion models, but now with BIG you have one model for everything.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-text">BIG stands for Back In (the) Game. If we ever get out of the game and get Back At the Game Again, we’ll have to go with BAGA. I hope we can afford the baseball caps.</div></div><p>In short, BIG lets you fine-tune Stable Diffusion to the next level, letting you create images of multiple subjects and in any style you want. That means you can take a picture of you and a picture of your pooch and combine them into a composite image in the style of Picasso, Pixar or pop art.</p><p>We created BIG by taking the <a href="https://doi.org/10.48550/arXiv.2208.12242?ref=jina-ai-gmbh.ghost.io">DreamBooth paper</a>, which allows fine-tuning with one subject, and leveling it up it into a metamodel to learn <em>multiple</em> new objects without using up all your compute. In this blog post we’ll go over how we did that, and how well it works.</p><p>But first, let’s take a quick look at how we got here, by starting off with Stable Diffusion itself.</p><h2 id="stable-diffusion-fine-tune-to-your-favorite-artist-but-forget-everyone-else">Stable Diffusion: Fine-tune to your favorite artist (but forget everyone else)</h2><p>In the beginning there was Stable Diffusion and it was good. “Create a Banksy picture” you would say, and verily a Banksy would be created. “Create an artwork in the style of Picasso” you would exclaim. And verily an image of a woman with too many angles would be created.</p><p>“Generate an image in the style of <a href="https://www.leonloewentraut.de/?ref=jina-ai-gmbh.ghost.io">Leon Löwentraut</a>” you proclaim. And Stable Diffusion did say “uh, what? lol I’ll give it my best. And verily it was rubbish.</p><p>Luckily, this can be fixed by fine-tuning (yeah, we’re dropping the Biblical speak). If you feed Stable Diffusion a Leon Löwentraut image it can learn his style (using, for example, <a href="https://huggingface.co/docs/diffusers/training/text2image?ref=jina-ai-gmbh.ghost.io">text-to-image fine-tuning for Stable Diffusion</a>.)</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/000000001-1.jpg" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1.0058 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2022-11-23-at-14.50.14-1.png" width="1040" height="1034" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2022-11-23-at-14.50.14-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2022-11-23-at-14.50.14-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2022-11-23-at-14.50.14-1.png 1040w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: An actual painting from Leon Löwentraut, Right: Generated image for Leon Löwentraut</figcaption></figure><p>The only problem is it gets amnesia for everything else it’s learned before. So if you then try to create the style of Banksy or Picasso on your newly fine-tuned model they all turn out pretty Löwentrautian:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-7-2.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1.0058 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2022-11-23-at-15.10.30-1.png" width="1040" height="1034" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2022-11-23-at-15.10.30-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2022-11-23-at-15.10.30-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2022-11-23-at-15.10.30-1.png 1040w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: Generated image by Stable Diffusionwith prompt <code>a banksy painting</code>, before fine-tuning; Right: Generated images for prompt <code>a banksy painting</code>, after fine-tuning to Löwentraut.</figcaption></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-3-1.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1.0058 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2022-11-23-at-14.49.09-1.png" width="1040" height="1034" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2022-11-23-at-14.49.09-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2022-11-23-at-14.49.09-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2022-11-23-at-14.49.09-1.png 1040w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: Generated image by Stable Diffusion with prompt <code>a picasso painting</code>, before fine-tuning; Right: Generated image for prompt <code>a picasso painting</code>, after fine-tuning to Löwentraut</figcaption></figure><h2 id="dreambooth-fine-tune-to-your-favorite-artist-and-remember">DreamBooth: Fine-tune to your favorite artist (and remember!)</h2><p>DreamBooth fixes that. At least to a point. You want to train it for your dog? Piece of cake. Fine-tune it for your favorite artist? A walk in the park. And Mona Lisa would still look like it came from Leonardo and Starry Night from Van Gogh.</p><p>It does this by extending Stable Diffusion’s fine-tuning loss with a prior preservation loss to train the model to still generate diverse images for the category of that style (e.g. Löwentraut) or object (e.g. a dog). The prior preservation loss is the mean squared error of the now generated images and the pre-training generated images for the category in the latent space.</p><p>This fine-tuning involves two prompts:</p><ul><li>a <code>[CATEGORY]</code>: The prompt for the prior preservation loss is the category of the style or object in question, like <code>dog</code> or <code>painting</code>.</li><li>a <code>[RARE_IDENTIFIER] [CATEGORY]</code>: The prompt for fine-tuning to a new object or style, generally a string that corresponds to a token the model is unfamiliar with. This is a unique reference to the object you want Stable Diffusion to learn. Example strings would be <code>sks</code> or <code>btb</code>.</li></ul><p>So, to fine-tune Stable Diffusion to create images of your dog, you would:</p><ul><li>Take 5-8 high quality images of your dog.</li><li>Fine-tune the model to recreate these images for the prompt <code>a sks dog</code> and the same time still create diverse images for the prompt <code>a dog</code>.</li></ul><p>Creating diverse images is helped along the way by generating images for the prompt <code>a dog</code> and using them as training images.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.52.28.png" class="kg-image" alt="" width="2000" height="1569" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.52.28.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.52.28.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.52.28.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.52.28.png 2004w" sizes="(min-width: 720px) 720px"><figcaption>Diagram taken from DreamBooth paper</figcaption></figure><h2 id="unstable-confusion-the-amnesia-creeps-back-in">Unstable Confusion: The amnesia creeps back in</h2><p>So far, so good! But what if you first use DreamBooth to fine-tune Stable Diffusion on your dog, then train on Leon Löwentraut, <em>then</em> ask it to create a picture of your dog in his style? Or train for <code>artist_1</code>, then train for <code>artist_2</code>, then try to create a new image by <code>artist_1</code>?</p><p>That shouldn’t be too hard, right?</p><p>Too hard for DreamBooth unfortunately.</p><p>DreamBooth falls over on this because it has a selective short-term memory. Using it to teach Stable Diffusion something new (let’s say the style of Löwentraut) works great. And then you can create images of all kinds of places and objects (already known to Stable Diffusion) in his style. But then if you decide to train it in the style of another artist it’ll forget everything it learned about Löwentraut’s style.</p><p>That’s why we created BIG: To let you train on multiple objects and styles <em>without</em> the amnesia. But more on that in a later section.</p><p>To see DreamBooth’s amnesia in action, let’s use it to fine-tune a model for two different artists:</p><ul><li>Leon Löwentraut (using the <code>RARE_IDENTIFIER</code> of <code>lnl</code>)</li><li><a href="https://www.instagram.com/vexx/?ref=jina-ai-gmbh.ghost.io">Vexx</a> (using the <code>RARE_IDENTIFIER</code> of <code>qzq</code>)</li></ul><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/000000003-1.jpg" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/000000000-2.jpg" width="512" height="512" alt=""></div></div></div><figcaption>Left: Another example of an actual Leon Löwentraut painting; Right: An image from Vexx.</figcaption></figure><p>To generate a painting in one of the above styles, we’d use a prompt like <code>a lnl painting</code> or <code>a qzq painting</code>.</p><p>Using DreamBooth and the prompt <code>a lnl painting</code> to fine-tune a model to fit the art style of Leon Löwentraut works great. &nbsp;For this we used four training images and trained for 400 steps with a learning rate of <code>1e-6</code>.</p><p>The left and center images show the model before fine-tuning. Note how it doesn’t know either <code>lnl</code> or <code>loewentraut</code>.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-8-1.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-5-1.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.05.05-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-11.05.05-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-11.05.05-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-11.05.05-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.05.05-1.png 1618w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: Generated image by Stable Diffusion with prompt <code>a qzq painting</code>; Center: Generated image by Stable Diffusion with prompt <code>a vexx painting</code>; Right: Generated image for <code>a qzq painting</code> after fine-tuning for Vexx.</figcaption></figure><p>But can the model still produce images in the styles of Picasso, Matisse and Banksy? Yes!</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-7--1--1.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-9-1.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-8--1--1.png" width="512" height="512" alt=""></div></div></div><figcaption>Left: Generated image for prompt <code>a banksy painting</code> after fine-tuning for Vexx; Center: Generated image for prompt <code>a mattisse painting</code> after fine-tuning for Vexx; Left: Generated image for prompt <code>a picasso painting</code> after fine-tuning for Vexx.</figcaption></figure><p>Now, after learning Vexx, does our model still remember Leon Löwentraut?</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.06.41.png" class="kg-image" alt="" width="1618" height="1618" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-11.06.41.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-11.06.41.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-11.06.41.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.06.41.png 1618w" sizes="(min-width: 720px) 720px"><figcaption>Generated image for <code>a lnl painting</code> after fine-tuning for Vexx.</figcaption></figure><p>Damn. Where did Leon go? It seems fine-tuning for Vexx overpowered Stable Diffusion’s memory of Leon. And it would do just the same if we trained it first on pictures of our favorite pooch and then secondly on our favorite artist. The result? Bye bye doggie.</p><h2 id="how-can-we-cure-dreambooth%E2%80%99s-amnesia">How can we cure DreamBooth’s amnesia?</h2><p>To solve the problem of forgetting Leon Löwentraut while learning Vexx, we included the images of Leon Löwentraut in the prior preservation loss during the fine-tuning. This is equivalent to further fine-tuning on Löwentraut while fine-tuning on Vexx, but less so than the original fine-tuning of Löwentraut. It works best to reuse the actual images for the style than the images the model generated.</p><p>So, now we can generate all the artists we encounter in our travels. After teaching &nbsp;Stable Diffusion model to create images in the style of Leon Löwentraut from the prompt <code>a lnl painting</code>, we wanted to create images of our favourite mate tea bottle. So, again we used the Leon Löwentraut fine-tuned model as initialization to train my Stable Diffusion model to create images of <a href="https://de.wikipedia.org/wiki/Mio_Mio_Mate?ref=jina-ai-gmbh.ghost.io">Mio Mio Mate</a> for <code>a sks bottle</code> (giving it a unique <code>RARE_IDENTIFIER</code>).</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/IMG_3551-1.jpg" width="2000" height="2000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/IMG_3551-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/IMG_3551-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/IMG_3551-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/01/IMG_3551-1.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-5--1--1.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-0-1.png" width="512" height="512" alt=""></div></div></div><figcaption>Left: Picture taken of a mio mio mate bottle, used for fine-tuning; Center: Generated image by Stable Diffusion with prompt: <code>a mio mio mate bottle</code>; Right: Generated image by Stable Diffusion with prompt: <code>a sks bottle</code></figcaption></figure><p>Again, this works for the new object, yet the model doesn’t quite remember how to produce images for Leon Löwentraut under <code>a lnl painting</code>.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.14.31-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-11.14.31-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-11.14.31-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-11.14.31-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.14.31-1.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.14.38-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-11.14.38-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-11.14.38-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-11.14.38-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.14.38-1.png 1618w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: Generated image for <code>a sks bottle</code> after fine-tuning for Mio Mio bottle; Right: Generated image for <code>a lnl painting</code> after fine-tuning for Mio Mio bottle.</figcaption></figure><p>To solve this issue, we can also think about using the previous images for Leon Löwentraut in the prior preservation loss. This helps remember the style of Leon Löwentraut. Yet, art styles which have similar geometric features (like Picasso) are not as accurately reproduced. This makes intuitive sense and is also the reason DreamBooth was introduced in the first place. Building on it, we need to not only incorporate the images of Leon Löwentraut in the prior preservation loss but also images of paintings, i.e., incorporate additionally the previous objects/styles and their categories into the prior preservation loss.</p><h2 id="big-metamodel-fine-tune-stable-diffusion-to-your-favorite-artist-and-dog">BIG Metamodel: Fine-tune Stable Diffusion to your favorite artist and dog</h2><p>Now piecing together the above ideas raises the question: how do we split the images for the prior preservation loss as a batch that always consists of <code>N</code> instance images and <code>N</code> prior preservation loss images? Well, the following intuitive split works great:</p><ul>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="bae2ceb2-4f9c-4546-82d8-d1760366b154" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="bae2ceb2-4f9c-4546-82d8-d1760366b154" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI's BIG metamodel lets you fine-tune Stable Diffusion to the next level, creating images of multiple subjects in any style you want</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/IMG_2227-5-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Joschka Braun, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 30, 2023 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/BIG_eq.png" class="kg-image" alt="" width="900" height="300" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/BIG_eq.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/BIG_eq.png 900w" sizes="(min-width: 720px) 720px"></figure><p>Jina AI is really into generative AI. It started out with <a href="https://github.com/jina-ai/dalle-flow?ref=jina-ai-gmbh.ghost.io">DALL·E Flow</a>, swiftly followed by <a href="https://colab.research.google.com/github/jina-ai/discoart/blob/main/discoart.ipynb?ref=jina-ai-gmbh.ghost.io">DiscoArt</a>. And then…<strong>🦗🦗</strong><em><strong>&lt;</strong>cricket sounds<strong>&gt;</strong></em><strong>🦗🦗</strong>. At least for a while…</p><p>That while has ended. We’re Back In the Game, baby. Big time, with our new <a href="https://github.com/jina-ai/big_creative_ai?ref=jina-ai-gmbh.ghost.io">BIG metamodel</a>. You might be wondering: What’s so meta about it? Before you needed multiple Stable Diffusion models, but now with BIG you have one model for everything.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-text">BIG stands for Back In (the) Game. If we ever get out of the game and get Back At the Game Again, we’ll have to go with BAGA. I hope we can afford the baseball caps.</div></div><p>In short, BIG lets you fine-tune Stable Diffusion to the next level, letting you create images of multiple subjects and in any style you want. That means you can take a picture of you and a picture of your pooch and combine them into a composite image in the style of Picasso, Pixar or pop art.</p><p>We created BIG by taking the <a href="https://doi.org/10.48550/arXiv.2208.12242?ref=jina-ai-gmbh.ghost.io">DreamBooth paper</a>, which allows fine-tuning with one subject, and leveling it up it into a metamodel to learn <em>multiple</em> new objects without using up all your compute. In this blog post we’ll go over how we did that, and how well it works.</p><p>But first, let’s take a quick look at how we got here, by starting off with Stable Diffusion itself.</p><h2 id="stable-diffusion-fine-tune-to-your-favorite-artist-but-forget-everyone-else">Stable Diffusion: Fine-tune to your favorite artist (but forget everyone else)</h2><p>In the beginning there was Stable Diffusion and it was good. “Create a Banksy picture” you would say, and verily a Banksy would be created. “Create an artwork in the style of Picasso” you would exclaim. And verily an image of a woman with too many angles would be created.</p><p>“Generate an image in the style of <a href="https://www.leonloewentraut.de/?ref=jina-ai-gmbh.ghost.io">Leon Löwentraut</a>” you proclaim. And Stable Diffusion did say “uh, what? lol I’ll give it my best. And verily it was rubbish.</p><p>Luckily, this can be fixed by fine-tuning (yeah, we’re dropping the Biblical speak). If you feed Stable Diffusion a Leon Löwentraut image it can learn his style (using, for example, <a href="https://huggingface.co/docs/diffusers/training/text2image?ref=jina-ai-gmbh.ghost.io">text-to-image fine-tuning for Stable Diffusion</a>.)</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/000000001-1.jpg" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2022-11-23-at-14.50.14-1.png" width="1040" height="1034" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2022-11-23-at-14.50.14-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2022-11-23-at-14.50.14-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2022-11-23-at-14.50.14-1.png 1040w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: An actual painting from Leon Löwentraut, Right: Generated image for Leon Löwentraut</figcaption></figure><p>The only problem is it gets amnesia for everything else it’s learned before. So if you then try to create the style of Banksy or Picasso on your newly fine-tuned model they all turn out pretty Löwentrautian:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-7-2.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2022-11-23-at-15.10.30-1.png" width="1040" height="1034" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2022-11-23-at-15.10.30-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2022-11-23-at-15.10.30-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2022-11-23-at-15.10.30-1.png 1040w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: Generated image by Stable Diffusionwith prompt <code>a banksy painting</code>, before fine-tuning; Right: Generated images for prompt <code>a banksy painting</code>, after fine-tuning to Löwentraut.</figcaption></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-3-1.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2022-11-23-at-14.49.09-1.png" width="1040" height="1034" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2022-11-23-at-14.49.09-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2022-11-23-at-14.49.09-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2022-11-23-at-14.49.09-1.png 1040w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: Generated image by Stable Diffusion with prompt <code>a picasso painting</code>, before fine-tuning; Right: Generated image for prompt <code>a picasso painting</code>, after fine-tuning to Löwentraut</figcaption></figure><h2 id="dreambooth-fine-tune-to-your-favorite-artist-and-remember">DreamBooth: Fine-tune to your favorite artist (and remember!)</h2><p>DreamBooth fixes that. At least to a point. You want to train it for your dog? Piece of cake. Fine-tune it for your favorite artist? A walk in the park. And Mona Lisa would still look like it came from Leonardo and Starry Night from Van Gogh.</p><p>It does this by extending Stable Diffusion’s fine-tuning loss with a prior preservation loss to train the model to still generate diverse images for the category of that style (e.g. Löwentraut) or object (e.g. a dog). The prior preservation loss is the mean squared error of the now generated images and the pre-training generated images for the category in the latent space.</p><p>This fine-tuning involves two prompts:</p><ul><li>a <code>[CATEGORY]</code>: The prompt for the prior preservation loss is the category of the style or object in question, like <code>dog</code> or <code>painting</code>.</li><li>a <code>[RARE_IDENTIFIER] [CATEGORY]</code>: The prompt for fine-tuning to a new object or style, generally a string that corresponds to a token the model is unfamiliar with. This is a unique reference to the object you want Stable Diffusion to learn. Example strings would be <code>sks</code> or <code>btb</code>.</li></ul><p>So, to fine-tune Stable Diffusion to create images of your dog, you would:</p><ul><li>Take 5-8 high quality images of your dog.</li><li>Fine-tune the model to recreate these images for the prompt <code>a sks dog</code> and the same time still create diverse images for the prompt <code>a dog</code>.</li></ul><p>Creating diverse images is helped along the way by generating images for the prompt <code>a dog</code> and using them as training images.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.52.28.png" class="kg-image" alt="" width="2000" height="1569" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.52.28.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.52.28.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.52.28.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.52.28.png 2004w" sizes="(min-width: 720px) 720px"><figcaption>Diagram taken from DreamBooth paper</figcaption></figure><h2 id="unstable-confusion-the-amnesia-creeps-back-in">Unstable Confusion: The amnesia creeps back in</h2><p>So far, so good! But what if you first use DreamBooth to fine-tune Stable Diffusion on your dog, then train on Leon Löwentraut, <em>then</em> ask it to create a picture of your dog in his style? Or train for <code>artist_1</code>, then train for <code>artist_2</code>, then try to create a new image by <code>artist_1</code>?</p><p>That shouldn’t be too hard, right?</p><p>Too hard for DreamBooth unfortunately.</p><p>DreamBooth falls over on this because it has a selective short-term memory. Using it to teach Stable Diffusion something new (let’s say the style of Löwentraut) works great. And then you can create images of all kinds of places and objects (already known to Stable Diffusion) in his style. But then if you decide to train it in the style of another artist it’ll forget everything it learned about Löwentraut’s style.</p><p>That’s why we created BIG: To let you train on multiple objects and styles <em>without</em> the amnesia. But more on that in a later section.</p><p>To see DreamBooth’s amnesia in action, let’s use it to fine-tune a model for two different artists:</p><ul><li>Leon Löwentraut (using the <code>RARE_IDENTIFIER</code> of <code>lnl</code>)</li><li><a href="https://www.instagram.com/vexx/?ref=jina-ai-gmbh.ghost.io">Vexx</a> (using the <code>RARE_IDENTIFIER</code> of <code>qzq</code>)</li></ul><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/000000003-1.jpg" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/000000000-2.jpg" width="512" height="512" alt=""></div></div></div><figcaption>Left: Another example of an actual Leon Löwentraut painting; Right: An image from Vexx.</figcaption></figure><p>To generate a painting in one of the above styles, we’d use a prompt like <code>a lnl painting</code> or <code>a qzq painting</code>.</p><p>Using DreamBooth and the prompt <code>a lnl painting</code> to fine-tune a model to fit the art style of Leon Löwentraut works great. &nbsp;For this we used four training images and trained for 400 steps with a learning rate of <code>1e-6</code>.</p><p>The left and center images show the model before fine-tuning. Note how it doesn’t know either <code>lnl</code> or <code>loewentraut</code>.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-8-1.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-5-1.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.05.05-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-11.05.05-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-11.05.05-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-11.05.05-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.05.05-1.png 1618w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: Generated image by Stable Diffusion with prompt <code>a qzq painting</code>; Center: Generated image by Stable Diffusion with prompt <code>a vexx painting</code>; Right: Generated image for <code>a qzq painting</code> after fine-tuning for Vexx.</figcaption></figure><p>But can the model still produce images in the styles of Picasso, Matisse and Banksy? Yes!</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-7--1--1.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-9-1.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-8--1--1.png" width="512" height="512" alt=""></div></div></div><figcaption>Left: Generated image for prompt <code>a banksy painting</code> after fine-tuning for Vexx; Center: Generated image for prompt <code>a mattisse painting</code> after fine-tuning for Vexx; Left: Generated image for prompt <code>a picasso painting</code> after fine-tuning for Vexx.</figcaption></figure><p>Now, after learning Vexx, does our model still remember Leon Löwentraut?</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.06.41.png" class="kg-image" alt="" width="1618" height="1618" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-11.06.41.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-11.06.41.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-11.06.41.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.06.41.png 1618w" sizes="(min-width: 720px) 720px"><figcaption>Generated image for <code>a lnl painting</code> after fine-tuning for Vexx.</figcaption></figure><p>Damn. Where did Leon go? It seems fine-tuning for Vexx overpowered Stable Diffusion’s memory of Leon. And it would do just the same if we trained it first on pictures of our favorite pooch and then secondly on our favorite artist. The result? Bye bye doggie.</p><h2 id="how-can-we-cure-dreambooth%E2%80%99s-amnesia">How can we cure DreamBooth’s amnesia?</h2><p>To solve the problem of forgetting Leon Löwentraut while learning Vexx, we included the images of Leon Löwentraut in the prior preservation loss during the fine-tuning. This is equivalent to further fine-tuning on Löwentraut while fine-tuning on Vexx, but less so than the original fine-tuning of Löwentraut. It works best to reuse the actual images for the style than the images the model generated.</p><p>So, now we can generate all the artists we encounter in our travels. After teaching &nbsp;Stable Diffusion model to create images in the style of Leon Löwentraut from the prompt <code>a lnl painting</code>, we wanted to create images of our favourite mate tea bottle. So, again we used the Leon Löwentraut fine-tuned model as initialization to train my Stable Diffusion model to create images of <a href="https://de.wikipedia.org/wiki/Mio_Mio_Mate?ref=jina-ai-gmbh.ghost.io">Mio Mio Mate</a> for <code>a sks bottle</code> (giving it a unique <code>RARE_IDENTIFIER</code>).</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/IMG_3551-1.jpg" width="2000" height="2000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/IMG_3551-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/IMG_3551-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/IMG_3551-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/01/IMG_3551-1.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-5--1--1.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/generation-0-1.png" width="512" height="512" alt=""></div></div></div><figcaption>Left: Picture taken of a mio mio mate bottle, used for fine-tuning; Center: Generated image by Stable Diffusion with prompt: <code>a mio mio mate bottle</code>; Right: Generated image by Stable Diffusion with prompt: <code>a sks bottle</code></figcaption></figure><p>Again, this works for the new object, yet the model doesn’t quite remember how to produce images for Leon Löwentraut under <code>a lnl painting</code>.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.14.31-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-11.14.31-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-11.14.31-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-11.14.31-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.14.31-1.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.14.38-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-11.14.38-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-11.14.38-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-11.14.38-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-11.14.38-1.png 1618w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: Generated image for <code>a sks bottle</code> after fine-tuning for Mio Mio bottle; Right: Generated image for <code>a lnl painting</code> after fine-tuning for Mio Mio bottle.</figcaption></figure><p>To solve this issue, we can also think about using the previous images for Leon Löwentraut in the prior preservation loss. This helps remember the style of Leon Löwentraut. Yet, art styles which have similar geometric features (like Picasso) are not as accurately reproduced. This makes intuitive sense and is also the reason DreamBooth was introduced in the first place. Building on it, we need to not only incorporate the images of Leon Löwentraut in the prior preservation loss but also images of paintings, i.e., incorporate additionally the previous objects/styles and their categories into the prior preservation loss.</p><h2 id="big-metamodel-fine-tune-stable-diffusion-to-your-favorite-artist-and-dog">BIG Metamodel: Fine-tune Stable Diffusion to your favorite artist and dog</h2><p>Now piecing together the above ideas raises the question: how do we split the images for the prior preservation loss as a batch that always consists of <code>N</code> instance images and <code>N</code> prior preservation loss images? Well, the following intuitive split works great:</p><ul>
 <li>Use half of the prior preservation loss image for the current category and its previously learned instances
 <ul>
 <li>50% of those are generated images for the category</li>
@@ -39,40 +39,40 @@
 </ul>
 </li>
 </ul>
-<h2 id="the-hitchhikers-guide-to-building-your-own-metamodel">The Hitchhiker's Guide to Building Your Own Metamodel</h2><p>So how do you train your metamodel? </p><p>First, fit a private model to find the right learning rate and training steps. A low learning rate of <code>1e-6</code> is best across different styles and objects. We found that starting from 200 training steps and slowly increasing to 600 is best to find the sweet spot of fitting and not overfitting for objects and styles. To recreate faces, we recommend starting from 600 training steps and increasing to 1,200. </p><p>The second and final step is to reuse the same parameters for the request but change the <code>target_model</code> to <code>meta</code> or <code>private_meta</code>. </p><p>Now you have your (private) metamodel. In a script, fine-tuning is made very simple as shown below:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Client, DocumentArray
-<span class="hljs-keyword">import</span> hubble
+<h2 id="the-hitchhikers-guide-to-building-your-own-metamodel">The Hitchhiker's Guide to Building Your Own Metamodel</h2><p>So how do you train your metamodel? </p><p>First, fit a private model to find the right learning rate and training steps. A low learning rate of <code>1e-6</code> is best across different styles and objects. We found that starting from 200 training steps and slowly increasing to 600 is best to find the sweet spot of fitting and not overfitting for objects and styles. To recreate faces, we recommend starting from 600 training steps and increasing to 1,200. </p><p>The second and final step is to reuse the same parameters for the request but change the <code>target_model</code> to <code>meta</code> or <code>private_meta</code>. </p><p>Now you have your (private) metamodel. In a script, fine-tuning is made very simple as shown below:</p><pre><code class="language-python">from jina import Client, DocumentArray
+import hubble
 
 
-<span class="hljs-comment"># specify the path to the images</span>
-path_to_instance_images = <span class="hljs-string">'/path/to/instance/images'</span>
-<span class="hljs-comment"># specify the category of the images, this could be e.g. 'painting', 'dog', 'bottle', etc.</span>
-category = <span class="hljs-string">'category of the objects'</span>
-<span class="hljs-comment"># 'private' for training private model from pretrained model, 'meta' for training metamodel</span>
-target_model = <span class="hljs-string">'private'</span>
+# specify the path to the images
+path_to_instance_images = '/path/to/instance/images'
+# specify the category of the images, this could be e.g. 'painting', 'dog', 'bottle', etc.
+category = 'category of the objects'
+# 'private' for training private model from pretrained model, 'meta' for training metamodel
+target_model = 'private'
 
-<span class="hljs-comment"># some custom parameters for the training</span>
-max_train_steps = <span class="hljs-number">300</span>
-learning_rate = <span class="hljs-number">1e-6</span>
+# some custom parameters for the training
+max_train_steps = 300
+learning_rate = 1e-6
 
-docs = DocumentArray.from_files(<span class="hljs-string">f'<span class="hljs-subst">{path_to_instance_images}</span>/**'</span>)
-<span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span> docs:
+docs = DocumentArray.from_files(f'{path_to_instance_images}/**')
+for doc in docs:
     doc.load_uri_to_blob()
-    doc.uri = <span class="hljs-literal">None</span>
+    doc.uri = None
 
-client = Client(host=<span class="hljs-string">'grpc://host_big_executor:port_big_executor'</span>)
+client = Client(host='grpc://host_big_executor:port_big_executor')
 
 identifier_doc = client.post(
-    on=<span class="hljs-string">'/finetune'</span>,
+    on='/finetune',
     inputs=docs,
     parameters={
-        <span class="hljs-string">'jwt'</span>: {
-            <span class="hljs-string">'token'</span>: hubble.get_token(),
+        'jwt': {
+            'token': hubble.get_token(),
         },
-        <span class="hljs-string">'category'</span>: category,
-        <span class="hljs-string">'target_model'</span>: target_model,
-        <span class="hljs-string">'learning_rate'</span>: learning_rate,
-        <span class="hljs-string">'max_train_steps'</span>: max_train_steps,
+        'category': category,
+        'target_model': target_model,
+        'learning_rate': learning_rate,
+        'max_train_steps': max_train_steps,
     },
 )
 
-<span class="hljs-built_in">print</span>(<span class="hljs-string">f'Finetuning was successful. The identifier for the object is "<span class="hljs-subst">{identifier_doc[<span class="hljs-number">0</span>].text}</span>"'</span>)</code></pre><h2 id="results">Results</h2><p>With our new metamodel we taught Stable Diffusion to create images of the Mio Mio Mate tea bottle, a sparking water bottle from a local manufacturer, a <a href="https://nuphy.com/products/air75?ref=jina-ai-gmbh.ghost.io">NuPhy Air75</a> keyboard, and an office desk chair and artwork in the styles of Leon Löwentraut and Vexx:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.20.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.55.20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.55.20.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.55.20.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.20.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.57.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.55.57.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.55.57.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.55.57.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.57.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.30.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.55.30.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.55.30.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.55.30.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.30.png 1618w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.49.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.55.49.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.55.49.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.55.49.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.49.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.41.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.55.41.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.55.41.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.55.41.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.41.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.56.05.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.56.05.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.56.05.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.56.05.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.56.05.png 1618w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>Note how for both bottles a hand appears holding it. For both generated images there were six images used for fine-tuning and for both there was only one image holding the bottle by hand. Yet, the model has somewhat collapsed to always showing this hand. This shows the importance of not only high-quality but also diverse representative images. Here are the images of a hand holding the bottle that we used for fine-tuning:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/IMG_3559-1.jpg" width="2000" height="2000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/IMG_3559-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/IMG_3559-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/IMG_3559-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/01/IMG_3559-1.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/IMG_3553-1.jpg" width="2000" height="2000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/IMG_3553-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/IMG_3553-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/IMG_3553-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/01/IMG_3553-1.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: Picture with hand used to fine-tune Stable Diffusion to sparking water bottle; Right: Picture with hand used to fine-tune Stable Diffusion to mate bottle.</figcaption></figure><p>The model isn’t just able to memorize the objects, but also learns how newly-learned objects and styles interact:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.18-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.04.18-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.04.18-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.04.18-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.18-1.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.43-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.04.43-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.04.43-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.04.43-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.43-1.png 1618w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: Sparkling water bottle in the style of Vexx, generated with prompt: <code>a qzq painting of a rvt bottle</code>; Right: Mate bottle in Leon Löwentraut's style, generated with prompt: <code>a lnl painting of a pyr bottle</code></figcaption></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.59-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.04.59-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.04.59-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.04.59-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.59-1.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.53-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.04.53-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.04.53-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.04.53-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.53-1.png 1618w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: NuPhy Air75 keyboard in style of Vexx, generated with prompt: <code>a qzq painting of a sph keyboard</code>; Right: NuPhy Air75 keyboard in style of Leon Löwentraut, generated with prompt: <code>a lnl painting of a sph keyboard</code></figcaption></figure><p>Last, but not least we trained it to create images of Joschka's company dog, Briscoe:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/IMG_3474-2-2-1.jpg" width="2000" height="2000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/IMG_3474-2-2-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/IMG_3474-2-2-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/IMG_3474-2-2-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/IMG_3474-2-2-1.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.05.09-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.05.09-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.05.09-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.05.09-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.05.09-1.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.05.16-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.05.16-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.05.16-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.05.16-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.05.16-1.png 1618w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: A picture of Briscoe used for fine-tuning; Center: A generated image of Briscoe with prompt: <code>a brc dog</code>; Right: A painting of Briscoe in the style of Leon Löwentraut generated with prompt: <code>a lnl</code> <code>painting of a brc dog</code>.</figcaption></figure><h2 id="what%E2%80%99s-next">What’s next?</h2><p>In future, it would be interesting to enhance the performance if we additionally apply <a href="https://textual-inversion.github.io/?ref=jina-ai-gmbh.ghost.io">Textual Inversion</a> to get better prompts for generating new images. This might also change how previously-learned objects are forgotten.</p><p>We could also explore other angles, like why previously learned objects and styles get overwritten, by understanding if the similarity in prompts is an issue or if semantic similarity of the new objects is a strong predictor of forgetting. The former can be solved by better sampling of the rare identifiers, using <a href="https://arxiv.org/abs/2201.12086?ref=jina-ai-gmbh.ghost.io">BLIP</a> to automatically generate captions, or adapting textual inversion to incorporate the forgetting effect.</p><p>Another question is when the current form of further learning in the metamodel leads to overfitting to previously-learned objects and styles as the model is continuously trained to minimize the loss of the generated images for them. For that it’s relevant to optimize the allocation of images for the prior preservation loss in order to push the amount of new learnt objects even further.</p><p>You can also start playing around with it yourself in <a href="https://colab.research.google.com/github/jina-ai/big_creative_ai/blob/main/big_metamodel.ipynb?ref=jina-ai-gmbh.ghost.io">Google Colab</a> or check out the <a href="https://github.com/jina-ai/big_creative_ai?ref=jina-ai-gmbh.ghost.io">GitHub repository</a>.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fhow-to-personalize-stable-diffusion-for-all-the-things%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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\ No newline at end of file
+print(f'Finetuning was successful. The identifier for the object is "{identifier_doc[0].text}"')</code></pre><h2 id="results">Results</h2><p>With our new metamodel we taught Stable Diffusion to create images of the Mio Mio Mate tea bottle, a sparking water bottle from a local manufacturer, a <a href="https://nuphy.com/products/air75?ref=jina-ai-gmbh.ghost.io">NuPhy Air75</a> keyboard, and an office desk chair and artwork in the styles of Leon Löwentraut and Vexx:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.20.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.55.20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.55.20.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.55.20.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.20.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.57.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.55.57.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.55.57.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.55.57.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.57.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.30.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.55.30.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.55.30.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.55.30.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.30.png 1618w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.49.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.55.49.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.55.49.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.55.49.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.49.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.41.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.55.41.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.55.41.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.55.41.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.55.41.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.56.05.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.56.05.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.56.05.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.56.05.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.56.05.png 1618w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>Note how for both bottles a hand appears holding it. For both generated images there were six images used for fine-tuning and for both there was only one image holding the bottle by hand. Yet, the model has somewhat collapsed to always showing this hand. This shows the importance of not only high-quality but also diverse representative images. Here are the images of a hand holding the bottle that we used for fine-tuning:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/IMG_3559-1.jpg" width="2000" height="2000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/IMG_3559-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/IMG_3559-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/IMG_3559-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/01/IMG_3559-1.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/IMG_3553-1.jpg" width="2000" height="2000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/IMG_3553-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/IMG_3553-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/IMG_3553-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/01/IMG_3553-1.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: Picture with hand used to fine-tune Stable Diffusion to sparking water bottle; Right: Picture with hand used to fine-tune Stable Diffusion to mate bottle.</figcaption></figure><p>The model isn’t just able to memorize the objects, but also learns how newly-learned objects and styles interact:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.18-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.04.18-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.04.18-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.04.18-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.18-1.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.43-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.04.43-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.04.43-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.04.43-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.43-1.png 1618w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: Sparkling water bottle in the style of Vexx, generated with prompt: <code>a qzq painting of a rvt bottle</code>; Right: Mate bottle in Leon Löwentraut's style, generated with prompt: <code>a lnl painting of a pyr bottle</code></figcaption></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.59-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.04.59-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.04.59-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.04.59-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.59-1.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.53-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.04.53-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.04.53-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.04.53-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.04.53-1.png 1618w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: NuPhy Air75 keyboard in style of Vexx, generated with prompt: <code>a qzq painting of a sph keyboard</code>; Right: NuPhy Air75 keyboard in style of Leon Löwentraut, generated with prompt: <code>a lnl painting of a sph keyboard</code></figcaption></figure><p>Last, but not least we trained it to create images of Joschka's company dog, Briscoe:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/IMG_3474-2-2-1.jpg" width="2000" height="2000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/IMG_3474-2-2-1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/IMG_3474-2-2-1.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/IMG_3474-2-2-1.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/IMG_3474-2-2-1.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.05.09-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.05.09-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.05.09-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.05.09-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.05.09-1.png 1618w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.05.16-1.png" width="1618" height="1618" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-15.05.16-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-15.05.16-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-15.05.16-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-15.05.16-1.png 1618w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: A picture of Briscoe used for fine-tuning; Center: A generated image of Briscoe with prompt: <code>a brc dog</code>; Right: A painting of Briscoe in the style of Leon Löwentraut generated with prompt: <code>a lnl</code> <code>painting of a brc dog</code>.</figcaption></figure><h2 id="what%E2%80%99s-next">What’s next?</h2><p>In future, it would be interesting to enhance the performance if we additionally apply <a href="https://textual-inversion.github.io/?ref=jina-ai-gmbh.ghost.io">Textual Inversion</a> to get better prompts for generating new images. This might also change how previously-learned objects are forgotten.</p><p>We could also explore other angles, like why previously learned objects and styles get overwritten, by understanding if the similarity in prompts is an issue or if semantic similarity of the new objects is a strong predictor of forgetting. The former can be solved by better sampling of the rare identifiers, using <a href="https://arxiv.org/abs/2201.12086?ref=jina-ai-gmbh.ghost.io">BLIP</a> to automatically generate captions, or adapting textual inversion to incorporate the forgetting effect.</p><p>Another question is when the current form of further learning in the metamodel leads to overfitting to previously-learned objects and styles as the model is continuously trained to minimize the loss of the generated images for them. For that it’s relevant to optimize the allocation of images for the prior preservation loss in order to push the amount of new learnt objects even further.</p><p>You can also start playing around with it yourself in <a href="https://colab.research.google.com/github/jina-ai/big_creative_ai/blob/main/big_metamodel.ipynb?ref=jina-ai-gmbh.ghost.io">Google Colab</a> or check out the <a href="https://github.com/jina-ai/big_creative_ai?ref=jina-ai-gmbh.ghost.io">GitHub repository</a>.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fhow-to-personalize-stable-diffusion-for-all-the-things%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>How to Start Your Career in Open Source</title><meta charset="utf-8"><meta name="title" content="How to Start Your Career in Open Source"><meta name="description" content="For fresh grads, we summarized some tips that you can use to make your profile stand out and help you to develop skills in engineering, marketing, and open-source community operations."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/how-to-start-your-career-in-open-source"><meta property="og:title" content="How to Start Your Career in Open Source"><meta property="og:description" content="For fresh grads, we summarized some tips that you can use to make your profile stand out and help you to develop skills in engineering, marketing, and open-source community operations."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--32-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/how-to-start-your-career-in-open-source"><meta property="twitter:title" content="How to Start Your Career in Open Source"><meta property="twitter:description" content="For fresh grads, we summarized some tips that you can use to make your profile stand out and help you to develop skills in engineering, marketing, and open-source community operations."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--32-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jerboa</div><div class="q-item__label q-item__label--caption text-caption">An experimental finetuner for open-source LLMs</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="1d6b4530-79de-4ce4-9aeb-1975ca87555e" aria-label="Expand &quot;Company&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><span class="q-icon" aria-hidden="true" role="presentation"><img src="/J.svg"></span></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Company</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="1d6b4530-79de-4ce4-9aeb-1975ca87555e" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/about-us"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">About us</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/contact-sales"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Contact sales</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/open-day"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Open day</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/internship"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Intern program</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://jobs.lever.co/jina-ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Join us</div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">open_in_new</i></div></div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div></div></div></div><div class="q-scrollarea__bar q-scrollarea__bar--v absolute-right q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__bar q-scrollarea__bar--h absolute-bottom q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--v absolute-right q-scrollarea__thumb--invisible" aria-hidden="true" style="top: 0px; height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 50%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--32-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How to Start Your Career in Open Source</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">For fresh grads, we summarized some tips that you can use to make your profile stand out and help you to develop skills in engineering, marketing, and open-source community operations.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 14, 2022 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>It was a pleasure to meet so many talented people at the <a href="https://jina.ai/news/berlin-tech-job-fair/?ref=jina-ai-gmbh.ghost.io">Tech Job Fair</a>. We were overwhelmed by the number of AI enthusiasts who came to our booth to ask about joining Jina AI. </p><p>The most common thing we were asked is how to raise your profile when applying at an open-source company like Jina AI. Lots of talented people want to work in AI and be a part of the open-source community, but there are a limited number of paid jobs in this field. Here are five tips and tricks that you can use to make your profile stand out and help you to develop skills in engineering, marketing, and open-source community operations.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.77778 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_123841231-2.jpg" width="1600" height="900" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/PXL_20221110_123841231-2.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/PXL_20221110_123841231-2.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_123841231-2.jpg 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.77778 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_153104125.jpg" width="1600" height="900" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/PXL_20221110_153104125.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/PXL_20221110_153104125.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_153104125.jpg 1600w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.77778 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_151115419.jpg" width="1600" height="900" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/PXL_20221110_151115419.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/PXL_20221110_151115419.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_151115419.jpg 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.77778 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_142200623.jpg" width="1600" height="900" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/PXL_20221110_142200623.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/PXL_20221110_142200623.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_142200623.jpg 1600w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Thank you for coming to our booth, we were thrilled to see you all!&nbsp;</figcaption></figure><h2 id="tip-1-be-an-active-member-of-a-project">Tip 1: Be an active member of a project!</h2><p>Engage with the project's development team and community via social media or other community channels to get exposure and, often, cool swag. </p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://jina.ai/news/from-zero-to-hero-at-jina-ai-community/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">New Community Reward Program is Coming!</div><div class="kg-bookmark-description">We are excited to introduce a new Reward Plan to recognize active community members! You can gain credits by engaging with the community. How? Read on!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Swag-Plan.png" alt=""></div></a><figcaption>Jina AI, like many open-source companies, has a reward system for active community members. Check out Jina AI's Reward Plan</figcaption></figure><p>You can also share industry news, start public conversations about technology or any other relevant topic, ask questions about the software, and help others with their problems in a public forum. The company will notice you and your efforts. </p><div class="kg-card kg-button-card kg-align-center"><a href="https://jina.ai/slack/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Want to be active in Jina AI's community? Start with our Slack channel</a></div><h2 id="tip-2-create-use-cases-and-work-on-applications">Tip 2: Create use-cases and work on applications</h2><p>The best way to promote an open-source project is to create cool apps. Identify a use-case that is interesting or useful and that you can build, then do it. You can get support from the project's development team and other community participants via their community channels, and then show off the result. A cool application draws a lot of attention and engagement.</p><figure class="kg-card kg-embed-card kg-card-hascaption"><iframe width="200" height="113" src="https://www.youtube.com/embed/KMeyjn3fcKY?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" title="用AI搜索梦华录刘亦菲口红同款！程序员爆肝66小时，给女朋友买的口红会翻车吗？"></iframe><figcaption>A cool application for Jina AI from one of our most active community members. (Turn on subtitles for English.)</figcaption></figure><p>You can create a website, YouTube video, or blog post for your project. That's even better than a spectacular resumé because it shows your skills working specifically with that company's products. <strong>By the time you've applied for a job, everyone at the company will already know your name!</strong></p><h2 id="tip-3-promote-the-project-on-social-media">Tip 3: Promote the project on social media </h2><p>Open-source projects thrive on attention. The more users, the more downloads, and the more active developers a project has, the more successful it is.</p><p>One of the easiest but most important ways you can show your support for the company and its projects is to actively boost it and link to it on social media platforms. Open-source companies pay close attention to their social media profiles and the quality and nature of the engagement they receive. If you belong to communities where people talk about open-source projects and new computer technologies, bringing attention to the projects you work on is one of the most valuable services you can offer. </p><figure class="kg-card kg-embed-card kg-card-hascaption"><iframe width="200" height="113" src="https://www.youtube.com/embed/yJvBKjqns7s?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" title="Keep my JCloud (Online!)"></iframe><figcaption>Peter Willemsen, a very active member of the Jina AI community, promoting his JCloud project on his YouTube channel. You rock, Peter!</figcaption></figure><p>When you apply for a job, the company will almost certainly google you, and if they find you doing a good job of representing their projects, that's going to be a foot in the door for you. &nbsp;</p><h2 id="tip-4-attend-events-related-to-open-source">Tip 4: Attend events related to open source </h2><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.749906 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Image-from-iOS--7-.jpg" width="2000" height="2667" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Image-from-iOS--7-.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Image-from-iOS--7-.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/Image-from-iOS--7-.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/Image-from-iOS--7-.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Image-from-iOS--8-.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Image-from-iOS--8-.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Image-from-iOS--8-.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/Image-from-iOS--8-.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/Image-from-iOS--8-.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Image-from-iOS--9-.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Image-from-iOS--9-.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Image-from-iOS--9-.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/Image-from-iOS--9-.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/Image-from-iOS--9-.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.749906 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_8408.jpg" width="2000" height="2667" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_8408.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_8408.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_8408.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_8408.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_8412.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_8412.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_8412.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_8412.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_8412.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_8537.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_8537.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_8537.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_8537.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_8537.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.33333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_8566.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_8566.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_8566.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_8566.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_8566.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p><a href="https://www.meetup.com/jina-community-meetup/?ref=jina-ai-gmbh.ghost.io">Meetup</a> is a great way to find people who share the same interest, and spread your network! It is an amazing chance for fresh graduates to learn some of the basics in their field or gain familiarity in an area necessary for their job. </p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://jina.ai/news/hackday-with-jina-ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Berlin Vector Search Day with Jina AI &amp; Haystack EU Community</div><div class="kg-bookmark-description">On Wednesday, Jina AI hosted a Vector Search Hackday with the Haystack EU Community in our Berlin office. Participants were grouped by interests and background, from beginners in vector search to information retrieval professionals. The “Beginning Vector Search” group built their first Image-to-Tex…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/IMG_0209-2.jpg" alt=""></div></a><figcaption>Read more about our events on our website</figcaption></figure><p>You can use Meetup to see which direction the market is moving in, especially when it comes to the IT community. With tools, technologies, frameworks, and methodologies always changing, it's helpful to see which existing Meetup groups are rebranding or new ones that are popping up. This way, you can stay ahead of the curve.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://www.meetup.com/jina-community-meetup/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Want to attend events at Jina AI? Join us on Meetup</a></div><h2 id="tip-5-start-contributing-to-an-open-source-project">Tip 5: Start contributing to an open source project</h2><p>Open-source projects are a great way to get started in coding and software development because you can learn by doing. Plus, your contributions can be used as a showcase of your skills to potential employers. To find an open-source project that interests you, check out GitHub. You might spend a day or more to find the project of your interest. Do not worry, all your efforts will be paid back! </p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/blob/master/CONTRIBUTING.md?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">jina/CONTRIBUTING.md at master · jina-ai/jina</div><div class="kg-bookmark-description">🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps - jina/CONTRIBUTING.md at master · jina-ai/jina</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/6d66c5cb-b3e8-4bc2-b2ee-b01b9d90933d" alt=""></div></a><figcaption>Start building your strong portfolio using our contribution guidance!&nbsp;</figcaption></figure><p>We hope these tips help you to get the job of your dreams! Let us know your thoughts via Slack, would love to hear more from you. </p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fhow-to-start-your-career-in-open-source%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How to Start Your Career in Open Source</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">For fresh grads, we summarized some tips that you can use to make your profile stand out and help you to develop skills in engineering, marketing, and open-source community operations.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 14, 2022 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>It was a pleasure to meet so many talented people at the <a href="https://jina.ai/news/berlin-tech-job-fair/?ref=jina-ai-gmbh.ghost.io">Tech Job Fair</a>. We were overwhelmed by the number of AI enthusiasts who came to our booth to ask about joining Jina AI. </p><p>The most common thing we were asked is how to raise your profile when applying at an open-source company like Jina AI. Lots of talented people want to work in AI and be a part of the open-source community, but there are a limited number of paid jobs in this field. Here are five tips and tricks that you can use to make your profile stand out and help you to develop skills in engineering, marketing, and open-source community operations.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_123841231-2.jpg" width="1600" height="900" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/PXL_20221110_123841231-2.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/PXL_20221110_123841231-2.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_123841231-2.jpg 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_153104125.jpg" width="1600" height="900" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/PXL_20221110_153104125.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/PXL_20221110_153104125.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_153104125.jpg 1600w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_151115419.jpg" width="1600" height="900" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/PXL_20221110_151115419.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/PXL_20221110_151115419.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_151115419.jpg 1600w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_142200623.jpg" width="1600" height="900" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/PXL_20221110_142200623.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/PXL_20221110_142200623.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/PXL_20221110_142200623.jpg 1600w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Thank you for coming to our booth, we were thrilled to see you all!&nbsp;</figcaption></figure><h2 id="tip-1-be-an-active-member-of-a-project">Tip 1: Be an active member of a project!</h2><p>Engage with the project's development team and community via social media or other community channels to get exposure and, often, cool swag. </p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://jina.ai/news/from-zero-to-hero-at-jina-ai-community/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">New Community Reward Program is Coming!</div><div class="kg-bookmark-description">We are excited to introduce a new Reward Plan to recognize active community members! You can gain credits by engaging with the community. How? Read on!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Swag-Plan.png" alt=""></div></a><figcaption>Jina AI, like many open-source companies, has a reward system for active community members. Check out Jina AI's Reward Plan</figcaption></figure><p>You can also share industry news, start public conversations about technology or any other relevant topic, ask questions about the software, and help others with their problems in a public forum. The company will notice you and your efforts. </p><div class="kg-card kg-button-card kg-align-center"><a href="https://jina.ai/slack/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Want to be active in Jina AI's community? Start with our Slack channel</a></div><h2 id="tip-2-create-use-cases-and-work-on-applications">Tip 2: Create use-cases and work on applications</h2><p>The best way to promote an open-source project is to create cool apps. Identify a use-case that is interesting or useful and that you can build, then do it. You can get support from the project's development team and other community participants via their community channels, and then show off the result. A cool application draws a lot of attention and engagement.</p><figure class="kg-card kg-embed-card kg-card-hascaption"><iframe width="200" height="113" src="https://www.youtube.com/embed/KMeyjn3fcKY?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" title="用AI搜索梦华录刘亦菲口红同款！程序员爆肝66小时，给女朋友买的口红会翻车吗？"></iframe><figcaption>A cool application for Jina AI from one of our most active community members. (Turn on subtitles for English.)</figcaption></figure><p>You can create a website, YouTube video, or blog post for your project. That's even better than a spectacular resumé because it shows your skills working specifically with that company's products. <strong>By the time you've applied for a job, everyone at the company will already know your name!</strong></p><h2 id="tip-3-promote-the-project-on-social-media">Tip 3: Promote the project on social media </h2><p>Open-source projects thrive on attention. The more users, the more downloads, and the more active developers a project has, the more successful it is.</p><p>One of the easiest but most important ways you can show your support for the company and its projects is to actively boost it and link to it on social media platforms. Open-source companies pay close attention to their social media profiles and the quality and nature of the engagement they receive. If you belong to communities where people talk about open-source projects and new computer technologies, bringing attention to the projects you work on is one of the most valuable services you can offer. </p><figure class="kg-card kg-embed-card kg-card-hascaption"><iframe width="200" height="113" src="https://www.youtube.com/embed/yJvBKjqns7s?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" title="Keep my JCloud (Online!)"></iframe><figcaption>Peter Willemsen, a very active member of the Jina AI community, promoting his JCloud project on his YouTube channel. You rock, Peter!</figcaption></figure><p>When you apply for a job, the company will almost certainly google you, and if they find you doing a good job of representing their projects, that's going to be a foot in the door for you. &nbsp;</p><h2 id="tip-4-attend-events-related-to-open-source">Tip 4: Attend events related to open source </h2><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Image-from-iOS--7-.jpg" width="2000" height="2667" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Image-from-iOS--7-.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Image-from-iOS--7-.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/Image-from-iOS--7-.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/Image-from-iOS--7-.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Image-from-iOS--8-.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Image-from-iOS--8-.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Image-from-iOS--8-.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/Image-from-iOS--8-.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/Image-from-iOS--8-.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Image-from-iOS--9-.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Image-from-iOS--9-.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Image-from-iOS--9-.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/Image-from-iOS--9-.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/Image-from-iOS--9-.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_8408.jpg" width="2000" height="2667" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_8408.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_8408.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_8408.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_8408.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_8412.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_8412.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_8412.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_8412.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_8412.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_8537.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_8537.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_8537.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_8537.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_8537.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_8566.jpg" width="2000" height="1500" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_8566.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_8566.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_8566.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_8566.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p><a href="https://www.meetup.com/jina-community-meetup/?ref=jina-ai-gmbh.ghost.io">Meetup</a> is a great way to find people who share the same interest, and spread your network! It is an amazing chance for fresh graduates to learn some of the basics in their field or gain familiarity in an area necessary for their job. </p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://jina.ai/news/hackday-with-jina-ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Berlin Vector Search Day with Jina AI &amp; Haystack EU Community</div><div class="kg-bookmark-description">On Wednesday, Jina AI hosted a Vector Search Hackday with the Haystack EU Community in our Berlin office. Participants were grouped by interests and background, from beginners in vector search to information retrieval professionals. The “Beginning Vector Search” group built their first Image-to-Tex…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/IMG_0209-2.jpg" alt=""></div></a><figcaption>Read more about our events on our website</figcaption></figure><p>You can use Meetup to see which direction the market is moving in, especially when it comes to the IT community. With tools, technologies, frameworks, and methodologies always changing, it's helpful to see which existing Meetup groups are rebranding or new ones that are popping up. This way, you can stay ahead of the curve.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://www.meetup.com/jina-community-meetup/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Want to attend events at Jina AI? Join us on Meetup</a></div><h2 id="tip-5-start-contributing-to-an-open-source-project">Tip 5: Start contributing to an open source project</h2><p>Open-source projects are a great way to get started in coding and software development because you can learn by doing. Plus, your contributions can be used as a showcase of your skills to potential employers. To find an open-source project that interests you, check out GitHub. You might spend a day or more to find the project of your interest. Do not worry, all your efforts will be paid back! </p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/blob/master/CONTRIBUTING.md?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">jina/CONTRIBUTING.md at master · jina-ai/jina</div><div class="kg-bookmark-description">🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps - jina/CONTRIBUTING.md at master · jina-ai/jina</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/6d66c5cb-b3e8-4bc2-b2ee-b01b9d90933d" alt=""></div></a><figcaption>Start building your strong portfolio using our contribution guidance!&nbsp;</figcaption></figure><p>We hope these tips help you to get the job of your dreams! 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diff --git a/news/how-to-use-every-vector-database-in-python-with-docarray/index.html b/news/how-to-use-every-vector-database-in-python-with-docarray/index.html
index fe43ad32279..23e8f684881 100644
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+++ b/news/how-to-use-every-vector-database-in-python-with-docarray/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>How to Use Every Vector Database in Python with DocArray</title><meta charset="utf-8"><meta name="title" content="How to Use Every Vector Database in Python with DocArray"><meta name="description" content="DocArray handles multimodal data and works with every vector database using a universal API. Here's how you can do it in Python."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/how-to-use-every-vector-database-in-python-with-docarray"><meta property="og:title" content="How to Use Every Vector Database in Python with DocArray"><meta property="og:description" content="DocArray handles multimodal data and works with every vector database using a universal API. Here's how you can do it in Python."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--70-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/how-to-use-every-vector-database-in-python-with-docarray"><meta property="twitter:title" content="How to Use Every Vector Database in Python with DocArray"><meta property="twitter:description" content="DocArray handles multimodal data and works with every vector database using a universal API. Here's how you can do it in Python."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--70-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>How to Use Every Vector Database in Python with DocArray</title><meta charset="utf-8"><meta name="title" content="How to Use Every Vector Database in Python with DocArray"><meta name="description" content="DocArray handles multimodal data and works with every vector database using a universal API. Here's how you can do it in Python."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/how-to-use-every-vector-database-in-python-with-docarray"><meta property="og:title" content="How to Use Every Vector Database in Python with DocArray"><meta property="og:description" content="DocArray handles multimodal data and works with every vector database using a universal API. Here's how you can do it in Python."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--70-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/how-to-use-every-vector-database-in-python-with-docarray"><meta property="twitter:title" content="How to Use Every Vector Database in Python with DocArray"><meta property="twitter:description" content="DocArray handles multimodal data and works with every vector database using a universal API. Here's how you can do it in Python."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--70-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How to Use Every Vector Database in Python with DocArray</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray handles multimodal data and works with every vector database using a universal API. Here's how you can do it in Python.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alaeddine Abdessalem</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 10, 2023 • 14 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Back in the day, pre-Google, the Internet was mostly text. Whether it was news updates, sports scores, blog posts or emails, ASCII and Unicode were the way to go.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-24.png" class="kg-image" alt="" width="933" height="533" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-24.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-24.png 933w" sizes="(min-width: 720px) 720px"><figcaption>Aaah, the good old days. Just pure ASCII as God intended.</figcaption></figure><p>But nowadays, data is becoming increasingly complex and multimodal, mostly coming in unstructured forms such as images, videos, text, 3D mesh, etc. Gone are the days of being limited to 26 characters and 10 numbers (or more for other character sets). Now there’s <em>much</em> more stuff to deal with.</p><p>Just think about your favorite YouTube videos, Spotify songs, or game NPCs.</p><p>Typical databases can’t handle these kinds of multimodal data. They can only store and process structured data (like simple text strings or numbers). This really limits our ability to extract valuable business insights and value from a huge chunk of the 21st century's data.</p><p>Lucky for us, recent advancements in machine learning techniques and approximate nearest neighbor search have made it possible to better utilize unstructured data:</p><ul><li>Deep learning models and representation learning to effectively represent complex data using vector embeddings.</li><li>Vector databases leverage vector embeddings to store and analyze unstructured data.</li></ul><h2 id="what-are-vector-databases">What are vector databases?</h2><p>A vector database is a type of database that can index and retrieve data using vectors, similar to how a traditional database uses keys or text to search for items using an index. </p><p>A vector database uses a <strong>vector index</strong> to enable fast retrieval and insertion by a vector, and also offers typical database features such as CRUD operations, filtering, and scalability.</p><p>This gives us the best of both worlds - we get the CRUDiness of traditional databases, coupled with the ability to store complex, unstructured data like images, videos, and 3D meshes.</p><p>So, vector databases are great, right? What’s even more awesome is having a library to use them all while being capable of handling unstructured data at the same time! One unstructured data library to rule them all!</p><p>We are, of course, talking about <a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io"><strong>DocArray</strong></a>. Let’s see what this project is all about.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Welcome to DocArray!</div><div class="kg-bookmark-description">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. 🚪 Door to multimodal world: s..…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docarray.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">DocArray 0.20.2 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docarray.jina.ai/_static/banner.png" alt=""></div></a></figure><h2 id="docarrays-universal-pythonic-api-to-all-vector-databases">DocArray's universal Pythonic API to all vector databases</h2><p>As the description suggests on the <a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io">project home page</a>, DocArray is a library for nested, unstructured and multimodal data.</p><p>This means that if you want to process unstructured data and represent it as vectors, DocArray is perfect for you.</p><p><strong>DocArray is also a universal entrypoint for many vector databases.</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-25.png" class="kg-image" alt="" width="1600" height="976" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-25.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-25.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-25.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>For the remainder of this post, we’ll be using DocArray to index and search data in the <a href="https://amazon-berkeley-objects.s3.amazonaws.com/index.html?ref=jina-ai-gmbh.ghost.io"><strong>Amazon Berkeley Objects Dataset</strong></a>. This dataset contains product items with accompanying images and metadata such as brand, country, and color, and represents the inventory of an e-commerce website.</p><p>Although a traditional database can perform filtering on metadata, it is unable to search image data or other unstructured data formats. That’s why we’re using a vector database!</p><p>We’ll start by loading <a href="https://github.com/jina-ai/product-recommendation-redis-docarray/tree/main/data?ref=jina-ai-gmbh.ghost.io">a subset of the Amazon Berkeley Objects Dataset</a> that comes in CSV format into DocArray and computing vector embeddings.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-26.png" class="kg-image" alt="" width="1382" height="470" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-26.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-26.png 1382w" sizes="(min-width: 720px) 720px"><figcaption>Sample images from the dataset</figcaption></figure><p>Then, we'll use DocArray with each database to perform search and insertion operations using vectors.</p><p>We’ll use the following databases via DocArray in Python:</p><ul><li><strong>Milvus</strong> - cloud-native vector database with storage and computation separated by design</li><li><strong>Weaviate</strong> - vector search engine that stores both objects and vectors and can be accessed through REST or GraphQL</li><li><strong>Qdrant</strong> - vector database written in Rust and designed to be fast and reliable under high loads</li><li><strong>Redis</strong> - in-memory key-value database that supports different kinds of data structures with vector search capabilities</li><li><strong>ElasticSearch</strong> - distributed, RESTful search engine with Approximate Nearest Neighbor search capabilities</li><li><strong>OpenSearch</strong> - open-source search software based on Apache Lucene originally forked from ElasticSearch</li><li><strong>AnnLite</strong> - a Python library for fast Approximate Nearest Neighbor Search with filtering capabilities</li></ul><p>For each database, we’ll:</p><ul><li>Setup the database and install requirements</li><li>Index the data in the vector database</li><li>Perform a vector search operation with filtering</li><li>Display the search results</li></ul><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">The returned results will be the same for each database, since we use the same vectors each time. The key differences are in resource usage, latency, etc.</div></div><h2 id="preparing-the-data">Preparing the data</h2><p>First, we’ll install a few dependencies, namely DocArray, <a href="docs.jina.ai/">Jina</a> (for cloud authentication), and the client for <a href="clip-as-service.jina.ai/">CLIP-as-service</a> (for generating embeddings):</p><pre><code class="language-bash hljs">pip install docarray[common] jina clip-client</code></pre><p>Let’s download a sample CSV dataset and load it into a <a href="https://docarray.jina.ai/fundamentals/documentarray/?ref=jina-ai-gmbh.ghost.io">DocumentArray</a> with <code><a href="https://docarray.jina.ai/datatypes/tabular/?ref=jina-ai-gmbh.ghost.io#load-csv-table">DocumentArray.from_csv()</a></code>:</p><pre><code class="language-bash hljs">wget https://github.com/jina-ai/product-recommendation-redis-docarray/raw/main/data/dataset.csv</code></pre><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray, Document
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">How to Use Every Vector Database in Python with DocArray</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">DocArray handles multimodal data and works with every vector database using a universal API. Here's how you can do it in Python.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alaeddine Abdessalem</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 10, 2023 • 14 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Back in the day, pre-Google, the Internet was mostly text. Whether it was news updates, sports scores, blog posts or emails, ASCII and Unicode were the way to go.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-24.png" class="kg-image" alt="" width="933" height="533" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-24.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-24.png 933w" sizes="(min-width: 720px) 720px"><figcaption>Aaah, the good old days. Just pure ASCII as God intended.</figcaption></figure><p>But nowadays, data is becoming increasingly complex and multimodal, mostly coming in unstructured forms such as images, videos, text, 3D mesh, etc. Gone are the days of being limited to 26 characters and 10 numbers (or more for other character sets). Now there’s <em>much</em> more stuff to deal with.</p><p>Just think about your favorite YouTube videos, Spotify songs, or game NPCs.</p><p>Typical databases can’t handle these kinds of multimodal data. They can only store and process structured data (like simple text strings or numbers). This really limits our ability to extract valuable business insights and value from a huge chunk of the 21st century's data.</p><p>Lucky for us, recent advancements in machine learning techniques and approximate nearest neighbor search have made it possible to better utilize unstructured data:</p><ul><li>Deep learning models and representation learning to effectively represent complex data using vector embeddings.</li><li>Vector databases leverage vector embeddings to store and analyze unstructured data.</li></ul><h2 id="what-are-vector-databases">What are vector databases?</h2><p>A vector database is a type of database that can index and retrieve data using vectors, similar to how a traditional database uses keys or text to search for items using an index. </p><p>A vector database uses a <strong>vector index</strong> to enable fast retrieval and insertion by a vector, and also offers typical database features such as CRUD operations, filtering, and scalability.</p><p>This gives us the best of both worlds - we get the CRUDiness of traditional databases, coupled with the ability to store complex, unstructured data like images, videos, and 3D meshes.</p><p>So, vector databases are great, right? What’s even more awesome is having a library to use them all while being capable of handling unstructured data at the same time! One unstructured data library to rule them all!</p><p>We are, of course, talking about <a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io"><strong>DocArray</strong></a>. Let’s see what this project is all about.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Welcome to DocArray!</div><div class="kg-bookmark-description">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. 🚪 Door to multimodal world: s..…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docarray.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">DocArray 0.20.2 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docarray.jina.ai/_static/banner.png" alt=""></div></a></figure><h2 id="docarrays-universal-pythonic-api-to-all-vector-databases">DocArray's universal Pythonic API to all vector databases</h2><p>As the description suggests on the <a href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io">project home page</a>, DocArray is a library for nested, unstructured and multimodal data.</p><p>This means that if you want to process unstructured data and represent it as vectors, DocArray is perfect for you.</p><p><strong>DocArray is also a universal entrypoint for many vector databases.</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-25.png" class="kg-image" alt="" width="1600" height="976" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-25.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-25.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-25.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>For the remainder of this post, we’ll be using DocArray to index and search data in the <a href="https://amazon-berkeley-objects.s3.amazonaws.com/index.html?ref=jina-ai-gmbh.ghost.io"><strong>Amazon Berkeley Objects Dataset</strong></a>. This dataset contains product items with accompanying images and metadata such as brand, country, and color, and represents the inventory of an e-commerce website.</p><p>Although a traditional database can perform filtering on metadata, it is unable to search image data or other unstructured data formats. That’s why we’re using a vector database!</p><p>We’ll start by loading <a href="https://github.com/jina-ai/product-recommendation-redis-docarray/tree/main/data?ref=jina-ai-gmbh.ghost.io">a subset of the Amazon Berkeley Objects Dataset</a> that comes in CSV format into DocArray and computing vector embeddings.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-26.png" class="kg-image" alt="" width="1382" height="470" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-26.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-26.png 1382w" sizes="(min-width: 720px) 720px"><figcaption>Sample images from the dataset</figcaption></figure><p>Then, we'll use DocArray with each database to perform search and insertion operations using vectors.</p><p>We’ll use the following databases via DocArray in Python:</p><ul><li><strong>Milvus</strong> - cloud-native vector database with storage and computation separated by design</li><li><strong>Weaviate</strong> - vector search engine that stores both objects and vectors and can be accessed through REST or GraphQL</li><li><strong>Qdrant</strong> - vector database written in Rust and designed to be fast and reliable under high loads</li><li><strong>Redis</strong> - in-memory key-value database that supports different kinds of data structures with vector search capabilities</li><li><strong>ElasticSearch</strong> - distributed, RESTful search engine with Approximate Nearest Neighbor search capabilities</li><li><strong>OpenSearch</strong> - open-source search software based on Apache Lucene originally forked from ElasticSearch</li><li><strong>AnnLite</strong> - a Python library for fast Approximate Nearest Neighbor Search with filtering capabilities</li></ul><p>For each database, we’ll:</p><ul><li>Setup the database and install requirements</li><li>Index the data in the vector database</li><li>Perform a vector search operation with filtering</li><li>Display the search results</li></ul><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">The returned results will be the same for each database, since we use the same vectors each time. The key differences are in resource usage, latency, etc.</div></div><h2 id="preparing-the-data">Preparing the data</h2><p>First, we’ll install a few dependencies, namely DocArray, <a href="docs.jina.ai/">Jina</a> (for cloud authentication), and the client for <a href="clip-as-service.jina.ai/">CLIP-as-service</a> (for generating embeddings):</p><pre><code class="language-bash hljs">pip install docarray[common] jina clip-client</code></pre><p>Let’s download a sample CSV dataset and load it into a <a href="https://docarray.jina.ai/fundamentals/documentarray/?ref=jina-ai-gmbh.ghost.io">DocumentArray</a> with <code><a href="https://docarray.jina.ai/datatypes/tabular/?ref=jina-ai-gmbh.ghost.io#load-csv-table">DocumentArray.from_csv()</a></code>:</p><pre><code class="language-bash hljs">wget https://github.com/jina-ai/product-recommendation-redis-docarray/raw/main/data/dataset.csv</code></pre><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray, Document
 
 <span class="hljs-keyword">with</span> <span class="hljs-built_in">open</span>(<span class="hljs-string">'dataset.csv'</span>) <span class="hljs-keyword">as</span> fp:
   da = DocumentArray.from_csv(fp)</code></pre><p>We get an overview using the <code>summary()</code> method:</p><pre><code class="hljs language-python">╭────────────────────── Documents Summary ──────────────────────╮
@@ -253,4 +253,4 @@
 <span class="hljs-comment"># Index data</span>
 annlite_da.extend(encoded_da)</code></pre><p>Now, make a search query for items similar to <code>doc</code> with filter <code>color='Blue'</code>:</p><pre><code class="language-python hljs"><span class="hljs-built_in">filter</span> = {<span class="hljs-string">'color'</span>: {<span class="hljs-string">'$eq'</span>: <span class="hljs-string">'Blue'</span>}}
 results = annlite_da.find(doc,<span class="hljs-built_in">filter</span>=<span class="hljs-built_in">filter</span>, limit=<span class="hljs-number">5</span>)
-results[<span class="hljs-number">0</span>].plot_image_sprites()</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-44.png" class="kg-image" alt="" width="1019" height="1019" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-44.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-44.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-44.png 1019w" sizes="(min-width: 720px) 720px"></figure><p>AnnLite is easy to install and use. With DocArray, it offers a great local vector search with filtering capabilities. Since it does not rely on a client-server architecture, there is no network overhead, yet it implements <a href="https://www.pinecone.io/learn/hnsw/?ref=jina-ai-gmbh.ghost.io">HNSW </a>for fast vector search.</p><p>This explains why it ranks first on Jina AI’s <a href="https://docarray.jina.ai/advanced/document-store/benchmark/?ref=jina-ai-gmbh.ghost.io">one million scale benchmark</a>.</p><p>Read more about <a href="https://docarray.jina.ai/advanced/document-store/annlite/?ref=jina-ai-gmbh.ghost.io">AnnLite integration in DocArray</a>:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docarray.jina.ai/advanced/document-store/annlite/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Annlite</div><div class="kg-bookmark-description">You can use Annlite as a document store for DocumentArray. It’s suitable for faster Document retrieval on embeddings, i.e..match(),.find(). Usage: You can instantiate a DocumentArray with Annlite storage like so: The usage would be the same as the ordinary DocumentArray. To access a DocumentArray...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docarray.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">DocArray 0.20.2 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docarray.jina.ai/_static/banner.png" alt=""></div></a></figure><h2 id="conclusion">Conclusion</h2><p>Vector databases let us efficiently leverage unstructured data and extract useful insights from it. They can perform vector searches, which are useful for similarity matching, recommendations, analysis, etc. </p><p>Choosing the right database can be challenging, depending on your resources, use cases, and requirements. For example, you would choose a different database for high speed versus low memory. </p><p>To help you decide, we’ve published <a href="https://docarray.jina.ai/advanced/document-store/benchmark/?ref=jina-ai-gmbh.ghost.io"><strong>benchmarks of vector databases using </strong></a><strong><a href="https://docarray.jina.ai/advanced/document-store/benchmark/?ref=jina-ai-gmbh.ghost.io">DocArray</a></strong>. That said, you may need to test out a few databases to find your match.</p><p>Normally that testing would mean learning each database before you could use it, taking lots of time and effort. But with DocArray’s unified API you can speak to all of these databases the same way. All it takes is changing one or two lines of code, and bam, you’re using a new database. You can check the <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">docs</a> for more information and install it with <code>pip install docarray</code>.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fhow-to-use-every-vector-database-in-python-with-docarray%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. 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+results[<span class="hljs-number">0</span>].plot_image_sprites()</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-44.png" class="kg-image" alt="" width="1019" height="1019" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-44.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-44.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-44.png 1019w" sizes="(min-width: 720px) 720px"></figure><p>AnnLite is easy to install and use. With DocArray, it offers a great local vector search with filtering capabilities. Since it does not rely on a client-server architecture, there is no network overhead, yet it implements <a href="https://www.pinecone.io/learn/hnsw/?ref=jina-ai-gmbh.ghost.io">HNSW </a>for fast vector search.</p><p>This explains why it ranks first on Jina AI’s <a href="https://docarray.jina.ai/advanced/document-store/benchmark/?ref=jina-ai-gmbh.ghost.io">one million scale benchmark</a>.</p><p>Read more about <a href="https://docarray.jina.ai/advanced/document-store/annlite/?ref=jina-ai-gmbh.ghost.io">AnnLite integration in DocArray</a>:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docarray.jina.ai/advanced/document-store/annlite/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Annlite</div><div class="kg-bookmark-description">You can use Annlite as a document store for DocumentArray. It’s suitable for faster Document retrieval on embeddings, i.e..match(),.find(). Usage: You can instantiate a DocumentArray with Annlite storage like so: The usage would be the same as the ordinary DocumentArray. To access a DocumentArray...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docarray.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">DocArray 0.20.2 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docarray.jina.ai/_static/banner.png" alt=""></div></a></figure><h2 id="conclusion">Conclusion</h2><p>Vector databases let us efficiently leverage unstructured data and extract useful insights from it. They can perform vector searches, which are useful for similarity matching, recommendations, analysis, etc. </p><p>Choosing the right database can be challenging, depending on your resources, use cases, and requirements. For example, you would choose a different database for high speed versus low memory. </p><p>To help you decide, we’ve published <a href="https://docarray.jina.ai/advanced/document-store/benchmark/?ref=jina-ai-gmbh.ghost.io"><strong>benchmarks of vector databases using </strong></a><strong><a href="https://docarray.jina.ai/advanced/document-store/benchmark/?ref=jina-ai-gmbh.ghost.io">DocArray</a></strong>. That said, you may need to test out a few databases to find your match.</p><p>Normally that testing would mean learning each database before you could use it, taking lots of time and effort. But with DocArray’s unified API you can speak to all of these databases the same way. All it takes is changing one or two lines of code, and bam, you’re using a new database. You can check the <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">docs</a> for more information and install it with <code>pip install docarray</code>.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fhow-to-use-every-vector-database-in-python-with-docarray%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Hype and Hybrids: Search is more than Keywords and Vectors</title><meta charset="utf-8"><meta name="title" content="Hype and Hybrids: Search is more than Keywords and Vectors"><meta name="description" content="Twenty years ago, “hybrid” was a term used only by botanists and chemists. Today, hybrid is booming… even in search. Many search systems are rolling out hybrid search schemes with the latest AI. But is &quot;hybrid search&quot; really more than a buzzword?"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/hype-and-hybrids-multimodal-search-means-more-than-keywords-and-vectors-2"><meta property="og:title" content="Hype and Hybrids: Search is more than Keywords and Vectors"><meta property="og:description" content="Twenty years ago, “hybrid” was a term used only by botanists and chemists. Today, hybrid is booming… even in search. Many search systems are rolling out hybrid search schemes with the latest AI. But is &quot;hybrid search&quot; really more than a buzzword?"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--21-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/hype-and-hybrids-multimodal-search-means-more-than-keywords-and-vectors-2"><meta property="twitter:title" content="Hype and Hybrids: Search is more than Keywords and Vectors"><meta property="twitter:description" content="Twenty years ago, “hybrid” was a term used only by botanists and chemists. Today, hybrid is booming… even in search. Many search systems are rolling out hybrid search schemes with the latest AI. But is &quot;hybrid search&quot; really more than a buzzword?"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--21-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Hype and Hybrids: Search is more than Keywords and Vectors</title><meta charset="utf-8"><meta name="title" content="Hype and Hybrids: Search is more than Keywords and Vectors"><meta name="description" content="Twenty years ago, “hybrid” was a term used only by botanists and chemists. Today, hybrid is booming… even in search. Many search systems are rolling out hybrid search schemes with the latest AI. But is &quot;hybrid search&quot; really more than a buzzword?"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/hype-and-hybrids-multimodal-search-means-more-than-keywords-and-vectors-2"><meta property="og:title" content="Hype and Hybrids: Search is more than Keywords and Vectors"><meta property="og:description" content="Twenty years ago, “hybrid” was a term used only by botanists and chemists. Today, hybrid is booming… even in search. Many search systems are rolling out hybrid search schemes with the latest AI. But is &quot;hybrid search&quot; really more than a buzzword?"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--21-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/hype-and-hybrids-multimodal-search-means-more-than-keywords-and-vectors-2"><meta property="twitter:title" content="Hype and Hybrids: Search is more than Keywords and Vectors"><meta property="twitter:description" content="Twenty years ago, “hybrid” was a term used only by botanists and chemists. Today, hybrid is booming… even in search. Many search systems are rolling out hybrid search schemes with the latest AI. But is &quot;hybrid search&quot; really more than a buzzword?"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--21-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Hype and Hybrids: Search is more than Keywords and Vectors</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Twenty years ago, “hybrid” was a term used only by botanists and chemists. Today, hybrid is booming… even in search. Many search systems are rolling out hybrid search schemes with the latest AI. But is "hybrid search" really more than a buzzword?</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Michael Günther, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 04, 2022 • 15 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Many search systems are rolling out hybrid search functionality that combines conventional keywords, traditional text information retrieval techniques, and some kind of “vector” or “neural” search based on recent advances in artificial intelligence. But is “hybrid search” really more than a buzzword? Text-based search is a very old technology, so old that users have now trained themselves to accept its idiosyncrasies and limitations. Do new AI technologies have a lot to add?</p><p>The unsurprising answer is: It depends.</p><p>Modern data stores are multimedia and multi-modal, with texts, images, video and audio stored together in the same databases and on the same computers. This means that to retrieve a picture of, for example, a screwdriver on the website of a hardware store, you can’t just query for the word “<em>screwdriver</em>” and expect that to match some index entry. You must first store and index a text or some kind of label with each picture. Unless you explicitly associate all the pictures of screwdrivers in your database with the label “<em>screwdriver</em>” or some text that says, one way or another, that it’s a picture of a screwdriver, there is no way of using traditional search techniques to find them.</p><p>Adding the best and newest AI technologies to search for texts and labels won’t help if you don’t have useful labels and texts. It doesn’t matter if it’s an improvement on traditional technologies if it has nothing to work with.</p><p>Let’s say we have a large hardware vendor with online shopping that sells potentially hundreds of thousands of different items. They don't have the staff to craft detailed product labels and descriptions or check their accuracy. They may not have pictures for every item and don’t have the time to take good ones. Even the very best text-only search is a flawed solution for them.</p><p>New AI techniques can address these limitations. Deep learning and <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">neural search</a> have made it possible to create powerful general purpose neural network models and to apply them to different kinds of media — texts, images, audio, and video — in a common way, so that, even without text labels, a search for “<em>screwdrivers</em>” finds pictures of screwdrivers!</p><p>But these newer technologies often give results that are hard to explain. Customers might reasonably expect that a query like “<em>Phillips screwdriver</em>” would match a product actually called “<em>Slotted and Phillips Screwdrivers, 4" Long</em>”. Users of traditional search technologies can expect that, but the new AI technologies by their very nature can’t guarantee it.</p><p>No single search model is genuinely adequate for this use-case.</p><p>We’re going to show you how construct a hybrid search system that takes advantage of traditional text matching technologies while retaining and even improving on the value of AI-based search methods. The techniques presented here focus on combining scores to improve results. There will be a follow-up post specifically <a href="https://jina.ai/product/nest/?ref=jina-ai-gmbh.ghost.io">implementing hybrid search using Jina AI inside of Elasticsearch</a>.</p><h2 id="search-models">Search Models</h2><p>We’re going to use three specific search models to build a hybrid search engine: BM25, SBERT and CLIP.</p><p>BM25 is the classic text-based information retrieval algorithm. It is widely used, having first been developed in the 1990s. For more information about BM25, see <a href="http://dx.doi.org/10.1561/1500000019?ref=jina-ai-gmbh.ghost.io">Robertson &amp; Zaragoza (2009)</a>, Spärck Jones et al. (<a href="https://doi.org/10.1016/S0306-4573(00)00015-7?ref=jina-ai-gmbh.ghost.io">2000a</a> and <a href="https://doi.org/10.1016/S0306-4573(00)00016-9?ref=jina-ai-gmbh.ghost.io">2000b</a>), or consult the <a href="https://en.wikipedia.org/wiki/Okapi_BM25?ref=jina-ai-gmbh.ghost.io">presentation on BM25 in Wikipedia</a>. We used the <a href="https://pypi.org/project/rank-bm25/?ref=jina-ai-gmbh.ghost.io"><code>rank_bm25</code></a> package for Python, which fully implements the BM25 ranking algorithm.</p><p><a href="https://www.sbert.net/?ref=jina-ai-gmbh.ghost.io">SBERT</a> is a neural network framework that is widely used in textual information retrieval. We used the <strong><a href="https://huggingface.co/sentence-transformers/msmarco-distilbert-base-v3?ref=jina-ai-gmbh.ghost.io">msmarco-distilbert-base-v3</a></strong> model, because it was trained for the <a href="https://microsoft.github.io/msmarco/?ref=jina-ai-gmbh.ghost.io">MS-MARCO</a> passage ranking task, which is more-or-less the same task as the ranking we’re doing here.</p><p><a href="https://openai.com/blog/clip/?ref=jina-ai-gmbh.ghost.io">CLIP</a> is a neural network trained with both images and descriptive texts. Although CLIP has a number of other usages, we will be using it in this article to match images to text queries, and return ranked results. For this work, we used the <a href="https://huggingface.co/openai/clip-vit-base-patch32?ref=jina-ai-gmbh.ghost.io"><strong>clip-vit-base-patch32</strong></a> model from OpenAI, which is the most widely used CLIP model.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/hybrid_search.png" class="kg-image" alt="" width="1471" height="618" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/hybrid_search.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/hybrid_search.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/hybrid_search.png 1471w" sizes="(min-width: 720px) 720px"><figcaption>All three models take a text query and return a user-specified number of results, each with a score. Query results are ranked by that score.</figcaption></figure><p>All three work by scoring and ranking matches in response to text queries, then returning some number of top results, with the number decided by the user. This makes it easier to integrate them. Both SBERT and CLIP produce scores between -1.0 (worst match for query) and 1.0 (best match). The lowest possible BM25 score is 0.0, but there are no upper bounds.</p><p>To make them fully comparable, we took a few measures:</p><ul><li>We reject all matches from CLIP or SBERT with scores less than zero. These are always bad matches anyway.</li><li>We normalize BM25 scores to the range 0.0 to 1.0 by applying a simple formula: Divide the BM25 score by itself plus 10.</li><li>When a match appears in the top results of one or two but not all three search methods, we assign it an interpolated score for the search methods that miss it. If we request the top <em>N</em> matches, we assign the missing match a small, non-zero value that we determined empirically for each model.</li></ul><p>For example, let’s say we search for “screwdriver” and get the twenty best matches from each of BM25, SBERT and CLIP. BM25 and SBERT search both identify a product “6-Piece Magnetic Tip Screwdriver Set, 3 Phillips and 3 Flat” in the top twenty matches, but CLIP does not have this product in its top twenty matches at all because the picture is of the box it ships in. We then find the lowest score CLIP assigned to any of its top 20 matches, and we use that as the score that CLIP gave to “6-Piece Magnetic Tip Screwdriver Set, 3 Phillips and 3 Flat”.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CodeCogsEqn--2-.svg" class="kg-image" alt="" width="143" height="35"><figcaption>BM25 score normalization</figcaption></figure><h2 id="hybrid-search">Hybrid Search</h2><p>We constructed a hybrid search scheme that combines the results of searches using BM25, SBERT and CLIP. &nbsp;For each query, we performed search using each of the three systems, and retrieved the twenty best matches from each system and adjusted their scores as described in the previous section. The score for each match is a weighted sum the scores given to it by each of the three search systems — SBERT, CLIP, and the normalized BM25.</p><p>Below is a schematization of how the hybrid search scheme works:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/hybrid_search_full.png" class="kg-image" alt="" width="1632" height="1265" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/hybrid_search_full.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/hybrid_search_full.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/hybrid_search_full.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/hybrid_search_full.png 1632w" sizes="(min-width: 720px) 720px"><figcaption>Hybrid search</figcaption></figure><p>Empirical testing found that the following weights worked fairly well:</p><table>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Twenty years ago, “hybrid” was a term used only by botanists and chemists. Today, hybrid is booming… even in search. Many search systems are rolling out hybrid search schemes with the latest AI. But is "hybrid search" really more than a buzzword?</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Michael Günther, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 04, 2022 • 15 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Many search systems are rolling out hybrid search functionality that combines conventional keywords, traditional text information retrieval techniques, and some kind of “vector” or “neural” search based on recent advances in artificial intelligence. But is “hybrid search” really more than a buzzword? Text-based search is a very old technology, so old that users have now trained themselves to accept its idiosyncrasies and limitations. Do new AI technologies have a lot to add?</p><p>The unsurprising answer is: It depends.</p><p>Modern data stores are multimedia and multi-modal, with texts, images, video and audio stored together in the same databases and on the same computers. This means that to retrieve a picture of, for example, a screwdriver on the website of a hardware store, you can’t just query for the word “<em>screwdriver</em>” and expect that to match some index entry. You must first store and index a text or some kind of label with each picture. Unless you explicitly associate all the pictures of screwdrivers in your database with the label “<em>screwdriver</em>” or some text that says, one way or another, that it’s a picture of a screwdriver, there is no way of using traditional search techniques to find them.</p><p>Adding the best and newest AI technologies to search for texts and labels won’t help if you don’t have useful labels and texts. It doesn’t matter if it’s an improvement on traditional technologies if it has nothing to work with.</p><p>Let’s say we have a large hardware vendor with online shopping that sells potentially hundreds of thousands of different items. They don't have the staff to craft detailed product labels and descriptions or check their accuracy. They may not have pictures for every item and don’t have the time to take good ones. Even the very best text-only search is a flawed solution for them.</p><p>New AI techniques can address these limitations. Deep learning and <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">neural search</a> have made it possible to create powerful general purpose neural network models and to apply them to different kinds of media — texts, images, audio, and video — in a common way, so that, even without text labels, a search for “<em>screwdrivers</em>” finds pictures of screwdrivers!</p><p>But these newer technologies often give results that are hard to explain. Customers might reasonably expect that a query like “<em>Phillips screwdriver</em>” would match a product actually called “<em>Slotted and Phillips Screwdrivers, 4" Long</em>”. Users of traditional search technologies can expect that, but the new AI technologies by their very nature can’t guarantee it.</p><p>No single search model is genuinely adequate for this use-case.</p><p>We’re going to show you how construct a hybrid search system that takes advantage of traditional text matching technologies while retaining and even improving on the value of AI-based search methods. The techniques presented here focus on combining scores to improve results. There will be a follow-up post specifically <a href="https://jina.ai/product/nest/?ref=jina-ai-gmbh.ghost.io">implementing hybrid search using Jina AI inside of Elasticsearch</a>.</p><h2 id="search-models">Search Models</h2><p>We’re going to use three specific search models to build a hybrid search engine: BM25, SBERT and CLIP.</p><p>BM25 is the classic text-based information retrieval algorithm. It is widely used, having first been developed in the 1990s. For more information about BM25, see <a href="http://dx.doi.org/10.1561/1500000019?ref=jina-ai-gmbh.ghost.io">Robertson &amp; Zaragoza (2009)</a>, Spärck Jones et al. (<a href="https://doi.org/10.1016/S0306-4573(00)00015-7?ref=jina-ai-gmbh.ghost.io">2000a</a> and <a href="https://doi.org/10.1016/S0306-4573(00)00016-9?ref=jina-ai-gmbh.ghost.io">2000b</a>), or consult the <a href="https://en.wikipedia.org/wiki/Okapi_BM25?ref=jina-ai-gmbh.ghost.io">presentation on BM25 in Wikipedia</a>. We used the <a href="https://pypi.org/project/rank-bm25/?ref=jina-ai-gmbh.ghost.io"><code>rank_bm25</code></a> package for Python, which fully implements the BM25 ranking algorithm.</p><p><a href="https://www.sbert.net/?ref=jina-ai-gmbh.ghost.io">SBERT</a> is a neural network framework that is widely used in textual information retrieval. We used the <strong><a href="https://huggingface.co/sentence-transformers/msmarco-distilbert-base-v3?ref=jina-ai-gmbh.ghost.io">msmarco-distilbert-base-v3</a></strong> model, because it was trained for the <a href="https://microsoft.github.io/msmarco/?ref=jina-ai-gmbh.ghost.io">MS-MARCO</a> passage ranking task, which is more-or-less the same task as the ranking we’re doing here.</p><p><a href="https://openai.com/blog/clip/?ref=jina-ai-gmbh.ghost.io">CLIP</a> is a neural network trained with both images and descriptive texts. Although CLIP has a number of other usages, we will be using it in this article to match images to text queries, and return ranked results. For this work, we used the <a href="https://huggingface.co/openai/clip-vit-base-patch32?ref=jina-ai-gmbh.ghost.io"><strong>clip-vit-base-patch32</strong></a> model from OpenAI, which is the most widely used CLIP model.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/hybrid_search.png" class="kg-image" alt="" width="1471" height="618" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/hybrid_search.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/hybrid_search.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/hybrid_search.png 1471w" sizes="(min-width: 720px) 720px"><figcaption>All three models take a text query and return a user-specified number of results, each with a score. Query results are ranked by that score.</figcaption></figure><p>All three work by scoring and ranking matches in response to text queries, then returning some number of top results, with the number decided by the user. This makes it easier to integrate them. Both SBERT and CLIP produce scores between -1.0 (worst match for query) and 1.0 (best match). The lowest possible BM25 score is 0.0, but there are no upper bounds.</p><p>To make them fully comparable, we took a few measures:</p><ul><li>We reject all matches from CLIP or SBERT with scores less than zero. These are always bad matches anyway.</li><li>We normalize BM25 scores to the range 0.0 to 1.0 by applying a simple formula: Divide the BM25 score by itself plus 10.</li><li>When a match appears in the top results of one or two but not all three search methods, we assign it an interpolated score for the search methods that miss it. If we request the top <em>N</em> matches, we assign the missing match a small, non-zero value that we determined empirically for each model.</li></ul><p>For example, let’s say we search for “screwdriver” and get the twenty best matches from each of BM25, SBERT and CLIP. BM25 and SBERT search both identify a product “6-Piece Magnetic Tip Screwdriver Set, 3 Phillips and 3 Flat” in the top twenty matches, but CLIP does not have this product in its top twenty matches at all because the picture is of the box it ships in. We then find the lowest score CLIP assigned to any of its top 20 matches, and we use that as the score that CLIP gave to “6-Piece Magnetic Tip Screwdriver Set, 3 Phillips and 3 Flat”.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CodeCogsEqn--2-.svg" class="kg-image" alt="" width="143" height="35"><figcaption>BM25 score normalization</figcaption></figure><h2 id="hybrid-search">Hybrid Search</h2><p>We constructed a hybrid search scheme that combines the results of searches using BM25, SBERT and CLIP. &nbsp;For each query, we performed search using each of the three systems, and retrieved the twenty best matches from each system and adjusted their scores as described in the previous section. The score for each match is a weighted sum the scores given to it by each of the three search systems — SBERT, CLIP, and the normalized BM25.</p><p>Below is a schematization of how the hybrid search scheme works:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/hybrid_search_full.png" class="kg-image" alt="" width="1632" height="1265" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/hybrid_search_full.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/hybrid_search_full.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/hybrid_search_full.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/hybrid_search_full.png 1632w" sizes="(min-width: 720px) 720px"><figcaption>Hybrid search</figcaption></figure><p>Empirical testing found that the following weights worked fairly well:</p><table>
 <thead>
 <tr>
 <th>Model</th>
@@ -33,38 +33,38 @@
 </tr>
 </tbody>
 </table>
-<p>Intuitively, we can interpret this as placing a bit more than half the weight on text retrieval (SBERT and BM25) and bit less than half on text-to-image retrieval (CLIP), with BM25’s 0.1 weight ensuring a bias in favor of traditional term matches, all else being equal, or acting as a fallback when neural models fail to produce any good results.</p><h2 id="comparing-search-schemes">Comparing Search Schemes</h2><h3 id="test-data">Test Data</h3><p>Ideally, we would have the product database and query log of a real online vendor<em>.</em> However, companies (especially fictional ones) generally don't make their users’ queries available to researchers for commercial and legal reasons. So we are forced to use a substitute.</p><p>We used the closest readily available alternative: the <a href="https://xmrec.github.io/?ref=jina-ai-gmbh.ghost.io">XMarket dataset</a>. This data is drawn from Amazon.com marketplaces in eighteen countries, and consists of product images found on Amazon websites, as well as product names, descriptions, categories and various metadata.</p><p>For this article, we used a subset of the XMarket data: Only entries in the category <em>Electronics</em>, and only from the US Amazon site. This comes to 15,934 products distributed over 837 categories.</p><p>Furthermore, of the information fields available for each item, we used only the following:</p><ul><li>ASIN — &nbsp;A unique product ID assigned by Amazon.</li><li>Title — The name of the product as used by Amazon.</li><li>Description — Free text description of the product, presumably from the manufacturer or vendor.</li><li>Categories — A label within Amazon’s hierarchical product ontology.</li><li>Image — The image or photo Amazon uses on this product’s page.</li></ul><p>You can see an example record below:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/example_document_sd_card.png" class="kg-image" alt="" width="1826" height="741" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/example_document_sd_card.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/example_document_sd_card.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/example_document_sd_card.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/example_document_sd_card.png 1826w" sizes="(min-width: 720px) 720px"><figcaption>An example of an entry in the XMarket dataset</figcaption></figure><p>You can examine the data yourself by <a href="https://docs.jina.ai/jina-ai-cloud/login/?ref=jina-ai-gmbh.ghost.io">logging in to Jina AI</a> (using <code>jina auth login</code> at the command line to access your existing account, or to create one) and downloading it using the DocArray Python module:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - docarray/docarray: 🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store</div><div class="kg-bookmark-description">🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store - GitHub - docarray/docarray: 🧬 The data structure for unstructured multimodal data · Neural S...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/438303578/57aae8cb-5b20-4e35-a46c-9a742af1470c" alt=""></div></a></figure><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
+<p>Intuitively, we can interpret this as placing a bit more than half the weight on text retrieval (SBERT and BM25) and bit less than half on text-to-image retrieval (CLIP), with BM25’s 0.1 weight ensuring a bias in favor of traditional term matches, all else being equal, or acting as a fallback when neural models fail to produce any good results.</p><h2 id="comparing-search-schemes">Comparing Search Schemes</h2><h3 id="test-data">Test Data</h3><p>Ideally, we would have the product database and query log of a real online vendor<em>.</em> However, companies (especially fictional ones) generally don't make their users’ queries available to researchers for commercial and legal reasons. So we are forced to use a substitute.</p><p>We used the closest readily available alternative: the <a href="https://xmrec.github.io/?ref=jina-ai-gmbh.ghost.io">XMarket dataset</a>. This data is drawn from Amazon.com marketplaces in eighteen countries, and consists of product images found on Amazon websites, as well as product names, descriptions, categories and various metadata.</p><p>For this article, we used a subset of the XMarket data: Only entries in the category <em>Electronics</em>, and only from the US Amazon site. This comes to 15,934 products distributed over 837 categories.</p><p>Furthermore, of the information fields available for each item, we used only the following:</p><ul><li>ASIN — &nbsp;A unique product ID assigned by Amazon.</li><li>Title — The name of the product as used by Amazon.</li><li>Description — Free text description of the product, presumably from the manufacturer or vendor.</li><li>Categories — A label within Amazon’s hierarchical product ontology.</li><li>Image — The image or photo Amazon uses on this product’s page.</li></ul><p>You can see an example record below:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/example_document_sd_card.png" class="kg-image" alt="" width="1826" height="741" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/example_document_sd_card.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/example_document_sd_card.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/example_document_sd_card.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/example_document_sd_card.png 1826w" sizes="(min-width: 720px) 720px"><figcaption>An example of an entry in the XMarket dataset</figcaption></figure><p>You can examine the data yourself by <a href="https://docs.jina.ai/jina-ai-cloud/login/?ref=jina-ai-gmbh.ghost.io">logging in to Jina AI</a> (using <code>jina auth login</code> at the command line to access your existing account, or to create one) and downloading it using the DocArray Python module:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/docarray/docarray?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - docarray/docarray: 🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store</div><div class="kg-bookmark-description">🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store - GitHub - docarray/docarray: 🧬 The data structure for unstructured multimodal data · Neural S...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">docarray</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/438303578/57aae8cb-5b20-4e35-a46c-9a742af1470c" alt=""></div></a></figure><pre><code class="language-python">from docarray import DocumentArray
 
-xmarket_dataset = DocumentArray.pull(<span class="hljs-string">'xmarket_dataset'</span>)
-xmarket_dataset.summary()</code></pre><pre><code class="hljs language-python">╭────────────────── Documents Summary ───────────────────╮
+xmarket_dataset = DocumentArray.pull('xmarket_dataset')
+xmarket_dataset.summary()</code></pre><pre><code>╭────────────────── Documents Summary ───────────────────╮
 │                                                        │
-│   <span class="hljs-type">Type</span>                      DocumentArrayInMemory      │
-│   Length                    <span class="hljs-number">16934</span>                      │
-│   Homogenous Documents      <span class="hljs-literal">True</span>                       │
-│   Has nested Documents <span class="hljs-keyword">in</span>   (<span class="hljs-string">'chunks'</span>,)                │
-│   Common Attributes         (<span class="hljs-string">'id'</span>, <span class="hljs-string">'tags'</span>, <span class="hljs-string">'chunks'</span>)   │
-│   Multimodal dataclass      <span class="hljs-literal">True</span>                       │
+│   Type                      DocumentArrayInMemory      │
+│   Length                    16934                      │
+│   Homogenous Documents      True                       │
+│   Has nested Documents in   ('chunks',)                │
+│   Common Attributes         ('id', 'tags', 'chunks')   │
+│   Multimodal dataclass      True                       │
 │                                                        │
 ╰────────────────────────────────────────────────────────╯
 ╭──────────────────────── Attributes Summary ────────────────────────╮
 │                                                                    │
-│   Attribute   Data <span class="hljs-built_in">type</span>         <span class="hljs-comment">#Unique values   Has empty value   │</span>
+│   Attribute   Data type         #Unique values   Has empty value   │
 │  ────────────────────────────────────────────────────────────────  │
-│   chunks      (<span class="hljs-string">'ChunkArray'</span>,)   <span class="hljs-number">16934</span>            <span class="hljs-literal">False</span>             │
-│   <span class="hljs-built_in">id</span>          (<span class="hljs-string">'str'</span>,)          <span class="hljs-number">16934</span>            <span class="hljs-literal">False</span>             │
-│   tags        (<span class="hljs-string">'dict'</span>,)         <span class="hljs-number">16934</span>            <span class="hljs-literal">False</span>             │
+│   chunks      ('ChunkArray',)   16934            False             │
+│   id          ('str',)          16934            False             │
+│   tags        ('dict',)         16934            False             │
 │                                                                    │
-╰────────────────────────────────────────────────────────────────────╯</code></pre><h3 id="task-description">Task Description</h3><p>Since we don’t have Amazon’s query logs either, we can’t test systems against a representative sample of queries. &nbsp;So we are forced to choose a similar but different task.</p><p>Amazon has assigned each product in the XMarket dataset is to a category in its product ontology, and those categories have text labels. For example, the <em>“Sandisk MicroSD Card”</em> in the previous section is assigned to the category <em>“Micro SD Cards”</em>.</p><p>The search task that we will use to compare search schemes is to use those category labels as text queries, and then check if the query result returns items belonging to that category. To turn this into a quantitative measure, we look at the <em>mean reciprocal rank</em> (MRR), which we measure as follows:</p><p>We queried search systems with each category label and retrieved the twenty highest-ranked results. We then found the rank of the highest ranked result that was actually in that category. We then assigned that query the score <em>1.0/rank</em>.</p><p>For example, if the first result from the query <em>“Micro SD Cards”</em> was a product that Amazon categorizes as belonging to “<em>Micro SD Cards</em>”, then that query has a score of 1.0. &nbsp;If the first four results were not members of that category but the fifth was, then the score is 0.2. If none of the top twenty belonged to that category, then the score is 0.0.</p><p>For each search system, we average the score for all queries to calculate the <em>mean reciprocal rank</em>. Since this is dependent on how many results we took for each query, we label it as <em>MRR@20</em> because we use the top twenty results for each query.</p><h3 id="preparing-the-search-databases-and-indexes">Preparing the search databases and indexes</h3><p>We selected 1,000 items from the 15,934 to use for testing. These ranged over 296 categories. The remaining data we held out for use in the next section.</p><p>We then prepared a BM25 index by getting the title and description for each item in the test set and using the <code>rank_bm25</code> package, and specifically the <code>BM25Okapi</code> algorithm, to create a text retrieval database. See the <a href="https://github.com/dorianbrown/rank_bm25/blob/master/README.md?ref=jina-ai-gmbh.ghost.io">relevant README on GitHub for specifics</a>.</p><p>For SBERT, we used Jina AI DocArray to create a vector retrieval database, using the title and description of each test set item as input texts. </p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> finetuner
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document, DocumentArray
+╰────────────────────────────────────────────────────────────────────╯</code></pre><h3 id="task-description">Task Description</h3><p>Since we don’t have Amazon’s query logs either, we can’t test systems against a representative sample of queries. &nbsp;So we are forced to choose a similar but different task.</p><p>Amazon has assigned each product in the XMarket dataset is to a category in its product ontology, and those categories have text labels. For example, the <em>“Sandisk MicroSD Card”</em> in the previous section is assigned to the category <em>“Micro SD Cards”</em>.</p><p>The search task that we will use to compare search schemes is to use those category labels as text queries, and then check if the query result returns items belonging to that category. To turn this into a quantitative measure, we look at the <em>mean reciprocal rank</em> (MRR), which we measure as follows:</p><p>We queried search systems with each category label and retrieved the twenty highest-ranked results. We then found the rank of the highest ranked result that was actually in that category. We then assigned that query the score <em>1.0/rank</em>.</p><p>For example, if the first result from the query <em>“Micro SD Cards”</em> was a product that Amazon categorizes as belonging to “<em>Micro SD Cards</em>”, then that query has a score of 1.0. &nbsp;If the first four results were not members of that category but the fifth was, then the score is 0.2. If none of the top twenty belonged to that category, then the score is 0.0.</p><p>For each search system, we average the score for all queries to calculate the <em>mean reciprocal rank</em>. Since this is dependent on how many results we took for each query, we label it as <em>MRR@20</em> because we use the top twenty results for each query.</p><h3 id="preparing-the-search-databases-and-indexes">Preparing the search databases and indexes</h3><p>We selected 1,000 items from the 15,934 to use for testing. These ranged over 296 categories. The remaining data we held out for use in the next section.</p><p>We then prepared a BM25 index by getting the title and description for each item in the test set and using the <code>rank_bm25</code> package, and specifically the <code>BM25Okapi</code> algorithm, to create a text retrieval database. See the <a href="https://github.com/dorianbrown/rank_bm25/blob/master/README.md?ref=jina-ai-gmbh.ghost.io">relevant README on GitHub for specifics</a>.</p><p>For SBERT, we used Jina AI DocArray to create a vector retrieval database, using the title and description of each test set item as input texts. </p><pre><code class="language-python">import finetuner
+from docarray import Document, DocumentArray
 
-sbert_model = finetuner.build_model(<span class="hljs-string">'sentence-transformers/msmarco-distilbert-base-v3'</span>)
+sbert_model = finetuner.build_model('sentence-transformers/msmarco-distilbert-base-v3')
 
 finetuner.encode(sbert_model, product_categories)
-finetuner.encode(sbert_model, product_texts)</code></pre><p>For CLIP, we followed the same procedure, but using product images from the same test set.</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> finetuner
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> Document, DocumentArray
+finetuner.encode(sbert_model, product_texts)</code></pre><p>For CLIP, we followed the same procedure, but using product images from the same test set.</p><pre><code class="language-python">import finetuner
+from docarray import Document, DocumentArray
 
-clip_text_model = finetuner.build_model(<span class="hljs-string">'openai/clip-vit-base-patch32'</span>, select_model=<span class="hljs-string">'clip-text'</span>)
-clip_vision_model = finetuner.build_model(<span class="hljs-string">'openai/clip-vit-base-patch32'</span>, select_model=<span class="hljs-string">'clip-vision'</span>)
+clip_text_model = finetuner.build_model('openai/clip-vit-base-patch32', select_model='clip-text')
+clip_vision_model = finetuner.build_model('openai/clip-vit-base-patch32', select_model='clip-vision')
 
 
 finetuner.encode(clip_text_model, product_categories)
@@ -125,38 +125,38 @@
 <td>49.1%</td>    
 </tr>
 </tbody>
-</table><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-text">All pairs of search models are better than their individual components.</div></div><p>These results alone show the potential for improving search using hybrid methods. The biggest jump comes from combining the two individually worst-scoring models: BM25 and CLIP, which go from scoring roughly 30% separately to over 40% together. Text and image search are complementary, the one compensating for the shortcomings of the other.</p><p>SBERT, however, is only a bit improved by adding CLIP and BM25, jumping from a score of 49% to 53%. &nbsp;This still represents an 8% relative improvement compared to SBERT alone.</p><h2 id="fine-tuning">Fine-tuning</h2><p>Fine-tuning improves the performance of pre-trained neural networks by adding training data that is more representative of your specific use-case.</p><p>Jina AI Finetuner makes fine-tuning easier, faster and more performant by streamlining the workflow and handling all the operational complexity and physical infrastructure in the cloud. </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>It works by applying <a href="https://finetuner.jina.ai/get-started/how-it-works/?ref=jina-ai-gmbh.ghost.io">contrastive metric learning</a>, which takes pairs of items that belong together, and then adjusts the model so that it makes better distinctions. There is no need to hand-annotate data or identify what products ought to match each query. As long as you have some kind of information about the semantic relatedness of pairs of data items that fit your use-case, you can use the Finetuner to improve performance.</p><p>Having already selected 1,000 items from the XMarket dataset as test data, we used the remaining almost 15,000 entries as training data to fine-tune SBERT and CLIP. </p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-text">The training set contains only <em>some </em>of the categories in the test set and <em>none </em>of the products.</div></div><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Finetuner_before_after.png" class="kg-image" alt="" width="986" height="607" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Finetuner_before_after.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Finetuner_before_after.png 986w" sizes="(min-width: 720px) 720px"><figcaption>A highly schematized representation of what fine-tuning does: Jina AI Finetuner works by training neural networks to bring closer together the output vectors of things that belong together, and move apart those that don’t.</figcaption></figure><p>For SBERT, we extracted product titles, product descriptions, and category names from the training set. The logic of fine-tuning is that we want to train SBERT to recognize that product names and descriptions belonging to products in the same category should be relatively good matches for each other and for their category label. Using this information, we reorganized the training data as a <code>DocumentArray</code>object for fine-tuning SBERT, as described in the <a href="https://finetuner.jina.ai/walkthrough/create-training-data/?ref=jina-ai-gmbh.ghost.io">Jina AI Finetuner documentation</a>.</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> finetuner
+</table><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-text">All pairs of search models are better than their individual components.</div></div><p>These results alone show the potential for improving search using hybrid methods. The biggest jump comes from combining the two individually worst-scoring models: BM25 and CLIP, which go from scoring roughly 30% separately to over 40% together. Text and image search are complementary, the one compensating for the shortcomings of the other.</p><p>SBERT, however, is only a bit improved by adding CLIP and BM25, jumping from a score of 49% to 53%. &nbsp;This still represents an 8% relative improvement compared to SBERT alone.</p><h2 id="fine-tuning">Fine-tuning</h2><p>Fine-tuning improves the performance of pre-trained neural networks by adding training data that is more representative of your specific use-case.</p><p>Jina AI Finetuner makes fine-tuning easier, faster and more performant by streamlining the workflow and handling all the operational complexity and physical infrastructure in the cloud. </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>It works by applying <a href="https://finetuner.jina.ai/get-started/how-it-works/?ref=jina-ai-gmbh.ghost.io">contrastive metric learning</a>, which takes pairs of items that belong together, and then adjusts the model so that it makes better distinctions. There is no need to hand-annotate data or identify what products ought to match each query. As long as you have some kind of information about the semantic relatedness of pairs of data items that fit your use-case, you can use the Finetuner to improve performance.</p><p>Having already selected 1,000 items from the XMarket dataset as test data, we used the remaining almost 15,000 entries as training data to fine-tune SBERT and CLIP. </p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-text">The training set contains only <em>some </em>of the categories in the test set and <em>none </em>of the products.</div></div><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Finetuner_before_after.png" class="kg-image" alt="" width="986" height="607" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Finetuner_before_after.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Finetuner_before_after.png 986w" sizes="(min-width: 720px) 720px"><figcaption>A highly schematized representation of what fine-tuning does: Jina AI Finetuner works by training neural networks to bring closer together the output vectors of things that belong together, and move apart those that don’t.</figcaption></figure><p>For SBERT, we extracted product titles, product descriptions, and category names from the training set. The logic of fine-tuning is that we want to train SBERT to recognize that product names and descriptions belonging to products in the same category should be relatively good matches for each other and for their category label. Using this information, we reorganized the training data as a <code>DocumentArray</code>object for fine-tuning SBERT, as described in the <a href="https://finetuner.jina.ai/walkthrough/create-training-data/?ref=jina-ai-gmbh.ghost.io">Jina AI Finetuner documentation</a>.</p><pre><code class="language-python">import finetuner
 
-<span class="hljs-comment"># login to finetuner api</span>
+# login to finetuner api
 finetuner.login()
 
-<span class="hljs-comment"># create and submit SBERT finetuning job</span>
+# create and submit SBERT finetuning job
 sbert_run = finetuner.fit(
-    model=<span class="hljs-string">'sentence-transformers/msmarco-distilbert-base-v3'</span>,
+    model='sentence-transformers/msmarco-distilbert-base-v3',
     train_data=sbert_train_data,
-    epochs=<span class="hljs-number">3</span>,
-    batch_size=<span class="hljs-number">64</span>,
-    learning_rate=<span class="hljs-number">1e-6</span>,
-    cpu=<span class="hljs-literal">False</span>,
+    epochs=3,
+    batch_size=64,
+    learning_rate=1e-6,
+    cpu=False,
 )
 
-<span class="hljs-comment"># Wait for the run to finish!</span>
+# Wait for the run to finish!
 
-finetuned_sbert_model = finetuner.get_model(sbert_run.artifact_id)</code></pre><p>We then extracted pairs of product images and their category names and did the same to construct a <code>DocumentArray</code>object for fine-tuning CLIP. The idea is to train it to place the category names and images closer together.</p><pre><code class="language-python hljs"><span class="hljs-comment"># create and submit CLIP finetuning job</span>
+finetuned_sbert_model = finetuner.get_model(sbert_run.artifact_id)</code></pre><p>We then extracted pairs of product images and their category names and did the same to construct a <code>DocumentArray</code>object for fine-tuning CLIP. The idea is to train it to place the category names and images closer together.</p><pre><code class="language-python"># create and submit CLIP finetuning job
 clip_run = finetuner.fit(
-    model=<span class="hljs-string">'openai/clip-vit-base-patch32'</span>,
-    loss=<span class="hljs-string">'CLIPLoss'</span>,
+    model='openai/clip-vit-base-patch32',
+    loss='CLIPLoss',
     train_data=clip_train_da,
-    epochs=<span class="hljs-number">3</span>,
-    batch_size=<span class="hljs-number">128</span>,
-    learning_rate=<span class="hljs-number">1e-6</span>,
-    cpu=<span class="hljs-literal">False</span>
+    epochs=3,
+    batch_size=128,
+    learning_rate=1e-6,
+    cpu=False
 )
 
-<span class="hljs-comment"># Wait for the run to finish!</span>
+# Wait for the run to finish!
 
-finetuned_clip_text_model = finetuner.get_model(clip_run.artifact_id, select_model=<span class="hljs-string">'clip-text'</span>)
-finetuned_clip_vision_model = finetuner.get_model(clip_run.artifact_id, select_model=<span class="hljs-string">'clip-vision'</span>)</code></pre><p>BM25 is not based on neural networks, so naturally, it cannot be fine-tuned. After fine-tuning, it will have a sharp disadvantage compared to SBERT and CLIP because it has no information about categories at all.</p><p>After fine-tuning SBERT and CLIP, we reran the evaluation with only the 1,000 item test set, and achieved the following average scores:</p><table>
+finetuned_clip_text_model = finetuner.get_model(clip_run.artifact_id, select_model='clip-text')
+finetuned_clip_vision_model = finetuner.get_model(clip_run.artifact_id, select_model='clip-vision')</code></pre><p>BM25 is not based on neural networks, so naturally, it cannot be fine-tuned. After fine-tuning, it will have a sharp disadvantage compared to SBERT and CLIP because it has no information about categories at all.</p><p>After fine-tuning SBERT and CLIP, we reran the evaluation with only the 1,000 item test set, and achieved the following average scores:</p><table>
 <thead>
 <tr>
 <th>Search model</th>
@@ -197,4 +197,4 @@
 </tr>
 </tbody>
 </table>
-<p>Although we see improvements in all scenarios, CLIP’s performance skyrockets with fine-tuning. And for hybrid search using all three techniques, there is over 12% relative improvement.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-text">A benefit of using neural network-based AI technologies is the ability to fine-tune pre-trained networks to your data.</div></div><h1 id="why-does-this-work">Why Does This Work?</h1><p>Clearly, hybrid searching rocks. But looking at the evaluation numbers alone understates the improvement each component brings.</p><p>For example, for the query "<em>CD-RW Discs</em>", BM25 gives a very high score to a product labeled "<em>Verbatim CD-RW 700MB 2X-12X Rewritable Media Disc - 25 Pack Spindle Style</em>". This is exactly right.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CD-RW_Discs_BM25-1.png" class="kg-image" alt="" width="233" height="120"><figcaption><em>Verbatim CD-RW 700MB 2X-12X Rewritable Media Disc - 25 Pack Spindle Style</em></figcaption></figure><p>SBERT, however, is misled by a long descriptive text that contains many terms it associates with the search terms:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CD-RW_Discs_SBERT-1.png" class="kg-image" alt="" width="255" height="173"><figcaption><em>Memorex 4x DVD+RW 25 Pack Spindle. </em>This 25-pack of 4x DVD+RW discs for newer DVD+R/+RW drives (part number 32025541) consists of rewriteable, single-sided discs that store up to 4.7 GB of data and approximately 240 minutes of video (depending on your mastering software; 120 minutes optimal)--that's more than six times as much data as will fit on a recordable CD. You can transfer your home movies from VHS or 8 mm cassettes, back-up computer hard drives and large files, or stuff them chock full of MP3 music files and JPEG image files from your digital camera. Rewritable "plus" discs require no finalizing--you can record, eject, and play them with minimal fuss, thanks to "background formatting." This feature, which lowers total burning time, is an advantage over the "dash" formats. For PC users, DVD+RW also offers advantages over DVD-RW, including on-disc content editing, built-in defect management, and multisession writing. What's in the Box 25 DVD+RW discs, 1 two-piece storage case, and a paper insert with product details.</figcaption></figure><p>CLIP, because it relies on visual similarity, is also poorly able to distinguish “C<em>D-RW Discs</em>” from other kinds of optical disks. They look exactly the same to humans too, if you take away the label text. It gives its highest ranking to this, a product that clearly doesn't match what the user is looking for:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CD-RW_Discs_CLIP-1.png" class="kg-image" alt="" width="285" height="280"><figcaption><em>Philips 52X 700MB CD-R 50PK Spindle</em></figcaption></figure><p>CLIP excels when query terms are poor matches for descriptions, but good matches for its visual analysis of product pictures. &nbsp;For example, the query “<em>Earbud Headphones</em>” is a poor match for the textual label "<em>Maxell 190329 Portable lightweight Behind The Head Extended Comfort Soft Touch Rubber Memory Neckband Stereo Line Neckband Head Buds - Silver</em>". But it's a good match for the image below:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Earbud-Headphones_CLIP.png" class="kg-image" alt="" width="450" height="319"><figcaption><em>Maxell 190329 Portable lightweight Behind The Head Extended Comfort Soft Touch Rubber Memory Neckband Stereo Line Neckband Head Buds - Silver</em></figcaption></figure><p>CLIP gives this product a high score because of its appearance, which it correctly identifies with “earbud”.</p><p>SBERT and BM25 both miss this match, giving their highest rankings to traditional “over-the-ear” headphones like this one:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Earbud-Headphones_SBERT-1.png" class="kg-image" alt="" width="343" height="559"><figcaption><em>Panasonic Headphones On-Ear Lightweight with XBS RP-HT21 (Black &amp; Silver)</em></figcaption></figure><p>SBERT excels where there is good textual information for matching, even if the match is not exact. For example, the query “<em>Fiber Optic Cables</em>” gives us this match from SBERT:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Fiber_Optic_Cables_SBERT-1.png" class="kg-image" alt="" width="261" height="323"><figcaption><em>CNE25969 6-Feet 1.8m PCD Basics Fiber Optic Audio Cable</em></figcaption></figure><p>CLIP, in contrast, is useless with this query because it is unable to visually distinguish fiber optic cables from any other kind of cable, and highly ranks matches like this:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Fiber_Optic_Cables_CLIP.png" class="kg-image" alt="" width="541" height="355"><figcaption><em>C2G 31348 Cat6 Cable - Snagless Unshielded Ethernet Network Patch Cable, Orange</em></figcaption></figure><h2 id="bring-hybrid-vigor-to-your-search">Bring Hybrid Vigor to Your Search</h2><p>Even with clean visual data and expansive descriptions, hybrid search with classical text retrieval technologies and AI-driven neural search is better than relying on just one technology.</p><p>Most use-cases are much less ideal. Descriptions are inaccurate, inadequate, or just plain missing. Photos are of poor quality or absent. And when users put in their queries texts with exact matches, they expect to see those matches in the results. Each of the three technologies is essential to meeting user expectations and providing good results.</p><p>With Jina AI’s framework, combining search results and fine-tuning for your use-case produces high quality retrieval software almost out of the box.</p><p>We are always moving forward at Jina AI, bringing state-of-the-art cloud-native neural AI to users through our intuitive Python framework and NoCode solutions. Feel free to contact us via our <a href="https://jina.ai/slack/?ref=jina-ai-gmbh.ghost.io">Community Slack</a> with comments or to discuss your use-case.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fhype-and-hybrids-multimodal-search-means-more-than-keywords-and-vectors-2%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; 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+<p>Although we see improvements in all scenarios, CLIP’s performance skyrockets with fine-tuning. And for hybrid search using all three techniques, there is over 12% relative improvement.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-text">A benefit of using neural network-based AI technologies is the ability to fine-tune pre-trained networks to your data.</div></div><h1 id="why-does-this-work">Why Does This Work?</h1><p>Clearly, hybrid searching rocks. But looking at the evaluation numbers alone understates the improvement each component brings.</p><p>For example, for the query "<em>CD-RW Discs</em>", BM25 gives a very high score to a product labeled "<em>Verbatim CD-RW 700MB 2X-12X Rewritable Media Disc - 25 Pack Spindle Style</em>". This is exactly right.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CD-RW_Discs_BM25-1.png" class="kg-image" alt="" width="233" height="120"><figcaption><em>Verbatim CD-RW 700MB 2X-12X Rewritable Media Disc - 25 Pack Spindle Style</em></figcaption></figure><p>SBERT, however, is misled by a long descriptive text that contains many terms it associates with the search terms:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CD-RW_Discs_SBERT-1.png" class="kg-image" alt="" width="255" height="173"><figcaption><em>Memorex 4x DVD+RW 25 Pack Spindle. </em>This 25-pack of 4x DVD+RW discs for newer DVD+R/+RW drives (part number 32025541) consists of rewriteable, single-sided discs that store up to 4.7 GB of data and approximately 240 minutes of video (depending on your mastering software; 120 minutes optimal)--that's more than six times as much data as will fit on a recordable CD. You can transfer your home movies from VHS or 8 mm cassettes, back-up computer hard drives and large files, or stuff them chock full of MP3 music files and JPEG image files from your digital camera. Rewritable "plus" discs require no finalizing--you can record, eject, and play them with minimal fuss, thanks to "background formatting." This feature, which lowers total burning time, is an advantage over the "dash" formats. For PC users, DVD+RW also offers advantages over DVD-RW, including on-disc content editing, built-in defect management, and multisession writing. What's in the Box 25 DVD+RW discs, 1 two-piece storage case, and a paper insert with product details.</figcaption></figure><p>CLIP, because it relies on visual similarity, is also poorly able to distinguish “C<em>D-RW Discs</em>” from other kinds of optical disks. They look exactly the same to humans too, if you take away the label text. It gives its highest ranking to this, a product that clearly doesn't match what the user is looking for:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CD-RW_Discs_CLIP-1.png" class="kg-image" alt="" width="285" height="280"><figcaption><em>Philips 52X 700MB CD-R 50PK Spindle</em></figcaption></figure><p>CLIP excels when query terms are poor matches for descriptions, but good matches for its visual analysis of product pictures. &nbsp;For example, the query “<em>Earbud Headphones</em>” is a poor match for the textual label "<em>Maxell 190329 Portable lightweight Behind The Head Extended Comfort Soft Touch Rubber Memory Neckband Stereo Line Neckband Head Buds - Silver</em>". But it's a good match for the image below:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Earbud-Headphones_CLIP.png" class="kg-image" alt="" width="450" height="319"><figcaption><em>Maxell 190329 Portable lightweight Behind The Head Extended Comfort Soft Touch Rubber Memory Neckband Stereo Line Neckband Head Buds - Silver</em></figcaption></figure><p>CLIP gives this product a high score because of its appearance, which it correctly identifies with “earbud”.</p><p>SBERT and BM25 both miss this match, giving their highest rankings to traditional “over-the-ear” headphones like this one:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Earbud-Headphones_SBERT-1.png" class="kg-image" alt="" width="343" height="559"><figcaption><em>Panasonic Headphones On-Ear Lightweight with XBS RP-HT21 (Black &amp; Silver)</em></figcaption></figure><p>SBERT excels where there is good textual information for matching, even if the match is not exact. For example, the query “<em>Fiber Optic Cables</em>” gives us this match from SBERT:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Fiber_Optic_Cables_SBERT-1.png" class="kg-image" alt="" width="261" height="323"><figcaption><em>CNE25969 6-Feet 1.8m PCD Basics Fiber Optic Audio Cable</em></figcaption></figure><p>CLIP, in contrast, is useless with this query because it is unable to visually distinguish fiber optic cables from any other kind of cable, and highly ranks matches like this:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Fiber_Optic_Cables_CLIP.png" class="kg-image" alt="" width="541" height="355"><figcaption><em>C2G 31348 Cat6 Cable - Snagless Unshielded Ethernet Network Patch Cable, Orange</em></figcaption></figure><h2 id="bring-hybrid-vigor-to-your-search">Bring Hybrid Vigor to Your Search</h2><p>Even with clean visual data and expansive descriptions, hybrid search with classical text retrieval technologies and AI-driven neural search is better than relying on just one technology.</p><p>Most use-cases are much less ideal. Descriptions are inaccurate, inadequate, or just plain missing. Photos are of poor quality or absent. And when users put in their queries texts with exact matches, they expect to see those matches in the results. Each of the three technologies is essential to meeting user expectations and providing good results.</p><p>With Jina AI’s framework, combining search results and fine-tuning for your use-case produces high quality retrieval software almost out of the box.</p><p>We are always moving forward at Jina AI, bringing state-of-the-art cloud-native neural AI to users through our intuitive Python framework and NoCode solutions. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models</title><meta charset="utf-8"><meta name="title" content="Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models"><meta name="description" content="Having trouble with non-English search queries? Fine-tuning your multilingual CLIP models may be the answer. In this post, we'll show you how Finetuner can be used on multilingual CLIP to improve search quality and give you better results."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/improving-search-quality-non-english-queries-fine-tuned-multilingual-clip-models"><meta property="og:title" content="Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models"><meta property="og:description" content="Having trouble with non-English search queries? Fine-tuning your multilingual CLIP models may be the answer. In this post, we'll show you how Finetuner can be used on multilingual CLIP to improve search quality and give you better results."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--63-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/improving-search-quality-non-english-queries-fine-tuned-multilingual-clip-models"><meta property="twitter:title" content="Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models"><meta property="twitter:description" content="Having trouble with non-English search queries? Fine-tuning your multilingual CLIP models may be the answer. In this post, we'll show you how Finetuner can be used on multilingual CLIP to improve search quality and give you better results."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--63-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models</title><meta charset="utf-8"><meta name="title" content="Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models"><meta name="description" content="Having trouble with non-English search queries? Fine-tuning your multilingual CLIP models may be the answer. In this post, we'll show you how Finetuner can be used on multilingual CLIP to improve search quality and give you better results."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/improving-search-quality-non-english-queries-fine-tuned-multilingual-clip-models"><meta property="og:title" content="Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models"><meta property="og:description" content="Having trouble with non-English search queries? Fine-tuning your multilingual CLIP models may be the answer. In this post, we'll show you how Finetuner can be used on multilingual CLIP to improve search quality and give you better results."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--63-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/improving-search-quality-non-english-queries-fine-tuned-multilingual-clip-models"><meta property="twitter:title" content="Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models"><meta property="twitter:description" content="Having trouble with non-English search queries? Fine-tuning your multilingual CLIP models may be the answer. In this post, we'll show you how Finetuner can be used on multilingual CLIP to improve search quality and give you better results."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--63-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 50%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--63-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Having trouble with non-English search queries? Fine-tuning your multilingual CLIP models may be the answer. In this post, we'll show you how Finetuner can be used on multilingual CLIP to improve search quality and give you better results.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/WIN_20221004_09_58_01_Pro.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Louis Milliken, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 19, 2022 • 15 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Since early 2021, <a href="https://openai.com/blog/clip/?ref=jina-ai-gmbh.ghost.io">CLIP-style models</a> have been the backbone of <a href="https://jina.ai/news/what-is-multimodal-deep-learning-and-what-are-the-applications/?ref=jina-ai-gmbh.ghost.io">multimodal AI</a>. They work by embedding inputs from more than one kind of media into a common high-dimensional vector space, using different models for different modalities. These different models are <em>co-trained</em> with multimodal data. For CLIP-models, this means images with captions.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/fashion-axes.png" class="kg-image" alt="" width="1049" height="773" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/fashion-axes.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/fashion-axes.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/fashion-axes.png 1049w" sizes="(min-width: 720px) 720px"><figcaption>A highly schematic representation of how CLIP embeddings make it possible to associate texts with images.</figcaption></figure><p>The result? A pair of models that embed images and texts close to each other if the text is descriptive of the image, or the image contains things that match the text. So if we have a picture of a skirt and the word “Rock” (German for “skirt”), they would be close together, while the word “Hemd” (German for “shirt”) would be closer to a picture of a shirt.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://jina.ai/news/applying-jina-ai-finetuner-to-clip-less-data-smaller-models-higher-performance/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">How Much Do We Get by Finetuning CLIP?</div><div class="kg-bookmark-description">Jina AI Finetuner can bring performance improvements of up to 63% to pre-trained CLIP models. Here is how we did that.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--12-.png" alt=""></div></a><figcaption>To learn how CLIP models work and how Jina AI can make them work better, please read this post.</figcaption></figure><h2 id="towards-multilingual-clip">Towards multilingual CLIP</h2><p>However, CLIP text models have mostly been trained on English data, and that’s a big problem: The world is full of people who don’t speak English.</p><p>Very recently, a few non-English and multilingual CLIP models have appeared, using various sources of training data. In this article, we’ll evaluate a multilingual CLIP model’s performance in a language other than English, and show how you can improve it even further using Jina AI’s Finetuner.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>To make this happen, we’re collaborating with <a href="https://toloka.ai/?ref=jina-ai-gmbh.ghost.io">Toloka</a>, a leading provider of data procurement services for machine learning, to create a dataset of images with high-quality German-language descriptions written by humans.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://toloka.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Powering data-centric AI - Toloka AI</div><div class="kg-bookmark-description">A unified environment to support fast and scalable AI/ML development: from data collection and annotation to model training, deployment and monitoring.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://tlk-infra-front.azureedge.net/portal-static/images/favicon-new/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Powering data-centric AI - Toloka AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://tlk-infra-front.azureedge.net/portal-static/images/page-head/share-img/img.jpg" alt=""></div></a><figcaption>We’re proud to make the result of this collaboration available to the community to use in your own projects. This article includes information on how to download the dataset yourself with your <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">Jina AI Cloud account</a>.</figcaption></figure><h2 id="how-does-multilingual-clip-work">How does multilingual CLIP work?</h2><p>Multilingual CLIP is any CLIP model trained with more than one language. So that could be English+French, German+English, or even Klingon+Elvish.</p><p>We’re going to look at a model that <a href="https://openai.com/?ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">Open AI</a> has trained with a broad multilingual dataset: The <code><a href="https://huggingface.co/laion/CLIP-ViT-B-32-xlm-roberta-base-laion5B-s13B-b90k?ref=jina-ai-gmbh.ghost.io">xlm-roberta-base-ViT-B-32</a></code> CLIP model, which uses the <code><a href="https://github.com/google-research/vision_transformer?ref=jina-ai-gmbh.ghost.io">ViT-B/32</a></code>image encoder, and the <code><a href="https://huggingface.co/xlm-roberta-large?ref=jina-ai-gmbh.ghost.io">XLM-RoBERTa</a></code> multilingual language model. Both of these are pre-trained:</p><ul><li><code>ViT-B/32</code>, using the <a href="https://github.com/Alibaba-MIIL/ImageNet21K?ref=jina-ai-gmbh.ghost.io">ImageNet-21k</a> dataset</li><li><code>XLM-RoBERTa</code>, using a multi-terabyte dataset of text from the Common Crawl, containing over 100 languages.</li></ul><p>So, from the outset, multilingual CLIP is different because it uses a multilingual text encoder, but can (and generally does) use the same image encoders as monolingual models.</p><p>Open AI then co-trained the two encoders with the multilingual <a href="https://laion.ai/blog/laion-5b?ref=jina-ai-gmbh.ghost.io"><code>laion5b</code></a> dataset, which contains 5.85 billion image-text pairs: 2.2 billion of these pairs are labelled in 100+ non-English languages, with the rest in English or containing text that can’t be nailed down to any one language (like place names or other proper nouns). These are taken from a sampling of images and their <a href="https://www.w3schools.com/tags/att_img_alt.asp?ref=jina-ai-gmbh.ghost.io">HTML alt-text</a> in the <a href="https://commoncrawl.org/?ref=jina-ai-gmbh.ghost.io">Common Crawl web archive</a>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/alt-txt-image.png" class="kg-image" alt="" width="1196" height="1190" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/alt-txt-image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/alt-txt-image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/alt-txt-image.png 1196w" sizes="(min-width: 720px) 720px"><figcaption>Some browsers will let you see the alt-text if you move your mouse over an image.</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Screenshot-2022-12-13-at-13.12.55-1.png" class="kg-image" alt="" width="858" height="144" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Screenshot-2022-12-13-at-13.12.55-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Screenshot-2022-12-13-at-13.12.55-1.png 858w" sizes="(min-width: 720px) 720px"><figcaption>How an alt-text is encoded in HTML.</figcaption></figure><p>This dataset isn’t balanced in the sense that no-one has tried to ensure that data for one language is comparable in size or scope to the data for any other. English still dominates.</p><h3 id="deep-dive-of-the-tokenizer-inside-multilingual-models">Deep dive of the tokenizer inside multilingual models</h3><p>So, how is a multilingual text encoder different from a bog-standard monolingual one? One big difference is how it handles <strong><strong><strong><strong>tokenization</strong></strong></strong></strong>.</p><p>Text transformer models like <code>XLM-RoBERTa</code> all start by tokenizing input texts — breaking them up into smaller parts — and replacing each part with an input vector constructed as part of the initial training. These input vectors are strung together and passed to the model to create an embedding vector.</p><p>You might expect these smaller parts to match <em>words</em>, and sometimes they do. But looking for words by just checking for spaces and punctuation doesn’t capture the fact that <em>call</em>, <em>calls</em>, <em>calling</em>, and <em>called </em>are not four totally different words, just like <em>small</em>, <em>smaller</em>, and <em>smallest</em>, or <em>annoy</em>, <em>annoyed</em>, <em>annoyingly</em>. In practice, this entire class of model uses, at least partly, a technique called <em>subword tokenization</em>, which uses the statistical properties of sequences of characters to decide what units are the “right-size” for learning.</p><p>It’s not really based in any linguistic theory, but doing it this way has many advantages for machine learning. Think of the suffix <em>-ed</em> in English. You might expect that a “right-sized” statistical tokenizer would notice that many English words end in -ed, and break those words into two parts:</p><p> <code>called → call -ed</code><br> <code>asked &nbsp;→ ask &nbsp;-ed</code><br> <code>worked → work -ed</code></p><p>And this makes sense, <em>most</em> of the time. But not always:</p><p> <code>weed → we -ed</code><br> <code>bed &nbsp;→ b &nbsp;-ed</code><br> <code>seed → se -ed</code></p><p>Large language models are very robust, and they can learn that “weed” has a meaning different from “we” + “-ed”. Using this kind of tokenization, even new words that were never part of the pre-training data get a distinct representation for the model to learn.</p><p>Nonetheless, the more that the tokenization matches meaningful units of language, the faster and better the model learns.</p><p>Let’s take a concrete example. The image below is from the data provided by Toloka with the German caption “<em>Leichte Damenjacke Frühling Herbst braun”</em> (”Light women's jacket spring autumn brown”):</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-14.png" class="kg-image" alt="" width="1646" height="320" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-14.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-14.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-14.png 1646w" sizes="(min-width: 720px) 720px"><figcaption>“<em>Leichte Damenjacke Frühling Herbst braun”</em></figcaption></figure><p>If we pass this German phrase to <code>XLM-RoBERTa</code>’s tokenizer, we get a very different result from when we pass it to a comparable tokenizer used for an English-only model:</p><pre><code class="hljs language-less">multilingual-<span class="hljs-attribute">CLIP</span>: leicht|e|Damen|jack|e|Frühling|Herbst|bra|un
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Having trouble with non-English search queries? Fine-tuning your multilingual CLIP models may be the answer. In this post, we'll show you how Finetuner can be used on multilingual CLIP to improve search quality and give you better results.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/WIN_20221004_09_58_01_Pro.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Louis Milliken, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 19, 2022 • 15 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Since early 2021, <a href="https://openai.com/blog/clip/?ref=jina-ai-gmbh.ghost.io">CLIP-style models</a> have been the backbone of <a href="https://jina.ai/news/what-is-multimodal-deep-learning-and-what-are-the-applications/?ref=jina-ai-gmbh.ghost.io">multimodal AI</a>. They work by embedding inputs from more than one kind of media into a common high-dimensional vector space, using different models for different modalities. These different models are <em>co-trained</em> with multimodal data. For CLIP-models, this means images with captions.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/fashion-axes.png" class="kg-image" alt="" width="1049" height="773" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/fashion-axes.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/fashion-axes.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/fashion-axes.png 1049w" sizes="(min-width: 720px) 720px"><figcaption>A highly schematic representation of how CLIP embeddings make it possible to associate texts with images.</figcaption></figure><p>The result? A pair of models that embed images and texts close to each other if the text is descriptive of the image, or the image contains things that match the text. So if we have a picture of a skirt and the word “Rock” (German for “skirt”), they would be close together, while the word “Hemd” (German for “shirt”) would be closer to a picture of a shirt.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://jina.ai/news/applying-jina-ai-finetuner-to-clip-less-data-smaller-models-higher-performance/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">How Much Do We Get by Finetuning CLIP?</div><div class="kg-bookmark-description">Jina AI Finetuner can bring performance improvements of up to 63% to pre-trained CLIP models. Here is how we did that.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--12-.png" alt=""></div></a><figcaption>To learn how CLIP models work and how Jina AI can make them work better, please read this post.</figcaption></figure><h2 id="towards-multilingual-clip">Towards multilingual CLIP</h2><p>However, CLIP text models have mostly been trained on English data, and that’s a big problem: The world is full of people who don’t speak English.</p><p>Very recently, a few non-English and multilingual CLIP models have appeared, using various sources of training data. In this article, we’ll evaluate a multilingual CLIP model’s performance in a language other than English, and show how you can improve it even further using Jina AI’s Finetuner.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-description">:dart: Task-oriented finetuning for better embeddings on neural search - GitHub - jina-ai/finetuner: Task-oriented finetuning for better embeddings on neural search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/394994747/b1cc3a87-d80f-4b52-9522-6647d88d0aaa" alt=""></div></a></figure><p>To make this happen, we’re collaborating with <a href="https://toloka.ai/?ref=jina-ai-gmbh.ghost.io">Toloka</a>, a leading provider of data procurement services for machine learning, to create a dataset of images with high-quality German-language descriptions written by humans.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://toloka.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Powering data-centric AI - Toloka AI</div><div class="kg-bookmark-description">A unified environment to support fast and scalable AI/ML development: from data collection and annotation to model training, deployment and monitoring.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://tlk-infra-front.azureedge.net/portal-static/images/favicon-new/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Powering data-centric AI - Toloka AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://tlk-infra-front.azureedge.net/portal-static/images/page-head/share-img/img.jpg" alt=""></div></a><figcaption>We’re proud to make the result of this collaboration available to the community to use in your own projects. This article includes information on how to download the dataset yourself with your <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">Jina AI Cloud account</a>.</figcaption></figure><h2 id="how-does-multilingual-clip-work">How does multilingual CLIP work?</h2><p>Multilingual CLIP is any CLIP model trained with more than one language. So that could be English+French, German+English, or even Klingon+Elvish.</p><p>We’re going to look at a model that <a href="https://openai.com/?ref=jina-ai-gmbh.ghost.io" rel="noopener noreferrer">Open AI</a> has trained with a broad multilingual dataset: The <code><a href="https://huggingface.co/laion/CLIP-ViT-B-32-xlm-roberta-base-laion5B-s13B-b90k?ref=jina-ai-gmbh.ghost.io">xlm-roberta-base-ViT-B-32</a></code> CLIP model, which uses the <code><a href="https://github.com/google-research/vision_transformer?ref=jina-ai-gmbh.ghost.io">ViT-B/32</a></code>image encoder, and the <code><a href="https://huggingface.co/xlm-roberta-large?ref=jina-ai-gmbh.ghost.io">XLM-RoBERTa</a></code> multilingual language model. Both of these are pre-trained:</p><ul><li><code>ViT-B/32</code>, using the <a href="https://github.com/Alibaba-MIIL/ImageNet21K?ref=jina-ai-gmbh.ghost.io">ImageNet-21k</a> dataset</li><li><code>XLM-RoBERTa</code>, using a multi-terabyte dataset of text from the Common Crawl, containing over 100 languages.</li></ul><p>So, from the outset, multilingual CLIP is different because it uses a multilingual text encoder, but can (and generally does) use the same image encoders as monolingual models.</p><p>Open AI then co-trained the two encoders with the multilingual <a href="https://laion.ai/blog/laion-5b?ref=jina-ai-gmbh.ghost.io"><code>laion5b</code></a> dataset, which contains 5.85 billion image-text pairs: 2.2 billion of these pairs are labelled in 100+ non-English languages, with the rest in English or containing text that can’t be nailed down to any one language (like place names or other proper nouns). These are taken from a sampling of images and their <a href="https://www.w3schools.com/tags/att_img_alt.asp?ref=jina-ai-gmbh.ghost.io">HTML alt-text</a> in the <a href="https://commoncrawl.org/?ref=jina-ai-gmbh.ghost.io">Common Crawl web archive</a>.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/alt-txt-image.png" class="kg-image" alt="" width="1196" height="1190" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/alt-txt-image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/alt-txt-image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/alt-txt-image.png 1196w" sizes="(min-width: 720px) 720px"><figcaption>Some browsers will let you see the alt-text if you move your mouse over an image.</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Screenshot-2022-12-13-at-13.12.55-1.png" class="kg-image" alt="" width="858" height="144" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Screenshot-2022-12-13-at-13.12.55-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Screenshot-2022-12-13-at-13.12.55-1.png 858w" sizes="(min-width: 720px) 720px"><figcaption>How an alt-text is encoded in HTML.</figcaption></figure><p>This dataset isn’t balanced in the sense that no-one has tried to ensure that data for one language is comparable in size or scope to the data for any other. English still dominates.</p><h3 id="deep-dive-of-the-tokenizer-inside-multilingual-models">Deep dive of the tokenizer inside multilingual models</h3><p>So, how is a multilingual text encoder different from a bog-standard monolingual one? One big difference is how it handles <strong><strong><strong><strong>tokenization</strong></strong></strong></strong>.</p><p>Text transformer models like <code>XLM-RoBERTa</code> all start by tokenizing input texts — breaking them up into smaller parts — and replacing each part with an input vector constructed as part of the initial training. These input vectors are strung together and passed to the model to create an embedding vector.</p><p>You might expect these smaller parts to match <em>words</em>, and sometimes they do. But looking for words by just checking for spaces and punctuation doesn’t capture the fact that <em>call</em>, <em>calls</em>, <em>calling</em>, and <em>called </em>are not four totally different words, just like <em>small</em>, <em>smaller</em>, and <em>smallest</em>, or <em>annoy</em>, <em>annoyed</em>, <em>annoyingly</em>. In practice, this entire class of model uses, at least partly, a technique called <em>subword tokenization</em>, which uses the statistical properties of sequences of characters to decide what units are the “right-size” for learning.</p><p>It’s not really based in any linguistic theory, but doing it this way has many advantages for machine learning. Think of the suffix <em>-ed</em> in English. You might expect that a “right-sized” statistical tokenizer would notice that many English words end in -ed, and break those words into two parts:</p><p> <code>called → call -ed</code><br> <code>asked &nbsp;→ ask &nbsp;-ed</code><br> <code>worked → work -ed</code></p><p>And this makes sense, <em>most</em> of the time. But not always:</p><p> <code>weed → we -ed</code><br> <code>bed &nbsp;→ b &nbsp;-ed</code><br> <code>seed → se -ed</code></p><p>Large language models are very robust, and they can learn that “weed” has a meaning different from “we” + “-ed”. Using this kind of tokenization, even new words that were never part of the pre-training data get a distinct representation for the model to learn.</p><p>Nonetheless, the more that the tokenization matches meaningful units of language, the faster and better the model learns.</p><p>Let’s take a concrete example. The image below is from the data provided by Toloka with the German caption “<em>Leichte Damenjacke Frühling Herbst braun”</em> (”Light women's jacket spring autumn brown”):</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-14.png" class="kg-image" alt="" width="1646" height="320" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-14.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-14.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-14.png 1646w" sizes="(min-width: 720px) 720px"><figcaption>“<em>Leichte Damenjacke Frühling Herbst braun”</em></figcaption></figure><p>If we pass this German phrase to <code>XLM-RoBERTa</code>’s tokenizer, we get a very different result from when we pass it to a comparable tokenizer used for an English-only model:</p><pre><code>multilingual-CLIP: leicht|e|Damen|jack|e|Frühling|Herbst|bra|un
 
-<span class="hljs-attribute">english-only-CLIP</span>: le|ich|te|dam|en|jac|ke|fr|ü|h|ling|her|bst|braun
-</code></pre><p>The tokens found by the multilingual tokenizer much more closely match our intuitions about meaningful units in German, while the English-only-trained tokenizer produces almost random chunks. Yes, it is still possible for a large language model to learn from badly tokenized data, if it’s consistent, but it will be slower and/or less accurate.</p><p>In contrast, the English equivalent — a word-for-word translation — is clearly better tokenized by the English-only tokenizer, but is not so badly tokenized by the multilingual one:</p><pre><code class="hljs language-less">multilingual-<span class="hljs-attribute">CLIP</span>: light|women|'|s|ja|cket|spring|a|utum|n|brown
+english-only-CLIP: le|ich|te|dam|en|jac|ke|fr|ü|h|ling|her|bst|braun
+</code></pre><p>The tokens found by the multilingual tokenizer much more closely match our intuitions about meaningful units in German, while the English-only-trained tokenizer produces almost random chunks. Yes, it is still possible for a large language model to learn from badly tokenized data, if it’s consistent, but it will be slower and/or less accurate.</p><p>In contrast, the English equivalent — a word-for-word translation — is clearly better tokenized by the English-only tokenizer, but is not so badly tokenized by the multilingual one:</p><pre><code>multilingual-CLIP: light|women|'|s|ja|cket|spring|a|utum|n|brown
 
-<span class="hljs-attribute">english-only-CLIP</span>: light|women|'s|jacket|spring|autumn|brown
+english-only-CLIP: light|women|'s|jacket|spring|autumn|brown
 </code></pre><p>Even from the first step in the process of producing text embeddings, we can see that multilingual language models make a large difference in producing multilingual CLIP models.</p><h2 id="multilingual-vs-monolingual-clip-on-the-search-quality">Multilingual vs. monolingual CLIP on the search quality</h2><p>Large language models are famously good at transfer learning. For example, if a monolingual English-only CLIP model has learned what “jacket” means, you can further train it, with very few additional examples, to know that the German word “Jacke” means the same thing. Then, it can carry all its knowledge about the English word “jacket” over to German.</p><p>It is possible that a model already trained on English could be retrained for German with less data than training a new German model from scratch.</p><p>Therefore, it’s worth asking: <strong>How much do we really gain using a model trained to be multilingual from the outset?</strong></p><p>In this article, we will use the German fashion dataset provided by Toloka to:</p><ol><li>Compare the zero-shot performance (i.e. out-of-the-box, without fine-tuning) of the multilingual CLIP model <code>xlm-roberta-base-ViT-B-32</code> and the English-only equivalent <code>clip-vit-base-patch32</code>. These two use the same image embedding model, but different text embedding models.</li><li>Attempt to improve both models by using a part of the German dataset to fine-tune them.</li><li>Compare the fine-tuned models using the same metrics, so we can both contrast non-fine-tuned and fine-tuned models, and contrast the English-only and multilingual models after adaptation to the German data.</li><li>Show how much advantage, if any, is gained from a multilingual CLIP model.</li></ol><h2 id="experiment-setup">Experiment Setup</h2><h3 id="the-german-fashion12k-dataset">The German Fashion12k dataset</h3><p>We have collaborated with Toloka to curate a 12,000 item dataset of fashion images drawn from e-commerce websites, to which human annotators have added descriptive captions in German. Toloka has made the data <a href="https://github.com/Toloka/Fashion12K_german_queries?ref=jina-ai-gmbh.ghost.io">available to the public on GitHub</a>, but you can also download it from Jina directly in DocArray format by following the instructions in the <a href="#download-the-dataset-via-docarray">next section</a>.</p><p>The images are a subset of the <a href="https://github.com/xthan/fashion-200k?ref=jina-ai-gmbh.ghost.io">xthan/fashion-200k dataset</a>, and we have commissioned their human annotations via Toloka’s crowdsourcing platform. Annotations were made in two steps. &nbsp;First, Toloka passed the 12,000 images to annotators in their large international user community, who added descriptive captions.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image--1---1-.png" class="kg-image" alt="" width="2000" height="1141" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image--1---1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image--1---1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image--1---1-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image--1---1-.png 2356w" sizes="(min-width: 720px) 720px"><figcaption>The Toloka app showing an item of clothing to a user and asking for a description.</figcaption></figure><p>The app prompted users to write descriptions that follow a common pattern, partially enforced by a simple pattern matcher. Specifically:</p><blockquote>Write a search query that would find this product: type, your guess about the material, where it might be worn, color, texture, details. […]<br><br>Requirements for the query:<br><strong>· </strong>At least SIX words<br><strong>· </strong>Words that are separated ONLY by spaces (or ", ")<br><strong>·</strong> Do NOT use "this is/these are"</blockquote><p>Then, in the second stage, other, randomly chosen users validated each description.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image--5-.png" class="kg-image" alt="" width="2000" height="1135" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image--5-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image--5-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image--5-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image--5-.png 2362w" sizes="(min-width: 720px) 720px"><figcaption>Validation screen in the Toloka app. The app presents the user with a text description created by someone else and asks if it’s an appropriate description, inappropriate description, or if the image failed to load.</figcaption></figure><p>Some examples from the resulting dataset:</p><table style="border-collapse: collapse; border: none;">
     <tbody><tr style="border: none;">
         <td width="50%" style="border: none;"><img loading="lazy" src="data:image/png;base64,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"><figcaption>‘Lange Winterjacke für Damen’<br><i>Long winter jacket for women.</i></figcaption></td>
         <td width="50%" style="border: none;"><img loading="lazy" 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"><figcaption>‘Blazerweste groß für Damen’<br><i>Large blazer-vest for women</i></figcaption></td>
     </tr>
-</tbody></table><p>Of the 12,000 image-text pairs in the data from Toloka, we randomly selected 10,000 for training and held the remaining 2,000 out for evaluation. By coincidence, and because some clothes are similar enough in nature, there are a few duplicate descriptions. However, since there are 11,582 unique descriptions, we didn’t consider this an important factor in using this data.</p><h3 id="download-the-dataset-via-docarray">Download the dataset via DocArray</h3><p>The German Fashion12k dataset is available for free use by the Jina AI community. After logging into Jina AI Cloud, you can download it directly in <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray</a> format:</p><pre><code class="language-python hljs">train_data = DocumentArray.pull(<span class="hljs-string">'DE-Fashion-Image-Text-Multimodal-train'</span>, show_progress=<span class="hljs-literal">True</span>)
-eval_data = DocumentArray.pull(<span class="hljs-string">'DE-Fashion-Image-Text-Multimodal-test'</span>, show_progress=<span class="hljs-literal">True</span>)
-</code></pre><h3 id="load-the-multilingual-clip-model">Load the multilingual CLIP model</h3><p>Because CLIP models are actually two different models that have been trained together, we have to load them as two models. </p><p>In this article, we will use the <a href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner interface</a>. To use the <code>xlm-roberta-base-ViT-B-32</code> CLIP model:</p><figure class="kg-card kg-code-card"><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> finetuner <span class="hljs-keyword">import</span> build_model
+</tbody></table><p>Of the 12,000 image-text pairs in the data from Toloka, we randomly selected 10,000 for training and held the remaining 2,000 out for evaluation. By coincidence, and because some clothes are similar enough in nature, there are a few duplicate descriptions. However, since there are 11,582 unique descriptions, we didn’t consider this an important factor in using this data.</p><h3 id="download-the-dataset-via-docarray">Download the dataset via DocArray</h3><p>The German Fashion12k dataset is available for free use by the Jina AI community. After logging into Jina AI Cloud, you can download it directly in <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray</a> format:</p><pre><code class="language-python">train_data = DocumentArray.pull('DE-Fashion-Image-Text-Multimodal-train', show_progress=True)
+eval_data = DocumentArray.pull('DE-Fashion-Image-Text-Multimodal-test', show_progress=True)
+</code></pre><h3 id="load-the-multilingual-clip-model">Load the multilingual CLIP model</h3><p>Because CLIP models are actually two different models that have been trained together, we have to load them as two models. </p><p>In this article, we will use the <a href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner interface</a>. To use the <code>xlm-roberta-base-ViT-B-32</code> CLIP model:</p><figure class="kg-card kg-code-card"><pre><code class="language-python">from finetuner import build_model
 
 mCLIP_text_model = build_model(
-    name = <span class="hljs-string">'xlm-roberta-base-ViT-B-32::laion5b_s13b_b90k'</span>,
-    select_model = <span class="hljs-string">'clip-text'</span>,
+    name = 'xlm-roberta-base-ViT-B-32::laion5b_s13b_b90k',
+    select_model = 'clip-text',
 )
 
 mCLIP_vision_model = build_model(
-    name = <span class="hljs-string">'xlm-roberta-base-ViT-B-32::laion5b_s13b_b90k'</span>,
-    select_model = <span class="hljs-string">'clip-vision'</span>
+    name = 'xlm-roberta-base-ViT-B-32::laion5b_s13b_b90k',
+    select_model = 'clip-vision'
 )
-</code></pre><figcaption>For models supported directly by Jina AI, you can load them <em>by name</em>, without having to directly deal with downloading or deserialization.</figcaption></figure><h3 id="load-the-english-clip-model">Load the English CLIP model</h3><p>For comparison, you can access the English-only <code>ViT-B-32::openai</code> CLIP model in the same way:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> finetuner <span class="hljs-keyword">import</span> build_model
+</code></pre><figcaption>For models supported directly by Jina AI, you can load them <em>by name</em>, without having to directly deal with downloading or deserialization.</figcaption></figure><h3 id="load-the-english-clip-model">Load the English CLIP model</h3><p>For comparison, you can access the English-only <code>ViT-B-32::openai</code> CLIP model in the same way:</p><pre><code class="language-python">from finetuner import build_model
 
 enCLIP_text_model = build_model(
-    name = <span class="hljs-string">'ViT-B-32::openai'</span>,
-    select_model = <span class="hljs-string">'clip-text'</span>,
+    name = 'ViT-B-32::openai',
+    select_model = 'clip-text',
 )
 
 enCLIP_vision_model = build_model(
-    name = <span class="hljs-string">'ViT-B-32::openai'</span>,
-    select_model = <span class="hljs-string">'clip-vision'</span>
+    name = 'ViT-B-32::openai',
+    select_model = 'clip-vision'
 )
 </code></pre><h2 id="evaluate-the-zero-shot-performance">Evaluate the zero-shot performance</h2><p>We measured the zero-shot performance of both the Multilingual CLIP model and the English-only one on German Fashion dataset, that is to say, how well they perform as downloaded, without additional training, on the 2,000 items we held out for evaluation.</p><p>We embed the text descriptions in the evaluation data, and used them to search for matches among the embedded images in the evaluation data, taking the 20 top matches for each text description. We took the results and performed a number of standard statistical tests on them, including <a href="https://en.wikipedia.org/wiki/Mean_reciprocal_rank?ref=jina-ai-gmbh.ghost.io">Mean Reciprocal Rank</a> (mRR), <a href="https://stats.stackexchange.com/questions/127041/mean-average-precision-vs-mean-reciprocal-rank?ref=jina-ai-gmbh.ghost.io">Mean Average Precision</a> (mAP), <a href="https://en.wikipedia.org/wiki/Discounted_cumulative_gain?ref=jina-ai-gmbh.ghost.io">Discounted Cumulative Gain</a> (DCG), and the share of queries that return the exact image whose description matches the query (labeled “<strong><em>Hits</em>”</strong>).</p><p>The performance results are:</p><table>
 <thead>
@@ -105,29 +105,29 @@
 <td>CLIPLoss</td>
 </tr>
 </tbody>
-</table><p>These hyperparameters are part of the command below.</p><h3 id="specify-the-evaluation-data">Specify the evaluation data</h3><p>We fine-tuned using the data split described previously: &nbsp;10,000 items were used as training data, and 2,000 as evaluation data. In order to evaluate models at the end of each training epoch, we turned the evaluation data into a “query” and “index” dataset. The “query” data consists of the German text descriptions in the evaluation data, and the “index” data contains the images.</p><pre><code class="language-python hljs"><span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span> eval_data:
-    tag = doc.chunks[<span class="hljs-number">1</span>].text
-    doc.chunks[<span class="hljs-number">0</span>].tags[<span class="hljs-string">'finetuner_label'</span>] = tag
-    doc.chunks[<span class="hljs-number">1</span>].tags[<span class="hljs-string">'finetuner_label'</span>] = tag
+</table><p>These hyperparameters are part of the command below.</p><h3 id="specify-the-evaluation-data">Specify the evaluation data</h3><p>We fine-tuned using the data split described previously: &nbsp;10,000 items were used as training data, and 2,000 as evaluation data. In order to evaluate models at the end of each training epoch, we turned the evaluation data into a “query” and “index” dataset. The “query” data consists of the German text descriptions in the evaluation data, and the “index” data contains the images.</p><pre><code class="language-python">for doc in eval_data:
+    tag = doc.chunks[1].text
+    doc.chunks[0].tags['finetuner_label'] = tag
+    doc.chunks[1].tags['finetuner_label'] = tag
     
-query_data = DocumentArray([doc.chunks[<span class="hljs-number">0</span>] <span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span> eval_data])
-index_data = DocumentArray([doc.chunks[<span class="hljs-number">1</span>] <span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span> eval_data])
-</code></pre><p>These are also passed to the fine-tuning command.</p><h3 id="put-everything-together-in-one-call">Put everything together in one call</h3><p>Running the command below uploads the training and evaluation data and fine-tunes the <code>xlm-roberta-base-ViT-B-32</code> model on <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a>:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> finetuner
+query_data = DocumentArray([doc.chunks[0] for doc in eval_data])
+index_data = DocumentArray([doc.chunks[1] for doc in eval_data])
+</code></pre><p>These are also passed to the fine-tuning command.</p><h3 id="put-everything-together-in-one-call">Put everything together in one call</h3><p>Running the command below uploads the training and evaluation data and fine-tunes the <code>xlm-roberta-base-ViT-B-32</code> model on <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a>:</p><pre><code class="language-python">import finetuner
 
 run = finetuner.fit(
-    model=<span class="hljs-string">'xlm-roberta-base-ViT-B-32::laion5b_s13b_b90k'</span>,
+    model='xlm-roberta-base-ViT-B-32::laion5b_s13b_b90k',
     train_data=toloka_train_data,
     eval_data=toloka_eval_data,
-    epochs=<span class="hljs-number">5</span>,
-    learning_rate=<span class="hljs-number">1e-6</span>,
-    loss=<span class="hljs-string">'CLIPLoss'</span>,
-    device=<span class="hljs-string">'cuda'</span>,
+    epochs=5,
+    learning_rate=1e-6,
+    loss='CLIPLoss',
+    device='cuda',
 		callbacks=[
         EvaluationCallback(
             query_data=toloka_query_data,
             index_data=toloka_index_data,
-            model=<span class="hljs-string">'clip-text'</span>,
-            index_model=<span class="hljs-string">'clip-vision'</span>
+            model='clip-text',
+            index_model='clip-vision'
         ),
         WandBLogger(),
     ]
@@ -209,4 +209,4 @@
 <td>0.775</td>
 </tr>
 </tbody>
-</table><p>Using German training data, we were able to bring a vast improvement to the English-only CLIP model, although not enough to bring it up to even with the zero-shot level of the Multilingual CLIP model. &nbsp;Mean average precision for the English-only model jumped 420%, compared to 31% for Multilingual CLIP, although the overall performance of the monolingual model was still much worse.</p><h3 id="does-more-labeled-data-improve-the-search-quality">Does more labeled data improve the search quality?</h3><p>We also ran multiple fine-tuning experiments with differing amounts of training data, on both the Multilingual and English-only CLIP models, to see how effective using more data was.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Average-precision-for-Multilingual-and-English-CLIP--1-.svg" class="kg-image" alt="" width="568" height="371"></figure><p>In both, we see that most of the gain comes from the first few thousand items of training data, with gain coming more slowly after initially fast learning. This confirms a conclusion Jina AI has already published.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-text">Read <strong><strong><a href="https://jina.ai/news/fine-tuning-with-low-budget-and-high-expectations/?ref=jina-ai-gmbh.ghost.io">Fine-tuning with Low Budget and High Expectations</a></strong></strong> for more discussion of the impressive results you can get with Finetuner and relatively little new training data.</div></div><p>Adding additional data may still improve results, but much more slowly. And in the case of fine-tuning the English-only CLIP model to handle German queries, we see performance improvement maximizes at less than 10,000 new items of data. It seems unlikely that we could train the English-only CLIP model to ever equal the Multilingual CLIP on German data, at least not using these kinds of methods.</p><h2 id="conclusion">Conclusion</h2><p>What lessons can we take from all this?</p><h3 id="multilingual-clip-is-the-first-choice-for-non-english-queries">Multilingual CLIP is the first choice for non-English queries</h3><p>The Multilingual CLIP model, trained from scratch with multilingual data, outperforms comparable English-only CLIP models by a very large margin on the German data we used. The same conclusion will likely apply for other non-English languages.</p><p>Even in an unfair competition, where we fine-tuned the English model and vastly improved its performance on German data, the Multilingual CLIP model without further training outperformed it by a large margin.</p><h3 id="fine-tuning-improves-search-quality-with-little-data">Fine-tuning improves search quality with little data</h3><p>We were shocked to see the English-only model improve its handling of German so much, and we see that we could have gotten nearly the same result using half as much data. The basic assumptions that go into fine-tuning are clearly very robust if they can teach German to an English model with only a few thousand examples.</p><p>On the other hand, we struggled to improve the performance of Multilingual CLIP, even with a fairly large quantity of high quality human-annotated training data. Although Finetuner makes a clear difference, you very rapidly reach upper bounds of how much you can improve a model that’s already pretty good.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/chart--1-.svg" class="kg-image" alt="" width="600" height="371"></figure><h3 id="trouble-free-fine-tuning-using-finetuner">Trouble-free fine-tuning using Finetuner</h3><p>Finetuner is easy enough to use that we could construct and perform all the experiments in this article in a few days. 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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+</table><p>Using German training data, we were able to bring a vast improvement to the English-only CLIP model, although not enough to bring it up to even with the zero-shot level of the Multilingual CLIP model. &nbsp;Mean average precision for the English-only model jumped 420%, compared to 31% for Multilingual CLIP, although the overall performance of the monolingual model was still much worse.</p><h3 id="does-more-labeled-data-improve-the-search-quality">Does more labeled data improve the search quality?</h3><p>We also ran multiple fine-tuning experiments with differing amounts of training data, on both the Multilingual and English-only CLIP models, to see how effective using more data was.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Average-precision-for-Multilingual-and-English-CLIP--1-.svg" class="kg-image" alt="" width="568" height="371"></figure><p>In both, we see that most of the gain comes from the first few thousand items of training data, with gain coming more slowly after initially fast learning. This confirms a conclusion Jina AI has already published.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-text">Read <strong><strong><a href="https://jina.ai/news/fine-tuning-with-low-budget-and-high-expectations/?ref=jina-ai-gmbh.ghost.io">Fine-tuning with Low Budget and High Expectations</a></strong></strong> for more discussion of the impressive results you can get with Finetuner and relatively little new training data.</div></div><p>Adding additional data may still improve results, but much more slowly. And in the case of fine-tuning the English-only CLIP model to handle German queries, we see performance improvement maximizes at less than 10,000 new items of data. It seems unlikely that we could train the English-only CLIP model to ever equal the Multilingual CLIP on German data, at least not using these kinds of methods.</p><h2 id="conclusion">Conclusion</h2><p>What lessons can we take from all this?</p><h3 id="multilingual-clip-is-the-first-choice-for-non-english-queries">Multilingual CLIP is the first choice for non-English queries</h3><p>The Multilingual CLIP model, trained from scratch with multilingual data, outperforms comparable English-only CLIP models by a very large margin on the German data we used. The same conclusion will likely apply for other non-English languages.</p><p>Even in an unfair competition, where we fine-tuned the English model and vastly improved its performance on German data, the Multilingual CLIP model without further training outperformed it by a large margin.</p><h3 id="fine-tuning-improves-search-quality-with-little-data">Fine-tuning improves search quality with little data</h3><p>We were shocked to see the English-only model improve its handling of German so much, and we see that we could have gotten nearly the same result using half as much data. The basic assumptions that go into fine-tuning are clearly very robust if they can teach German to an English model with only a few thousand examples.</p><p>On the other hand, we struggled to improve the performance of Multilingual CLIP, even with a fairly large quantity of high quality human-annotated training data. Although Finetuner makes a clear difference, you very rapidly reach upper bounds of how much you can improve a model that’s already pretty good.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/chart--1-.svg" class="kg-image" alt="" width="600" height="371"></figure><h3 id="trouble-free-fine-tuning-using-finetuner">Trouble-free fine-tuning using Finetuner</h3><p>Finetuner is easy enough to use that we could construct and perform all the experiments in this article in a few days. Although it does take some understanding of deep learning to make the best configuration choices, Finetuner greatly reduces the boring labor of running and paying attention to large-scale neural network models to mere parameter setting.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://finetuner.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Welcome to Finetuner!</div><div class="kg-bookmark-description">Fine-tuning is an effective way to improve the performance on neural search tasks. However, it is non-trivial for many deep learning engineers. Finetuner makes fine-tuning easier, faster and performant by streamlining the workflow and handling all complexity and infrastructure on the cloud. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Newsroom</title><meta charset="utf-8"><meta name="title" content="Newsroom"><meta name="description" content="Read the latest news and updates from Jina AI."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news"><meta property="og:title" content="Newsroom"><meta property="og:description" content="Read the latest news and updates from Jina AI."><meta property="og:image" content="https://jina.ai/banner-newsroom.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news"><meta property="twitter:title" content="Newsroom"><meta property="twitter:description" content="Read the latest news and updates from Jina AI."><meta property="twitter:image" content="https://jina.ai/banner-newsroom.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="q-card__section q-card__section--vert"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Artificial General Intelligence is Cursed, And Science Fiction isn't Helping</div><div class="q-item__label q-item__label--caption text-caption">AI is cursed by intellectual hubris, moving goalposts, bad incentives, and science fiction. Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div></div><div class="q-card__section q-card__section--vert"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div></a></div></div><div class="col-12 col-md-6 column self-stretch no-wrap"><div class="col-6 q-pa-sm"><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable full-height" href="/news/jina-ai-launches-worlds-first-open-source-8k-text-embedding-rivaling-openai" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">October 25, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels--11-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div><div class="col-6 q-pa-sm"><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable full-height" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div><div class="row q-my-xl"></div><div class="row"><div class="q-tabs row no-wrap items-center q-tabs--scrollable 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q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon notranslate material-icons q-tab__icon" aria-hidden="true" role="presentation">hotel_class</i><div class="q-tab__label">Featured</div></div><div class="q-tab__indicator absolute-bottom"></div></div></div><i class="q-icon fas fa-chevron-left q-tabs__arrow q-tabs__arrow--left absolute q-tab__icon q-tabs__arrow--faded" aria-hidden="true" role="presentation"> </i><i class="q-icon fas fa-chevron-right q-tabs__arrow q-tabs__arrow--right absolute q-tab__icon" aria-hidden="true" role="presentation"> </i></div><div class="q-space"></div><label class="q-field row no-wrap items-start q-field--filled q-input q-field--square q-field--dark col-auto" for="f_3dda6dc2-04aa-4678-8126-cb040bbeb9e6"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" placeholder="Search by title" id="f_3dda6dc2-04aa-4678-8126-cb040bbeb9e6" type="text"></div><div class="q-field__append q-field__marginal row no-wrap items-center"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">search</i></div></div></div></label></div><hr class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div class="row justify-between"><div class="col-12 col-md-9 q-px-sm"><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.385%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/theres-a-time-and-a-place-unleashing-dynamic-variables-in-promptperfect" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">There's a Time and a Place: Unleashing Dynamic Variables in PromptPerfect</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Incorporate users' time, date and location into your prompts. Plus contents of other websites, and outputs of other prompts themselves!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 07, 2023 • 8 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Blog-images--13-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/dify-ai-integrates-jina-embeddings-for-rag" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Dify.AI integrates Jina Embeddings for RAG</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dify.AI, a leading open-source platform specialized in creating generative AI applications, is now leveraging Jina Embeddings v2! </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 06, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Difyco.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-embeddings-v2-and-mongodb-atlas" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina Embeddings v2 and MongoDB Atlas</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Supercharge MongoDB Atlas multi-cloud vector search solutions with Jina AI’s industry-leading embeddings!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/profile-option-2.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens, Saahil Ognawala</div><div class="q-item__label q-item__label--caption text-caption">December 06, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Blog-images--8-.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><div class="q-pagination row no-wrap items-center row justify-center q-ma-xl" aria-disabled="false" role="navigation" style=""><div class="q-pagination__content row no-wrap items-center"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle text-grey-6 disabled" tabindex="-1" type="button" disabled="" aria-disabled="true" aria-label="1" aria-current="false" style="padding: 3px 2px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-backward-step" aria-hidden="true" role="img"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle 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min-width: 2em; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">…</span></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle text-grey-6 q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button" aria-label="18" aria-current="false" style="padding: 3px 2px; min-width: 2em; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">18</span></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle text-grey-6 q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button" aria-label="2" aria-current="false" style="padding: 3px 2px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center 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no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"> Embeddings</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input 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style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://scenex.jina.ai/SceneX - Light.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> SceneXplain</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path 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no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://chat.jina.ai/JinaChat - Light.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> JinaChat</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div 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class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> DocArray</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> Jina</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 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aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> CLIP-as-service</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> JCloud</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> LangChain-Serve</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> VectorDB</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> Executor Hub</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> DALL-E Flow</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> DiscoArt</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> ThinkGPT</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> DevGPT</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> RunGPT</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> Jerboa</div></div></div></div></div><div class="row justify-between items-center"><div class="text-h6 text-overline"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">filter_alt</i> By author</div></div><div class="q-option-group q-gutter-x-sm q-option-group--inline" role="group"><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Alaeddine Abdessalem" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Alaeddine Abdessalem</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Alex C-G" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Alex C-G</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Andrei Ungureanu" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Andrei Ungureanu</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Aziz Belaweid" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Aziz Belaweid</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Bo Wang" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Bo Wang</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Charlotte Gerhaher" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Charlotte Gerhaher</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Deepankar Mahapatro" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Deepankar Mahapatro</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Degi" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Degi</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Engineering Group" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Engineering Group</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Felix Wang" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Felix Wang</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Florian Hönicke" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Florian Hönicke</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Ge Jin" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Ge Jin</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Girish Chandrashekar" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Girish Chandrashekar</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Haiwei Li" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Haiwei Li</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Han Xiao" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Han Xiao</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Isabelle Mohr" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Isabelle Mohr</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Jack Min Ong" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Jack Min Ong</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Jie Fu" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Jie Fu</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Jina AI" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Jina AI</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Jocelyn Matthews" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Jocelyn Matthews</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Johannes Messner" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Johannes Messner</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Joschka Braun" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Joschka Braun</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Leon Wolf" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Leon Wolf</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Lisa Li" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Lisa Li</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Louis Milliken" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Louis Milliken</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Maximilian Werk" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Maximilian Werk</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Michael Günther" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Michael Günther</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Miruna Nedelcu" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Miruna Nedelcu</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Nicholas Dunham" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Nicholas Dunham</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Sa Zhang" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Sa Zhang</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Saahil Ognawala" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Saahil Ognawala</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Saba Sturua" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Saba Sturua</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Sami Jaghouar" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Sami Jaghouar</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Scott Martens" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Scott Martens</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Sebastian Weisshaar" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Sebastian Weisshaar</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Susana Guzmán" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Susana Guzmán</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Tao Ran" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Tao Ran</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Tianshi Kan" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Tianshi Kan</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Zihao Jing" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Zihao Jing</div></div></div></div></div></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main class="q-page" style="min-height: 449px;"><div class="row justify-center q-my-xl q-py-xl"><div class="col-11 col-lg-10 col-xl-9"><div class="row q-mt-xl q-pa-sm justify-around items-center"><div class="col text-h1 text-weight-bold text-h2">Newsroom</div><button class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square col-auto" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">rss_feed</i><span class="block">RSS</span></span></button></div><div class="row justify-start q-pa-sm items-center q-mt-lg text-grey-2 text-h5"><i class="q-icon notranslate material-icons q-mr-sm" aria-hidden="true" role="presentation">hotel_class</i><div class="q-my-lg">Top stories</div></div><div class="row justify-between items-center q-mb-xl"><div class="col-12 col-md-6 cursor-pointer self-stretch"><div class="q-pa-sm full-height"><a class="q-card q-card--dark q-dark q-card--flat no-shadow block full-height q-hoverable non-selectable" href="/news/artificial-general-intelligence-is-cursed-and-science-fiction-isnt-helping" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div><div class="q-card__section q-card__section--vert"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Artificial General Intelligence is Cursed, And Science Fiction isn't Helping</div><div class="q-item__label q-item__label--caption text-caption">AI is cursed by intellectual hubris, moving goalposts, bad incentives, and science fiction. Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div></div><div class="q-card__section q-card__section--vert"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div></a></div></div><div class="col-12 col-md-6 column self-stretch no-wrap"><div class="col-6 q-pa-sm"><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable full-height" href="/news/jina-ai-launches-worlds-first-open-source-8k-text-embedding-rivaling-openai" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">October 25, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels--11-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div><div class="col-6 q-pa-sm"><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable full-height" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div><div class="row q-my-xl"></div><div class="row"><div class="q-tabs row no-wrap items-center q-tabs--scrollable 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q-anchor--skip non-selectable row no-wrap q-tab__content--inline"><i class="q-icon notranslate material-icons q-tab__icon" aria-hidden="true" role="presentation">hotel_class</i><div class="q-tab__label">Featured</div></div><div class="q-tab__indicator absolute-bottom"></div></div></div><i class="q-icon fas fa-chevron-left q-tabs__arrow q-tabs__arrow--left absolute q-tab__icon q-tabs__arrow--faded" aria-hidden="true" role="presentation"> </i><i class="q-icon fas fa-chevron-right q-tabs__arrow q-tabs__arrow--right absolute q-tab__icon" aria-hidden="true" role="presentation"> </i></div><div class="q-space"></div><label class="q-field row no-wrap items-start q-field--filled q-input q-field--square q-field--dark col-auto" for="f_05cf35e3-32ec-4657-8f7d-2f10db1338aa"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" placeholder="Search by title" id="f_05cf35e3-32ec-4657-8f7d-2f10db1338aa" type="text"></div><div class="q-field__append q-field__marginal row no-wrap items-center"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">search</i></div></div></div></label></div><hr class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div class="row justify-between"><div class="col-12 col-md-9 q-px-sm"><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.385%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/theres-a-time-and-a-place-unleashing-dynamic-variables-in-promptperfect" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">There's a Time and a Place: Unleashing Dynamic Variables in PromptPerfect</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Incorporate users' time, date and location into your prompts. Plus contents of other websites, and outputs of other prompts themselves!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 07, 2023 • 8 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Blog-images--13-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/dify-ai-integrates-jina-embeddings-for-rag" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Dify.AI integrates Jina Embeddings for RAG</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dify.AI, a leading open-source platform specialized in creating generative AI applications, is now leveraging Jina Embeddings v2! </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 06, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Difyco.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-embeddings-v2-and-mongodb-atlas" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina Embeddings v2 and MongoDB Atlas</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Supercharge MongoDB Atlas multi-cloud vector search solutions with Jina AI’s industry-leading embeddings!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/profile-option-2.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens, Saahil Ognawala</div><div class="q-item__label q-item__label--caption text-caption">December 06, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Blog-images--8-.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><div class="q-pagination row no-wrap items-center row justify-center q-ma-xl" aria-disabled="false" role="navigation" style=""><div class="q-pagination__content row no-wrap items-center"><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle text-grey-6 disabled" tabindex="-1" type="button" disabled="" aria-disabled="true" aria-label="1" aria-current="false" style="padding: 3px 2px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-backward-step" aria-hidden="true" role="img"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle 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min-width: 2em; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">…</span></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle text-grey-6 q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button" aria-label="18" aria-current="false" style="padding: 3px 2px; min-width: 2em; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">18</span></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle text-grey-6 q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button" aria-label="2" aria-current="false" style="padding: 3px 2px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-chevron-right" aria-hidden="true" role="img"> </i></span></button><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle text-grey-6 q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button" aria-label="18" aria-current="false" style="padding: 3px 2px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fas fa-forward-step" aria-hidden="true" role="img"> </i></span></button></div></div></div><div class="col-12 col-md-3 q-pa-md"><div class="row justify-between items-center"><div class="text-h6 text-overline"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">filter_alt</i> By product</div></div><div class="q-option-group q-gutter-x-sm q-option-group--inline q-mb-xl" role="group"><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"> Embeddings</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input 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50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> PromptPerfect</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://scenex.jina.ai/SceneX - Light.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> SceneXplain</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://bestbanner.jina.ai/bestbanner-light.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> BestBanner</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://chat.jina.ai/JinaChat - Light.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> JinaChat</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> Rationale</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> DocArray</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> Jina</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> Finetuner</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> CLIP-as-service</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> JCloud</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> LangChain-Serve</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> VectorDB</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> Executor Hub</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> DALL-E Flow</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> DiscoArt</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> ThinkGPT</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> DevGPT</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> RunGPT</div></div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div class="row items-center"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><div class="q-img q-img--menu" role="img" style="width: 32px; height: 32px;"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" height="32px" width="32px" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: contain; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div> Jerboa</div></div></div></div></div><div class="row justify-between items-center"><div class="text-h6 text-overline"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">filter_alt</i> By author</div></div><div class="q-option-group q-gutter-x-sm q-option-group--inline" role="group"><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Alaeddine Abdessalem" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Alaeddine Abdessalem</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Alex C-G" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Alex C-G</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Andrei Ungureanu" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Andrei Ungureanu</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Aziz Belaweid" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Aziz Belaweid</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Bo Wang" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Bo Wang</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Charlotte Gerhaher" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Charlotte Gerhaher</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Deepankar Mahapatro" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Deepankar Mahapatro</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Degi" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Degi</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Engineering Group" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Engineering Group</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Felix Wang" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Felix Wang</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Florian Hönicke" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Florian Hönicke</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Ge Jin" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Ge Jin</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Girish Chandrashekar" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Girish Chandrashekar</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Haiwei Li" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Haiwei Li</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Han Xiao" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Han Xiao</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Isabelle Mohr" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Isabelle Mohr</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Jack Min Ong" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Jack Min Ong</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Jie Fu" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Jie Fu</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Jina AI" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Jina AI</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Jocelyn Matthews" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Jocelyn Matthews</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Johannes Messner" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Johannes Messner</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Joschka Braun" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Joschka Braun</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Leon Wolf" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Leon Wolf</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Lisa Li" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Lisa Li</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Louis Milliken" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Louis Milliken</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Maximilian Werk" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Maximilian Werk</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Michael Günther" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Michael Günther</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Miruna Nedelcu" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Miruna Nedelcu</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Nicholas Dunham" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Nicholas Dunham</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Sa Zhang" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Sa Zhang</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Saahil Ognawala" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Saahil Ognawala</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Saba Sturua" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Saba Sturua</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Sami Jaghouar" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Sami Jaghouar</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Scott Martens" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Scott Martens</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Sebastian Weisshaar" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Sebastian Weisshaar</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Susana Guzmán" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip">Susana Guzmán</div></div></div><div><div class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-label="Tao Ran" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Inference: How Can Jina AI Offer the Best-in-Class Model-as-a-Service So Affordably?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI's Inference is an unparalleled, cost-effective model-as-a-service offering for multimodal AI. Here's why you should be using it.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/--.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 121.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/profile-option-2.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jie Fu, Saahil Ognawala</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 25, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In today's rapidly evolving business landscape, enterprises face many challenges. From managing large volumes of unstructured data to delivering personalized customer experiences, businesses need advanced solutions to stay ahead of the curve. Machine learning (ML) has emerged as a powerful tool for addressing these challenges by automating repetitive tasks, processing data efficiently, and generating insights from multimedia content.</p><p>However, implementing ML solutions has traditionally been plagued by roadblocks such as costly and time-consuming MLOps steps and the need to distinguish between public and custom neural network models. This is where <a href="https://jina.ai/product/inference/?ref=jina-ai-gmbh.ghost.io">Jina AI's Inference</a> steps in, offering a comprehensive solution to streamline access to curated, state-of-the-art ML models.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/product/inference/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Inference | Effortlessly integrate state-of-the-art ML models into your software | Jina AI</div><div class="kg-bookmark-description">Effortlessly integrate state-of-the-art ML models into your software</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/assets/images/banner/inference.png" alt=""></div></a></figure><h2 id="what-is-inference"><strong>What is Inference?</strong></h2><p>Inference is a secure, scalable cloud platform that allows enterprises to harness the power of highly curated ML models without the complexities of traditional ML implementation. Jina AI's team of experts researches and selects the best models for various tasks, including text embedding, image embedding, image captioning, super-resolution, visual reasoning, visual question answering, and neural search, ensuring top performance and cost-efficiency for your business needs.</p><p>The upcoming release of Inference will also include support for text generation, further expanding its capabilities.</p><p>In this article, we're going to work through the technical and academic innovations that our team has leveraged to be able to provide models-as-a-service, which is at least as performant, and most cases more, in terms of queries-per-second, while being significantly more affordable compared to alternatives on the market.</p><h2 id="the-art-of-model-curation"><strong>The Art of Model Curation</strong></h2><p>Jina AI's model curation process involves an in-depth evaluation and comparison of state-of-the-art models, drafting efficient architectures for splitting and hosting models to achieve fast and cost-effective inference, and validating performance and reliability before making them available to the public. By entrusting us with the curation process, businesses can focus on leveraging these robust ML solutions to enhance identified tasks to be automated using machine learning.</p><h2 id="the-science-of-model-deployment"><strong>The Science of Model Deployment</strong></h2><p><a href="https://docs.jina.ai/concepts/serving/executor/?ref=jina-ai-gmbh.ghost.io">Jina Executors</a> encapsulate specific functionalities and enable the construction of scalable and efficient inference systems. They are responsible for performing specific tasks within the pipeline, called a <a href="https://docs.jina.ai/concepts/orchestration/flow/?ref=jina-ai-gmbh.ghost.io">Jina Flow</a>.</p><p>Generally, the following is the way to wrap a model using a Jina Executor:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Inference: How Can Jina AI Offer the Best-in-Class Model-as-a-Service So Affordably?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI's Inference is an unparalleled, cost-effective model-as-a-service offering for multimodal AI. Here's why you should be using it.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/--.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 121.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/profile-option-2.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jie Fu, Saahil Ognawala</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 25, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In today's rapidly evolving business landscape, enterprises face many challenges. From managing large volumes of unstructured data to delivering personalized customer experiences, businesses need advanced solutions to stay ahead of the curve. Machine learning (ML) has emerged as a powerful tool for addressing these challenges by automating repetitive tasks, processing data efficiently, and generating insights from multimedia content.</p><p>However, implementing ML solutions has traditionally been plagued by roadblocks such as costly and time-consuming MLOps steps and the need to distinguish between public and custom neural network models. This is where <a href="https://jina.ai/product/inference/?ref=jina-ai-gmbh.ghost.io">Jina AI's Inference</a> steps in, offering a comprehensive solution to streamline access to curated, state-of-the-art ML models.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/product/inference/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Inference | Effortlessly integrate state-of-the-art ML models into your software | Jina AI</div><div class="kg-bookmark-description">Effortlessly integrate state-of-the-art ML models into your software</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/assets/images/banner/inference.png" alt=""></div></a></figure><h2 id="what-is-inference"><strong>What is Inference?</strong></h2><p>Inference is a secure, scalable cloud platform that allows enterprises to harness the power of highly curated ML models without the complexities of traditional ML implementation. Jina AI's team of experts researches and selects the best models for various tasks, including text embedding, image embedding, image captioning, super-resolution, visual reasoning, visual question answering, and neural search, ensuring top performance and cost-efficiency for your business needs.</p><p>The upcoming release of Inference will also include support for text generation, further expanding its capabilities.</p><p>In this article, we're going to work through the technical and academic innovations that our team has leveraged to be able to provide models-as-a-service, which is at least as performant, and most cases more, in terms of queries-per-second, while being significantly more affordable compared to alternatives on the market.</p><h2 id="the-art-of-model-curation"><strong>The Art of Model Curation</strong></h2><p>Jina AI's model curation process involves an in-depth evaluation and comparison of state-of-the-art models, drafting efficient architectures for splitting and hosting models to achieve fast and cost-effective inference, and validating performance and reliability before making them available to the public. By entrusting us with the curation process, businesses can focus on leveraging these robust ML solutions to enhance identified tasks to be automated using machine learning.</p><h2 id="the-science-of-model-deployment"><strong>The Science of Model Deployment</strong></h2><p><a href="https://docs.jina.ai/concepts/serving/executor/?ref=jina-ai-gmbh.ghost.io">Jina Executors</a> encapsulate specific functionalities and enable the construction of scalable and efficient inference systems. They are responsible for performing specific tasks within the pipeline, called a <a href="https://docs.jina.ai/concepts/orchestration/flow/?ref=jina-ai-gmbh.ghost.io">Jina Flow</a>.</p><p>Generally, the following is the way to wrap a model using a Jina Executor:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests
 
 <span class="hljs-keyword">class</span> <span class="hljs-title class_">MyModelExecutor</span>(<span class="hljs-title class_ inherited__">Executor</span>):
     <span class="hljs-keyword">def</span> <span class="hljs-title function_">__init__</span>(<span class="hljs-params">self</span>):
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Introducing Rationale: a Decision-Making Tool Powered by Latest GPT and In-Context Learning</title><meta charset="utf-8"><meta name="title" content="Introducing Rationale: a Decision-Making Tool Powered by Latest GPT and In-Context Learning"><meta name="description" content="With the incredible capabilities of generative AI, 2023 is shaping up to be a game-changing year for startups and builders. Don’t just take our word for it; try Rationale out for yourself and see the difference it can make for your business. Get started today!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/introducing-rationale-decision-making-tool-powered-latest-gpt-context-learning"><meta property="og:title" content="Introducing Rationale: a Decision-Making Tool Powered by Latest GPT and In-Context Learning"><meta property="og:description" content="With the incredible capabilities of generative AI, 2023 is shaping up to be a game-changing year for startups and builders. Don’t just take our word for it; try Rationale out for yourself and see the difference it can make for your business. Get started today!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--66-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/introducing-rationale-decision-making-tool-powered-latest-gpt-context-learning"><meta property="twitter:title" content="Introducing Rationale: a Decision-Making Tool Powered by Latest GPT and In-Context Learning"><meta property="twitter:description" content="With the incredible capabilities of generative AI, 2023 is shaping up to be a game-changing year for startups and builders. Don’t just take our word for it; try Rationale out for yourself and see the difference it can make for your business. Get started today!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--66-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Introducing Rationale: a Decision-Making Tool Powered by Latest GPT and In-Context Learning</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With the incredible capabilities of generative AI, 2023 is shaping up to be a game-changing year for startups and builders. Don’t just take our word for it; try Rationale out for yourself and see the difference it can make for your business. Get started today!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 02, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Today, we're thrilled to announce <a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io">Rationale</a>, an AI-powered decision-making tool that's here to help business owners, managers, and individuals make tough decisions with confidence.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - the revolutionary decision-making tool powered by GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-promo.mp4" poster="https://img.spacergif.org/v1/2266x1720/0a/spacer.png" width="2266" height="1720" loop="" autoplay="" muted="" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember1023.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay kg-video-hide-animated"><button class="kg-video-large-play-icon kg-video-hide-animated"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container kg-video-hide"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>Decision-making can be a daunting task, especially when you have to weigh multiple factors and consider the potential consequences of your choices. That's where Rationale comes in. With state-of-the-art <strong>GPT3.x </strong>and<strong> in-context learning </strong>algorithms, our app is specifically designed to help you make informed decisions.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">🥳</div><div class="kg-callout-text">Get 50% discount on your first purchase. Check out the coupon code at the end of the article!</div></div><h2 id="pros-cons-listing-swot-analysis">Pros &amp; Cons listing &amp; SWOT analysis</h2><p>One of the standout features of Rationale is its ability to generate cost-benefit analyses, pros and cons lists, SWOT analyses, and other decision-making techniques in seconds. This means you can quickly and easily weigh your options and make a more rational decision.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.689655 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--38-.png" width="1200" height="1740" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--38-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--38-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--38-.png 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.900901 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--41-.png" width="1200" height="1332" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--41-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--41-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--41-.png 1200w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>SWOT analysis on the left; Pros &amp; Cons list on the right.</figcaption></figure><h2 id="personalized-analysis">Personalized analysis</h2><p>But that's not all. Rationale is also personalized to you and your company, taking into account relevant information to deliver more accurate analysis and better inform your decisions. Plus, you can customize the tone of the analysis to align with your preferred narrative, making it more relatable and effective.</p><p>And the best part? Our AI is constantly learning from your decisions, which means it will get more accurate and personalized over time. So not only will you be able to make better decisions with Rationale, but the app will also get better at helping you make those decisions.</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-2.mp4" poster="https://img.spacergif.org/v1/1170x1020/0a/spacer.png" width="1170" height="1020" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember252.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>After filling in the personal and company information, Rationale will generate a more professional analysis tailored just for you.</figcaption></figure><h2 id="multilingual-support">Multilingual support</h2><p>One of the key features of Rationale is its multilingual support. Not only is the user interface available in multiple languages, but the algorithm itself is designed to provide analysis in any language that you input. This means you can get high-quality, accurate analysis in your preferred language, allowing for even more comprehensive decision-making.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.06383 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--51-.png" width="1200" height="1128" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--51-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--51-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--51-.png 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.1236 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--50-.png" width="1200" height="1068" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--50-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--50-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--50-.png 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.986842 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--49-.png" width="1200" height="1216" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--49-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--49-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--49-.png 1200w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.465839 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--48-.png" width="1200" height="2576" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--48-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--48-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--48-.png 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.990099 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--46-.png" width="1200" height="1212" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--46-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--46-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--46-.png 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.09489 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--47-.png" width="1200" height="1096" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--47-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--47-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--47-.png 1200w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h2 id="universal-experience-on-every-device">Universal experience on every device</h2><p>One of the great things about Rationale is that it's built as a <strong>progressive web app (PWA)</strong>, which means it can be used on both phones and desktop browsers with a native app-like user experience. This makes it easy and convenient to use, no matter where you are or what device you have.</p><p>To use Rationale as a PWA, simply visit our website on your phone or desktop browser and follow the prompts to install the app. It's just like installing a native app, but without the need to visit an app store.</p><p>And if you prefer a traditional native app experience, don't worry – we'll be launching iOS and Android apps in the near future. Keep an eye out for updates, and be sure to download the app when it becomes available.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/desktop-electron.png" class="kg-image" alt="" width="1296" height="885" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/desktop-electron.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/desktop-electron.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/desktop-electron.png 1296w" sizes="(min-width: 720px) 720px"><figcaption>Our Electron-powered native MacOS/Windows app is on the way!</figcaption></figure><h2 id="summary">Summary</h2><p>So, if you're someone who values their time and wants to make the best decisions possible, give Rationale a try. With fast, high-quality analysis reports and the ability to access the app in your preferred language, it's never been easier to make informed, rational decisions. And with API access to our AI engine, you can even export your data and integrate it into your own applications.</p><p>We're excited to see how Rationale can help you make smarter, more confident decisions. Give it a try today and see for yourself the power of AI-assisted decision-making.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - the revolutionary decision-making tool powered by GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a><figcaption>Use coupon code <strong>1STRELEASE </strong>to get 50% off before Jan. 31, 2022</figcaption></figure><h2 id="get-50-off-on-your-first-purchase">Get 50% off on your first purchase</h2><p>As a special promotion for the launch of Rationale, we're offering a coupon code for 50% off any of our plans. Simply use code <code><strong>1STRELEASE</strong></code> when you purchase <strong>before January 31, 2023 </strong>to take advantage of this limited-time offer.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">50% off coupon code: 1STRELEASE</a></div><p>We want as many people as possible to experience the benefits of Rationale, and this coupon is our way of encouraging you to give it a try. Whether you're a business owner, manager, or simply someone who values making informed decisions, we believe Rationale can help you make smarter, more confident choices.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fintroducing-rationale-decision-making-tool-powered-latest-gpt-context-learning%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Introducing Rationale: a Decision-Making Tool Powered by Latest GPT and In-Context Learning</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With the incredible capabilities of generative AI, 2023 is shaping up to be a game-changing year for startups and builders. Don’t just take our word for it; try Rationale out for yourself and see the difference it can make for your business. Get started today!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 02, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Today, we're thrilled to announce <a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io">Rationale</a>, an AI-powered decision-making tool that's here to help business owners, managers, and individuals make tough decisions with confidence.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - the revolutionary decision-making tool powered by GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-promo.mp4" poster="https://img.spacergif.org/v1/2266x1720/0a/spacer.png" width="2266" height="1720" loop="" autoplay="" muted="" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember1023.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay kg-video-hide-animated"><button class="kg-video-large-play-icon kg-video-hide-animated"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container kg-video-hide"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>Decision-making can be a daunting task, especially when you have to weigh multiple factors and consider the potential consequences of your choices. That's where Rationale comes in. With state-of-the-art <strong>GPT3.x </strong>and<strong> in-context learning </strong>algorithms, our app is specifically designed to help you make informed decisions.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">🥳</div><div class="kg-callout-text">Get 50% discount on your first purchase. Check out the coupon code at the end of the article!</div></div><h2 id="pros-cons-listing-swot-analysis">Pros &amp; Cons listing &amp; SWOT analysis</h2><p>One of the standout features of Rationale is its ability to generate cost-benefit analyses, pros and cons lists, SWOT analyses, and other decision-making techniques in seconds. This means you can quickly and easily weigh your options and make a more rational decision.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.689655 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--38-.png" width="1200" height="1740" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--38-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--38-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--38-.png 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.900901 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--41-.png" width="1200" height="1332" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--41-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--41-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--41-.png 1200w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>SWOT analysis on the left; Pros &amp; Cons list on the right.</figcaption></figure><h2 id="personalized-analysis">Personalized analysis</h2><p>But that's not all. Rationale is also personalized to you and your company, taking into account relevant information to deliver more accurate analysis and better inform your decisions. Plus, you can customize the tone of the analysis to align with your preferred narrative, making it more relatable and effective.</p><p>And the best part? Our AI is constantly learning from your decisions, which means it will get more accurate and personalized over time. So not only will you be able to make better decisions with Rationale, but the app will also get better at helping you make those decisions.</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-2.mp4" poster="https://img.spacergif.org/v1/1170x1020/0a/spacer.png" width="1170" height="1020" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember252.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>After filling in the personal and company information, Rationale will generate a more professional analysis tailored just for you.</figcaption></figure><h2 id="multilingual-support">Multilingual support</h2><p>One of the key features of Rationale is its multilingual support. Not only is the user interface available in multiple languages, but the algorithm itself is designed to provide analysis in any language that you input. This means you can get high-quality, accurate analysis in your preferred language, allowing for even more comprehensive decision-making.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.06383 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--51-.png" width="1200" height="1128" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--51-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--51-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--51-.png 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.1236 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--50-.png" width="1200" height="1068" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--50-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--50-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--50-.png 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.986842 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--49-.png" width="1200" height="1216" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--49-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--49-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--49-.png 1200w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.465839 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--48-.png" width="1200" height="2576" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--48-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--48-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--48-.png 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.990099 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--46-.png" width="1200" height="1212" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--46-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--46-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--46-.png 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.09489 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--47-.png" width="1200" height="1096" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--47-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--47-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--47-.png 1200w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h2 id="universal-experience-on-every-device">Universal experience on every device</h2><p>One of the great things about Rationale is that it's built as a <strong>progressive web app (PWA)</strong>, which means it can be used on both phones and desktop browsers with a native app-like user experience. This makes it easy and convenient to use, no matter where you are or what device you have.</p><p>To use Rationale as a PWA, simply visit our website on your phone or desktop browser and follow the prompts to install the app. It's just like installing a native app, but without the need to visit an app store.</p><p>And if you prefer a traditional native app experience, don't worry – we'll be launching iOS and Android apps in the near future. Keep an eye out for updates, and be sure to download the app when it becomes available.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/desktop-electron.png" class="kg-image" alt="" width="1296" height="885" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/desktop-electron.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/desktop-electron.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/desktop-electron.png 1296w" sizes="(min-width: 720px) 720px"><figcaption>Our Electron-powered native MacOS/Windows app is on the way!</figcaption></figure><h2 id="summary">Summary</h2><p>So, if you're someone who values their time and wants to make the best decisions possible, give Rationale a try. With fast, high-quality analysis reports and the ability to access the app in your preferred language, it's never been easier to make informed, rational decisions. And with API access to our AI engine, you can even export your data and integrate it into your own applications.</p><p>We're excited to see how Rationale can help you make smarter, more confident decisions. Give it a try today and see for yourself the power of AI-assisted decision-making.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - the revolutionary decision-making tool powered by GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a><figcaption>Use coupon code <strong>1STRELEASE </strong>to get 50% off before Jan. 31, 2022</figcaption></figure><h2 id="get-50-off-on-your-first-purchase">Get 50% off on your first purchase</h2><p>As a special promotion for the launch of Rationale, we're offering a coupon code for 50% off any of our plans. Simply use code <code><strong>1STRELEASE</strong></code> when you purchase <strong>before January 31, 2023 </strong>to take advantage of this limited-time offer.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">50% off coupon code: 1STRELEASE</a></div><p>We want as many people as possible to experience the benefits of Rationale, and this coupon is our way of encouraging you to give it a try. Whether you're a business owner, manager, or simply someone who values making informed decisions, we believe Rationale can help you make smarter, more confident choices.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fintroducing-rationale-decision-making-tool-powered-latest-gpt-context-learning%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="a6fe9b41-cc14-4c0d-aa41-51f61199a275" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="a6fe9b41-cc14-4c0d-aa41-51f61199a275" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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Thankfully,  Jina framework supports sharding out of the box. Users can process their data between multiple machines to get faster performance.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 132.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Profile-Picture.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Maximilian Werk, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 28, 2022 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2></h2><p>We live in a “predictable” world of “logic”, where things go (more or less) as expected. Every day the sun rises, fish swim, birds fly, and people hurl abuse at each other on Twitter. Just another day on social media</p><p align="center">
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="42d0ded7-f9d9-4bae-a763-272cf50704eb" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="42d0ded7-f9d9-4bae-a763-272cf50704eb" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Sharding is a piece of cake, or is it? Thankfully,  Jina framework supports sharding out of the box. Users can process their data between multiple machines to get faster performance.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Profile-Picture.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Maximilian Werk, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 28, 2022 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2></h2><p>We live in a “predictable” world of “logic”, where things go (more or less) as expected. Every day the sun rises, fish swim, birds fly, and people hurl abuse at each other on Twitter. Just another day on social media</p><p align="center">
 <img loading="lazy" src="https://media.tenor.com/bgkPZCa6qKcAAAAC/angry.gif" class="kg-image" alt="" width="200">
 </p>
-<p>If you drink more coffee, you get more hyper. If you browse more social media, you get more miserable. If you have a big problem and throw more CPUs at it, you get that problem solved more quickly.</p><p>One of these things is not like the others. Take a wild guess which.</p><p>Turns out that whole throwing CPUs at a problem thing? It doesn’t always work so well.</p><p>It <em>should</em> be straightforward. CPUs are just <a href="https://old.reddit.com/r/Showerthoughts/comments/74h2wo/computers_are_just_rocks_we_tricked_into_thinking/?ref=jina-ai-gmbh.ghost.io">magical rocks full of lightning</a>. More rocks should equal more speed. What the hell is happening here?</p><p>To start, let’s go back to the misty days of a few weeks ago, when our team was running some sharding experiments…</p><h2 id="sharding">Sharding</h2><p>Katie is building a search engine for delicious cake recipes. There are a <em>lot</em> of cake recipes around the world, so she’ll soon have gazillions of recipes.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://veggiedesserts.com/tomato-soup-cake/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Tomato Soup Cake</div><div class="kg-bookmark-description">Make this Magic Tomato Soup Cake! Based on a classic retro 1950s recipe printed on cans. You can’t taste the soup in the spice layer cake.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://veggiedesserts.com/wp-content/uploads/2017/05/cropped-VeggieDessertscover-270x270.jpg" alt=""><span class="kg-bookmark-author">Veggie Desserts</span><span class="kg-bookmark-publisher">Kate Hackworthy</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://veggiedesserts.com/wp-content/uploads/2021/04/tomato-soup-cake-cover.jpg" alt=""></div></a><figcaption>"Yum"</figcaption></figure><p>With Jina, that’s a piece of cake.<strong> The Jina framework supports <a href="https://docs.jina.ai/how-to/scale-out/?ref=jina-ai-gmbh.ghost.io#split-data-into-partitions-shards">sharding out of the box</a>:</strong> when the data doesn't fit on one machine any more, Katie can split her data between multiple machines. She can do this split &nbsp;to speed up computation of a single request as well.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docs.jina.ai/how-to/scale-out/?ref=jina-ai-gmbh.ghost.io#split-data-into-partitions-shards"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Scale out with replicas and shards</div><div class="kg-bookmark-description">A Jina Flow orchestrates multiple Executor s. By default, an Executor runs with a single replica and shard. Some Executors in the Flow may be less performant than others, which could cause performance bottlenecks in an application. To solve this, you can configure the number of replicas and shard...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docs.jina.ai/_static/favicon.ico" alt=""><span class="kg-bookmark-author">Jina 3.11.1 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docs.jina.ai/_static/banner.png" alt=""></div></a></figure><p>Let’s jump in and help Katie out. Maybe we’ll even get a <a href="https://www.theonion.com/something-called-guacamole-donut-burying-news-of-doze-1849701649?ref=jina-ai-gmbh.ghost.io">guacamole donut</a> for our troubles.</p><h2 id="preliminary-testing">Preliminary testing</h2><p>We wrote some benchmarking code that generates <a href="https://docarray.jina.ai/fundamentals/document/?ref=jina-ai-gmbh.ghost.io">Document</a>s with random embeddings and splits them between different shards of an indexer. We used that code to run a sharding experiment on an M2 mac.</p><figure class="kg-card kg-code-card"><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> time
-<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
-<span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests, Flow, DocumentArray
+<p>If you drink more coffee, you get more hyper. If you browse more social media, you get more miserable. If you have a big problem and throw more CPUs at it, you get that problem solved more quickly.</p><p>One of these things is not like the others. Take a wild guess which.</p><p>Turns out that whole throwing CPUs at a problem thing? It doesn’t always work so well.</p><p>It <em>should</em> be straightforward. CPUs are just <a href="https://old.reddit.com/r/Showerthoughts/comments/74h2wo/computers_are_just_rocks_we_tricked_into_thinking/?ref=jina-ai-gmbh.ghost.io">magical rocks full of lightning</a>. More rocks should equal more speed. What the hell is happening here?</p><p>To start, let’s go back to the misty days of a few weeks ago, when our team was running some sharding experiments…</p><h2 id="sharding">Sharding</h2><p>Katie is building a search engine for delicious cake recipes. There are a <em>lot</em> of cake recipes around the world, so she’ll soon have gazillions of recipes.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://veggiedesserts.com/tomato-soup-cake/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Tomato Soup Cake</div><div class="kg-bookmark-description">Make this Magic Tomato Soup Cake! Based on a classic retro 1950s recipe printed on cans. You can’t taste the soup in the spice layer cake.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://veggiedesserts.com/wp-content/uploads/2017/05/cropped-VeggieDessertscover-270x270.jpg" alt=""><span class="kg-bookmark-author">Veggie Desserts</span><span class="kg-bookmark-publisher">Kate Hackworthy</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://veggiedesserts.com/wp-content/uploads/2021/04/tomato-soup-cake-cover.jpg" alt=""></div></a><figcaption>"Yum"</figcaption></figure><p>With Jina, that’s a piece of cake.<strong> The Jina framework supports <a href="https://docs.jina.ai/how-to/scale-out/?ref=jina-ai-gmbh.ghost.io#split-data-into-partitions-shards">sharding out of the box</a>:</strong> when the data doesn't fit on one machine any more, Katie can split her data between multiple machines. She can do this split &nbsp;to speed up computation of a single request as well.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docs.jina.ai/how-to/scale-out/?ref=jina-ai-gmbh.ghost.io#split-data-into-partitions-shards"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Scale out with replicas and shards</div><div class="kg-bookmark-description">A Jina Flow orchestrates multiple Executor s. By default, an Executor runs with a single replica and shard. Some Executors in the Flow may be less performant than others, which could cause performance bottlenecks in an application. To solve this, you can configure the number of replicas and shard...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docs.jina.ai/_static/favicon.ico" alt=""><span class="kg-bookmark-author">Jina 3.11.1 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docs.jina.ai/_static/banner.png" alt=""></div></a></figure><p>Let’s jump in and help Katie out. Maybe we’ll even get a <a href="https://www.theonion.com/something-called-guacamole-donut-burying-news-of-doze-1849701649?ref=jina-ai-gmbh.ghost.io">guacamole donut</a> for our troubles.</p><h2 id="preliminary-testing">Preliminary testing</h2><p>We wrote some benchmarking code that generates <a href="https://docarray.jina.ai/fundamentals/document/?ref=jina-ai-gmbh.ghost.io">Document</a>s with random embeddings and splits them between different shards of an indexer. We used that code to run a sharding experiment on an M2 mac.</p><figure class="kg-card kg-code-card"><pre><code class="language-python">import time
+import numpy as np
+from jina import Executor, requests, Flow, DocumentArray
 
-top_k = <span class="hljs-number">100</span>
-num_dim = <span class="hljs-number">512</span>
-total_queries = <span class="hljs-number">16</span>
-total_docs = <span class="hljs-number">1_000_000</span>
-shards = <span class="hljs-number">2</span>
+top_k = 100
+num_dim = 512
+total_queries = 16
+total_docs = 1_000_000
+shards = 2
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyExec1</span>(<span class="hljs-title class_ inherited__">Executor</span>):
+class MyExec1(Executor):
 
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">__init__</span>(<span class="hljs-params">self, **kwargs</span>):
-        <span class="hljs-built_in">super</span>().__init__(**kwargs)
-        num_docs = <span class="hljs-built_in">int</span>(total_docs // shards)
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        num_docs = int(total_docs // shards)
         self.da = DocumentArray.empty(num_docs)
         self.da.embeddings = np.random.random((num_docs, num_dim)).astype(np.float32)
 
-<span class="hljs-meta">    @requests</span>
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">foo</span>(<span class="hljs-params">self, docs, **kwargs</span>):
-        <span class="hljs-keyword">return</span> self.da.find(docs, limit=<span class="hljs-built_in">int</span>(top_k // shards), metric=<span class="hljs-string">'cosine'</span>)[<span class="hljs-number">0</span>]
+    @requests
+    def foo(self, docs, **kwargs):
+        return self.da.find(docs, limit=int(top_k // shards), metric='cosine')[0]
 
 
-f = Flow().add(uses=MyExec1, shards=shards, polling=<span class="hljs-string">'all'</span>)
+f = Flow().add(uses=MyExec1, shards=shards, polling='all')
 
 queries = DocumentArray.empty(total_queries)
 queries.embeddings = np.random.random((total_queries, num_dim)).astype(np.float32)
 
 
-<span class="hljs-keyword">with</span> f:
+with f:
     st = time.perf_counter()
-    f.post(<span class="hljs-string">'/'</span>, queries, request_size=<span class="hljs-number">1</span>)
+    f.post('/', queries, request_size=1)
     elapse = time.perf_counter() - st
     qps = total_queries / elapse</code></pre><figcaption>Benchmark code we used for this experiment. One can see that by specifying `shards=shards, polling='all'`, <strong>Jina can support sharding out of the box with no extra effort.</strong></figcaption></figure><p>We tested a variety of scenarios, with differing numbers of Documents and shards. For each scenario we:</p><ol><li>Created <a href="https://docarray.jina.ai/fundamentals/documentarray/?ref=jina-ai-gmbh.ghost.io">DocumentArray</a>s with random 512-dimensional embeddings. The number of Documents varied between 10,000 and 1 million.</li><li>Created a <a href="https://docs.jina.ai/fundamentals/flow/?ref=jina-ai-gmbh.ghost.io">Flow</a> with a single dummy indexer <a href="https://docs.jina.ai/fundamentals/executor/?ref=jina-ai-gmbh.ghost.io">Executor</a>. The shard count varied from 1 to 8.</li><li>Ran several queries through the Flow and timed how long it took to get search results back.</li></ol><p>Naturally, we assumed that <strong>more shards == better performance</strong>. Specifically, that querying Documents would be faster with more shards.</p><p>Well, you know what they say about “assume":</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://dict.leo.org/forum/viewUnsolvedquery.php?idForum=2&amp;idThread=1010594&amp;lp=ende&amp;lang=en&amp;ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">When you ASSUME you make an ASS out of U and Me. - German missing: English ⇔ German Forums - leo.org</div><div class="kg-bookmark-description">LEO.org: Your online dictionary for English-German translations. Offering forums, vocabulary trainer and language courses. Also available as App!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://dict.leo.org/img/favicons/ende-32.png" alt=""><span class="kg-bookmark-author">English ⇔ German Forums - leo.org</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://dict.leo.org/img/svg/leo_ende.svg" alt=""></div></a></figure><p>Needless to say, we didn’t get the results we expected:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/experiment-0-5.png" class="kg-image" alt="" width="589" height="505"></figure><p><strong>Not only did the shards not speed up the process as much as thought they should, but they actually slowed things down!</strong> C’mon shards, you had one job!</p><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Don’t worry about how generally slow everything is in the graph. This dummy indexer isn’t intended for production use, just for testing!</div></div><p>From the graph we can see:</p><ul><li>Sharding only makes sense when the overhead of sharding is smaller than the gain in multiprocessing. Sharding for 10,000 documents doesn’t make sense.</li><li>Sharding beyond the number of cores in a machine brings no benefit. When CPU utilization hits 100% it’s pointless to split the task any further.</li></ul><p>However, the line for 1 million Documents seems suspicious. Why don't we see any improvement when going from 2 to 4 shards?</p><h2 id="juicing-up-our-testing">Juicing up our testing</h2><p>Let’s throw some serious compute at this baby and see what happens. I have an i9-12900KF with 16 cores and 24 threads under my desk. That amount of power should erase any bottlenecks for 4 shards, right?</p><p align="center">
 <img loading="lazy" src="https://media.tenor.com/C4Mq2N6UiQEAAAAC/power-aladdin.gif" class="kg-image" alt="" width="200">
 </p>
-<p>In all experiments below, we did this:</p><ol><li>Create one DocumentArray consisting of 500,000 to 4 million Documents with random 512-dimension embeddings. Let’s call this the index.</li><li>Create a Flow with a single dummy indexer Executor. The shard count varied from 1 to 8.</li><li>Ran warm-up queries through the Flow. This ensures no initial hiccups in the benchmarking.</li><li>Ran benchmark queries through the Flow. We used five queries, also with 512-dimension embeddings.</li><li>Performed a <code>da.find()</code> with both warm-up and benchmark queries.</li><li>Timed how long it took to run all five queries together.</li></ol><p>Under the hood <code>.find()</code> calculates the cosine distance between the index embeddings and &nbsp;query embeddings. Be aware that <code>.find()</code> is designed for easy experimentation and not for big matrix multiplications in live systems. So don’t be shocked by the runtime below. Our target here is to analyze sharding and not to get the best performing vector search engine.</p><p>You can find all code in this repository:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/maximilianwerk/jina-sharding-analysis?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - maximilianwerk/jina-sharding-analysis</div><div class="kg-bookmark-description">Contribute to maximilianwerk/jina-sharding-analysis development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">maximilianwerk</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/e033db22be7497426f697dc0e674faae5ef302a9b6050c32d25e7d7837b8b482/maximilianwerk/jina-sharding-analysis" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">This code was written for quick experimentation changes and not for beauty. You have been warned!</div></div><h3 id="experiment-1-the-basics">Experiment 1: the basics</h3><p>Let’s run two tests:</p><ul><li>1A: 4 million docs in total with 1, 2, 4 or 8 shards. (total docs are constant, docs per shard varies)</li><li>1B: 500,000 docs per shard with 1, 2, 4 or 8 shards. (total docs vary, docs per shard is constant)</li></ul><p>For each test, we run five queries. Our expectation would be to see the runtime halving for each step in 1A (blue) and a flat line for 1B (red).</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/experiment-1.png" class="kg-image" alt="" width="589" height="505"></figure><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Don’t be shocked by the slow runtime. It’s our dummy indexer, which should not be used in production for more than 100,000 Documents.</div></div><p>Hmmm…Not quite what we expected. Let’s have a quick look at <code>htop</code> for 1 and 4 shards in experiment 1B:</p><figure class="kg-card kg-image-card kg-width-full"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--1--3.png" class="kg-image" alt="" width="1668" height="377" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Untitled--1--3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/Untitled--1--3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/Untitled--1--3.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--1--3.png 1668w"></figure><p>We see that NumPy does a pretty good job in multiprocessing itself. So when using 1 shard, we utilize ~4.5 CPUs and when using 4 shards we utilize ~8.75 CPUs. The total workload for 4 shards was 4 times as much as for 1 shard, and as such doubling the runtime seems to be legit.</p><h3 id="experiment-2-disabling-multiprocessing">Experiment 2: Disabling multiprocessing</h3><p>Now let’s run the same experiment, with NumPy multiprocessing turned off:</p><pre><code class="language-python hljs">os.environ[<span class="hljs-string">'OPENBLAS_NUM_THREADS'</span>] = <span class="hljs-string">'1'</span>
-os.environ[<span class="hljs-string">'MKL_NUM_THREADS'</span>] = <span class="hljs-string">'1'</span></code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/experiment-2.png" class="kg-image" alt="" width="589" height="505"></figure><p>Whoopsie! Yes, this is almost the very same result as above. Did we really disable multiprocessing? Let’s have a look at <code>htop</code> again for one shard:</p><figure class="kg-card kg-image-card kg-width-full"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--2--1.png" class="kg-image" alt="" width="1673" height="177" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Untitled--2--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/Untitled--2--1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/Untitled--2--1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--2--1.png 1673w"></figure><p>Yes, there really is only one core utilized. So NumPy performs the computation at the same speed regardless of whether it’s fully using 4.5 cores or just one.</p><p>Perhaps the main computation isn’t even the cosine distance computation. Luckily, our core team just implemented tracing for Jina. Let’s take a look at the “search” span:</p><figure class="kg-card kg-image-card kg-width-full"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--3--1.png" class="kg-image" alt="" width="1411" height="824" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Untitled--3--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/Untitled--3--1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--3--1.png 1411w"></figure><p>We can see my five requests and how they’re sequentially processed. The “search” span is where all the computation happens and takes almost all the time. So we have certainty that the main computation is the cosine distance. Our sharding seems to work just fine.</p><h2 id="my-theory">My theory</h2><p>I’m very grateful that I saw similar behavior some years ago. At that time, <a href="https://www.linkedin.com/in/dehora/?ref=jina-ai-gmbh.ghost.io">Bill de hÓra</a> (as a senior architect) took time to give me a hint to the solution. I’m no expert in low-level processor architecture, but let me give you my understanding of what just happened:</p><p>When you parallelize memory- and CPU-intensive workloads on a single physical chip, each processor needs to load the to-be-processed data into the lowest level cache (L1 cache). When a single core needs more than <code>1/(utilized cores)</code> of the L1 cache, the processors do their computations in a kind of round-robin fashion, constantly interrupting each other. By doing that, they are busier reloading data into the cache than performing actual computation. My processor’s specs say “Max Memory Bandwidth: 76.8 GB/s”, which should ensure I can load all the needed data into the cache in a fraction of a second.</p><p>My guess: the individual cores interrupt each other so often that they are busier loading from memory than doing the actual computation.</p><h3 id="verifying-my-theory-different-plain-matrix-multiplications">Verifying my theory: Different plain matrix multiplications</h3><p>Let's try different matrix multiplications.</p><ul><li>A: (2,000,000, 100) * (100, 100) ⇒ 2,000,000*100*100 = 2*10^10 operations</li><li>B: (3,000, 3,000) * (3,000, 3,000) ⇒ 3,000*3,000*3,000 = 2.7*10^10 operations</li></ul><p>The data loading for the same amount of basic multiplications in both cases roughly looks like this:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Sharding-matrix-multiplication--2---1--1.png" class="kg-image" alt="" width="710" height="385" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Sharding-matrix-multiplication--2---1--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Sharding-matrix-multiplication--2---1--1.png 710w"></figure><p>We need to load 2.5 times more data into the cache for the same amount of operations. Therefore the individual cores are more likely to need to do memory swapping.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/experiment-3.png" class="kg-image" alt="" width="589" height="505"></figure><p>For unbalanced matrices we see the same behavior as in our <code>da.find()</code> experiment above. For quadratic matrices we see, that up to 8 shards there’s only a small increase in runtime and the shards behave well. I can’t judge if the runtime increases beyond 8 shards for quadratic matrices due to having only 8 high-performance CPUs and 8 low-performance CPUs, or in having the decreased part of the cache that every shard gets.</p><p>Oh, I almost forgot to mention: This experiment also shows us the bad behavior doesn’t come from the small overhead that our DocumentArray produces. Lucky us!</p><p>I also ran experiment 1B with AnnLite to see how sharding behaves with a proper implementation of HNSW (a very common vector search algorithm). </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/annlite?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/annlite: ⚡ A fast embedded library for approximate nearest neighbor search</div><div class="kg-bookmark-description">⚡ A fast embedded library for approximate nearest neighbor search - GitHub - jina-ai/annlite: ⚡ A fast embedded library for approximate nearest neighbor search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/400352346/d5e5de62-d7af-424c-b059-141e69ef3835" alt=""></div></a></figure><p>The outcome: sharding had no impact on the runtime. Tracing showed that the actual computation was blazingly fast (under 3ms). Furthermore, tracing showed that the actual computations really ran in parallel and didn’t affect each other’s runtimes.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">We've found that using sharding on multiprocessor systems to take advantage of the multiprocessor architecture may not work as well as expected. We suspect the cause is shared low-level resources.</div></div><h2 id="conclusion">Conclusion</h2><p>Luckily for us, sharding works just fine in a real world scenario. In a future post we’ll look at sharding across different machines. Given the traces above (and a lot of other traces I looked upon during the process) it should work just fine.</p><p>But multiprocessing memory- <strong>and</strong> CPU-intensive work on one machine is tricky. What I find really concerning: <strong>A lot of computations are run on the cloud, where we have no control over the hardware.</strong></p><p>Coming back to our cake search engine: Let’s say Katie’s company is starting to grow and wants to run the service on the cloud, via multiple virtual machines. There’s no guarantee that these are independent physical machines - they could all be running on the same box with the same L1 cache, and thus ruin Katie’s performance. That would really leave a bad taste in her mouth.</p><p align="center"><img loading="lazy" src="https://media.tenor.com/krqwU2K9hq8AAAAC/elliegato-pound-cake.gif" class="kg-image" alt="" width="200"></p><p>Perhaps worse: When using Kubernetes we often explicitly have multiple Pods on the same machine. Even when the neighbors are not noisy in the sense of over-utilizing CPU/memory resources, they can have a workload that does bad things to low-level cache or another non-obvious resource and slow neighbors down.</p><hr><p>Do you like the post, or think my low-level cache analysis or conclusion is wrong? Talk to me in the comments or on <a href="https://www.twitter.com/maximilianwerk?ref=jina-ai-gmbh.ghost.io">Twitter</a>.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fits-hard-to-shard%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<p>In all experiments below, we did this:</p><ol><li>Create one DocumentArray consisting of 500,000 to 4 million Documents with random 512-dimension embeddings. Let’s call this the index.</li><li>Create a Flow with a single dummy indexer Executor. The shard count varied from 1 to 8.</li><li>Ran warm-up queries through the Flow. This ensures no initial hiccups in the benchmarking.</li><li>Ran benchmark queries through the Flow. We used five queries, also with 512-dimension embeddings.</li><li>Performed a <code>da.find()</code> with both warm-up and benchmark queries.</li><li>Timed how long it took to run all five queries together.</li></ol><p>Under the hood <code>.find()</code> calculates the cosine distance between the index embeddings and &nbsp;query embeddings. Be aware that <code>.find()</code> is designed for easy experimentation and not for big matrix multiplications in live systems. So don’t be shocked by the runtime below. Our target here is to analyze sharding and not to get the best performing vector search engine.</p><p>You can find all code in this repository:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/maximilianwerk/jina-sharding-analysis?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - maximilianwerk/jina-sharding-analysis</div><div class="kg-bookmark-description">Contribute to maximilianwerk/jina-sharding-analysis development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">maximilianwerk</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/e033db22be7497426f697dc0e674faae5ef302a9b6050c32d25e7d7837b8b482/maximilianwerk/jina-sharding-analysis" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">⚠️</div><div class="kg-callout-text">This code was written for quick experimentation changes and not for beauty. You have been warned!</div></div><h3 id="experiment-1-the-basics">Experiment 1: the basics</h3><p>Let’s run two tests:</p><ul><li>1A: 4 million docs in total with 1, 2, 4 or 8 shards. (total docs are constant, docs per shard varies)</li><li>1B: 500,000 docs per shard with 1, 2, 4 or 8 shards. (total docs vary, docs per shard is constant)</li></ul><p>For each test, we run five queries. Our expectation would be to see the runtime halving for each step in 1A (blue) and a flat line for 1B (red).</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/experiment-1.png" class="kg-image" alt="" width="589" height="505"></figure><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Don’t be shocked by the slow runtime. It’s our dummy indexer, which should not be used in production for more than 100,000 Documents.</div></div><p>Hmmm…Not quite what we expected. Let’s have a quick look at <code>htop</code> for 1 and 4 shards in experiment 1B:</p><figure class="kg-card kg-image-card kg-width-full"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--1--3.png" class="kg-image" alt="" width="1668" height="377" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Untitled--1--3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/Untitled--1--3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/Untitled--1--3.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--1--3.png 1668w"></figure><p>We see that NumPy does a pretty good job in multiprocessing itself. So when using 1 shard, we utilize ~4.5 CPUs and when using 4 shards we utilize ~8.75 CPUs. The total workload for 4 shards was 4 times as much as for 1 shard, and as such doubling the runtime seems to be legit.</p><h3 id="experiment-2-disabling-multiprocessing">Experiment 2: Disabling multiprocessing</h3><p>Now let’s run the same experiment, with NumPy multiprocessing turned off:</p><pre><code class="language-python">os.environ['OPENBLAS_NUM_THREADS'] = '1'
+os.environ['MKL_NUM_THREADS'] = '1'</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/experiment-2.png" class="kg-image" alt="" width="589" height="505"></figure><p>Whoopsie! Yes, this is almost the very same result as above. Did we really disable multiprocessing? Let’s have a look at <code>htop</code> again for one shard:</p><figure class="kg-card kg-image-card kg-width-full"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--2--1.png" class="kg-image" alt="" width="1673" height="177" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Untitled--2--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/Untitled--2--1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/Untitled--2--1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--2--1.png 1673w"></figure><p>Yes, there really is only one core utilized. So NumPy performs the computation at the same speed regardless of whether it’s fully using 4.5 cores or just one.</p><p>Perhaps the main computation isn’t even the cosine distance computation. Luckily, our core team just implemented tracing for Jina. Let’s take a look at the “search” span:</p><figure class="kg-card kg-image-card kg-width-full"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--3--1.png" class="kg-image" alt="" width="1411" height="824" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Untitled--3--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/Untitled--3--1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--3--1.png 1411w"></figure><p>We can see my five requests and how they’re sequentially processed. The “search” span is where all the computation happens and takes almost all the time. So we have certainty that the main computation is the cosine distance. Our sharding seems to work just fine.</p><h2 id="my-theory">My theory</h2><p>I’m very grateful that I saw similar behavior some years ago. At that time, <a href="https://www.linkedin.com/in/dehora/?ref=jina-ai-gmbh.ghost.io">Bill de hÓra</a> (as a senior architect) took time to give me a hint to the solution. I’m no expert in low-level processor architecture, but let me give you my understanding of what just happened:</p><p>When you parallelize memory- and CPU-intensive workloads on a single physical chip, each processor needs to load the to-be-processed data into the lowest level cache (L1 cache). When a single core needs more than <code>1/(utilized cores)</code> of the L1 cache, the processors do their computations in a kind of round-robin fashion, constantly interrupting each other. By doing that, they are busier reloading data into the cache than performing actual computation. My processor’s specs say “Max Memory Bandwidth: 76.8 GB/s”, which should ensure I can load all the needed data into the cache in a fraction of a second.</p><p>My guess: the individual cores interrupt each other so often that they are busier loading from memory than doing the actual computation.</p><h3 id="verifying-my-theory-different-plain-matrix-multiplications">Verifying my theory: Different plain matrix multiplications</h3><p>Let's try different matrix multiplications.</p><ul><li>A: (2,000,000, 100) * (100, 100) ⇒ 2,000,000*100*100 = 2*10^10 operations</li><li>B: (3,000, 3,000) * (3,000, 3,000) ⇒ 3,000*3,000*3,000 = 2.7*10^10 operations</li></ul><p>The data loading for the same amount of basic multiplications in both cases roughly looks like this:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Sharding-matrix-multiplication--2---1--1.png" class="kg-image" alt="" width="710" height="385" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Sharding-matrix-multiplication--2---1--1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Sharding-matrix-multiplication--2---1--1.png 710w"></figure><p>We need to load 2.5 times more data into the cache for the same amount of operations. Therefore the individual cores are more likely to need to do memory swapping.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/experiment-3.png" class="kg-image" alt="" width="589" height="505"></figure><p>For unbalanced matrices we see the same behavior as in our <code>da.find()</code> experiment above. For quadratic matrices we see, that up to 8 shards there’s only a small increase in runtime and the shards behave well. I can’t judge if the runtime increases beyond 8 shards for quadratic matrices due to having only 8 high-performance CPUs and 8 low-performance CPUs, or in having the decreased part of the cache that every shard gets.</p><p>Oh, I almost forgot to mention: This experiment also shows us the bad behavior doesn’t come from the small overhead that our DocumentArray produces. Lucky us!</p><p>I also ran experiment 1B with AnnLite to see how sharding behaves with a proper implementation of HNSW (a very common vector search algorithm). </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/annlite?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/annlite: ⚡ A fast embedded library for approximate nearest neighbor search</div><div class="kg-bookmark-description">⚡ A fast embedded library for approximate nearest neighbor search - GitHub - jina-ai/annlite: ⚡ A fast embedded library for approximate nearest neighbor search</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/400352346/d5e5de62-d7af-424c-b059-141e69ef3835" alt=""></div></a></figure><p>The outcome: sharding had no impact on the runtime. Tracing showed that the actual computation was blazingly fast (under 3ms). Furthermore, tracing showed that the actual computations really ran in parallel and didn’t affect each other’s runtimes.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">We've found that using sharding on multiprocessor systems to take advantage of the multiprocessor architecture may not work as well as expected. We suspect the cause is shared low-level resources.</div></div><h2 id="conclusion">Conclusion</h2><p>Luckily for us, sharding works just fine in a real world scenario. In a future post we’ll look at sharding across different machines. Given the traces above (and a lot of other traces I looked upon during the process) it should work just fine.</p><p>But multiprocessing memory- <strong>and</strong> CPU-intensive work on one machine is tricky. What I find really concerning: <strong>A lot of computations are run on the cloud, where we have no control over the hardware.</strong></p><p>Coming back to our cake search engine: Let’s say Katie’s company is starting to grow and wants to run the service on the cloud, via multiple virtual machines. There’s no guarantee that these are independent physical machines - they could all be running on the same box with the same L1 cache, and thus ruin Katie’s performance. That would really leave a bad taste in her mouth.</p><p align="center"><img loading="lazy" src="https://media.tenor.com/krqwU2K9hq8AAAAC/elliegato-pound-cake.gif" class="kg-image" alt="" width="200"></p><p>Perhaps worse: When using Kubernetes we often explicitly have multiple Pods on the same machine. Even when the neighbors are not noisy in the sense of over-utilizing CPU/memory resources, they can have a workload that does bad things to low-level cache or another non-obvious resource and slow neighbors down.</p><hr><p>Do you like the post, or think my low-level cache analysis or conclusion is wrong? 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\ No newline at end of file
diff --git a/news/jina-3-10-0-release-note/index.html b/news/jina-3-10-0-release-note/index.html
index b0c1923284e..be6f8321bce 100644
--- a/news/jina-3-10-0-release-note/index.html
+++ b/news/jina-3-10-0-release-note/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.10.0 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.10.0 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-10-0-release-note"><meta property="og:title" content="Jina 3.10.0 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/Blue-Pink-Gradient-Fashion-Banner--30---15-in---3-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-10-0-release-note"><meta property="twitter:title" content="Jina 3.10.0 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/Blue-Pink-Gradient-Fashion-Banner--30---15-in---3-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.10.0 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.10.0 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-10-0-release-note"><meta property="og:title" content="Jina 3.10.0 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/Blue-Pink-Gradient-Fashion-Banner--30---15-in---3-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-10-0-release-note"><meta property="twitter:title" content="Jina 3.10.0 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/Blue-Pink-Gradient-Fashion-Banner--30---15-in---3-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><script src="https://jina-ai-gmbh.ghost.io/public/cards.min.js" async=""></script><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.10.0 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 29, 2022 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps</div><div class="kg-bookmark-description">🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps - GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cl...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/6d66c5cb-b3e8-4bc2-b2ee-b01b9d90933d" alt=""></div></a></figure><p><em>Release time: 2022-09-29 18:51</em></p><p>This release contains 10 new features, 9 bug fixes and 12 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="enable-jina-ping-as-readiness-probe-on-local-and-kubernetes-5200">Enable <code>jina ping</code> as readiness probe on local and Kubernetes (<a href="https://github.com/jina-ai/jina/pull/5200?ref=jina-ai-gmbh.ghost.io">#5200</a>)</h3><p>This feature lets you <strong>check the readiness of an entire Flow or its individual components</strong>:</p><pre><code class="hljs language-bash">jina ping flow grpc://localhost:12345 
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.10.0 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 29, 2022 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps</div><div class="kg-bookmark-description">🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps - GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cl...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/6d66c5cb-b3e8-4bc2-b2ee-b01b9d90933d" alt=""></div></a></figure><p><em>Release time: 2022-09-29 18:51</em></p><p>This release contains 10 new features, 9 bug fixes and 12 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="enable-jina-ping-as-readiness-probe-on-local-and-kubernetes-5200">Enable <code>jina ping</code> as readiness probe on local and Kubernetes (<a href="https://github.com/jina-ai/jina/pull/5200?ref=jina-ai-gmbh.ghost.io">#5200</a>)</h3><p>This feature lets you <strong>check the readiness of an entire Flow or its individual components</strong>:</p><pre><code class="hljs language-bash">jina ping flow grpc://localhost:12345 
 jina ping executor localhost:12346 
 jina ping gateway grpc://localhost:12345</code></pre><p><strong>Successful output:</strong></p><pre><code class="hljs language-perl">INFO   JINA@28600 readiness check succeeded <span class="hljs-number">1</span> <span class="hljs-keyword">times</span>!!!</code></pre><p><strong>Unsuccessful output:</strong></p><p>This command exits with code 1 when the readiness check is not successful.<br>Therefore, it is a good choice to use as a readiness probe for Executor and Gateway when deployed in <strong>Kubernetes</strong>.</p><h3 id="add-argument-to-specify-exceptions-that-will-exit-the-runtime-5165">Add argument to specify exceptions that will exit the runtime (<a href="https://github.com/jina-ai/jina/pull/5165?ref=jina-ai-gmbh.ghost.io">#5165</a>)</h3><p>You can <strong>specify which Exceptions should trigger termination of an affected Executor</strong>:</p><pre><code class="hljs language-csharp">Flow().<span class="hljs-keyword">add</span>(uses=MyExecutor, exit_on_exceptions: [<span class="hljs-string">'Exception'</span>,  <span class="hljs-string">'RuntimeException'</span>])</code></pre><p>This <strong>ensures an Executor is not stuck in an unusable but technically alive state</strong>, and that the Executor can be restarted. This is especially useful when Executor restarts are automated through Kubernetes.</p><h3 id="retry-mechanism-for-clientpost-5176">Retry mechanism for <code>client.post</code> (<a href="https://github.com/jina-ai/jina/pull/5176?ref=jina-ai-gmbh.ghost.io">#5176</a>)</h3><p><code>client.post()</code> accepts <code>max_attempts</code>, <code>initial_backoff</code>, <code>max_backoff</code> and <code>backoff_multiplier</code> parameters to control the capacity to retry requests, when a transient connectivity error occurs, using an <strong>exponential backoff strategy</strong>:</p><pre><code class="hljs language-csharp">client.post( <span class="hljs-keyword">on</span>=<span class="hljs-string">'/'</span>, inputs=docs, max_attempts=<span class="hljs-number">5</span>, initial_backoff=<span class="hljs-number">0.1</span>, max_backoff=<span class="hljs-number">0.5</span>, backoff_multiplier=<span class="hljs-number">1.5</span>)</code></pre><h3 id="add-monitoring-of-requests-size-everywhere-5111">Add monitoring of requests size everywhere (<a href="https://github.com/jina-ai/jina/pull/5111?ref=jina-ai-gmbh.ghost.io">#5111</a>)</h3><p>The size of requests (<code>jina_request_size_bytes</code>) is now monitored everywhere: On every Executor, every Gateway, and every sharding Head.</p><p>Consequently, this new metric can now be accessed via Prometheus and Grafana.</p><h3 id="json-logging-for-jcloud-5201">JSON logging for JCloud (<a href="https://github.com/jina-ai/jina/pull/5201?ref=jina-ai-gmbh.ghost.io">#5201</a>)</h3><p>It is now possible to create logs in JSON format, instead of the standard line-by-line text output.</p><p><strong>Sample output:</strong></p><pre><code class="hljs language-json"><span class="hljs-punctuation">{</span><span class="hljs-attr">"created"</span><span class="hljs-punctuation">:</span> <span class="hljs-number">1663930387.5850368</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"filename"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"data_request_handler.py"</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"funcName"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"_load_executor"</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"levelname"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"DEBUG"</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"lineno"</span><span class="hljs-punctuation">:</span> <span class="hljs-number">98</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"module"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"data_request_handler"</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"msg"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"&lt;jina.serve.executors.BaseExecutor object at 0x7fc1951f78d0&gt; is successfully loaded!"</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"name"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"WorkerRuntime"</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"pathname"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"/home/foo/jina/serve/runtimes/request_handlers/data_request_handler.py"</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"process"</span><span class="hljs-punctuation">:</span> <span class="hljs-number">13386</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"processName"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"Pod"</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"thread"</span><span class="hljs-punctuation">:</span> <span class="hljs-number">140469860276032</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"threadName"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"MainThread"</span><span class="hljs-punctuation">}</span></code></pre><p>To enable this, set the environment variable <code>'JINA_LOG_CONFIG</code> to <code>'json'</code>.</p><h3 id="support-list-like-syntax-to-specify-visible-cuda-devices-5187">Support list-like syntax to specify visible cuda devices (<a href="https://github.com/jina-ai/jina/pull/5187?ref=jina-ai-gmbh.ghost.io">#5187</a>)</h3><p>You can now <strong>use device id's to specify visible CUDA devices</strong> that should be used in the round-robin GPU assignment:</p><pre><code class="hljs language-ini"><span class="hljs-attr">CUDA_VISIBLE_DEVICES</span>=RR1,<span class="hljs-number">3</span></code></pre><p>This will assign CUDA devices 1 and 3 to the different Executor replicas in a round-robin fashion.</p><h3 id="make-jina-hub-push-non-blocking-5129">Make <code>jina hub push</code> non-blocking (<a href="https://github.com/jina-ai/jina/pull/5129?ref=jina-ai-gmbh.ghost.io">#5129</a>)</h3><p><code>jina hub push</code> is now a <strong>non-blocking operation</strong>, meaning that the user does not have to wait for the entire push to be completed on the server side.</p><p>While the push is being processed in the background, its status can be checked with the following command:</p><pre><code class="hljs language-css">jina hub status <span class="hljs-selector-attr">[&lt;path_to_executor_folder&gt;]</span> <span class="hljs-selector-attr">[--id TASK_ID]</span> <span class="hljs-selector-attr">[--verbose]</span> <span class="hljs-selector-attr">[--replay]</span>
 </code></pre><h3 id="warning-messages-in-jina-hub-push-5156">Warning messages in <code>jina hub push</code> (<a href="https://github.com/jina-ai/jina/pull/5156?ref=jina-ai-gmbh.ghost.io">#5156</a>)</h3><p><code>jina hub push</code> can now display helpful warning messages, such as deprecation warnings:<br></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://user-images.githubusercontent.com/15995496/189309105-5255d5a9-4fa0-4af1-bc6a-bd531664f8a8.png" class="kg-image" alt="Screen Shot 2022-09-09 at 16 32 58"></figure><h3 id="add-duration-info-in-events-5157">Add duration info in events (<a href="https://github.com/jina-ai/jina/pull/5157?ref=jina-ai-gmbh.ghost.io">#5157</a>)</h3><p>Telemetry data now also includes the duration of every event that is reported.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-compatibility-with-protobuf-python-backend-5222">Fix compatibility with Protobuf Python backend (<a href="https://github.com/jina-ai/jina/pull/5222?ref=jina-ai-gmbh.ghost.io">#5222</a>)</h3><p>This bug caused an exception when Python was used as a backend for Protobuf, rather than cpp or udp.</p><p>With this fix, Python can also be used as a backend for Protobuf.</p><h3 id="move-significant-params-to-sequential-5205">Move significant params to sequential (<a href="https://github.com/jina-ai/jina/pull/5205?ref=jina-ai-gmbh.ghost.io">#5205</a>)</h3><p>This bug (occasionally) caused <code>docker.errors.NullResource: Resource ID was not provided</code> when pulling from Jina Hub. This was due to a faulty local caching implementation, which is now fixed.</p><h3 id="fix-missing-secret-when-logged-in-user-withforce-update-5180">Fix missing secret when logged-in user &nbsp;with --force-update (<a href="https://github.com/jina-ai/jina/pull/5180?ref=jina-ai-gmbh.ghost.io">#5180</a>)</h3><p>This bug caused a failure for logged in users when force pushing to Jina Hub: Their secret would not be passed. This is now fixed and force push works as expected.</p><h3 id="use-default-grpc-parameters-for-grpc-connection-pool-connection-5211">Use default gRPC parameters for gRPC connection pool connection (<a href="https://github.com/jina-ai/jina/pull/5211?ref=jina-ai-gmbh.ghost.io">#5211</a>)</h3><p>We brought our gRPC client in line with the <a href="https://github.com/grpc/grpc/blob/master/doc/keepalive.md?ref=jina-ai-gmbh.ghost.io">recommended configuration</a>. </p><h3 id="bump-docarray-version-for-new-column-syntax-5171">Bump DocArray version for new column syntax (<a href="https://github.com/jina-ai/jina/pull/5171?ref=jina-ai-gmbh.ghost.io">#5171</a>)</h3><p>Some changes to the column syntax in DocArray required a version bump.</p><h3 id="increase-minimum-protobuf-version-5166">Increase minimum Protobuf version (<a href="https://github.com/jina-ai/jina/pull/5166?ref=jina-ai-gmbh.ghost.io">#5166</a>)</h3><p>Some changes in the Protobuf library required a version bump.</p><h3 id="remove-leftover-prints-5199">Remove leftover prints (<a href="https://github.com/jina-ai/jina/pull/5199?ref=jina-ai-gmbh.ghost.io">#5199</a>)</h3><p>Some unwanted print statements had sneaked their way into our codebase, and we kicked them right back out!</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Change setenv into environ (<a href="https://github.com/jina-ai/jina/pull/5223?ref=jina-ai-gmbh.ghost.io">#5223</a>)</li><li>Mention prefetch (<a href="https://github.com/jina-ai/jina/pull/5220?ref=jina-ai-gmbh.ghost.io">#5220</a>)</li><li>Fix install instructions docker (<a href="https://github.com/jina-ai/jina/pull/5213?ref=jina-ai-gmbh.ghost.io">#5213</a>)</li><li>Fix grammar, wording, punctuation (<a href="https://github.com/jina-ai/jina/pull/5209?ref=jina-ai-gmbh.ghost.io">#5209</a>)</li><li>Fix grammar, punctuation (<a href="https://github.com/jina-ai/jina/pull/5208?ref=jina-ai-gmbh.ghost.io">#5208</a>)</li><li>Clarify exec endpoint usage in http (<a href="https://github.com/jina-ai/jina/pull/5202?ref=jina-ai-gmbh.ghost.io">#5202</a>)</li><li>Document grpc client limitation (<a href="https://github.com/jina-ai/jina/pull/5193?ref=jina-ai-gmbh.ghost.io">#5193</a>)</li><li>Update faq and lifetime (<a href="https://github.com/jina-ai/jina/pull/5191?ref=jina-ai-gmbh.ghost.io">#5191</a>)</li><li>Improve warning about config file in custom docker (<a href="https://github.com/jina-ai/jina/pull/5190?ref=jina-ai-gmbh.ghost.io">#5190</a>)</li><li>Clarify <strong>return</strong> behavior in parameters (<a href="https://github.com/jina-ai/jina/pull/5179?ref=jina-ai-gmbh.ghost.io">#5179</a>)</li><li>Add section for exit_on_exceptions argument (<a href="https://github.com/jina-ai/jina/pull/5172?ref=jina-ai-gmbh.ghost.io">#5172</a>)</li><li>Labels in flow yaml (<a href="https://github.com/jina-ai/jina/pull/5164?ref=jina-ai-gmbh.ghost.io">#5164</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Girish Chandrashekar (<a href="https://github.com/girishc13?ref=jina-ai-gmbh.ghost.io">@girishc13</a>)</li><li>Andrei Ungureanu (<a href="https://github.com/Andrei997?ref=jina-ai-gmbh.ghost.io">@Andrei997</a>)</li><li>Michael Günther (<a href="https://github.com/guenthermi?ref=jina-ai-gmbh.ghost.io">@guenthermi</a>)</li><li>Deepankar Mahapatro (<a href="https://github.com/deepankarm?ref=jina-ai-gmbh.ghost.io">@deepankarm</a>)</li><li>Han Xiao (<a href="https://github.com/hanxiao?ref=jina-ai-gmbh.ghost.io">@hanxiao</a>)</li><li>zhangkai (<a href="https://github.com/floralatin?ref=jina-ai-gmbh.ghost.io">@floralatin</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>Yanlong Wang (<a href="https://github.com/nomagick?ref=jina-ai-gmbh.ghost.io">@nomagick</a>)</li><li>Nikolas Pitsillos (<a href="https://github.com/npitsillos?ref=jina-ai-gmbh.ghost.io">@npitsillos</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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 Release 💫 Patch v3.10.1 · jina-ai/jinaRelease Note (3.10.1) Release time: 2022-10-06 15:05:48 This release contains 1 new feature, 1 refactor, 3 bug fixes and 7 documentation improvements.🆕 Feat"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/5.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-10-1-update"><meta property="twitter:title" content="Jina 3.10.1 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.
 
-Release 💫 Patch v3.10.1 · jina-ai/jinaRelease Note (3.10.1) Release time: 2022-10-06 15:05:48 This release contains 1 new feature, 1 refactor, 3 bug fixes and 7 documentation improvements.🆕 Feat"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/5.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="0b97aeb9-76d5-47be-bd3b-a9e019bbd5cd" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="0b97aeb9-76d5-47be-bd3b-a9e019bbd5cd" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.
 
 Release 💫 Patch v3.10.1 · jina-ai/jinaRelease Note (3.10.1) Release time: 2022-10-06 15:05:48 This release contains 1 new feature, 1 refactor, 3 bug fixes and 7 documentation improvements.🆕 Feat</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 06, 2022 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.10.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.10.1 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.10.1) Release time: 2022-10-06 15:05:48 This release contains 1 new feature, 1 refactor, 3 bug fixes and 7 documentation improvements.🆕 FeaturesDistributed replicas across diffe...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/a169e6011fdfd996f8d4d8315bc29a8308e7278fc78e00c1e64bcfb39051146c/jina-ai/jina/releases/tag/v3.10.1" alt=""></div></a><figcaption>Full release note with links to pull requests</figcaption></figure><h2 id="release-note-3101">Release Note (<code>3.10.1</code>)</h2>
 <p><em>Release time: 2022-10-06 15:05:48</em></p>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.11.2 Hotfix</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 22, 2022 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.11.2?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.11.2 · jina-ai/jina</div><div class="kg-bookmark-description">Release noteThis release contains 1 hot fix.🐞 Bug FixUnpin jina-hubble-sdkTo avoid conflicting dependency versions with docarray, unpin the jina-hubble-sdk version dependency🤟 ContributorsJoa...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/e0c033f614dc756675e9791f48fcee03cae8b4248626f28411e7b1d095c0c05a/jina-ai/jina/releases/tag/v3.11.2" alt=""></div></a></figure><h2 id="hotfix">Hotfix</h2><p>This release contains 1 hot fix. </p><p>Previously, we had a dependency problem between <code>jina</code> and <code>docarray</code>: Users couldn't install the latest version of both of them at the same time. Jina required <code>hubble-sdk== 0.22.2</code> while DocArray required <code>&gt;=0.24</code>. </p><p>This hot fix unpins the <code>jina-hubble-sdk</code> dependency inside Jina and solves this issue.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-11-2-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.11.2 Hotfix</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 22, 2022 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.11.2?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.11.2 · jina-ai/jina</div><div class="kg-bookmark-description">Release noteThis release contains 1 hot fix.🐞 Bug FixUnpin jina-hubble-sdkTo avoid conflicting dependency versions with docarray, unpin the jina-hubble-sdk version dependency🤟 ContributorsJoa...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/e0c033f614dc756675e9791f48fcee03cae8b4248626f28411e7b1d095c0c05a/jina-ai/jina/releases/tag/v3.11.2" alt=""></div></a></figure><h2 id="hotfix">Hotfix</h2><p>This release contains 1 hot fix. </p><p>Previously, we had a dependency problem between <code>jina</code> and <code>docarray</code>: Users couldn't install the latest version of both of them at the same time. Jina required <code>hubble-sdk== 0.22.2</code> while DocArray required <code>&gt;=0.24</code>. </p><p>This hot fix unpins the <code>jina-hubble-sdk</code> dependency inside Jina and solves this issue.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-11-2-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.11 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.11 Update"><meta name="description" content="Announcing OpenTelemetry tracing and metrics"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-11"><meta property="og:title" content="Jina 3.11 Update"><meta property="og:description" content="Announcing OpenTelemetry tracing and metrics"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--2--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-11"><meta property="twitter:title" content="Jina 3.11 Update"><meta property="twitter:description" content="Announcing OpenTelemetry tracing and metrics"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--2--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.11 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Announcing OpenTelemetry tracing and metrics</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 24, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.11.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.11.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.11.0) Release time: 2022-10-24 14:42:35 This release contains 6 new features, 1 bug fix and 10 documentation improvements.🆕 FeaturesAdd OpenTelemetry tracing and metrics with ba...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/24833c2d2c6e1c39fbd00efe0807374775be7516ded28fce3a1f54a170ef3eb2/jina-ai/jina/releases/tag/v3.11.0" alt=""></div></a></figure><h1 id="release-note-3110">Release Note (<code>3.11.0</code>)</h1><p>This release contains 6 new features, 1 bug fix and 10 documentation improvements.</p><h1 id="%F0%9F%86%95-features">🆕 Features</h1><h3 id="add-opentelemetry-tracing-and-metrics-with-basic-configuration-5175">Add OpenTelemetry tracing and metrics with basic configuration (<a href="https://github.com/jina-ai/jina/pull/5175?ref=jina-ai-gmbh.ghost.io">#5175</a>)</h3><p>Jina now supports <a href="https://opentelemetry.io/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">OpenTelemetry</a> Tracing and Metrics libraries for increased observability and instrumentation of Jina <code>Runtimes</code>. Read the docs (<a href="https://github.com/jina-ai/jina/pull/5291?ref=jina-ai-gmbh.ghost.io">#5291</a>) for details. We also provide a migration guide for a smooth transition from the previously-supported Prometheus-only based metrics instrumentation.</p><p>You can integrate <a href="https://www.jaegertracing.io/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Jaeger</a> or other distributed tracing tools to collect and visualize request-level and application level service operation attributes. This helps you analyze request-response lifecycle, application behavior and performance.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests, DocumentArray
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="57120fc5-ab06-40b7-a18e-8ecd5ed5c977" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="57120fc5-ab06-40b7-a18e-8ecd5ed5c977" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.11 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Announcing OpenTelemetry tracing and metrics</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 24, 2022 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.11.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.11.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.11.0) Release time: 2022-10-24 14:42:35 This release contains 6 new features, 1 bug fix and 10 documentation improvements.🆕 FeaturesAdd OpenTelemetry tracing and metrics with ba...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/24833c2d2c6e1c39fbd00efe0807374775be7516ded28fce3a1f54a170ef3eb2/jina-ai/jina/releases/tag/v3.11.0" alt=""></div></a></figure><h1 id="release-note-3110">Release Note (<code>3.11.0</code>)</h1><p>This release contains 6 new features, 1 bug fix and 10 documentation improvements.</p><h1 id="%F0%9F%86%95-features">🆕 Features</h1><h3 id="add-opentelemetry-tracing-and-metrics-with-basic-configuration-5175">Add OpenTelemetry tracing and metrics with basic configuration (<a href="https://github.com/jina-ai/jina/pull/5175?ref=jina-ai-gmbh.ghost.io">#5175</a>)</h3><p>Jina now supports <a href="https://opentelemetry.io/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">OpenTelemetry</a> Tracing and Metrics libraries for increased observability and instrumentation of Jina <code>Runtimes</code>. Read the docs (<a href="https://github.com/jina-ai/jina/pull/5291?ref=jina-ai-gmbh.ghost.io">#5291</a>) for details. We also provide a migration guide for a smooth transition from the previously-supported Prometheus-only based metrics instrumentation.</p><p>You can integrate <a href="https://www.jaegertracing.io/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Jaeger</a> or other distributed tracing tools to collect and visualize request-level and application level service operation attributes. This helps you analyze request-response lifecycle, application behavior and performance.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests, DocumentArray
 
 <span class="hljs-keyword">class</span> <span class="hljs-title class_">MyExec</span>(<span class="hljs-title class_ inherited__">Executor</span>):
 <span class="hljs-meta">    @requests</span>
@@ -29,4 +29,4 @@
                 docs.embedding = model_inference(docs.tensors)</code></pre><h3 id="record-existing-prometheus-metrics-into-opentelemetry-histograms-5275">Record existing Prometheus metrics into OpenTelemetry histograms (<a href="https://github.com/jina-ai/jina/pull/5275?ref=jina-ai-gmbh.ghost.io">#5275</a>)</h3><p>Prometheus-only based metrics are also available as OpenTelemetry supported metrics. You can switch to OpenTelemetry metrics with little effort.</p><h3 id="add-default-tracing-interceptors-to-head-grpc-connection-pool-5271">Add default tracing interceptors to head gRPC connection pool (<a href="https://github.com/jina-ai/jina/pull/5271?ref=jina-ai-gmbh.ghost.io">#5271</a>)</h3><p>Head <code>Runtime</code> supports default traces when forwarding requests to the shard replica.</p><h3 id="add-grpc-metadata-to-executors-and-gateway-deployments-5221">Add gRPC metadata to Executors and Gateway deployments (<a href="https://github.com/jina-ai/jina/pull/5221?ref=jina-ai-gmbh.ghost.io">#5221</a>)</h3><p>You can now provide HTTP header access tokens as client metadata for accessing external and authentication protected services.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Client
 
 client = Client(host=<span class="hljs-string">'api.clip.jina.ai'</span>, port=<span class="hljs-number">2096</span>, tls=<span class="hljs-literal">True</span>, protocol=<span class="hljs-string">'grpc'</span>)
-client.post(on=<span class="hljs-string">'/encode'</span>, metadata=((<span class="hljs-string">'authorization'</span>, <span class="hljs-string">'&lt;your access token&gt;'</span>),))</code></pre><h3 id="show-local-location-of-executors-in-hub-5282">Show local location of Executors in Hub (<a href="https://github.com/jina-ai/jina/pull/5282?ref=jina-ai-gmbh.ghost.io">#5282</a>)</h3><p>Use the <code>list</code> sub command to list the locations of local <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Hub Executors</a>:</p><pre><code class="hljs language-undefined">jina hub list</code></pre><figure class="kg-card kg-image-card"><a href="https://asciinema.org/a/z81wi9gwVm7gYjfl5ocBD1RH3?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://camo.githubusercontent.com/6b3e7a7a131d901517a4e33e103575439df8c7063294bc1df2ad4ebd2020165e/68747470733a2f2f61736369696e656d612e6f72672f612f7a38317769396777566d3767596a666c356f634244315248332e737667" class="kg-image" alt="asciicast"></a></figure><h3 id="dump-to-statefulset-in-k8s-when-volumes-are-passed-to-executor-5265">Dump to Statefulset in K8s when volumes are passed to Executor (<a href="https://github.com/jina-ai/jina/pull/5265?ref=jina-ai-gmbh.ghost.io">#5265</a>)</h3><p>Jina will generate a Kubernetes <code>Statefulset</code> manifest for Executors if you provide <code>volumes</code> to the <code>Flow.to_kubernets_yaml()</code> method. Executors can persist data on mounted volumes and correctly scale horizontally if required.</p><h1 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h1><h3 id="invalid-input-raise-exception-5141">Invalid input raise exception (<a href="https://github.com/jina-ai/jina/pull/5141?ref=jina-ai-gmbh.ghost.io">#5141</a>)</h3><ul><li>The<code>client.post()</code> method was not raising an exception if any of the underlying async requests raised an exception.</li><li>The new version correctly raises the exception raised by any async request. The user can now correctly catch any exceptions and act upon the exception.</li></ul><h1 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h1><ul><li>Docs for OpenTelemetry instrumentation (<a href="https://github.com/jina-ai/jina/pull/5291?ref=jina-ai-gmbh.ghost.io">#5291</a>)</li><li>Add Jina AI Cloud restructure Jcloud and Hub (<a href="https://github.com/jina-ai/jina/pull/5298?ref=jina-ai-gmbh.ghost.io">#5298</a>)</li><li>Standardize naming conventions (<a href="https://github.com/jina-ai/jina/pull/5285?ref=jina-ai-gmbh.ghost.io">#5285</a>)</li><li>Fix metrics naming (<a href="https://github.com/jina-ai/jina/pull/5277?ref=jina-ai-gmbh.ghost.io">#5277</a>)</li><li>Misc clean up (<a href="https://github.com/jina-ai/jina/pull/5255?ref=jina-ai-gmbh.ghost.io">#5255</a>, <a href="https://github.com/jina-ai/jina/pull/5287?ref=jina-ai-gmbh.ghost.io">#5287</a>, <a href="https://github.com/jina-ai/jina/pull/5284?ref=jina-ai-gmbh.ghost.io">#5284</a>, <a href="https://github.com/jina-ai/jina/pull/5290?ref=jina-ai-gmbh.ghost.io">#5290</a>, <a href="https://github.com/jina-ai/jina/pull/5289?ref=jina-ai-gmbh.ghost.io">#5289</a>, <a href="https://github.com/jina-ai/jina/pull/5288?ref=jina-ai-gmbh.ghost.io">#5288</a>)</li></ul><h1 id="%F0%9F%A4%98-contributors">🤘 Contributors</h1><p>We would like to thank all contributors to this release:</p><ul><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Anthony Le (<a href="https://github.com/AnthonyLe93?ref=jina-ai-gmbh.ghost.io">@AnthonyLe93</a>)</li><li>felix-wang (<a href="https://github.com/numb3r3?ref=jina-ai-gmbh.ghost.io">@numb3r3</a>)</li><li>Girish Chandrashekar (<a href="https://github.com/girishc13?ref=jina-ai-gmbh.ghost.io">@girishc13</a>)</li><li>zhangkai (<a href="https://github.com/floralatin?ref=jina-ai-gmbh.ghost.io">@floralatin</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Han Xiao (<a href="https://github.com/hanxiao?ref=jina-ai-gmbh.ghost.io">@hanxiao</a>)</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>Andrei Ungureanu (<a href="https://github.com/Andrei997?ref=jina-ai-gmbh.ghost.io">@Andrei997</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-11%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+client.post(on=<span class="hljs-string">'/encode'</span>, metadata=((<span class="hljs-string">'authorization'</span>, <span class="hljs-string">'&lt;your access token&gt;'</span>),))</code></pre><h3 id="show-local-location-of-executors-in-hub-5282">Show local location of Executors in Hub (<a href="https://github.com/jina-ai/jina/pull/5282?ref=jina-ai-gmbh.ghost.io">#5282</a>)</h3><p>Use the <code>list</code> sub command to list the locations of local <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Hub Executors</a>:</p><pre><code class="hljs language-undefined">jina hub list</code></pre><figure class="kg-card kg-image-card"><a href="https://asciinema.org/a/z81wi9gwVm7gYjfl5ocBD1RH3?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://camo.githubusercontent.com/6b3e7a7a131d901517a4e33e103575439df8c7063294bc1df2ad4ebd2020165e/68747470733a2f2f61736369696e656d612e6f72672f612f7a38317769396777566d3767596a666c356f634244315248332e737667" class="kg-image" alt="asciicast"></a></figure><h3 id="dump-to-statefulset-in-k8s-when-volumes-are-passed-to-executor-5265">Dump to Statefulset in K8s when volumes are passed to Executor (<a href="https://github.com/jina-ai/jina/pull/5265?ref=jina-ai-gmbh.ghost.io">#5265</a>)</h3><p>Jina will generate a Kubernetes <code>Statefulset</code> manifest for Executors if you provide <code>volumes</code> to the <code>Flow.to_kubernets_yaml()</code> method. Executors can persist data on mounted volumes and correctly scale horizontally if required.</p><h1 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h1><h3 id="invalid-input-raise-exception-5141">Invalid input raise exception (<a href="https://github.com/jina-ai/jina/pull/5141?ref=jina-ai-gmbh.ghost.io">#5141</a>)</h3><ul><li>The<code>client.post()</code> method was not raising an exception if any of the underlying async requests raised an exception.</li><li>The new version correctly raises the exception raised by any async request. The user can now correctly catch any exceptions and act upon the exception.</li></ul><h1 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h1><ul><li>Docs for OpenTelemetry instrumentation (<a href="https://github.com/jina-ai/jina/pull/5291?ref=jina-ai-gmbh.ghost.io">#5291</a>)</li><li>Add Jina AI Cloud restructure Jcloud and Hub (<a href="https://github.com/jina-ai/jina/pull/5298?ref=jina-ai-gmbh.ghost.io">#5298</a>)</li><li>Standardize naming conventions (<a href="https://github.com/jina-ai/jina/pull/5285?ref=jina-ai-gmbh.ghost.io">#5285</a>)</li><li>Fix metrics naming (<a href="https://github.com/jina-ai/jina/pull/5277?ref=jina-ai-gmbh.ghost.io">#5277</a>)</li><li>Misc clean up (<a href="https://github.com/jina-ai/jina/pull/5255?ref=jina-ai-gmbh.ghost.io">#5255</a>, <a href="https://github.com/jina-ai/jina/pull/5287?ref=jina-ai-gmbh.ghost.io">#5287</a>, <a href="https://github.com/jina-ai/jina/pull/5284?ref=jina-ai-gmbh.ghost.io">#5284</a>, <a href="https://github.com/jina-ai/jina/pull/5290?ref=jina-ai-gmbh.ghost.io">#5290</a>, <a href="https://github.com/jina-ai/jina/pull/5289?ref=jina-ai-gmbh.ghost.io">#5289</a>, <a href="https://github.com/jina-ai/jina/pull/5288?ref=jina-ai-gmbh.ghost.io">#5288</a>)</li></ul><h1 id="%F0%9F%A4%98-contributors">🤘 Contributors</h1><p>We would like to thank all contributors to this release:</p><ul><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Anthony Le (<a href="https://github.com/AnthonyLe93?ref=jina-ai-gmbh.ghost.io">@AnthonyLe93</a>)</li><li>felix-wang (<a href="https://github.com/numb3r3?ref=jina-ai-gmbh.ghost.io">@numb3r3</a>)</li><li>Girish Chandrashekar (<a href="https://github.com/girishc13?ref=jina-ai-gmbh.ghost.io">@girishc13</a>)</li><li>zhangkai (<a href="https://github.com/floralatin?ref=jina-ai-gmbh.ghost.io">@floralatin</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Han Xiao (<a href="https://github.com/hanxiao?ref=jina-ai-gmbh.ghost.io">@hanxiao</a>)</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>Andrei Ungureanu (<a href="https://github.com/Andrei997?ref=jina-ai-gmbh.ghost.io">@Andrei997</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-11%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.12 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.12 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-12-update"><meta property="og:title" content="Jina 3.12 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--8-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-12-update"><meta property="twitter:title" content="Jina 3.12 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--8-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.12 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.12 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-12-update"><meta property="og:title" content="Jina 3.12 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--8-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-12-update"><meta property="twitter:title" content="Jina 3.12 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--8-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.12 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 25, 2022 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.12.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.12.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.12.0) Release time: 2022-11-25 12:28:29 This release contains 8 new features, 16 bug fixes and 15 documentation improvements.🆕 FeaturesSupport multiple protocols at the same tim...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/e3f6a325d239e59620eb880629c5f104832601ca6a47716d62701ffd9c4dc68c/jina-ai/jina/releases/tag/v3.12.0" alt=""></div></a></figure><h2 id="release-note-3120">Release Note (<code>3.12.0</code>)</h2><p>This release contains 8 new features, 16 bug fixes and 15 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="support-multiple-protocols-at-the-same-time-in-flow-gateways-5435-and-5378">Support multiple protocols at the same time in Flow Gateways (<a href="https://github.com/jina-ai/jina/pull/5435?ref=jina-ai-gmbh.ghost.io">#5435</a> and <a href="https://github.com/jina-ai/jina/pull/5378?ref=jina-ai-gmbh.ghost.io">#5378</a>)</h3><p>Prior to this release, a Flow only exposed one server in its Gateway with one of the following protocols: HTTP, gRPC or WebSockets.</p><p>Now, you can specify multiple protocols and for each one, a separate server is started. Each server is bound to its own port.</p><p>For instance, you can do:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Flow
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="4015f0d0-b035-44b5-b12a-71db75af4ab1" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="4015f0d0-b035-44b5-b12a-71db75af4ab1" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.12 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 25, 2022 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.12.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.12.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.12.0) Release time: 2022-11-25 12:28:29 This release contains 8 new features, 16 bug fixes and 15 documentation improvements.🆕 FeaturesSupport multiple protocols at the same tim...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/e3f6a325d239e59620eb880629c5f104832601ca6a47716d62701ffd9c4dc68c/jina-ai/jina/releases/tag/v3.12.0" alt=""></div></a></figure><h2 id="release-note-3120">Release Note (<code>3.12.0</code>)</h2><p>This release contains 8 new features, 16 bug fixes and 15 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="support-multiple-protocols-at-the-same-time-in-flow-gateways-5435-and-5378">Support multiple protocols at the same time in Flow Gateways (<a href="https://github.com/jina-ai/jina/pull/5435?ref=jina-ai-gmbh.ghost.io">#5435</a> and <a href="https://github.com/jina-ai/jina/pull/5378?ref=jina-ai-gmbh.ghost.io">#5378</a>)</h3><p>Prior to this release, a Flow only exposed one server in its Gateway with one of the following protocols: HTTP, gRPC or WebSockets.</p><p>Now, you can specify multiple protocols and for each one, a separate server is started. Each server is bound to its own port.</p><p>For instance, you can do:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Flow
 
 flow = Flow(port=[<span class="hljs-number">12345</span>, <span class="hljs-number">12345</span>, <span class="hljs-number">12345</span>], protocol=[<span class="hljs-string">'http'</span>, <span class="hljs-string">'grpc'</span>, <span class="hljs-string">'websocket'</span>])
 
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="5d25cc66-6985-4570-a191-80e96e3c347c" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="5d25cc66-6985-4570-a191-80e96e3c347c" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.13.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 21, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.13.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.13.1 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.13.1) Release time: 2022-12-21 12:58:15 This release contains 3 bug fixes and 1 documentation improvement.🐞 Bug FixesSupport Gateway with multiple protocols for Kubernetes expor...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/63e727effc858b60d8c2a9d9a3fb8011e36d096cf6cfc91b4d328ad789ac3b09/jina-ai/jina/releases/tag/v3.13.1" alt=""></div></a></figure><h2 id="release-note-3131">Release Note (<code>3.13.1</code>)</h2><p>This release contains 3 bug fixes and 1 documentation improvement.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="support-gateway-with-multiple-protocols-for-kubernetes-export-5532">Support Gateway with multiple protocols for Kubernetes export (<a href="https://github.com/jina-ai/jina/pull/5532?ref=jina-ai-gmbh.ghost.io">#5532</a>)</h3><p>You can now export Flows with multiple protocols to Kubernetes. Previously this would cause an error.</p><pre><code class="language-python hljs">flow = Flow().config_gateway(protocol=[<span class="hljs-string">'http'</span>, <span class="hljs-string">'grpc'</span>])
-flow.to_kubernetes_yaml(<span class="hljs-string">'k8s_flow_folder'</span>)</code></pre><h3 id="fix-python-311-support-5529">Fix Python 3.11 support (<a href="https://github.com/jina-ai/jina/pull/5529?ref=jina-ai-gmbh.ghost.io">#5529</a>)</h3><p>It was previously impossible to install Jina with Python 3.11 due to a <code>grpcio</code> dependency problem. <code>grpcio</code> added support for Python 3.11 only with version 1.49.0, <a href="https://github.com/grpc/grpc/issues/30303?ref=jina-ai-gmbh.ghost.io">causing potential problems when used by Jina and other projects</a>.</p><p>In this release <code>grpcio&gt;=1.49.0</code> is installed alongside Jina when using Python 3.11. However, be aware of potential problems related to <a href="https://github.com/grpc/grpc/issues/30843?ref=jina-ai-gmbh.ghost.io">grpc hanging</a>.</p><h3 id="unary-rpc-from-client-respects-resultsinorder-5513">Unary RPC from Client respects <code>results_in_order</code> (<a href="https://github.com/jina-ai/jina/pull/5513?ref=jina-ai-gmbh.ghost.io">#5513</a>)</h3><p>In prior releases, calling the <code>post</code> method of a client with <code>grpc</code> and using <code>stream=False</code> did not respect the <code>results_in_order</code> parameter and results were always returned in order:</p><pre><code class="language-python hljs"><span class="hljs-comment"># this returns results in wrong order</span>
-c = Client(protocol=<span class="hljs-string">'grpc'</span>)
-c.post(on=<span class="hljs-string">'/'</span>, inputs=DocumentArray.empty(<span class="hljs-number">10000</span>), stream=<span class="hljs-literal">False</span>, results_in_order=<span class="hljs-literal">False</span>)  </code></pre><p>Also this implied that using the Client with <code>asyncio=True</code> and <code>stream=False</code> in the post call would return results in the order that they were returned by the Flow, rather than respecting the input order:</p><pre><code class="language-python hljs"><span class="hljs-comment"># this returns results wrong in order</span>
-c = Client(protocol=<span class="hljs-string">'grpc'</span>, asyncio=<span class="hljs-literal">True</span>)
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 21, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.13.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.13.1 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.13.1) Release time: 2022-12-21 12:58:15 This release contains 3 bug fixes and 1 documentation improvement.🐞 Bug FixesSupport Gateway with multiple protocols for Kubernetes expor...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/63e727effc858b60d8c2a9d9a3fb8011e36d096cf6cfc91b4d328ad789ac3b09/jina-ai/jina/releases/tag/v3.13.1" alt=""></div></a></figure><h2 id="release-note-3131">Release Note (<code>3.13.1</code>)</h2><p>This release contains 3 bug fixes and 1 documentation improvement.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="support-gateway-with-multiple-protocols-for-kubernetes-export-5532">Support Gateway with multiple protocols for Kubernetes export (<a href="https://github.com/jina-ai/jina/pull/5532?ref=jina-ai-gmbh.ghost.io">#5532</a>)</h3><p>You can now export Flows with multiple protocols to Kubernetes. Previously this would cause an error.</p><pre><code class="language-python">flow = Flow().config_gateway(protocol=['http', 'grpc'])
+flow.to_kubernetes_yaml('k8s_flow_folder')</code></pre><h3 id="fix-python-311-support-5529">Fix Python 3.11 support (<a href="https://github.com/jina-ai/jina/pull/5529?ref=jina-ai-gmbh.ghost.io">#5529</a>)</h3><p>It was previously impossible to install Jina with Python 3.11 due to a <code>grpcio</code> dependency problem. <code>grpcio</code> added support for Python 3.11 only with version 1.49.0, <a href="https://github.com/grpc/grpc/issues/30303?ref=jina-ai-gmbh.ghost.io">causing potential problems when used by Jina and other projects</a>.</p><p>In this release <code>grpcio&gt;=1.49.0</code> is installed alongside Jina when using Python 3.11. However, be aware of potential problems related to <a href="https://github.com/grpc/grpc/issues/30843?ref=jina-ai-gmbh.ghost.io">grpc hanging</a>.</p><h3 id="unary-rpc-from-client-respects-resultsinorder-5513">Unary RPC from Client respects <code>results_in_order</code> (<a href="https://github.com/jina-ai/jina/pull/5513?ref=jina-ai-gmbh.ghost.io">#5513</a>)</h3><p>In prior releases, calling the <code>post</code> method of a client with <code>grpc</code> and using <code>stream=False</code> did not respect the <code>results_in_order</code> parameter and results were always returned in order:</p><pre><code class="language-python"># this returns results in wrong order
+c = Client(protocol='grpc')
+c.post(on='/', inputs=DocumentArray.empty(10000), stream=False, results_in_order=False)  </code></pre><p>Also this implied that using the Client with <code>asyncio=True</code> and <code>stream=False</code> in the post call would return results in the order that they were returned by the Flow, rather than respecting the input order:</p><pre><code class="language-python"># this returns results wrong in order
+c = Client(protocol='grpc', asyncio=True)
 
-<span class="hljs-keyword">async</span> <span class="hljs-keyword">for</span> resp <span class="hljs-keyword">in</span> c.post(on=<span class="hljs-string">'/'</span>, inputs=DocumentArray.empty(<span class="hljs-number">10000</span>), stream=<span class="hljs-literal">False</span>, results_in_order=<span class="hljs-literal">False</span>)
-    <span class="hljs-built_in">print</span>(resp)</code></pre><p>This release fixes the ordering bug.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Document inheritance of arguments from Flow API to Executors and Gateway (<a href="https://github.com/jina-ai/jina/pull/5535?ref=jina-ai-gmbh.ghost.io">#5535</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Jackmin801 (<a href="https://github.com/Jackmin801?ref=jina-ai-gmbh.ghost.io">@Jackmin801</a>)</li><li>Anne Yang (<a href="https://github.com/AnneYang720?ref=jina-ai-gmbh.ghost.io">@AnneYang720</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-13-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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\ No newline at end of file
+async for resp in c.post(on='/', inputs=DocumentArray.empty(10000), stream=False, results_in_order=False)
+    print(resp)</code></pre><p>This release fixes the ordering bug.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Document inheritance of arguments from Flow API to Executors and Gateway (<a href="https://github.com/jina-ai/jina/pull/5535?ref=jina-ai-gmbh.ghost.io">#5535</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Jackmin801 (<a href="https://github.com/Jackmin801?ref=jina-ai-gmbh.ghost.io">@Jackmin801</a>)</li><li>Anne Yang (<a href="https://github.com/AnneYang720?ref=jina-ai-gmbh.ghost.io">@AnneYang720</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-13-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.13.2 Hotfix</title><meta charset="utf-8"><meta name="title" content="Jina 3.13.2 Hotfix"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-13-2-hotfix"><meta property="og:title" content="Jina 3.13.2 Hotfix"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--13-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-13-2-hotfix"><meta property="twitter:title" content="Jina 3.13.2 Hotfix"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--13-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.13.2 Hotfix</title><meta charset="utf-8"><meta name="title" content="Jina 3.13.2 Hotfix"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-13-2-hotfix"><meta property="og:title" content="Jina 3.13.2 Hotfix"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--13-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-13-2-hotfix"><meta property="twitter:title" content="Jina 3.13.2 Hotfix"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--13-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 30, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.13.2?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.13.2 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.13.2)This release contains 1 bug fix.🐞 Bug Fixesfix: respect timeout_ready when generating startup probe (#5560)As Kubernetes Startup Probes were added to all deployments in rel...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/8921ad480be9dbcbcccfe3befbadf5093de46769a0b5fee8fc2c6e8e2d093b5f/jina-ai/jina/releases/tag/v3.13.2" alt=""></div></a></figure><h2 id="release-note-3132">Release Note (<code>3.13.2</code>)</h2><p>This release contains 1 bug fix.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="respect-timeoutready-when-generating-startup-probe-5560">Respect <code>timeout_ready</code> when generating startup probe (<a href="https://github.com/jina-ai/jina/pull/5560?ref=jina-ai-gmbh.ghost.io">#5560</a>)</h3><p>As Kubernetes Startup Probes were added to all deployments in <a href="https://github.com/jina-ai/jina/releases/tag/v3.13.0?ref=jina-ai-gmbh.ghost.io">release v3.13.0</a>, we added default values for all probe configurations. However, if those default configurations were not enough to wait for an Executor that takes time to load and become ready, the Executor deployment would become subject to the configured restart policy. Therefore, Executors that are slow to load would keep restarting forever.</p><p>In this patch, this behavior is fixed by making sure that Startup Probe configurations respect the <code>timeout_ready</code> argument of Executors.<br>Startup Probes are configured like so:</p><ul><li><code>periodSeconds</code> always set to 5 seconds</li><li><code>timeoutSeconds</code> always set to 10 seconds</li><li><code>failureThreshold</code> varies according to <code>timeout_ready</code>. The formula used is <code>failureThreshold = timeout_ready / 5</code> and in all cases, it will be at least 3. If <code>timeout_ready</code> is <code>-1</code> (in Jina it means waiting forever for the Executor to<br>become ready), since waiting forever is not supported in Kubernetes, the value for <code>failureThreshold</code> will be 120 attempts.</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-13-2-hotfix%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.13.2 Hotfix</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 30, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.13.2?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.13.2 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.13.2)This release contains 1 bug fix.🐞 Bug Fixesfix: respect timeout_ready when generating startup probe (#5560)As Kubernetes Startup Probes were added to all deployments in rel...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/8921ad480be9dbcbcccfe3befbadf5093de46769a0b5fee8fc2c6e8e2d093b5f/jina-ai/jina/releases/tag/v3.13.2" alt=""></div></a></figure><h2 id="release-note-3132">Release Note (<code>3.13.2</code>)</h2><p>This release contains 1 bug fix.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="respect-timeoutready-when-generating-startup-probe-5560">Respect <code>timeout_ready</code> when generating startup probe (<a href="https://github.com/jina-ai/jina/pull/5560?ref=jina-ai-gmbh.ghost.io">#5560</a>)</h3><p>As Kubernetes Startup Probes were added to all deployments in <a href="https://github.com/jina-ai/jina/releases/tag/v3.13.0?ref=jina-ai-gmbh.ghost.io">release v3.13.0</a>, we added default values for all probe configurations. However, if those default configurations were not enough to wait for an Executor that takes time to load and become ready, the Executor deployment would become subject to the configured restart policy. Therefore, Executors that are slow to load would keep restarting forever.</p><p>In this patch, this behavior is fixed by making sure that Startup Probe configurations respect the <code>timeout_ready</code> argument of Executors.<br>Startup Probes are configured like so:</p><ul><li><code>periodSeconds</code> always set to 5 seconds</li><li><code>timeoutSeconds</code> always set to 10 seconds</li><li><code>failureThreshold</code> varies according to <code>timeout_ready</code>. The formula used is <code>failureThreshold = timeout_ready / 5</code> and in all cases, it will be at least 3. If <code>timeout_ready</code> is <code>-1</code> (in Jina it means waiting forever for the Executor to<br>become ready), since waiting forever is not supported in Kubernetes, the value for <code>failureThreshold</code> will be 120 attempts.</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-13-2-hotfix%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.13 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.13 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-13-update"><meta property="og:title" content="Jina 3.13 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--11-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-13-update"><meta property="twitter:title" content="Jina 3.13 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--11-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.13 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 15, 2022 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.13.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.13.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.13.0) Release time: 2022-12-15 15:33:43 This release contains 14 new features, 9 bug fixes and 7 documentation improvements.This release introduces major features like Custom Gat...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/5acc2296864995d8590fdededf0dde12fcd44945cc8d79bd957c65c003c50849/jina-ai/jina/releases/tag/v3.13.0" alt=""></div></a></figure><h2 id="release-note-3130"><strong>Release Note (<code>3.13.0</code>)</strong></h2><p>This release contains 14 new features, 9 bug fixes and 7 documentation improvements.</p><p>This release introduces major features like Custom Gateways, Dynamic Batching for Executors, development support with auto-reloading, support for the new namespaced Executor scheme <code>jinaai</code>, improvements for our gRPC transport layer, and more.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="custom-gateways-5153-5189-5342-5457-5465-5472-and-5477">Custom Gateways (<a href="https://github.com/jina-ai/jina/pull/5153?ref=jina-ai-gmbh.ghost.io">#5153</a>, <a href="https://github.com/jina-ai/jina/pull/5189?ref=jina-ai-gmbh.ghost.io">#5189</a>, <a href="https://github.com/jina-ai/jina/pull/5342?ref=jina-ai-gmbh.ghost.io">#5342</a>, <a href="https://github.com/jina-ai/jina/pull/5457?ref=jina-ai-gmbh.ghost.io">#5457</a>, <a href="https://github.com/jina-ai/jina/pull/5465?ref=jina-ai-gmbh.ghost.io">#5465</a>, <a href="https://github.com/jina-ai/jina/pull/5472?ref=jina-ai-gmbh.ghost.io">#5472</a> and <a href="https://github.com/jina-ai/jina/pull/5477?ref=jina-ai-gmbh.ghost.io">#5477</a>)</h3><p>Jina Gateways are now customizable in the sense that you can implement them in much the same way as an Executor. With this feature, Jina gives power to the user to implement any server, protocol or interface at the Gateway level. There's no more need to build an extra service that uses the Flow.</p><p>For instance, you can define a Jina Gateway that communicates with the rest of Flow Executors like so:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina.serve.runtimes.gateway.http.fastapi <span class="hljs-keyword">import</span> FastAPIBaseGateway
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.13 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 15, 2022 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.13.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.13.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.13.0) Release time: 2022-12-15 15:33:43 This release contains 14 new features, 9 bug fixes and 7 documentation improvements.This release introduces major features like Custom Gat...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/5acc2296864995d8590fdededf0dde12fcd44945cc8d79bd957c65c003c50849/jina-ai/jina/releases/tag/v3.13.0" alt=""></div></a></figure><h2 id="release-note-3130"><strong>Release Note (<code>3.13.0</code>)</strong></h2><p>This release contains 14 new features, 9 bug fixes and 7 documentation improvements.</p><p>This release introduces major features like Custom Gateways, Dynamic Batching for Executors, development support with auto-reloading, support for the new namespaced Executor scheme <code>jinaai</code>, improvements for our gRPC transport layer, and more.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="custom-gateways-5153-5189-5342-5457-5465-5472-and-5477">Custom Gateways (<a href="https://github.com/jina-ai/jina/pull/5153?ref=jina-ai-gmbh.ghost.io">#5153</a>, <a href="https://github.com/jina-ai/jina/pull/5189?ref=jina-ai-gmbh.ghost.io">#5189</a>, <a href="https://github.com/jina-ai/jina/pull/5342?ref=jina-ai-gmbh.ghost.io">#5342</a>, <a href="https://github.com/jina-ai/jina/pull/5457?ref=jina-ai-gmbh.ghost.io">#5457</a>, <a href="https://github.com/jina-ai/jina/pull/5465?ref=jina-ai-gmbh.ghost.io">#5465</a>, <a href="https://github.com/jina-ai/jina/pull/5472?ref=jina-ai-gmbh.ghost.io">#5472</a> and <a href="https://github.com/jina-ai/jina/pull/5477?ref=jina-ai-gmbh.ghost.io">#5477</a>)</h3><p>Jina Gateways are now customizable in the sense that you can implement them in much the same way as an Executor. With this feature, Jina gives power to the user to implement any server, protocol or interface at the Gateway level. There's no more need to build an extra service that uses the Flow.</p><p>For instance, you can define a Jina Gateway that communicates with the rest of Flow Executors like so:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina.serve.runtimes.gateway.http.fastapi <span class="hljs-keyword">import</span> FastAPIBaseGateway
 
 <span class="hljs-keyword">class</span> <span class="hljs-title class_">MyGateway</span>(<span class="hljs-title class_ inherited__">FastAPIBaseGateway</span>):
 <span class="hljs-meta">    @property</span>
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.14.1 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.14.1 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-14-1-update"><meta property="og:title" content="Jina 3.14.1 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Jina-core--1-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-14-1-update"><meta property="twitter:title" content="Jina 3.14.1 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Jina-core--1-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.14.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 24, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</p><h2 id="release-note-3141">Release Note (<code>3.14.1</code>)</h2><p>This release contains 3 bug fixes and 3 documentation improvements.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="respect-replication-and-host-configuration-for-executor-deployments-5705">Respect replication and host configuration for Executor Deployments (<a href="https://github.com/jina-ai/jina/pull/5705?ref=jina-ai-gmbh.ghost.io">#5705</a>)</h3><p>Prior to this release, this setting wasn't fully respected when an Executor was deployed with a replication setup or specific host configuration.</p><p>It turns out that even though all replicas would be spun up, the Gateway would only know about one of them and would forward incoming requests to that replica. Additionally, all replica hostnames would be set to <code>0.0.0.0</code>, although the user may have chosen other hostname settings.</p><p>This release properly respects settings. All replicas are now configured with the specified hostname and the Jina Gateway properly load balances traffic to all replicas.</p><pre><code class="language-python">from jina import Deployment, Executor, requests, DocumentArray
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.14.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 24, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</p><h2 id="release-note-3141">Release Note (<code>3.14.1</code>)</h2><p>This release contains 3 bug fixes and 3 documentation improvements.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="respect-replication-and-host-configuration-for-executor-deployments-5705">Respect replication and host configuration for Executor Deployments (<a href="https://github.com/jina-ai/jina/pull/5705?ref=jina-ai-gmbh.ghost.io">#5705</a>)</h3><p>Prior to this release, this setting wasn't fully respected when an Executor was deployed with a replication setup or specific host configuration.</p><p>It turns out that even though all replicas would be spun up, the Gateway would only know about one of them and would forward incoming requests to that replica. Additionally, all replica hostnames would be set to <code>0.0.0.0</code>, although the user may have chosen other hostname settings.</p><p>This release properly respects settings. All replicas are now configured with the specified hostname and the Jina Gateway properly load balances traffic to all replicas.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment, Executor, requests, DocumentArray
 
-class MyExecutor(Executor):
-    @requests
-    def foo(self, **kwargs):
-        print(self.runtime_args.name)
+<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyExecutor</span>(<span class="hljs-title class_ inherited__">Executor</span>):
+<span class="hljs-meta">    @requests</span>
+    <span class="hljs-keyword">def</span> <span class="hljs-title function_">foo</span>(<span class="hljs-params">self, **kwargs</span>):
+        <span class="hljs-built_in">print</span>(self.runtime_args.name)
 
-with Deployment(uses=MyExecutor, replicas=3, host='127.0.0.1') as dep:
-    dep.post(on='/', inputs=DocumentArray.empty(5), request_size=1)</code></pre><pre><code>─────────────────────── 🎉 Deployment is ready to serve! ───────────────────────
+<span class="hljs-keyword">with</span> Deployment(uses=MyExecutor, replicas=<span class="hljs-number">3</span>, host=<span class="hljs-string">'127.0.0.1'</span>) <span class="hljs-keyword">as</span> dep:
+    dep.post(on=<span class="hljs-string">'/'</span>, inputs=DocumentArray.empty(<span class="hljs-number">5</span>), request_size=<span class="hljs-number">1</span>)</code></pre><pre><code class="hljs language-bash">─────────────────────── 🎉 Deployment is ready to serve! ───────────────────────
 ╭─────────────────────── 🔗 Endpoint ───────────────────────╮
 │  ⛓   Protocol                                       GRPC │
 │  🏠     Local                            127.0.0.1:64503  │
@@ -31,4 +31,4 @@
 executor/rep-1
 executor/rep-2
 executor/rep-2
-</code></pre><h3 id="hide-known-warnings-in-google-colab-5706">Hide known warnings in Google Colab (<a href="https://github.com/jina-ai/jina/pull/5706?ref=jina-ai-gmbh.ghost.io">#5706</a>)</h3><p>When using Jina in Google Colab, you may have received warnings about coroutines not being awaited. These warnings were mainly about Jina detecting a Jupyter environment and didn't really represent wrong behaviour. Thus, we have suppressed these warnings in this release.</p><h3 id="docarray-v2-support-with-protobuf-v4-5702">DocArray v2 support with protobuf v4 (<a href="https://github.com/jina-ai/jina/pull/5702?ref=jina-ai-gmbh.ghost.io">#5702</a>)</h3><p>Prior to this release, Jina did not support DocArray v2 if <code>protobuf</code> v4 was installed. This release fixes the support and DocArray v2 should work fine for both versions of <code>protobuf</code> (<code>v3</code> and <code>v4</code>). We have also increased test coverage so support is tested for both versions.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Make Flow and Deployment difference clearer (<a href="https://github.com/jina-ai/jina/pull/5709?ref=jina-ai-gmbh.ghost.io">#5709</a>)</li><li>Add warning about cleaning up Flows (<a href="https://github.com/jina-ai/jina/pull/5708?ref=jina-ai-gmbh.ghost.io">#5708</a>)</li><li>Add JCloud Executor level labels (<a href="https://github.com/jina-ai/jina/pull/5704?ref=jina-ai-gmbh.ghost.io">#5704</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Subba Reddy Veeramreddy (<a href="https://github.com/subbuv26?ref=jina-ai-gmbh.ghost.io">@subbuv26</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-14-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
+</code></pre><h3 id="hide-known-warnings-in-google-colab-5706">Hide known warnings in Google Colab (<a href="https://github.com/jina-ai/jina/pull/5706?ref=jina-ai-gmbh.ghost.io">#5706</a>)</h3><p>When using Jina in Google Colab, you may have received warnings about coroutines not being awaited. These warnings were mainly about Jina detecting a Jupyter environment and didn't really represent wrong behaviour. Thus, we have suppressed these warnings in this release.</p><h3 id="docarray-v2-support-with-protobuf-v4-5702">DocArray v2 support with protobuf v4 (<a href="https://github.com/jina-ai/jina/pull/5702?ref=jina-ai-gmbh.ghost.io">#5702</a>)</h3><p>Prior to this release, Jina did not support DocArray v2 if <code>protobuf</code> v4 was installed. This release fixes the support and DocArray v2 should work fine for both versions of <code>protobuf</code> (<code>v3</code> and <code>v4</code>). We have also increased test coverage so support is tested for both versions.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Make Flow and Deployment difference clearer (<a href="https://github.com/jina-ai/jina/pull/5709?ref=jina-ai-gmbh.ghost.io">#5709</a>)</li><li>Add warning about cleaning up Flows (<a href="https://github.com/jina-ai/jina/pull/5708?ref=jina-ai-gmbh.ghost.io">#5708</a>)</li><li>Add JCloud Executor level labels (<a href="https://github.com/jina-ai/jina/pull/5704?ref=jina-ai-gmbh.ghost.io">#5704</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Subba Reddy Veeramreddy (<a href="https://github.com/subbuv26?ref=jina-ai-gmbh.ghost.io">@subbuv26</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-14-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.14 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.14 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-14-update"><meta property="og:title" content="Jina 3.14 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Jina-core.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-14-update"><meta property="twitter:title" content="Jina 3.14 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Jina-core.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.14 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 21, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.14.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.14.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.14.0) Release time: 2023-02-20 09:15:47 This release contains 11 new features, 6 refactors, 12 bug fixes and 10 documentation improvements.🆕 FeaturesReshaping Executors as stand…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/c1d303bf9528ea7aca6af4ea414da9deda853ed83ae7602fc8ed870be8c25fde/jina-ai/jina/releases/tag/v3.14.0" alt=""></div></a></figure><h2 id="release-note-3140"><strong>Release Note (<code>3.14.0</code>)</strong></h2><p>This release contains 11 new features, 6 refactors, 12 bug fixes and 10 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="reshaping-executors-as-standalone-services-with-the-deployment-layer-5563-5590-5628-5672-and-5673">Reshaping Executors as standalone services with the Deployment layer (<a href="https://github.com/jina-ai/jina/pull/5563?ref=jina-ai-gmbh.ghost.io">#5563</a>, <a href="https://github.com/jina-ai/jina/pull/5590?ref=jina-ai-gmbh.ghost.io">#5590</a>, <a href="https://github.com/jina-ai/jina/pull/5628?ref=jina-ai-gmbh.ghost.io">#5628</a>, <a href="https://github.com/jina-ai/jina/pull/5672?ref=jina-ai-gmbh.ghost.io">#5672</a> and <a href="https://github.com/jina-ai/jina/pull/5673?ref=jina-ai-gmbh.ghost.io">#5673</a>)</h3><p>In this release we aim to unlock more use cases, mainly building highly performant and scalable services. With its built-in layers of abstraction, Jina lets users build scalable, containerized, cloud-native components which we call Executors. Executors have always been services, but they were mostly used in Flows to form pipelines.</p><p>Now you can deploy an Executor on its own, without needing a Flow. Whether it's for model inference, prediction, embedding, generation or search, an Executor can wrap your business logic, and you get a gRPC microservice with Jina's cloud-native features (shards, replicas, dynamic batching, etc.)</p><p>To do this we offer the Deployment layer to deploy an Executor. Just like a Flow groups and orchestrates many Executors, a Deployment orchestrates just one Executor.</p><p>A Deployment can be used with both the Python API and YAML. For instance, after you define an Executor, use the Deployment class to serve it:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 21, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.14.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.14.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.14.0) Release time: 2023-02-20 09:15:47 This release contains 11 new features, 6 refactors, 12 bug fixes and 10 documentation improvements.🆕 FeaturesReshaping Executors as stand…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/c1d303bf9528ea7aca6af4ea414da9deda853ed83ae7602fc8ed870be8c25fde/jina-ai/jina/releases/tag/v3.14.0" alt=""></div></a></figure><h2 id="release-note-3140"><strong>Release Note (<code>3.14.0</code>)</strong></h2><p>This release contains 11 new features, 6 refactors, 12 bug fixes and 10 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="reshaping-executors-as-standalone-services-with-the-deployment-layer-5563-5590-5628-5672-and-5673">Reshaping Executors as standalone services with the Deployment layer (<a href="https://github.com/jina-ai/jina/pull/5563?ref=jina-ai-gmbh.ghost.io">#5563</a>, <a href="https://github.com/jina-ai/jina/pull/5590?ref=jina-ai-gmbh.ghost.io">#5590</a>, <a href="https://github.com/jina-ai/jina/pull/5628?ref=jina-ai-gmbh.ghost.io">#5628</a>, <a href="https://github.com/jina-ai/jina/pull/5672?ref=jina-ai-gmbh.ghost.io">#5672</a> and <a href="https://github.com/jina-ai/jina/pull/5673?ref=jina-ai-gmbh.ghost.io">#5673</a>)</h3><p>In this release we aim to unlock more use cases, mainly building highly performant and scalable services. With its built-in layers of abstraction, Jina lets users build scalable, containerized, cloud-native components which we call Executors. Executors have always been services, but they were mostly used in Flows to form pipelines.</p><p>Now you can deploy an Executor on its own, without needing a Flow. Whether it's for model inference, prediction, embedding, generation or search, an Executor can wrap your business logic, and you get a gRPC microservice with Jina's cloud-native features (shards, replicas, dynamic batching, etc.)</p><p>To do this we offer the Deployment layer to deploy an Executor. Just like a Flow groups and orchestrates many Executors, a Deployment orchestrates just one Executor.</p><p>A Deployment can be used with both the Python API and YAML. For instance, after you define an Executor, use the Deployment class to serve it:</p><pre><code class="language-python">from jina import Deployment
 
-<span class="hljs-keyword">with</span> Deployment(uses=MyExecutor, port=<span class="hljs-number">12345</span>, replicas=<span class="hljs-number">2</span>) <span class="hljs-keyword">as</span> dep:
-    dep.block() <span class="hljs-comment"># serve forever</span></code></pre><pre><code class="hljs language-vbnet">─────────────────────── 🎉 Deployment <span class="hljs-built_in">is</span> ready <span class="hljs-keyword">to</span> serve! ───────────────────────
+with Deployment(uses=MyExecutor, port=12345, replicas=2) as dep:
+    dep.block() # serve forever</code></pre><pre><code>─────────────────────── 🎉 Deployment is ready to serve! ───────────────────────
 ╭────────────── 🔗 Endpoint ────────────────╮
 │  ⛓     Protocol                    GRPC  │
-│  🏠       Local           <span class="hljs-number">0.0</span>.<span class="hljs-number">0.0</span>:<span class="hljs-number">12345</span>   │
-│  🔒     <span class="hljs-keyword">Private</span>     <span class="hljs-number">192.168</span>.<span class="hljs-number">3.147</span>:<span class="hljs-number">12345</span>   │
-│  🌍      <span class="hljs-keyword">Public</span>    <span class="hljs-number">87.191</span>.<span class="hljs-number">159.105</span>:<span class="hljs-number">12345</span>   │
+│  🏠       Local           0.0.0.0:12345   │
+│  🔒     Private     192.168.3.147:12345   │
+│  🌍      Public    87.191.159.105:12345   │
 ╰───────────────────────────────────────────╯
-</code></pre><p>Or implement a Deployment in YAML and run it from the CLI:</p><pre><code class="language-yaml hljs"><span class="hljs-attr">jtype:</span> <span class="hljs-string">Deployment</span>
-<span class="hljs-attr">with:</span>
-  <span class="hljs-attr">port:</span> <span class="hljs-number">12345</span>
-  <span class="hljs-attr">replicas:</span> <span class="hljs-number">2</span>
-  <span class="hljs-attr">uses:</span> <span class="hljs-string">MyExecutor</span>
-  <span class="hljs-attr">py_modules:</span>
-    <span class="hljs-bullet">-</span> <span class="hljs-string">my_executor.py</span></code></pre><pre><code class="language-shell hljs">jina deployment --uses deployment.yml</code></pre><p>The Deployment class offers the same interface as a Flow, so it can be used as a client too:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment
+</code></pre><p>Or implement a Deployment in YAML and run it from the CLI:</p><pre><code class="language-yaml">jtype: Deployment
+with:
+  port: 12345
+  replicas: 2
+  uses: MyExecutor
+  py_modules:
+    - my_executor.py</code></pre><pre><code class="language-shell">jina deployment --uses deployment.yml</code></pre><p>The Deployment class offers the same interface as a Flow, so it can be used as a client too:</p><pre><code class="language-python">from jina import Deployment
 
-<span class="hljs-keyword">with</span> Deployment(uses=MyExecutor, port=<span class="hljs-number">12345</span>, replicas=<span class="hljs-number">2</span>) <span class="hljs-keyword">as</span> dep:
-    docs = dep.post(on=<span class="hljs-string">'/foo'</span>, inputs=DocumentArray.empty(<span class="hljs-number">1</span>)
-    <span class="hljs-built_in">print</span>(docs.texts)</code></pre><p>Furthermore, you can use the Deployment to create Kubernetes and Docker Compose YAML configurations of a single Executor deployment. So, to export to Kubernetes with the Python API:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment
+with Deployment(uses=MyExecutor, port=12345, replicas=2) as dep:
+    docs = dep.post(on='/foo', inputs=DocumentArray.empty(1)
+    print(docs.texts)</code></pre><p>Furthermore, you can use the Deployment to create Kubernetes and Docker Compose YAML configurations of a single Executor deployment. So, to export to Kubernetes with the Python API:</p><pre><code class="language-python">from jina import Deployment
 
-dep = Deployment(uses=<span class="hljs-string">'jinaai+docker://jina-ai/DummyHubExecutor'</span>, port_expose=<span class="hljs-number">8080</span>, replicas=<span class="hljs-number">3</span>)
-dep.to_kubernetes_yaml(<span class="hljs-string">'/tmp/config_out_folder'</span>, k8s_namespace=<span class="hljs-string">'my-namespace'</span>)</code></pre><p>And exporting to Kubernetes with the CLI is just as straightforward:</p><pre><code class="language-shell hljs">jina export kubernetes deployment.yml output_path</code></pre><p>As is exporting to Docker Compose with the Python API:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment
+dep = Deployment(uses='jinaai+docker://jina-ai/DummyHubExecutor', port_expose=8080, replicas=3)
+dep.to_kubernetes_yaml('/tmp/config_out_folder', k8s_namespace='my-namespace')</code></pre><p>And exporting to Kubernetes with the CLI is just as straightforward:</p><pre><code class="language-shell">jina export kubernetes deployment.yml output_path</code></pre><p>As is exporting to Docker Compose with the Python API:</p><pre><code class="language-python">from jina import Deployment
 
-dep = Deployment(uses=<span class="hljs-string">'jinaai+docker://jina-ai/DummyHubExecutor'</span>, port_expose=<span class="hljs-number">8080</span>, replicas=<span class="hljs-number">3</span>)
+dep = Deployment(uses='jinaai+docker://jina-ai/DummyHubExecutor', port_expose=8080, replicas=3)
 
 dep.to_docker_compose_yaml(
-    output_path=<span class="hljs-string">'/tmp/docker-compose.yml'</span>,
-)</code></pre><p>And of course, you can also export to Docker Compose with the CLI:</p><pre><code class="language-shell hljs">jina export docker-compose deployment.yml output_path</code></pre><p>Read more about <a href="https://docs.jina.ai/concepts/executor/serve/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">serving standalone Executors in our documentation</a>.</p><h3 id="beta-support-docarray-v2-5603">(Beta) Support DocArray v2 (<a href="https://github.com/jina-ai/jina/pull/5603?ref=jina-ai-gmbh.ghost.io">#5603</a>)</h3><p>As <a href="https://github.com/docarray/docarray/issues/780?ref=jina-ai-gmbh.ghost.io">the DocArray refactoring</a> is shaping up nicely, we've decided to integrate initial support. Although this support is still experimental, we believe DocArray v2 offers nice abstractions to clearly define the data of your services, especially with the single Executor deployment that we introduce in this release.</p><p>With this new experimental feature, you can define your input and output schemas with DocArray v2 and use type hints to define schemas of each endpoint:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDocument, DocumentArray
-<span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> AnyTensor, ImageUrl
+    output_path='/tmp/docker-compose.yml',
+)</code></pre><p>And of course, you can also export to Docker Compose with the CLI:</p><pre><code class="language-shell">jina export docker-compose deployment.yml output_path</code></pre><p>Read more about <a href="https://docs.jina.ai/concepts/executor/serve/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">serving standalone Executors in our documentation</a>.</p><h3 id="beta-support-docarray-v2-5603">(Beta) Support DocArray v2 (<a href="https://github.com/jina-ai/jina/pull/5603?ref=jina-ai-gmbh.ghost.io">#5603</a>)</h3><p>As <a href="https://github.com/docarray/docarray/issues/780?ref=jina-ai-gmbh.ghost.io">the DocArray refactoring</a> is shaping up nicely, we've decided to integrate initial support. Although this support is still experimental, we believe DocArray v2 offers nice abstractions to clearly define the data of your services, especially with the single Executor deployment that we introduce in this release.</p><p>With this new experimental feature, you can define your input and output schemas with DocArray v2 and use type hints to define schemas of each endpoint:</p><pre><code class="language-python">from jina import Executor, requests
+from docarray import BaseDocument, DocumentArray
+from docarray.typing import AnyTensor, ImageUrl
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">InputDoc</span>(<span class="hljs-title class_ inherited__">BaseDocument</span>):
+class InputDoc(BaseDocument):
     img: ImageUrl
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">OutputDoc</span>(<span class="hljs-title class_ inherited__">BaseDocument</span>):
+class OutputDoc(BaseDocument):
     embedding: AnyTensor
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyExec</span>(<span class="hljs-title class_ inherited__">Executor</span>):
-<span class="hljs-meta">    @requests(<span class="hljs-params">on=<span class="hljs-string">'/bar'</span></span>)</span>
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">bar</span>(<span class="hljs-params">
+class MyExec(Executor):
+    @requests(on='/bar')
+    def bar(
         self, docs: DocumentArray[InputDoc], **kwargs
-    </span>) -&gt; DocumentArray[OutputDoc]:
+    ) -&gt; DocumentArray[OutputDoc]:
         return_docs = DocumentArray[OutputDoc](
-            [OutputDoc(embedding=embed(doc.img)) <span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span> docs]
+            [OutputDoc(embedding=embed(doc.img)) for doc in docs]
         )
-        <span class="hljs-keyword">return</span> return_docs</code></pre><p>Read more about the integration in <a href="https://docs.jina.ai/concepts/executor/docarray-v2/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">the DocArray v2 section of our docs</a>.</p><h3 id="communicate-with-individual-executors-in-custom-gateways-5558">Communicate with individual Executors in Custom Gateways (<a href="https://github.com/jina-ai/jina/pull/5558?ref=jina-ai-gmbh.ghost.io">#5558</a>)</h3><p>Custom Gateways can now make separate calls to specific Executors without respecting the Flow's topology.</p><p>With this feature, we target a different set of use cases, where the task does not necessarily have to be defined by a DAG pipeline. Rather, you define processing order using explicit calls to Executors and implement any use case where there's a central service (Gateway) communicating with remote services (Executors).</p><p>For instance, you can implement a Gateway like so:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina.serve.runtimes.gateway.http.fastapi <span class="hljs-keyword">import</span> FastAPIBaseGateway
-<span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Document, DocumentArray, Flow, Executor, requests
-<span class="hljs-keyword">from</span> fastapi <span class="hljs-keyword">import</span> FastAPI
+        return return_docs</code></pre><p>Read more about the integration in <a href="https://docs.jina.ai/concepts/executor/docarray-v2/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">the DocArray v2 section of our docs</a>.</p><h3 id="communicate-with-individual-executors-in-custom-gateways-5558">Communicate with individual Executors in Custom Gateways (<a href="https://github.com/jina-ai/jina/pull/5558?ref=jina-ai-gmbh.ghost.io">#5558</a>)</h3><p>Custom Gateways can now make separate calls to specific Executors without respecting the Flow's topology.</p><p>With this feature, we target a different set of use cases, where the task does not necessarily have to be defined by a DAG pipeline. Rather, you define processing order using explicit calls to Executors and implement any use case where there's a central service (Gateway) communicating with remote services (Executors).</p><p>For instance, you can implement a Gateway like so:</p><pre><code class="language-python">from jina.serve.runtimes.gateway.http.fastapi import FastAPIBaseGateway
+from jina import Document, DocumentArray, Flow, Executor, requests
+from fastapi import FastAPI
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyGateway</span>(<span class="hljs-title class_ inherited__">FastAPIBaseGateway</span>):
-<span class="hljs-meta">    @property</span>
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">app</span>(<span class="hljs-params">self</span>):
+class MyGateway(FastAPIBaseGateway):
+    @property
+    def app(self):
         app = FastAPI()
 
-<span class="hljs-meta">        @app.get(<span class="hljs-params"><span class="hljs-string">"/endpoint"</span></span>)</span>
-        <span class="hljs-keyword">async</span> <span class="hljs-keyword">def</span> <span class="hljs-title function_">get</span>(<span class="hljs-params">text: <span class="hljs-built_in">str</span></span>):
-            doc1 = <span class="hljs-keyword">await</span> self.executor[<span class="hljs-string">'executor1'</span>].post(on=<span class="hljs-string">'/'</span>, inputs=DocumentArray([Document(text=text)]))
-            doc2 = <span class="hljs-keyword">await</span> self.executor[<span class="hljs-string">'executor2'</span>].post(on=<span class="hljs-string">'/'</span>, inputs=DocumentArray([Document(text=text)]))
-            <span class="hljs-keyword">return</span> {<span class="hljs-string">'result'</span>: doc1.texts + doc2.texts}
+        @app.get("/endpoint")
+        async def get(text: str):
+            doc1 = await self.executor['executor1'].post(on='/', inputs=DocumentArray([Document(text=text)]))
+            doc2 = await self.executor['executor2'].post(on='/', inputs=DocumentArray([Document(text=text)]))
+            return {'result': doc1.texts + doc2.texts}
 
-        <span class="hljs-keyword">return</span> app
+        return app
 
-<span class="hljs-comment"># Add the Gateway and Executors to a Flow</span>
+# Add the Gateway and Executors to a Flow
 flow = Flow() \
-    .config_gateway(uses=MyGateway, protocol=<span class="hljs-string">'http'</span>, port=<span class="hljs-number">12345</span>) \
-    .add(uses=FirstExec, name=<span class="hljs-string">'executor1'</span>) \
-    .add(uses=SecondExec, name=<span class="hljs-string">'executor2'</span>)</code></pre><p>Read more about <a href="https://docs.jina.ai/concepts/gateway/customization/?ref=jina-ai-gmbh.ghost.io#calling-an-individual-executor" rel="nofollow">calling individual Executors</a>.</p><h3 id="add-secrets-to-jina-on-kubernetes-5557">Add secrets to Jina on Kubernetes (<a href="https://github.com/jina-ai/jina/pull/5557?ref=jina-ai-gmbh.ghost.io">#5557</a>)</h3><p>To support building secure apps, we've added support for secrets on Kubernetes in Jina. Mainly, you can create environment variables whose sources are Kubernetes Secrets.</p><p>Add the secret using the <code>env_from_secret</code> parameter either in Python API or YAML:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Flow
+    .config_gateway(uses=MyGateway, protocol='http', port=12345) \
+    .add(uses=FirstExec, name='executor1') \
+    .add(uses=SecondExec, name='executor2')</code></pre><p>Read more about <a href="https://docs.jina.ai/concepts/gateway/customization/?ref=jina-ai-gmbh.ghost.io#calling-an-individual-executor" rel="nofollow">calling individual Executors</a>.</p><h3 id="add-secrets-to-jina-on-kubernetes-5557">Add secrets to Jina on Kubernetes (<a href="https://github.com/jina-ai/jina/pull/5557?ref=jina-ai-gmbh.ghost.io">#5557</a>)</h3><p>To support building secure apps, we've added support for secrets on Kubernetes in Jina. Mainly, you can create environment variables whose sources are Kubernetes Secrets.</p><p>Add the secret using the <code>env_from_secret</code> parameter either in Python API or YAML:</p><pre><code class="language-python">from jina import Flow
 
 f = (
     Flow().add(
-        uses=<span class="hljs-string">'jinaai+docker://jina-ai/DummyHubExecutor'</span>,
+        uses='jinaai+docker://jina-ai/DummyHubExecutor',
         env_from_secret={
-            <span class="hljs-string">'SECRET_USERNAME'</span>: {<span class="hljs-string">'name'</span>: <span class="hljs-string">'mysecret'</span>, <span class="hljs-string">'key'</span>: <span class="hljs-string">'username'</span>},
-            <span class="hljs-string">'SECRET_PASSWORD'</span>: {<span class="hljs-string">'name'</span>: <span class="hljs-string">'mysecret'</span>, <span class="hljs-string">'key'</span>: <span class="hljs-string">'password'</span>},
+            'SECRET_USERNAME': {'name': 'mysecret', 'key': 'username'},
+            'SECRET_PASSWORD': {'name': 'mysecret', 'key': 'password'},
         },
     )
 )
 
-f.to_kubernetes_yaml(<span class="hljs-string">'./k8s_flow'</span>, k8s_namespace=<span class="hljs-string">'custom-namespace'</span>)</code></pre><p><a href="https://docs.jina.ai/cloud-nativeness/kubernetes/?ref=jina-ai-gmbh.ghost.io#deploy-flow-with-custom-environment-variables-and-secrets" rel="nofollow">Read more in the docs</a>.</p><h3 id="add-gatewaystreamerstream-to-yield-response-and-executor-errors-5650">Add <code>GatewayStreamer.stream()</code> to yield response and Executor errors (<a href="https://github.com/jina-ai/jina/pull/5650?ref=jina-ai-gmbh.ghost.io">#5650</a>)</h3><p>If you're implementing a custom Gateway, you can use the <code>GatewayStreamer.stream()</code> method to catch errors raised in Executors. Catching such errors wasn't possible with the <code>GatewayStreamer.stream_docs()</code> method.</p><pre><code class="language-python hljs"><span class="hljs-keyword">async</span> <span class="hljs-keyword">for</span> docs, error <span class="hljs-keyword">in</span> self.streamer.stream(
+f.to_kubernetes_yaml('./k8s_flow', k8s_namespace='custom-namespace')</code></pre><p><a href="https://docs.jina.ai/cloud-nativeness/kubernetes/?ref=jina-ai-gmbh.ghost.io#deploy-flow-with-custom-environment-variables-and-secrets" rel="nofollow">Read more in the docs</a>.</p><h3 id="add-gatewaystreamerstream-to-yield-response-and-executor-errors-5650">Add <code>GatewayStreamer.stream()</code> to yield response and Executor errors (<a href="https://github.com/jina-ai/jina/pull/5650?ref=jina-ai-gmbh.ghost.io">#5650</a>)</h3><p>If you're implementing a custom Gateway, you can use the <code>GatewayStreamer.stream()</code> method to catch errors raised in Executors. Catching such errors wasn't possible with the <code>GatewayStreamer.stream_docs()</code> method.</p><pre><code class="language-python">async for docs, error in self.streamer.stream(
     docs=my_da,
-    exec_endpoint=<span class="hljs-string">'/'</span>,
+    exec_endpoint='/',
 ):
-    <span class="hljs-keyword">if</span> error:
-        <span class="hljs-comment"># raise error</span>
-    <span class="hljs-keyword">else</span>:
-        <span class="hljs-comment"># process results</span></code></pre><p><a href="https://docs.jina.ai/concepts/gateway/customization/?ref=jina-ai-gmbh.ghost.io#recovering-executor-errors" rel="nofollow">Read more about the feature in the documentation</a>.</p><h3 id="add-argument-suppressrootlogging-to-remove-or-preserve-root-logging-handlers-5635">Add argument <code>suppress_root_logging</code> to remove or preserve root logging handlers (<a href="https://github.com/jina-ai/jina/pull/5635?ref=jina-ai-gmbh.ghost.io">#5635</a>)</h3><p>In this release, we've added the argument <code>suppress_root_logging</code> to (you guessed it) suppress root logger messages. By default, root logs are suppressed.</p><p>Kudos to our community member <a href="https://github.com/Jake-00?ref=jina-ai-gmbh.ghost.io">@Jake-00</a> for the contribution!</p><h3 id="add-grpc-streaming-endpoint-to-worker-and-head-runtimes-5614">Add gRPC streaming endpoint to Worker and Head runtimes (<a href="https://github.com/jina-ai/jina/pull/5614?ref=jina-ai-gmbh.ghost.io">#5614</a>)</h3><p>To empower Executors we've added a gRPC streaming endpoint to both the Worker and Head runtimes. This means that an Executor or Head gRPC server exposes the same interface as a Jina gRPC Gateway. Therefore, you can use Jina's gRPC Client with each of those entities.</p><h3 id="add-prefetch-argument-to-client-post-method-5607">Add <code>prefetch</code> argument to client post method (<a href="https://github.com/jina-ai/jina/pull/5607?ref=jina-ai-gmbh.ghost.io">#5607</a>)</h3><p>A <code>prefetch</code> argument has been added to the <code>Client.post()</code> method. Previously, this argument was only available to the Gateway and it controlled how many requests a Gateway could <em>send</em> to Executors at a time.</p><p>However, it was not possible to control how many requests a Gateway (or Executor in case of a single Executor Deployment) could <em>receive</em> at a time.</p><p>Therefore, we've added the argument to the <code>Client.post()</code> to give you better control over your requests.</p><p><a href="https://docs.jina.ai/concepts/client/rate-limit/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Read more in the documentation</a>.</p><h3 id="run-warmup-on-runtimes-and-executor-5579">Run warmup on runtimes and Executor (<a href="https://github.com/jina-ai/jina/pull/5579?ref=jina-ai-gmbh.ghost.io">#5579</a>)</h3><p>On startup, all Jina entities that hold gRPC connections and stubs to other entities (Head and Gateway) now start warming up before the services become ready. This ensures lower latencies on first requests submitted to the Flow.</p><h3 id="make-grpc-client-thread-safe-5533">Make gRPC Client thread safe (<a href="https://github.com/jina-ai/jina/pull/5533?ref=jina-ai-gmbh.ghost.io">#5533</a>)</h3><p>Previously, as <a href="https://github.com/grpc/grpc/issues/25364?ref=jina-ai-gmbh.ghost.io">gRPC asyncio clients offer limited support for multi-threading</a>, using the Jina gRPC Client in multiple threads would print errors.</p><p>Therefore, in this release, we make the gRPC Client thread-safe in the sense that a thread can re-use it multiple times without another thread using it simultaneously. This means you can use the gRPC Client with multi-threading, while being sure only asyncio tasks belonging to the same thread have access to the gRPC stub at the same time.</p><h3 id="add-user-survey-5667">Add user survey (<a href="https://github.com/jina-ai/jina/pull/5667?ref=jina-ai-gmbh.ghost.io">#5667</a>)</h3><p>When running a Flow, a message now shows up in the terminal with a survey link. Feel free to fill in <a href="https://10sw1tcpld4.typeform.com/to/EGAEReM7?utm_source=doc&amp;utm_medium=ghost&amp;utm_campaign=user%20experience&amp;utm_term=feb2023&amp;utm_content=survey">our survey</a> to help us improve Jina. Your feedback is much appreciated!</p><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="use-single-gateway-streamer-for-multiprotocol-gateway-5598">Use single Gateway streamer for multiprotocol Gateway (<a href="https://github.com/jina-ai/jina/pull/5598?ref=jina-ai-gmbh.ghost.io">#5598</a>)</h3><p>When we released <a href="https://docs.jina.ai/concepts/gateway/?ref=jina-ai-gmbh.ghost.io#enable-multiple-protocols" rel="nofollow">multiprotocol Gateways</a>, the implementation relied on exposing a separate gRPC connection and stubs protocol. As this turned out to be unnecessary, this release re-uses the same connections and stubs.</p><h3 id="remove-manual-deletion-of-channel-resources-5633">Remove manual deletion of channel resources (<a href="https://github.com/jina-ai/jina/pull/5633?ref=jina-ai-gmbh.ghost.io">#5633</a>)</h3><p>This release refactors how we handle channel resources. Mainly, deletion of channel resources is no longer handled manually and is left to the garbage collector.</p><h3 id="no-need-to-run-summary-in-thread-5632">No need to run summary in thread (<a href="https://github.com/jina-ai/jina/pull/5632?ref=jina-ai-gmbh.ghost.io">#5632</a>)</h3><p>Getting and printing Flow summary information is no longer executed in a separate thread, and is now handled in the main thread.</p><h3 id="refactor-grpcconnectionpool-implementation-into-a-package-5623">Refactor <code>GRPCConnectionPool</code> implementation into a package (<a href="https://github.com/jina-ai/jina/pull/5623?ref=jina-ai-gmbh.ghost.io">#5623</a>)</h3><p>All gRPC connection pool logic has been refactored into a separate package, rather than having a <code>GRPCConnectionPool</code> class.</p><h3 id="remove-reversing-request-order-5580">Remove reversing request order (<a href="https://github.com/jina-ai/jina/pull/5580?ref=jina-ai-gmbh.ghost.io">#5580</a>)</h3><p>Reversing request order has been removed from runtime logic.</p><h3 id="simplify-getdocsfromrequest-helper-function-5567">Simplify <code>get_docs_from_request</code> helper function (<a href="https://github.com/jina-ai/jina/pull/5567?ref=jina-ai-gmbh.ghost.io">#5567</a>)</h3><p>The <code>get_docs_from_request</code> helper function in the request handler module has been simplified and no longer accepts unneeded parameters.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="relax-protobuf-version-5591">Relax protobuf version (<a href="https://github.com/jina-ai/jina/pull/5591?ref=jina-ai-gmbh.ghost.io">#5591</a>)</h3><p>To better support different environments, we've relaxed Jina's protobuf version so it no longer conflicts with Google Colab's pre-installed version (which may result in breaking some installed dependencies).</p><h3 id="fix-loading-gateway-arguments-from-yaml-5664-and-5678">Fix loading Gateway arguments from YAML (<a href="https://github.com/jina-ai/jina/pull/5664?ref=jina-ai-gmbh.ghost.io">#5664</a> and <a href="https://github.com/jina-ai/jina/pull/5678?ref=jina-ai-gmbh.ghost.io">#5678</a>)</h3><p>Prior to this release, loading Gateway configurations from YAML had a few bugs. Mainly, some parameters were not passed correctly to the Gateway runtime when configs were loaded. Also, other default runtime Gateway arguments would always override arguments from YAML configs.</p><h3 id="fix-usage-with-cudavisibledevices-5654">Fix usage with <code>cuda_visible_devices</code> (<a href="https://github.com/jina-ai/jina/pull/5654?ref=jina-ai-gmbh.ghost.io">#5654</a>)</h3><p>Prior to this release, <a href="https://docs.jina.ai/concepts/flow/scale-out/?ref=jina-ai-gmbh.ghost.io#replicate-on-multiple-gpus" rel="nofollow">using replicas on multiple GPUs</a> would fail if the <code>CUDA_VISIBLE_DEVICES</code> environment variable was passed with the <code>env</code> parameter, rather than actually being set in the environment variables.</p><h3 id="properly-use-logging-configuration-in-executor-gateway-and-client-5638">Properly use logging configuration in Executor, Gateway and Client (<a href="https://github.com/jina-ai/jina/pull/5638?ref=jina-ai-gmbh.ghost.io">#5638</a>)</h3><p>This release unifies the logging configuration in Executors, Gateways and Clients and exposes configuration parameters properly. You can now pass log configuration to your Clients and Flows and expect consistent logging behavior:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Client
-client = Client(log_config=<span class="hljs-string">'./logging.json.yml'</span>)
-
-<span class="hljs-comment"># or with a Flow object</span>
-
-<span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Flow
-f = Flow(log_config=<span class="hljs-string">'./logging.json.yml'</span>)
-<span class="hljs-keyword">with</span> f:
-    <span class="hljs-comment"># the implicit client automatically uses the log_config from the Flow for consistency</span>
-    f.post(<span class="hljs-string">'/'</span>)</code></pre><h3 id="pass-extra-arguments-to-the-gateway-runtime-in-case-of-containerized-gateways-5631">Pass extra arguments to the Gateway runtime in case of containerized Gateways (<a href="https://github.com/jina-ai/jina/pull/5631?ref=jina-ai-gmbh.ghost.io">#5631</a>)</h3><p>Prior to this release, if a <a href="https://docs.jina.ai/concepts/gateway/customization/?ref=jina-ai-gmbh.ghost.io#containerize-the-custom-gateway" rel="nofollow">containerized Custom Gateway</a> was started, Jina wouldn't pass some arguments to the container entrypoint. This could break some behaviour, for instance, the runtime not knowing which port to use for serving the Gateway. The issue is fixed in this release.</p><h3 id="clean-up-opentelemetry-resources-in-the-flow-context-manager-exit-procedure-5619">Clean up OpenTelemetry resources in the Flow context manager exit procedure (<a href="https://github.com/jina-ai/jina/pull/5619?ref=jina-ai-gmbh.ghost.io">#5619</a>)</h3><p>This release adds proper cleanup to the OpenTelemetry resources. The cleanup logic has been added to the <code>Client</code> class and is called automatically in the Flow's context manager.</p><p>If you're using the <code>Client</code> with OpenTelemetry enabled, call <code>client.teardown_instrumentation()</code> to have correct spans of the client.</p><h3 id="improve-error-messages-for-grpc-notfound-errors-5617">Improve error messages for gRPC <code>NOT_FOUND</code> errors (<a href="https://github.com/jina-ai/jina/pull/5617?ref=jina-ai-gmbh.ghost.io">#5617</a>)</h3><p>When an external Executor/Flow is behind an API Gateway (which is the case for JCloud), but is down, then DNS resolution succeeds but a "resource" (the Executor/Flow) cannot be found, resulting in a gRPC error with the <code>NOT_FOUND</code> code.</p><p>This error case wasn't properly handled before, giving output like the following:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://user-images.githubusercontent.com/44071807/214031911-11c77c7a-3b02-44f9-a319-ba41088a4334.png" class="kg-image" alt=""></figure><p>This output did not include information about which part of the Flow failed.</p><p>In this release, the affected deployment and its address are displayed:</p><pre><code class="hljs language-perl">ERROR  gateway/rep-<span class="hljs-number">0</span>/GatewayRuntime@123711 Error <span class="hljs-keyword">while</span>       [<span class="hljs-number">01</span>/<span class="hljs-number">23</span>/<span class="hljs-number">23</span> <span class="hljs-number">12</span>:<span class="hljs-number">35</span>:<span class="hljs-number">15</span>]
-       getting responses from deployments: <span class="hljs-keyword">no</span> Route matched                     
-       with those <span class="hljs-keyword">values</span>                                                        
-       trailing_metadata=Metadata(((<span class="hljs-string">'date'</span>, <span class="hljs-string">'Mon, 23 Jan                        
-       2023 11:35:15 GMT'</span>), (<span class="hljs-string">'content-length'</span>, <span class="hljs-string">'0'</span>),                            
-       (<span class="hljs-string">'x-kong-response-latency'</span>, <span class="hljs-string">'0'</span>), (<span class="hljs-string">'server'</span>,                             
-       <span class="hljs-string">'kong/3.0.2'</span>)))                                                          
-       trailing_metadata=Metadata(((<span class="hljs-string">'date'</span>, <span class="hljs-string">'Mon, 23 Jan                        
-       2023 11:35:15 GMT'</span>), (<span class="hljs-string">'content-length'</span>, <span class="hljs-string">'0'</span>),                            
-       (<span class="hljs-string">'x-kong-response-latency'</span>, <span class="hljs-string">'0'</span>), (<span class="hljs-string">'server'</span>,                             
-       <span class="hljs-string">'kong/3.0.2'</span>)))                                                          
+    if error:
+        # raise error
+    else:
+        # process results</code></pre><p><a href="https://docs.jina.ai/concepts/gateway/customization/?ref=jina-ai-gmbh.ghost.io#recovering-executor-errors" rel="nofollow">Read more about the feature in the documentation</a>.</p><h3 id="add-argument-suppressrootlogging-to-remove-or-preserve-root-logging-handlers-5635">Add argument <code>suppress_root_logging</code> to remove or preserve root logging handlers (<a href="https://github.com/jina-ai/jina/pull/5635?ref=jina-ai-gmbh.ghost.io">#5635</a>)</h3><p>In this release, we've added the argument <code>suppress_root_logging</code> to (you guessed it) suppress root logger messages. By default, root logs are suppressed.</p><p>Kudos to our community member <a href="https://github.com/Jake-00?ref=jina-ai-gmbh.ghost.io">@Jake-00</a> for the contribution!</p><h3 id="add-grpc-streaming-endpoint-to-worker-and-head-runtimes-5614">Add gRPC streaming endpoint to Worker and Head runtimes (<a href="https://github.com/jina-ai/jina/pull/5614?ref=jina-ai-gmbh.ghost.io">#5614</a>)</h3><p>To empower Executors we've added a gRPC streaming endpoint to both the Worker and Head runtimes. This means that an Executor or Head gRPC server exposes the same interface as a Jina gRPC Gateway. Therefore, you can use Jina's gRPC Client with each of those entities.</p><h3 id="add-prefetch-argument-to-client-post-method-5607">Add <code>prefetch</code> argument to client post method (<a href="https://github.com/jina-ai/jina/pull/5607?ref=jina-ai-gmbh.ghost.io">#5607</a>)</h3><p>A <code>prefetch</code> argument has been added to the <code>Client.post()</code> method. Previously, this argument was only available to the Gateway and it controlled how many requests a Gateway could <em>send</em> to Executors at a time.</p><p>However, it was not possible to control how many requests a Gateway (or Executor in case of a single Executor Deployment) could <em>receive</em> at a time.</p><p>Therefore, we've added the argument to the <code>Client.post()</code> to give you better control over your requests.</p><p><a href="https://docs.jina.ai/concepts/client/rate-limit/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Read more in the documentation</a>.</p><h3 id="run-warmup-on-runtimes-and-executor-5579">Run warmup on runtimes and Executor (<a href="https://github.com/jina-ai/jina/pull/5579?ref=jina-ai-gmbh.ghost.io">#5579</a>)</h3><p>On startup, all Jina entities that hold gRPC connections and stubs to other entities (Head and Gateway) now start warming up before the services become ready. This ensures lower latencies on first requests submitted to the Flow.</p><h3 id="make-grpc-client-thread-safe-5533">Make gRPC Client thread safe (<a href="https://github.com/jina-ai/jina/pull/5533?ref=jina-ai-gmbh.ghost.io">#5533</a>)</h3><p>Previously, as <a href="https://github.com/grpc/grpc/issues/25364?ref=jina-ai-gmbh.ghost.io">gRPC asyncio clients offer limited support for multi-threading</a>, using the Jina gRPC Client in multiple threads would print errors.</p><p>Therefore, in this release, we make the gRPC Client thread-safe in the sense that a thread can re-use it multiple times without another thread using it simultaneously. This means you can use the gRPC Client with multi-threading, while being sure only asyncio tasks belonging to the same thread have access to the gRPC stub at the same time.</p><h3 id="add-user-survey-5667">Add user survey (<a href="https://github.com/jina-ai/jina/pull/5667?ref=jina-ai-gmbh.ghost.io">#5667</a>)</h3><p>When running a Flow, a message now shows up in the terminal with a survey link. Feel free to fill in <a href="https://10sw1tcpld4.typeform.com/to/EGAEReM7?utm_source=doc&amp;utm_medium=ghost&amp;utm_campaign=user%20experience&amp;utm_term=feb2023&amp;utm_content=survey">our survey</a> to help us improve Jina. Your feedback is much appreciated!</p><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="use-single-gateway-streamer-for-multiprotocol-gateway-5598">Use single Gateway streamer for multiprotocol Gateway (<a href="https://github.com/jina-ai/jina/pull/5598?ref=jina-ai-gmbh.ghost.io">#5598</a>)</h3><p>When we released <a href="https://docs.jina.ai/concepts/gateway/?ref=jina-ai-gmbh.ghost.io#enable-multiple-protocols" rel="nofollow">multiprotocol Gateways</a>, the implementation relied on exposing a separate gRPC connection and stubs protocol. As this turned out to be unnecessary, this release re-uses the same connections and stubs.</p><h3 id="remove-manual-deletion-of-channel-resources-5633">Remove manual deletion of channel resources (<a href="https://github.com/jina-ai/jina/pull/5633?ref=jina-ai-gmbh.ghost.io">#5633</a>)</h3><p>This release refactors how we handle channel resources. Mainly, deletion of channel resources is no longer handled manually and is left to the garbage collector.</p><h3 id="no-need-to-run-summary-in-thread-5632">No need to run summary in thread (<a href="https://github.com/jina-ai/jina/pull/5632?ref=jina-ai-gmbh.ghost.io">#5632</a>)</h3><p>Getting and printing Flow summary information is no longer executed in a separate thread, and is now handled in the main thread.</p><h3 id="refactor-grpcconnectionpool-implementation-into-a-package-5623">Refactor <code>GRPCConnectionPool</code> implementation into a package (<a href="https://github.com/jina-ai/jina/pull/5623?ref=jina-ai-gmbh.ghost.io">#5623</a>)</h3><p>All gRPC connection pool logic has been refactored into a separate package, rather than having a <code>GRPCConnectionPool</code> class.</p><h3 id="remove-reversing-request-order-5580">Remove reversing request order (<a href="https://github.com/jina-ai/jina/pull/5580?ref=jina-ai-gmbh.ghost.io">#5580</a>)</h3><p>Reversing request order has been removed from runtime logic.</p><h3 id="simplify-getdocsfromrequest-helper-function-5567">Simplify <code>get_docs_from_request</code> helper function (<a href="https://github.com/jina-ai/jina/pull/5567?ref=jina-ai-gmbh.ghost.io">#5567</a>)</h3><p>The <code>get_docs_from_request</code> helper function in the request handler module has been simplified and no longer accepts unneeded parameters.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="relax-protobuf-version-5591">Relax protobuf version (<a href="https://github.com/jina-ai/jina/pull/5591?ref=jina-ai-gmbh.ghost.io">#5591</a>)</h3><p>To better support different environments, we've relaxed Jina's protobuf version so it no longer conflicts with Google Colab's pre-installed version (which may result in breaking some installed dependencies).</p><h3 id="fix-loading-gateway-arguments-from-yaml-5664-and-5678">Fix loading Gateway arguments from YAML (<a href="https://github.com/jina-ai/jina/pull/5664?ref=jina-ai-gmbh.ghost.io">#5664</a> and <a href="https://github.com/jina-ai/jina/pull/5678?ref=jina-ai-gmbh.ghost.io">#5678</a>)</h3><p>Prior to this release, loading Gateway configurations from YAML had a few bugs. Mainly, some parameters were not passed correctly to the Gateway runtime when configs were loaded. Also, other default runtime Gateway arguments would always override arguments from YAML configs.</p><h3 id="fix-usage-with-cudavisibledevices-5654">Fix usage with <code>cuda_visible_devices</code> (<a href="https://github.com/jina-ai/jina/pull/5654?ref=jina-ai-gmbh.ghost.io">#5654</a>)</h3><p>Prior to this release, <a href="https://docs.jina.ai/concepts/flow/scale-out/?ref=jina-ai-gmbh.ghost.io#replicate-on-multiple-gpus" rel="nofollow">using replicas on multiple GPUs</a> would fail if the <code>CUDA_VISIBLE_DEVICES</code> environment variable was passed with the <code>env</code> parameter, rather than actually being set in the environment variables.</p><h3 id="properly-use-logging-configuration-in-executor-gateway-and-client-5638">Properly use logging configuration in Executor, Gateway and Client (<a href="https://github.com/jina-ai/jina/pull/5638?ref=jina-ai-gmbh.ghost.io">#5638</a>)</h3><p>This release unifies the logging configuration in Executors, Gateways and Clients and exposes configuration parameters properly. You can now pass log configuration to your Clients and Flows and expect consistent logging behavior:</p><pre><code class="language-python">from jina import Client
+client = Client(log_config='./logging.json.yml')
+
+# or with a Flow object
+
+from jina import Flow
+f = Flow(log_config='./logging.json.yml')
+with f:
+    # the implicit client automatically uses the log_config from the Flow for consistency
+    f.post('/')</code></pre><h3 id="pass-extra-arguments-to-the-gateway-runtime-in-case-of-containerized-gateways-5631">Pass extra arguments to the Gateway runtime in case of containerized Gateways (<a href="https://github.com/jina-ai/jina/pull/5631?ref=jina-ai-gmbh.ghost.io">#5631</a>)</h3><p>Prior to this release, if a <a href="https://docs.jina.ai/concepts/gateway/customization/?ref=jina-ai-gmbh.ghost.io#containerize-the-custom-gateway" rel="nofollow">containerized Custom Gateway</a> was started, Jina wouldn't pass some arguments to the container entrypoint. This could break some behaviour, for instance, the runtime not knowing which port to use for serving the Gateway. The issue is fixed in this release.</p><h3 id="clean-up-opentelemetry-resources-in-the-flow-context-manager-exit-procedure-5619">Clean up OpenTelemetry resources in the Flow context manager exit procedure (<a href="https://github.com/jina-ai/jina/pull/5619?ref=jina-ai-gmbh.ghost.io">#5619</a>)</h3><p>This release adds proper cleanup to the OpenTelemetry resources. The cleanup logic has been added to the <code>Client</code> class and is called automatically in the Flow's context manager.</p><p>If you're using the <code>Client</code> with OpenTelemetry enabled, call <code>client.teardown_instrumentation()</code> to have correct spans of the client.</p><h3 id="improve-error-messages-for-grpc-notfound-errors-5617">Improve error messages for gRPC <code>NOT_FOUND</code> errors (<a href="https://github.com/jina-ai/jina/pull/5617?ref=jina-ai-gmbh.ghost.io">#5617</a>)</h3><p>When an external Executor/Flow is behind an API Gateway (which is the case for JCloud), but is down, then DNS resolution succeeds but a "resource" (the Executor/Flow) cannot be found, resulting in a gRPC error with the <code>NOT_FOUND</code> code.</p><p>This error case wasn't properly handled before, giving output like the following:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://user-images.githubusercontent.com/44071807/214031911-11c77c7a-3b02-44f9-a319-ba41088a4334.png" class="kg-image" alt=""></figure><p>This output did not include information about which part of the Flow failed.</p><p>In this release, the affected deployment and its address are displayed:</p><pre><code>ERROR  gateway/rep-0/GatewayRuntime@123711 Error while       [01/23/23 12:35:15]
+       getting responses from deployments: no Route matched                     
+       with those values                                                        
+       trailing_metadata=Metadata((('date', 'Mon, 23 Jan                        
+       2023 11:35:15 GMT'), ('content-length', '0'),                            
+       ('x-kong-response-latency', '0'), ('server',                             
+       'kong/3.0.2')))                                                          
+       trailing_metadata=Metadata((('date', 'Mon, 23 Jan                        
+       2023 11:35:15 GMT'), ('content-length', '0'),                            
+       ('x-kong-response-latency', '0'), ('server',                             
+       'kong/3.0.2')))                                                          
        |Gateway: Connection error with deployment                               
-       <span class="hljs-string">`executor0`</span> at address(es) {<span class="hljs-string">'blah.wolf.jina.ai'</span>}.                        
-       Connection with {<span class="hljs-string">'blah.wolf.jina.ai'</span>} succeeded, but                     
-       <span class="hljs-string">`executor0`</span> was <span class="hljs-keyword">not</span> found. Possibly <span class="hljs-string">`executor0`</span> is                       
-       behind an API gateway but <span class="hljs-keyword">not</span> reachable.                                 
-       trailing_metadata=Metadata(((<span class="hljs-string">'date'</span>, <span class="hljs-string">'Mon, 23 Jan                        
-       2023 11:35:15 GMT'</span>), (<span class="hljs-string">'content-length'</span>, <span class="hljs-string">'0'</span>),                            
-       (<span class="hljs-string">'x-kong-response-latency'</span>, <span class="hljs-string">'0'</span>), (<span class="hljs-string">'server'</span>,                             
-       <span class="hljs-string">'kong/3.0.2'</span>)))
-</code></pre><h3 id="use-mixinhubpulloptionsparser-from-hubble-5586">Use <code>mixin_hub_pull_options_parser</code> from Hubble (<a href="https://github.com/jina-ai/jina/pull/5586?ref=jina-ai-gmbh.ghost.io">#5586</a>)</h3><p>Some Hub parameters were implemented in both Jina and <code>jina-hubble-sdk</code>. This meant that if <code>jina-hubble-sdk</code> updated some parameters, there would be a mismatch and potentially bugs. This release removes these parameters from Jina to rely entirely on <code>jina-hubble-sdk</code> for Hubble-specific parameters.</p><h3 id="disable-timeout-for-liveness-probe-in-kubernetes-and-keep-only-kubernetes-timeout-5594">Disable timeout for Liveness Probe in Kubernetes and keep only Kubernetes timeout (<a href="https://github.com/jina-ai/jina/pull/5594?ref=jina-ai-gmbh.ghost.io">#5594</a>)</h3><p>When an Executor is deployed to Kubernetes, a <a href="https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Kubernetes Liveness Probe</a> is configured. The liveness probe uses the <code>jina ping</code> command under the hood to check the Executor health. However, this health-check is subject to the Kubernetes Liveness Probe timeout as well as the <code>jina ping</code> command timeout. This release removes (actually relaxes) the <code>jina ping</code> command timeout to keep only one configurable timeout (it respects <code>timeout_ready</code>) so that you can deploy Executors that are slow to load.</p><h3 id="enable-timeout-for-pinging-executor-and-gateway-5600">Enable timeout for pinging Executor and Gateway (<a href="https://github.com/jina-ai/jina/pull/5600?ref=jina-ai-gmbh.ghost.io">#5600</a>)</h3><p>The <code>jina ping</code> CLI can submit ping requests to Gateways and Executors. However, this command previously accepted a <code>timeout</code> parameter that was not respected. This release fixes this behavior and specifying the <code>timeout</code> parameter now makes the command fail if the ping requests are not successful after the <code>timeout</code> is exceeded.</p><h3 id="edit-terminal-profile-file-even-if-it-does-not-exist-5597">Edit terminal profile file even if it does not exist (<a href="https://github.com/jina-ai/jina/pull/5597?ref=jina-ai-gmbh.ghost.io">#5597</a>)</h3><p>When Jina is installed with <code>pip</code>, the installation script attempts to configure the user's terminal profile (<code>.bashrc</code>, <code>.zshrc</code>, <code>.fish</code> files) to add configuration needed for the <code>jina</code> command. However, this would be ignored if a user's terminal profile didn't exist.</p><p>With this release, the installation script now identifies the required terminal profile file depending on the user's environment and writes a new one if it does not exist already.</p><h3 id="multi-protocol-gateway-supports-monitoring-5570">Multi-protocol gateway supports monitoring (<a href="https://github.com/jina-ai/jina/pull/5570?ref=jina-ai-gmbh.ghost.io">#5570</a>)</h3><p>Prior to this release, using <a href="https://docs.jina.ai/concepts/gateway/?ref=jina-ai-gmbh.ghost.io#enable-multiple-protocols" rel="nofollow">multiple protocols</a> in the Gateway along with <code>monitoring</code> would raise an error. In this release, there are no issues when using multiple protocols along with monitoring in your Gateway.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation improvements</h2><ul><li>Document <code>tracing</code> support in <code>jcloud</code> (<a href="https://github.com/jina-ai/jina/pull/5688?ref=jina-ai-gmbh.ghost.io">#5688</a>)</li><li>Add survey banner (<a href="https://github.com/jina-ai/jina/pull/5649?ref=jina-ai-gmbh.ghost.io">#5649</a>)</li><li>Refactor example code for experimenting with OpenTelemetry (<a href="https://github.com/jina-ai/jina/pull/5656?ref=jina-ai-gmbh.ghost.io">#5656</a>)</li><li>Document <code>arm64</code> architecture support in <code>jina push</code> command (<a href="https://github.com/jina-ai/jina/pull/5644?ref=jina-ai-gmbh.ghost.io">#5644</a>)</li><li>Add <code>jcloud</code> Executor availability parameters (<a href="https://github.com/jina-ai/jina/pull/5624?ref=jina-ai-gmbh.ghost.io">#5624</a>)</li><li>Use one GPU in Jcloud deployment example (<a href="https://github.com/jina-ai/jina/pull/5620?ref=jina-ai-gmbh.ghost.io">#5620</a>)</li><li>Add caution about exceptions inside Flow context (<a href="https://github.com/jina-ai/jina/pull/5615?ref=jina-ai-gmbh.ghost.io">#5615</a>)</li><li>Document Flow update, restart, pause and resume on <code>jcloud</code> (<a href="https://github.com/jina-ai/jina/pull/5577?ref=jina-ai-gmbh.ghost.io">#5577</a>)</li><li>Document <code>ephemeral</code> storage type in JCloud (<a href="https://github.com/jina-ai/jina/pull/5583?ref=jina-ai-gmbh.ghost.io">#5583</a>)</li><li>Document Executor data retention with <code>retain</code> parameter in JCloud (<a href="https://github.com/jina-ai/jina/pull/5572?ref=jina-ai-gmbh.ghost.io">#5572</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Yanlong Wang (<a href="https://github.com/nomagick?ref=jina-ai-gmbh.ghost.io">@nomagick</a>)</li><li>tarrantro (<a href="https://github.com/tarrantro?ref=jina-ai-gmbh.ghost.io">@tarrantro</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Alaeddine Abdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Girish Chandrashekar (<a href="https://github.com/girishc13?ref=jina-ai-gmbh.ghost.io">@girishc13</a>)</li><li>Subba Reddy Veeramreddy (<a href="https://github.com/subbuv26?ref=jina-ai-gmbh.ghost.io">@subbuv26</a>)</li><li>Alaeddine Abdessalem (<a href="https://github.com/nan-wang?ref=jina-ai-gmbh.ghost.io">@nan-wang</a>)</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>Jake-00 (<a href="https://github.com/Jake-00?ref=jina-ai-gmbh.ghost.io">@Jake-00</a>)</li><li>Anne Yang (<a href="https://github.com/AnneYang720?ref=jina-ai-gmbh.ghost.io">@AnneYang720</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Nikolas Pitsillos (<a href="https://github.com/npitsillos?ref=jina-ai-gmbh.ghost.io">@npitsillos</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li><li>Jackmin801 (<a href="https://github.com/Jackmin801?ref=jina-ai-gmbh.ghost.io">@Jackmin801</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-14-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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\ No newline at end of file
+       `executor0` at address(es) {'blah.wolf.jina.ai'}.                        
+       Connection with {'blah.wolf.jina.ai'} succeeded, but                     
+       `executor0` was not found. Possibly `executor0` is                       
+       behind an API gateway but not reachable.                                 
+       trailing_metadata=Metadata((('date', 'Mon, 23 Jan                        
+       2023 11:35:15 GMT'), ('content-length', '0'),                            
+       ('x-kong-response-latency', '0'), ('server',                             
+       'kong/3.0.2')))
+</code></pre><h3 id="use-mixinhubpulloptionsparser-from-hubble-5586">Use <code>mixin_hub_pull_options_parser</code> from Hubble (<a href="https://github.com/jina-ai/jina/pull/5586?ref=jina-ai-gmbh.ghost.io">#5586</a>)</h3><p>Some Hub parameters were implemented in both Jina and <code>jina-hubble-sdk</code>. This meant that if <code>jina-hubble-sdk</code> updated some parameters, there would be a mismatch and potentially bugs. This release removes these parameters from Jina to rely entirely on <code>jina-hubble-sdk</code> for Hubble-specific parameters.</p><h3 id="disable-timeout-for-liveness-probe-in-kubernetes-and-keep-only-kubernetes-timeout-5594">Disable timeout for Liveness Probe in Kubernetes and keep only Kubernetes timeout (<a href="https://github.com/jina-ai/jina/pull/5594?ref=jina-ai-gmbh.ghost.io">#5594</a>)</h3><p>When an Executor is deployed to Kubernetes, a <a href="https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes/?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Kubernetes Liveness Probe</a> is configured. The liveness probe uses the <code>jina ping</code> command under the hood to check the Executor health. However, this health-check is subject to the Kubernetes Liveness Probe timeout as well as the <code>jina ping</code> command timeout. This release removes (actually relaxes) the <code>jina ping</code> command timeout to keep only one configurable timeout (it respects <code>timeout_ready</code>) so that you can deploy Executors that are slow to load.</p><h3 id="enable-timeout-for-pinging-executor-and-gateway-5600">Enable timeout for pinging Executor and Gateway (<a href="https://github.com/jina-ai/jina/pull/5600?ref=jina-ai-gmbh.ghost.io">#5600</a>)</h3><p>The <code>jina ping</code> CLI can submit ping requests to Gateways and Executors. However, this command previously accepted a <code>timeout</code> parameter that was not respected. This release fixes this behavior and specifying the <code>timeout</code> parameter now makes the command fail if the ping requests are not successful after the <code>timeout</code> is exceeded.</p><h3 id="edit-terminal-profile-file-even-if-it-does-not-exist-5597">Edit terminal profile file even if it does not exist (<a href="https://github.com/jina-ai/jina/pull/5597?ref=jina-ai-gmbh.ghost.io">#5597</a>)</h3><p>When Jina is installed with <code>pip</code>, the installation script attempts to configure the user's terminal profile (<code>.bashrc</code>, <code>.zshrc</code>, <code>.fish</code> files) to add configuration needed for the <code>jina</code> command. However, this would be ignored if a user's terminal profile didn't exist.</p><p>With this release, the installation script now identifies the required terminal profile file depending on the user's environment and writes a new one if it does not exist already.</p><h3 id="multi-protocol-gateway-supports-monitoring-5570">Multi-protocol gateway supports monitoring (<a href="https://github.com/jina-ai/jina/pull/5570?ref=jina-ai-gmbh.ghost.io">#5570</a>)</h3><p>Prior to this release, using <a href="https://docs.jina.ai/concepts/gateway/?ref=jina-ai-gmbh.ghost.io#enable-multiple-protocols" rel="nofollow">multiple protocols</a> in the Gateway along with <code>monitoring</code> would raise an error. In this release, there are no issues when using multiple protocols along with monitoring in your Gateway.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation improvements</h2><ul><li>Document <code>tracing</code> support in <code>jcloud</code> (<a href="https://github.com/jina-ai/jina/pull/5688?ref=jina-ai-gmbh.ghost.io">#5688</a>)</li><li>Add survey banner (<a href="https://github.com/jina-ai/jina/pull/5649?ref=jina-ai-gmbh.ghost.io">#5649</a>)</li><li>Refactor example code for experimenting with OpenTelemetry (<a href="https://github.com/jina-ai/jina/pull/5656?ref=jina-ai-gmbh.ghost.io">#5656</a>)</li><li>Document <code>arm64</code> architecture support in <code>jina push</code> command (<a href="https://github.com/jina-ai/jina/pull/5644?ref=jina-ai-gmbh.ghost.io">#5644</a>)</li><li>Add <code>jcloud</code> Executor availability parameters (<a href="https://github.com/jina-ai/jina/pull/5624?ref=jina-ai-gmbh.ghost.io">#5624</a>)</li><li>Use one GPU in Jcloud deployment example (<a href="https://github.com/jina-ai/jina/pull/5620?ref=jina-ai-gmbh.ghost.io">#5620</a>)</li><li>Add caution about exceptions inside Flow context (<a href="https://github.com/jina-ai/jina/pull/5615?ref=jina-ai-gmbh.ghost.io">#5615</a>)</li><li>Document Flow update, restart, pause and resume on <code>jcloud</code> (<a href="https://github.com/jina-ai/jina/pull/5577?ref=jina-ai-gmbh.ghost.io">#5577</a>)</li><li>Document <code>ephemeral</code> storage type in JCloud (<a href="https://github.com/jina-ai/jina/pull/5583?ref=jina-ai-gmbh.ghost.io">#5583</a>)</li><li>Document Executor data retention with <code>retain</code> parameter in JCloud (<a href="https://github.com/jina-ai/jina/pull/5572?ref=jina-ai-gmbh.ghost.io">#5572</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Yanlong Wang (<a href="https://github.com/nomagick?ref=jina-ai-gmbh.ghost.io">@nomagick</a>)</li><li>tarrantro (<a href="https://github.com/tarrantro?ref=jina-ai-gmbh.ghost.io">@tarrantro</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Alaeddine Abdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Girish Chandrashekar (<a href="https://github.com/girishc13?ref=jina-ai-gmbh.ghost.io">@girishc13</a>)</li><li>Subba Reddy Veeramreddy (<a href="https://github.com/subbuv26?ref=jina-ai-gmbh.ghost.io">@subbuv26</a>)</li><li>Alaeddine Abdessalem (<a href="https://github.com/nan-wang?ref=jina-ai-gmbh.ghost.io">@nan-wang</a>)</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>Jake-00 (<a href="https://github.com/Jake-00?ref=jina-ai-gmbh.ghost.io">@Jake-00</a>)</li><li>Anne Yang (<a href="https://github.com/AnneYang720?ref=jina-ai-gmbh.ghost.io">@AnneYang720</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Nikolas Pitsillos (<a href="https://github.com/npitsillos?ref=jina-ai-gmbh.ghost.io">@npitsillos</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a>)</li><li>Jackmin801 (<a href="https://github.com/Jackmin801?ref=jina-ai-gmbh.ghost.io">@Jackmin801</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-14-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.15 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.15 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-15-update"><meta property="og:title" content="Jina 3.15 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-core--2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-15-update"><meta property="twitter:title" content="Jina 3.15 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-core--2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 14, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3150">Release Note (<code>3.15.0</code>)</h2><blockquote>Release time: 2023-04-14 09:55:25</blockquote><p>This release contains 6 new features, &nbsp;6 bug fixes, and 5 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.15.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.15.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.15.0) Release time: 2023-04-14 09:55:25 This release contains 6 new features, 6 bug fixes and 5 documentation improvements.🆕 FeaturesHTTP and composite protocols for Deployment…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/c2feac89afa05bccae7b0ae03b69dd570b5f23b7d75fee9c9a24c9d29e71ece2/jina-ai/jina/releases/tag/v3.15.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="http-and-composite-protocols-for-deployment-5764">HTTP and composite protocols for Deployment (<a href="https://github.com/jina-ai/jina/pull/5764?ref=jina-ai-gmbh.ghost.io">#5764</a>)</h3><p>When using a <code>Deployment</code> to serve a single <code>Executor</code>, you can now expose it via HTTP or a combination of HTTP and gRPC protocols:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment, Executor, requests
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.15 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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 <span class="hljs-keyword">class</span> <span class="hljs-title class_">MyExec</span>(<span class="hljs-title class_ inherited__">Executor</span>):
 
@@ -111,4 +111,4 @@
         return_type=DocList[OutputDoc],
     )
     <span class="hljs-keyword">assert</span> docs[<span class="hljs-number">0</span>].embedding.shape == (<span class="hljs-number">100</span>, <span class="hljs-number">1</span>)
-    <span class="hljs-keyword">assert</span> docs.__class__.document_type == OutputDoc</code></pre><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>JCloud Flow name customization (<a href="https://github.com/jina-ai/jina/pull/5778?ref=jina-ai-gmbh.ghost.io">#5778</a>)</li><li>JCloud docs revamp for instance (<a href="https://github.com/jina-ai/jina/pull/5759?ref=jina-ai-gmbh.ghost.io">#5759</a>)</li><li>Fix Colab link (<a href="https://github.com/jina-ai/jina/pull/5760?ref=jina-ai-gmbh.ghost.io">#5760</a>)</li><li>Remove docsQA (<a href="https://github.com/jina-ai/jina/pull/5743?ref=jina-ai-gmbh.ghost.io">#5743</a>)</li><li>Miscellaneous polishing</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Girish Chandrashekar (<a href="https://github.com/girishc13?ref=jina-ai-gmbh.ghost.io">@girishc13</a>)</li><li>Asuzu Kosisochukwu (<a href="https://github.com/asuzukosi?ref=jina-ai-gmbh.ghost.io">@asuzukosi</a>)</li><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Zac Li (<a href="https://github.com/zac-li?ref=jina-ai-gmbh.ghost.io">@zac-li</a>)</li><li>nikitashrivastava29 (<a href="https://github.com/nikitashrivastava29?ref=jina-ai-gmbh.ghost.io">@nikitashrivastava29</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Deepankar Mahapatro (<a href="https://github.com/deepankarm?ref=jina-ai-gmbh.ghost.io">@deepankarm</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-15-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
+    <span class="hljs-keyword">assert</span> docs.__class__.document_type == OutputDoc</code></pre><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>JCloud Flow name customization (<a href="https://github.com/jina-ai/jina/pull/5778?ref=jina-ai-gmbh.ghost.io">#5778</a>)</li><li>JCloud docs revamp for instance (<a href="https://github.com/jina-ai/jina/pull/5759?ref=jina-ai-gmbh.ghost.io">#5759</a>)</li><li>Fix Colab link (<a href="https://github.com/jina-ai/jina/pull/5760?ref=jina-ai-gmbh.ghost.io">#5760</a>)</li><li>Remove docsQA (<a href="https://github.com/jina-ai/jina/pull/5743?ref=jina-ai-gmbh.ghost.io">#5743</a>)</li><li>Miscellaneous polishing</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Girish Chandrashekar (<a href="https://github.com/girishc13?ref=jina-ai-gmbh.ghost.io">@girishc13</a>)</li><li>Asuzu Kosisochukwu (<a href="https://github.com/asuzukosi?ref=jina-ai-gmbh.ghost.io">@asuzukosi</a>)</li><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Zac Li (<a href="https://github.com/zac-li?ref=jina-ai-gmbh.ghost.io">@zac-li</a>)</li><li>nikitashrivastava29 (<a href="https://github.com/nikitashrivastava29?ref=jina-ai-gmbh.ghost.io">@nikitashrivastava29</a>)</li><li>samsja (<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">@samsja</a>)</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Deepankar Mahapatro (<a href="https://github.com/deepankarm?ref=jina-ai-gmbh.ghost.io">@deepankarm</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-15-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.16.1 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.16.1 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-16-1-update"><meta property="og:title" content="Jina 3.16.1 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Jina-core--4-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-16-1-update"><meta property="twitter:title" content="Jina 3.16.1 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Jina-core--4-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.16.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 24, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3161">Release Note (<code>3.16.1</code>)</h2><blockquote>Release time: 2023-05-23 14:59:35</blockquote><p>This patch contains 1 refactoring, 3 bug fixes and 3 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.16.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.16.1 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.16.1) Release time: 2023-05-23 14:59:35 This patch contains 1 refactoring, 3 bug fixes and 3 documentation improvements.⚙ RefactoringRemove aiostream dependency (#5891)Remove a…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/305135ae36af95b3728b718f0331ae0dd169d6f241b82ed55761d98fee6b743e/jina-ai/jina/releases/tag/v3.16.1" alt=""></div></a></figure><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="remove-aiostream-dependency-5891">Remove aiostream dependency (<a href="https://github.com/jina-ai/jina/pull/5891?ref=jina-ai-gmbh.ghost.io">#5891</a>)</h3><p>Remove aiostream dependency which could be the root of improper licensing.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-usage-of-ports-and-protocols-alias-5885">Fix usage of <code>ports</code> and <code>protocols</code> alias (<a href="https://github.com/jina-ai/jina/pull/5885?ref=jina-ai-gmbh.ghost.io">#5885</a>)</h3><p>You can now use plural <code>ports</code> and <code>protocols</code>:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Flow
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 24, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3161">Release Note (<code>3.16.1</code>)</h2><blockquote>Release time: 2023-05-23 14:59:35</blockquote><p>This patch contains 1 refactoring, 3 bug fixes and 3 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.16.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.16.1 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.16.1) Release time: 2023-05-23 14:59:35 This patch contains 1 refactoring, 3 bug fixes and 3 documentation improvements.⚙ RefactoringRemove aiostream dependency (#5891)Remove a…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/305135ae36af95b3728b718f0331ae0dd169d6f241b82ed55761d98fee6b743e/jina-ai/jina/releases/tag/v3.16.1" alt=""></div></a></figure><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="remove-aiostream-dependency-5891">Remove aiostream dependency (<a href="https://github.com/jina-ai/jina/pull/5891?ref=jina-ai-gmbh.ghost.io">#5891</a>)</h3><p>Remove aiostream dependency which could be the root of improper licensing.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-usage-of-ports-and-protocols-alias-5885">Fix usage of <code>ports</code> and <code>protocols</code> alias (<a href="https://github.com/jina-ai/jina/pull/5885?ref=jina-ai-gmbh.ghost.io">#5885</a>)</h3><p>You can now use plural <code>ports</code> and <code>protocols</code>:</p><pre><code class="language-python">from jina import Flow
 
-f = Flow(ports=[<span class="hljs-number">12345</span>, <span class="hljs-number">12346</span>], protocols=[<span class="hljs-string">'grpc'</span>, <span class="hljs-string">'http'</span>]).add()
+f = Flow(ports=[12345, 12346], protocols=['grpc', 'http']).add()
 
-<span class="hljs-keyword">with</span> f:
-    f.block()</code></pre><p>Previously, the arguments would correctly be applied to the inner <code>Deployments</code>.</p><h3 id="fix-endpoint-printing-5884">Fix endpoint printing (<a href="https://github.com/jina-ai/jina/pull/5884?ref=jina-ai-gmbh.ghost.io">#5884</a>)</h3><p>Fix endpoint printing when no ports are specified with multi-protocol Deployments:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment, Executor, requests, Client
+with f:
+    f.block()</code></pre><p>Previously, the arguments would correctly be applied to the inner <code>Deployments</code>.</p><h3 id="fix-endpoint-printing-5884">Fix endpoint printing (<a href="https://github.com/jina-ai/jina/pull/5884?ref=jina-ai-gmbh.ghost.io">#5884</a>)</h3><p>Fix endpoint printing when no ports are specified with multi-protocol Deployments:</p><pre><code class="language-python">from jina import Deployment, Executor, requests, Client
 
-d = Deployment(protocols=[<span class="hljs-string">'grpc'</span>, <span class="hljs-string">'http'</span>])
+d = Deployment(protocols=['grpc', 'http'])
 
-<span class="hljs-keyword">with</span> d:
-    <span class="hljs-keyword">pass</span></code></pre><p>Before:<br></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/jina/assets/19825685/afbbdb69-2cf3-4670-afff-2912dc20cf78" class="kg-image" alt="image"></figure><p>After:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/jina/assets/19825685/07bdfbdc-cbf0-4b1c-a84b-ae4a0ecbdfdd" class="kg-image" alt="image"></figure><h3 id="fix-docs-and-redocs-links-5883">Fix docs and redocs links (<a href="https://github.com/jina-ai/jina/pull/5883?ref=jina-ai-gmbh.ghost.io">#5883</a>)</h3><p>Fix the printed links to <code>docs</code> and <code>redocs</code> pages when <code>HTTP</code> protocol is used in combination with other protocols.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment, Executor, requests, Client
+with d:
+    pass</code></pre><p>Before:<br></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/jina/assets/19825685/afbbdb69-2cf3-4670-afff-2912dc20cf78" class="kg-image" alt="image"></figure><p>After:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/jina/assets/19825685/07bdfbdc-cbf0-4b1c-a84b-ae4a0ecbdfdd" class="kg-image" alt="image"></figure><h3 id="fix-docs-and-redocs-links-5883">Fix docs and redocs links (<a href="https://github.com/jina-ai/jina/pull/5883?ref=jina-ai-gmbh.ghost.io">#5883</a>)</h3><p>Fix the printed links to <code>docs</code> and <code>redocs</code> pages when <code>HTTP</code> protocol is used in combination with other protocols.</p><pre><code class="language-python">from jina import Deployment, Executor, requests, Client
 
-d = Deployment(protocol=[<span class="hljs-string">'grpc'</span>, <span class="hljs-string">'http'</span>], port=[<span class="hljs-number">12345</span>, <span class="hljs-number">12346</span>])
+d = Deployment(protocol=['grpc', 'http'], port=[12345, 12346])
 
-<span class="hljs-keyword">with</span> d:
-    <span class="hljs-keyword">pass</span></code></pre><p>Old behavior:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/jina/assets/19825685/bbe06489-b32b-4b68-9a25-c483bf08c909" class="kg-image" alt="image"></figure><p>New behavior:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/jina/assets/19825685/19ca7092-df47-4fb6-9d47-96df91ac5850" class="kg-image" alt="image"></figure><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Fix import in notebook causing a crash (<a href="https://github.com/jina-ai/jina/pull/5888?ref=jina-ai-gmbh.ghost.io">#5888</a>)</li><li>Add docs for Jina Cloud logs (<a href="https://github.com/jina-ai/jina/pull/5892?ref=jina-ai-gmbh.ghost.io">#5892</a>)</li><li>Fix YAML specs links (<a href="https://github.com/jina-ai/jina/pull/5887?ref=jina-ai-gmbh.ghost.io">#5887</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Han Xiao (<a href="https://github.com/hanxiao?ref=jina-ai-gmbh.ghost.io">@hanxiao</a> )</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>Nikolas Pitsillos (<a href="https://github.com/npitsillos?ref=jina-ai-gmbh.ghost.io">@npitsillos</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-16-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; 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+with d:
+    pass</code></pre><p>Old behavior:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/jina/assets/19825685/bbe06489-b32b-4b68-9a25-c483bf08c909" class="kg-image" alt="image"></figure><p>New behavior:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/jina/assets/19825685/19ca7092-df47-4fb6-9d47-96df91ac5850" class="kg-image" alt="image"></figure><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Fix import in notebook causing a crash (<a href="https://github.com/jina-ai/jina/pull/5888?ref=jina-ai-gmbh.ghost.io">#5888</a>)</li><li>Add docs for Jina Cloud logs (<a href="https://github.com/jina-ai/jina/pull/5892?ref=jina-ai-gmbh.ghost.io">#5892</a>)</li><li>Fix YAML specs links (<a href="https://github.com/jina-ai/jina/pull/5887?ref=jina-ai-gmbh.ghost.io">#5887</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Han Xiao (<a href="https://github.com/hanxiao?ref=jina-ai-gmbh.ghost.io">@hanxiao</a> )</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a>)</li><li>Nikolas Pitsillos (<a href="https://github.com/npitsillos?ref=jina-ai-gmbh.ghost.io">@npitsillos</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-16-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.16 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.16 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-16-update"><meta property="og:title" content="Jina 3.16 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Jina-core--3-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-16-update"><meta property="twitter:title" content="Jina 3.16 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Jina-core--3-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 15, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3160">Release Note (<code>3.16.0</code>)</h2><blockquote>Release time: 2023-05-05 06:35:58</blockquote><p>This release contains 4 new features, 5 bug fixes, and 8 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="beta-replicate-with-consensus-stateful-executors-using-raft-algorithm-with-new-docarray-version-docarray-030-5564">(Beta) Replicate with consensus stateful Executors using RAFT algorithm with new DocArray version (<code>docarray &gt;= 0.30</code>) (<a href="https://github.com/jina-ai/jina/pull/5564?ref=jina-ai-gmbh.ghost.io">#5564</a>)</h3><p>When scaling Executors inside a <code>Deployment</code>, you can now ensure internal state (if the Executor has one) can be synced across every replica by ensuring they all work in consensus. This means the internal state of every replica will be consistent and they can thus serve requests in an equivalent manner.</p><p>For this, you need to decorate the Executor methods that alter its inner state with the <code>@write</code> decorator. Then, when adding the Executor inside a Deployment, you need to add the <code>stateful=True</code> flag and optionally configure the ports of every peer in the replication cluster using the <code>--peer-ports</code> argument:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment, Executor, requests
-<span class="hljs-keyword">from</span> jina.serve.executors.decorators <span class="hljs-keyword">import</span> write
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocList
-<span class="hljs-keyword">from</span> docarray.documents <span class="hljs-keyword">import</span> TextDoc
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 15, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3160">Release Note (<code>3.16.0</code>)</h2><blockquote>Release time: 2023-05-05 06:35:58</blockquote><p>This release contains 4 new features, 5 bug fixes, and 8 documentation improvements.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="beta-replicate-with-consensus-stateful-executors-using-raft-algorithm-with-new-docarray-version-docarray-030-5564">(Beta) Replicate with consensus stateful Executors using RAFT algorithm with new DocArray version (<code>docarray &gt;= 0.30</code>) (<a href="https://github.com/jina-ai/jina/pull/5564?ref=jina-ai-gmbh.ghost.io">#5564</a>)</h3><p>When scaling Executors inside a <code>Deployment</code>, you can now ensure internal state (if the Executor has one) can be synced across every replica by ensuring they all work in consensus. This means the internal state of every replica will be consistent and they can thus serve requests in an equivalent manner.</p><p>For this, you need to decorate the Executor methods that alter its inner state with the <code>@write</code> decorator. Then, when adding the Executor inside a Deployment, you need to add the <code>stateful=True</code> flag and optionally configure the ports of every peer in the replication cluster using the <code>--peer-ports</code> argument:</p><pre><code class="language-python">from jina import Deployment, Executor, requests
+from jina.serve.executors.decorators import write
+from docarray import DocList
+from docarray.documents import TextDoc
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyStateStatefulExecutor</span>(<span class="hljs-title class_ inherited__">Executor</span>):
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">__init__</span>(<span class="hljs-params">self, *args, **kwargs</span>):
-        <span class="hljs-built_in">super</span>().__init__(*args, **kwargs)
+class MyStateStatefulExecutor(Executor):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
         self._docs_dict = {}
      
-<span class="hljs-meta">    @write</span>
-<span class="hljs-meta">    @requests(<span class="hljs-params">on=[<span class="hljs-string">'/index'</span>]</span>)</span>
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">index</span>(<span class="hljs-params">self, docs: DocList[TextDoc], **kwargs</span>) -&gt; DocList[TextDoc]:
-        <span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span> docs:
-            self._docs_dict[doc.<span class="hljs-built_in">id</span>] = doc
+    @write
+    @requests(on=['/index'])
+    def index(self, docs: DocList[TextDoc], **kwargs) -&gt; DocList[TextDoc]:
+        for doc in docs:
+            self._docs_dict[doc.id] = doc
     
-<span class="hljs-meta">    @requests(<span class="hljs-params">on=[<span class="hljs-string">'/search'</span>]</span>)</span>
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">search</span>(<span class="hljs-params">self,  docs: DocList[TextDoc], **kwargs</span>) -&gt; DocList[TextDoc]:
-        <span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span> docs:
-            self.logger.debug(<span class="hljs-string">f'Searching against <span class="hljs-subst">{<span class="hljs-built_in">len</span>(self._docs_dict)}</span> documents'</span>)
-            doc.text = self._docs_dict[doc.<span class="hljs-built_in">id</span>].text
+    @requests(on=['/search'])
+    def search(self,  docs: DocList[TextDoc], **kwargs) -&gt; DocList[TextDoc]:
+        for doc in docs:
+            self.logger.debug(f'Searching against {len(self._docs_dict)} documents')
+            doc.text = self._docs_dict[doc.id].text
 
-d = Deployment(name=<span class="hljs-string">'stateful_executor'</span>, 
+d = Deployment(name='stateful_executor', 
                uses=MyStateStatefulExecutor,
-               replicas=<span class="hljs-number">3</span>, 
-               stateful=<span class="hljs-literal">True</span>, 
-               peer_ports=[<span class="hljs-number">12345</span>, <span class="hljs-number">12346</span>, <span class="hljs-number">12347</span>])
-<span class="hljs-keyword">with</span> d:
-    d.block()</code></pre><p>The <code>consensus</code> module in Jina will ensure that the three replicas all hold the same state. Jina uses the <a href="https://raft.github.io/?ref=jina-ai-gmbh.ghost.io">RAFT algorithm</a> to provide this feature.</p><h3 id="support-http-and-combined-protocols-for-deployment-with-new-docarray-version-docarray-030-5826">Support HTTP and combined protocols for Deployment with new DocArray version (<code>docarray &gt;= 0.30</code>) (<a href="https://github.com/jina-ai/jina/pull/5826?ref=jina-ai-gmbh.ghost.io">#5826</a>)</h3><p>You can now use the new DocArray version when using HTTP as the protocol to serve a Deployment, or a composition of HTTP and gRPC.</p><p>This allows OpenAPI specs matching the exact Document schemas defined by the Executor:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests
-<span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocList, BaseDoc
-<span class="hljs-keyword">from</span> docarray.documents <span class="hljs-keyword">import</span> ImageDoc
-<span class="hljs-keyword">from</span> docarray.typing <span class="hljs-keyword">import</span> AnyTensor
+               replicas=3, 
+               stateful=True, 
+               peer_ports=[12345, 12346, 12347])
+with d:
+    d.block()</code></pre><p>The <code>consensus</code> module in Jina will ensure that the three replicas all hold the same state. Jina uses the <a href="https://raft.github.io/?ref=jina-ai-gmbh.ghost.io">RAFT algorithm</a> to provide this feature.</p><h3 id="support-http-and-combined-protocols-for-deployment-with-new-docarray-version-docarray-030-5826">Support HTTP and combined protocols for Deployment with new DocArray version (<code>docarray &gt;= 0.30</code>) (<a href="https://github.com/jina-ai/jina/pull/5826?ref=jina-ai-gmbh.ghost.io">#5826</a>)</h3><p>You can now use the new DocArray version when using HTTP as the protocol to serve a Deployment, or a composition of HTTP and gRPC.</p><p>This allows OpenAPI specs matching the exact Document schemas defined by the Executor:</p><pre><code class="language-python">from jina import Executor, requests
+from docarray import DocList, BaseDoc
+from docarray.documents import ImageDoc
+from docarray.typing import AnyTensor
 
-<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
+import numpy as np
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">InputDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
+class InputDoc(BaseDoc):
     img: ImageDoc
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">OutputDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
+class OutputDoc(BaseDoc):
     embedding: AnyTensor
 
-<span class="hljs-keyword">class</span> <span class="hljs-title class_">MyExec</span>(<span class="hljs-title class_ inherited__">Executor</span>):
-<span class="hljs-meta">    @requests(<span class="hljs-params">on=<span class="hljs-string">'/bar'</span></span>)</span>
-    <span class="hljs-keyword">def</span> <span class="hljs-title function_">bar</span>(<span class="hljs-params">
+class MyExec(Executor):
+    @requests(on='/bar')
+    def bar(
             self, docs: DocList[InputDoc], **kwargs
-    </span>) -&gt; DocList[OutputDoc]:
+    ) -&gt; DocList[OutputDoc]:
         docs_return = DocList[OutputDoc](
-            [OutputDoc(embedding=np.zeros((<span class="hljs-number">100</span>, <span class="hljs-number">1</span>))) <span class="hljs-keyword">for</span> _ <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-built_in">len</span>(docs))]
+            [OutputDoc(embedding=np.zeros((100, 1))) for _ in range(len(docs))]
         )
-        <span class="hljs-keyword">return</span> docs_return
+        return docs_return
 
-d = Deployment(uses=MyExec, protocol=<span class="hljs-string">'http'</span>)
+d = Deployment(uses=MyExec, protocol='http')
 
-<span class="hljs-keyword">with</span> d:
+with d:
     d.block()
-</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://user-images.githubusercontent.com/19825685/235653813-ea89a198-7899-4870-9ce2-14b810df2cb1.png" class="kg-image" alt="Screenshot from 2023-05-02 13-26-37"></figure><h3 id="support-sharding-in-deployment-with-new-docarray-version-docarray-030-5828">Support sharding in Deployment with new DocArray version (<code>docarray &gt;= 0.30</code>) (<a href="https://github.com/jina-ai/jina/pull/5828?ref=jina-ai-gmbh.ghost.io">#5828</a>)</h3><p>Using <code>shards</code> inside a <code>Deployment</code> (where the <code>Executor</code> works with <code>docarray&gt;=0.30</code>) will now work the same as with previous versions of <code>docarray</code> as described in the <a href="https://docs.jina.ai/concepts/orchestration/scale-out/?ref=jina-ai-gmbh.ghost.io#understand-behaviors-of-replicas-and-shards-with-polling" rel="nofollow">documentation</a>.</p><h3 id="clickable-link-to-docs-openapi-endpoint-5854">Clickable link to <code>/docs</code> OpenAPI endpoint (<a href="https://github.com/jina-ai/jina/pull/5854?ref=jina-ai-gmbh.ghost.io">#5854</a>)</h3><p>When starting a Flow or a Deployment with the HTTP protocol, the <code>/docs</code> and <code>/redocs</code> links will now appear complete and can be clicked to open the browser directly from the terminal.</p><p>Previously, you would see:<br></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/jina/assets/19825685/6c1069f7-83cb-474a-91ab-ae167bb97883" class="kg-image" alt="image"></figure><p>Now:<br></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/jina/assets/19825685/c50d0acc-6f75-4395-90bf-b296bea05484" class="kg-image" alt="image"></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="improved-platform-specific-dependency-for-uvloop-5841">Improved platform-specific dependency for <code>uvloop</code>. (<a href="https://github.com/jina-ai/jina/pull/5841?ref=jina-ai-gmbh.ghost.io">#5841</a>)</h3><p>Fix installation issues when downstream dependencies try to install Jina on Windows using <code>poetry</code>.</p><h3 id="use-utf-8-encoding-when-opening-files-5821">Use <code>utf-8</code> encoding when opening files (<a href="https://github.com/jina-ai/jina/pull/5821?ref=jina-ai-gmbh.ghost.io">#5821</a>)</h3><p>Use <code>utf-8</code> encoding when opening files to fix potential problems when using Jina in Windows.</p><h3 id="fix-new-deployment-cli-5819">Fix new Deployment CLI (<a href="https://github.com/jina-ai/jina/pull/5819?ref=jina-ai-gmbh.ghost.io">#5819</a>)</h3><p>Fix the output YAML file when using <code>jina new &lt;project-name&gt; --type deployment</code>. It previously dumped an invalid Deployment YAML. The syntax has now been fixed so that it can be deployed.</p><h3 id="use-container-stop-so-that-containers-running-cuda-can-be-killed-5816">Use container <code>stop</code> so that containers running cuda can be killed (<a href="https://github.com/jina-ai/jina/pull/5816?ref=jina-ai-gmbh.ghost.io">#5816</a>)</h3><p>Use <a href="https://docker-py.readthedocs.io/en/stable/containers.html?ref=jina-ai-gmbh.ghost.io#docker.models.containers.Container.stop" rel="nofollow"><code>stop</code></a> instead of <a href="https://docker-py.readthedocs.io/en/stable/containers.html?ref=jina-ai-gmbh.ghost.io#docker.models.containers.Container.kill" rel="nofollow"><code>kill</code></a> from the <a href="https://docker-py.readthedocs.io/en/stable/index.html?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Python Docker SDK</a>. This allows containerized Executors that are run with <code>conda run</code> to terminate, since conda does not propagate its captured signals to its Python subprocesses.</p><h3 id="catch-contenttypeerror-for-retry-in-post-requests-5825">Catch <code>ContentTypeError</code> for retry in post requests (<a href="https://github.com/jina-ai/jina/pull/5825?ref=jina-ai-gmbh.ghost.io">#5825</a>)</h3><p><code>ContentTypeError</code> responses in the Client will now be caught and retries applied if required.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Update Slack count (<a href="https://github.com/jina-ai/jina/pull/5842?ref=jina-ai-gmbh.ghost.io">#5842</a>)</li><li>Add storage section (<a href="https://github.com/jina-ai/jina/pull/5831?ref=jina-ai-gmbh.ghost.io">#5831</a>)</li><li>Remove layer from orchestration layer title (<a href="https://github.com/jina-ai/jina/pull/5829?ref=jina-ai-gmbh.ghost.io">#5829</a>)</li><li>Fix broken links (<a href="https://github.com/jina-ai/jina/pull/5822?ref=jina-ai-gmbh.ghost.io">#5822</a>)</li><li>Add docs for <code>jc recreate</code> (<a href="https://github.com/jina-ai/jina/pull/5815?ref=jina-ai-gmbh.ghost.io">#5815</a>)</li><li>Point to legacy <code>DocumentArray</code> docs (<a href="https://github.com/jina-ai/jina/pull/5810?ref=jina-ai-gmbh.ghost.io">#5810</a>)</li><li>Fix some English in docstrings (<a href="https://github.com/jina-ai/jina/pull/5718?ref=jina-ai-gmbh.ghost.io">#5718</a>)</li><li>Fix some links in scalability chapter (<a href="https://github.com/jina-ai/jina/pull/5809?ref=jina-ai-gmbh.ghost.io">#5809</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>notandor (<a href="https://github.com/NotAndOr?ref=jina-ai-gmbh.ghost.io">@NotAndOr</a> )</li><li>Deepankar Mahapatro (<a href="https://github.com/deepankarm?ref=jina-ai-gmbh.ghost.io">@deepankarm</a> )</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a> )</li><li>Tanguy Abel (<a href="https://github.com/Tanguyabel?ref=jina-ai-gmbh.ghost.io">@Tanguyabel</a> )</li><li>Nikolas Pitsillos (<a href="https://github.com/npitsillos?ref=jina-ai-gmbh.ghost.io">@npitsillos</a> )</li><li>Felix Mönckemeyer (<a href="https://github.com/NemesisFLX?ref=jina-ai-gmbh.ghost.io">@NemesisFLX</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Florian Hönicke (<a href="https://github.com/florian-hoenicke?ref=jina-ai-gmbh.ghost.io">@florian-hoenicke</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-16-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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\ No newline at end of file
+</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://user-images.githubusercontent.com/19825685/235653813-ea89a198-7899-4870-9ce2-14b810df2cb1.png" class="kg-image" alt="Screenshot from 2023-05-02 13-26-37"></figure><h3 id="support-sharding-in-deployment-with-new-docarray-version-docarray-030-5828">Support sharding in Deployment with new DocArray version (<code>docarray &gt;= 0.30</code>) (<a href="https://github.com/jina-ai/jina/pull/5828?ref=jina-ai-gmbh.ghost.io">#5828</a>)</h3><p>Using <code>shards</code> inside a <code>Deployment</code> (where the <code>Executor</code> works with <code>docarray&gt;=0.30</code>) will now work the same as with previous versions of <code>docarray</code> as described in the <a href="https://docs.jina.ai/concepts/orchestration/scale-out/?ref=jina-ai-gmbh.ghost.io#understand-behaviors-of-replicas-and-shards-with-polling" rel="nofollow">documentation</a>.</p><h3 id="clickable-link-to-docs-openapi-endpoint-5854">Clickable link to <code>/docs</code> OpenAPI endpoint (<a href="https://github.com/jina-ai/jina/pull/5854?ref=jina-ai-gmbh.ghost.io">#5854</a>)</h3><p>When starting a Flow or a Deployment with the HTTP protocol, the <code>/docs</code> and <code>/redocs</code> links will now appear complete and can be clicked to open the browser directly from the terminal.</p><p>Previously, you would see:<br></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/jina/assets/19825685/6c1069f7-83cb-474a-91ab-ae167bb97883" class="kg-image" alt="image"></figure><p>Now:<br></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/jina/assets/19825685/c50d0acc-6f75-4395-90bf-b296bea05484" class="kg-image" alt="image"></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="improved-platform-specific-dependency-for-uvloop-5841">Improved platform-specific dependency for <code>uvloop</code>. (<a href="https://github.com/jina-ai/jina/pull/5841?ref=jina-ai-gmbh.ghost.io">#5841</a>)</h3><p>Fix installation issues when downstream dependencies try to install Jina on Windows using <code>poetry</code>.</p><h3 id="use-utf-8-encoding-when-opening-files-5821">Use <code>utf-8</code> encoding when opening files (<a href="https://github.com/jina-ai/jina/pull/5821?ref=jina-ai-gmbh.ghost.io">#5821</a>)</h3><p>Use <code>utf-8</code> encoding when opening files to fix potential problems when using Jina in Windows.</p><h3 id="fix-new-deployment-cli-5819">Fix new Deployment CLI (<a href="https://github.com/jina-ai/jina/pull/5819?ref=jina-ai-gmbh.ghost.io">#5819</a>)</h3><p>Fix the output YAML file when using <code>jina new &lt;project-name&gt; --type deployment</code>. It previously dumped an invalid Deployment YAML. The syntax has now been fixed so that it can be deployed.</p><h3 id="use-container-stop-so-that-containers-running-cuda-can-be-killed-5816">Use container <code>stop</code> so that containers running cuda can be killed (<a href="https://github.com/jina-ai/jina/pull/5816?ref=jina-ai-gmbh.ghost.io">#5816</a>)</h3><p>Use <a href="https://docker-py.readthedocs.io/en/stable/containers.html?ref=jina-ai-gmbh.ghost.io#docker.models.containers.Container.stop" rel="nofollow"><code>stop</code></a> instead of <a href="https://docker-py.readthedocs.io/en/stable/containers.html?ref=jina-ai-gmbh.ghost.io#docker.models.containers.Container.kill" rel="nofollow"><code>kill</code></a> from the <a href="https://docker-py.readthedocs.io/en/stable/index.html?ref=jina-ai-gmbh.ghost.io" rel="nofollow">Python Docker SDK</a>. This allows containerized Executors that are run with <code>conda run</code> to terminate, since conda does not propagate its captured signals to its Python subprocesses.</p><h3 id="catch-contenttypeerror-for-retry-in-post-requests-5825">Catch <code>ContentTypeError</code> for retry in post requests (<a href="https://github.com/jina-ai/jina/pull/5825?ref=jina-ai-gmbh.ghost.io">#5825</a>)</h3><p><code>ContentTypeError</code> responses in the Client will now be caught and retries applied if required.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Update Slack count (<a href="https://github.com/jina-ai/jina/pull/5842?ref=jina-ai-gmbh.ghost.io">#5842</a>)</li><li>Add storage section (<a href="https://github.com/jina-ai/jina/pull/5831?ref=jina-ai-gmbh.ghost.io">#5831</a>)</li><li>Remove layer from orchestration layer title (<a href="https://github.com/jina-ai/jina/pull/5829?ref=jina-ai-gmbh.ghost.io">#5829</a>)</li><li>Fix broken links (<a href="https://github.com/jina-ai/jina/pull/5822?ref=jina-ai-gmbh.ghost.io">#5822</a>)</li><li>Add docs for <code>jc recreate</code> (<a href="https://github.com/jina-ai/jina/pull/5815?ref=jina-ai-gmbh.ghost.io">#5815</a>)</li><li>Point to legacy <code>DocumentArray</code> docs (<a href="https://github.com/jina-ai/jina/pull/5810?ref=jina-ai-gmbh.ghost.io">#5810</a>)</li><li>Fix some English in docstrings (<a href="https://github.com/jina-ai/jina/pull/5718?ref=jina-ai-gmbh.ghost.io">#5718</a>)</li><li>Fix some links in scalability chapter (<a href="https://github.com/jina-ai/jina/pull/5809?ref=jina-ai-gmbh.ghost.io">#5809</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>notandor (<a href="https://github.com/NotAndOr?ref=jina-ai-gmbh.ghost.io">@NotAndOr</a> )</li><li>Deepankar Mahapatro (<a href="https://github.com/deepankarm?ref=jina-ai-gmbh.ghost.io">@deepankarm</a> )</li><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a> )</li><li>Tanguy Abel (<a href="https://github.com/Tanguyabel?ref=jina-ai-gmbh.ghost.io">@Tanguyabel</a> )</li><li>Nikolas Pitsillos (<a href="https://github.com/npitsillos?ref=jina-ai-gmbh.ghost.io">@npitsillos</a> )</li><li>Felix Mönckemeyer (<a href="https://github.com/NemesisFLX?ref=jina-ai-gmbh.ghost.io">@NemesisFLX</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Florian Hönicke (<a href="https://github.com/florian-hoenicke?ref=jina-ai-gmbh.ghost.io">@florian-hoenicke</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-16-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.17 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.17 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-17-update"><meta property="og:title" content="Jina 3.17 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Jina-core.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-17-update"><meta property="twitter:title" content="Jina 3.17 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Jina-core.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="fafc6cc6-ace0-4365-adc3-998f0eece9ab" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="fafc6cc6-ace0-4365-adc3-998f0eece9ab" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 07, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3170">Release Note (<code>3.17.0</code>)</h2><p>This release contains 1 new feature and 1 bug fix.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.17.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.17.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.17.0) Release time: 2023-06-06 15:25:15 This release contains 1 new feature and 1 bug fix.🆕 FeaturesFlows now compatible with DocArray v2 (#5861)Finally, Flows and Deployments…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/1a43e4f27b372ba69a65192f09bffc9abb9a82b40227b4a363d25e39edfc7701/jina-ai/jina/releases/tag/v3.17.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="flows-now-compatible-with-docarray-v2-5861">Flows now compatible with DocArray v2 (<a href="https://github.com/jina-ai/jina/pull/5861?ref=jina-ai-gmbh.ghost.io">#5861</a>)</h3><p>Finally, Flows and Deployments are fully compatible with the new DocArray version (above 0.30.0). This includes all supported protocols and features, namely <code>http</code>, <code>grpc</code> and <code>websocket</code> for <code>Flow</code> and <code>http</code> and <code>grpc</code> for <code>Deployment</code>.</p><p>Now you can enjoy the capacity and expressivity of the new <code>DocArray</code> together with the performance, scalability and richness of Jina.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocList
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="861c74ab-fa04-4a73-971b-71a2bc6109f1" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="861c74ab-fa04-4a73-971b-71a2bc6109f1" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.17 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 07, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3170">Release Note (<code>3.17.0</code>)</h2><p>This release contains 1 new feature and 1 bug fix.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.17.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.17.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.17.0) Release time: 2023-06-06 15:25:15 This release contains 1 new feature and 1 bug fix.🆕 FeaturesFlows now compatible with DocArray v2 (#5861)Finally, Flows and Deployments…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/1a43e4f27b372ba69a65192f09bffc9abb9a82b40227b4a363d25e39edfc7701/jina-ai/jina/releases/tag/v3.17.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="flows-now-compatible-with-docarray-v2-5861">Flows now compatible with DocArray v2 (<a href="https://github.com/jina-ai/jina/pull/5861?ref=jina-ai-gmbh.ghost.io">#5861</a>)</h3><p>Finally, Flows and Deployments are fully compatible with the new DocArray version (above 0.30.0). This includes all supported protocols and features, namely <code>http</code>, <code>grpc</code> and <code>websocket</code> for <code>Flow</code> and <code>http</code> and <code>grpc</code> for <code>Deployment</code>.</p><p>Now you can enjoy the capacity and expressivity of the new <code>DocArray</code> together with the performance, scalability and richness of Jina.</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocList
 <span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Flow, Executor, requests
 
 <span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="b72c0735-b234-4b39-a066-a65c170fbd5e" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="b72c0735-b234-4b39-a066-a65c170fbd5e" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 22, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3180">Release Note (<code>3.18.0</code>)</h2><p>This release contains 2 new features, 4 bug fixes, and 2 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.18.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.18.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.18.0) Release time: 2023-06-22 13:32:50 This release contains 2 new features, 4 bug fixes, and 2 documentation improvements.🆕 FeaturesStreaming single Document with HTTP SSE for…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/bec6779e59f11d858ac2d9af687dda72d2908a563bb620a608f5db8565a69755/jina-ai/jina/releases/tag/v3.18.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="streaming-single-document-with-http-sse-for-deployment-5899">Streaming single Document with HTTP SSE for Deployment (<a href="https://github.com/jina-ai/jina/pull/5899?ref=jina-ai-gmbh.ghost.io">#5899</a>)</h3><p>In this release, we have added support for Server-Sent Events (SSE) to Jina's HTTP protocol with the <code>Deployment</code> orchestration. A Jina server can now stream single Documents to a client, one at a time. This is useful for applications that require a continuous stream of data, such as chatbots (using Large Language Models) or real-time translation.</p><p>Simply define an endpoint function that receives a single Document and yields Documents one by one:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests, Document, Deployment
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="d014912a-7fa1-4fee-8671-84cdd3686be2" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="d014912a-7fa1-4fee-8671-84cdd3686be2" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.18 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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A Jina server can now stream single Documents to a client, one at a time. This is useful for applications that require a continuous stream of data, such as chatbots (using Large Language Models) or real-time translation.</p><p>Simply define an endpoint function that receives a single Document and yields Documents one by one:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests, Document, Deployment
 
 <span class="hljs-keyword">class</span> <span class="hljs-title class_">MyExecutor</span>(<span class="hljs-title class_ inherited__">Executor</span>):
 <span class="hljs-meta">    @requests(<span class="hljs-params">on=<span class="hljs-string">'/hello'</span></span>)</span>
@@ -64,4 +64,4 @@
 d = Deployment(uses=MyExec, shards=<span class="hljs-number">2</span>)
 <span class="hljs-keyword">with</span> d:
     res = d.post(on=<span class="hljs-string">'/'</span>, inputs=DocList[MyDoc]([MyDoc(text=<span class="hljs-string">'hey ha'</span>, embedding=np.random.rand(<span class="hljs-number">128</span>))]))
-    <span class="hljs-keyword">assert</span> <span class="hljs-built_in">len</span>(res) == <span class="hljs-number">1</span></code></pre><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>README revamp to put more emphasis on generative AI use cases (<a href="https://github.com/jina-ai/jina/pull/5895?ref=jina-ai-gmbh.ghost.io">#5895</a>)</li><li>Fix links in docs (<a href="https://github.com/jina-ai/jina/pull/5909?ref=jina-ai-gmbh.ghost.io">#5909</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a> )</li><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-18-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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\ No newline at end of file
+    <span class="hljs-keyword">assert</span> <span class="hljs-built_in">len</span>(res) == <span class="hljs-number">1</span></code></pre><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>README revamp to put more emphasis on generative AI use cases (<a href="https://github.com/jina-ai/jina/pull/5895?ref=jina-ai-gmbh.ghost.io">#5895</a>)</li><li>Fix links in docs (<a href="https://github.com/jina-ai/jina/pull/5909?ref=jina-ai-gmbh.ghost.io">#5909</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Alex Cureton-Griffiths (<a href="https://github.com/alexcg1?ref=jina-ai-gmbh.ghost.io">@alexcg1</a> )</li><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-18-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.19.1 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.19.1 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-19-1-update"><meta property="og:title" content="Jina 3.19.1 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Jina-core.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-19-1-update"><meta property="twitter:title" content="Jina 3.19.1 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Jina-core.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 19, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3191">Release Note (3.19.1)</h2><p>This release contains 5 bug fixes.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.19.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.19.1 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.19.1) Release time: 2023-07-19 07:54:28 This release contains 5 bug fixes.🐞 Bug FixesDynamic batching with docarray&gt;=0.30 (#5970)Dynamic batching requests for Executors were no…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/18609aa974e43da017db0fca387677c0e736ecdce6c36ee15d4420d62afc1aeb/jina-ai/jina/releases/tag/v3.19.1" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="dynamic-batching-with-docarray030-5970">Dynamic batching with docarray&gt;=0.30 (<a href="https://github.com/jina-ai/jina/pull/5970?ref=jina-ai-gmbh.ghost.io">#5970</a>)</h3><p>Dynamic batching requests for Executors were not working when using docarray&gt;=0.30.0. This fix makes this feature fully compatible with newer versions of docarray.</p><h3 id="monitoring-validation-error-with-docarray0305965">Monitoring validation error with docarray&gt;=0.30(<a href="https://github.com/jina-ai/jina/pull/5965?ref=jina-ai-gmbh.ghost.io">#5965</a>)</h3><p>When using docarray&gt;=0.30 in combination with monitoring, there was a risk of getting a validation error because the input and output schemas were not properly considered.</p><h3 id="fail-fast-when-no-valid-schemas-5962">Fail fast when no valid schemas (<a href="https://github.com/jina-ai/jina/pull/5962?ref=jina-ai-gmbh.ghost.io">#5962</a>)</h3><p>When no valid schemas were used, Executors sometimes failed to load, but the Gateway would continue to try getting the endpoints from them until it timed out. Now, everything will stop faster without the long wait.</p><h3 id="properly-handle-multiprotocol-deployments-to-kubernetes-5961">Properly handle multiprotocol deployments to Kubernetes (<a href="https://github.com/jina-ai/jina/pull/5961?ref=jina-ai-gmbh.ghost.io">#5961</a>)</h3><p>When converting a <code>Deployment</code> using multiple protocols to Kubernetes YAML, the resulting services did not use or expose the ports and protocols as expected. This has now been fixed.</p><h3 id="fix-grpc-connectivity-issues-for-health-check-5972">Fix gRPC connectivity issues for health check (<a href="https://github.com/jina-ai/jina/pull/5972?ref=jina-ai-gmbh.ghost.io">#5972</a>)</h3><p>Fixed issues for Flow not being able to health-check Executors due to HTTP proxy used.</p><p>Now this is changed, and when doing:</p><pre><code class="language-Python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 19, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3191">Release Note (3.19.1)</h2><p>This release contains 5 bug fixes.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.19.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.19.1 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.19.1) Release time: 2023-07-19 07:54:28 This release contains 5 bug fixes.🐞 Bug FixesDynamic batching with docarray&gt;=0.30 (#5970)Dynamic batching requests for Executors were no…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/18609aa974e43da017db0fca387677c0e736ecdce6c36ee15d4420d62afc1aeb/jina-ai/jina/releases/tag/v3.19.1" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="dynamic-batching-with-docarray030-5970">Dynamic batching with docarray&gt;=0.30 (<a href="https://github.com/jina-ai/jina/pull/5970?ref=jina-ai-gmbh.ghost.io">#5970</a>)</h3><p>Dynamic batching requests for Executors were not working when using docarray&gt;=0.30.0. This fix makes this feature fully compatible with newer versions of docarray.</p><h3 id="monitoring-validation-error-with-docarray0305965">Monitoring validation error with docarray&gt;=0.30(<a href="https://github.com/jina-ai/jina/pull/5965?ref=jina-ai-gmbh.ghost.io">#5965</a>)</h3><p>When using docarray&gt;=0.30 in combination with monitoring, there was a risk of getting a validation error because the input and output schemas were not properly considered.</p><h3 id="fail-fast-when-no-valid-schemas-5962">Fail fast when no valid schemas (<a href="https://github.com/jina-ai/jina/pull/5962?ref=jina-ai-gmbh.ghost.io">#5962</a>)</h3><p>When no valid schemas were used, Executors sometimes failed to load, but the Gateway would continue to try getting the endpoints from them until it timed out. Now, everything will stop faster without the long wait.</p><h3 id="properly-handle-multiprotocol-deployments-to-kubernetes-5961">Properly handle multiprotocol deployments to Kubernetes (<a href="https://github.com/jina-ai/jina/pull/5961?ref=jina-ai-gmbh.ghost.io">#5961</a>)</h3><p>When converting a <code>Deployment</code> using multiple protocols to Kubernetes YAML, the resulting services did not use or expose the ports and protocols as expected. This has now been fixed.</p><h3 id="fix-grpc-connectivity-issues-for-health-check-5972">Fix gRPC connectivity issues for health check (<a href="https://github.com/jina-ai/jina/pull/5972?ref=jina-ai-gmbh.ghost.io">#5972</a>)</h3><p>Fixed issues for Flow not being able to health-check Executors due to HTTP proxy used.</p><p>Now this is changed, and when doing:</p><pre><code class="language-Python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment
 
 d = Deployment(protocol=[<span class="hljs-string">'grpc'</span>, <span class="hljs-string">'http'</span>])
-d.to_kubernetes_yaml(<span class="hljs-string">'./k8s-deployment'</span>)</code></pre><p>You will get a YAML where the two services expose each protocol.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-19-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+d.to_kubernetes_yaml(<span class="hljs-string">'./k8s-deployment'</span>)</code></pre><p>You will get a YAML where the two services expose each protocol.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-19-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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\ No newline at end of file
diff --git a/news/jina-3-19-update/index.html b/news/jina-3-19-update/index.html
index 3f9ffa0579e..f65399a341b 100644
--- a/news/jina-3-19-update/index.html
+++ b/news/jina-3-19-update/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.19 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.19 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-19-update"><meta property="og:title" content="Jina 3.19 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Jina-core--2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-19-update"><meta property="twitter:title" content="Jina 3.19 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Jina-core--2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.19 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.19 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-19-update"><meta property="og:title" content="Jina 3.19 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Jina-core--2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-19-update"><meta property="twitter:title" content="Jina 3.19 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Jina-core--2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><script src="https://jina-ai-gmbh.ghost.io/public/cards.min.js" async=""></script><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 10, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3190">Release Note (<code>3.19.0</code>)</h2><p>This release contains 3 new features, 4 bug fixes, and 3 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.19.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.19.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.19.0) Release time: 2023-07-10 09:01:16 This release contains 3 new features, 4 bug fixes, and 3 documentation improvements.🆕 FeaturesJina is now compatible with all versions o…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/03e09f359a883faa438aa5faf5e018734ad1ee684383bc46166f56e96898375f/jina-ai/jina/releases/tag/v3.19.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="jina-is-now-compatible-with-all-versions-of-docarray-unpin-version-in-requirements-5941">Jina is now compatible with all versions of DocArray. Unpin version in requirements (<a href="https://github.com/jina-ai/jina/pull/5941?ref=jina-ai-gmbh.ghost.io">#5941</a>)</h3><p>Jina is now fully compatible with <code>docarray&gt;=0.30</code>, which uncaps the version requirement.</p><p>By default, Jina will install the latest DocArray version, however, it remains compatible with the older version. If you still want to use the old version and syntax, manually install <code>docarray&lt;0.30</code> or pin the requirement in your project.</p><pre><code class="language-Python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocList
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.19 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 10, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3190">Release Note (<code>3.19.0</code>)</h2><p>This release contains 3 new features, 4 bug fixes, and 3 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.19.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.19.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.19.0) Release time: 2023-07-10 09:01:16 This release contains 3 new features, 4 bug fixes, and 3 documentation improvements.🆕 FeaturesJina is now compatible with all versions o…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/03e09f359a883faa438aa5faf5e018734ad1ee684383bc46166f56e96898375f/jina-ai/jina/releases/tag/v3.19.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="jina-is-now-compatible-with-all-versions-of-docarray-unpin-version-in-requirements-5941">Jina is now compatible with all versions of DocArray. Unpin version in requirements (<a href="https://github.com/jina-ai/jina/pull/5941?ref=jina-ai-gmbh.ghost.io">#5941</a>)</h3><p>Jina is now fully compatible with <code>docarray&gt;=0.30</code>, which uncaps the version requirement.</p><p>By default, Jina will install the latest DocArray version, however, it remains compatible with the older version. If you still want to use the old version and syntax, manually install <code>docarray&lt;0.30</code> or pin the requirement in your project.</p><pre><code class="language-Python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocList
 <span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Deployment, Executor, requests
 
 <span class="hljs-keyword">class</span> <span class="hljs-title class_">MyDoc</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
diff --git a/news/jina-3-20-1-update/index.html b/news/jina-3-20-1-update/index.html
index 7c3baad310a..4f1abaac532 100644
--- a/news/jina-3-20-1-update/index.html
+++ b/news/jina-3-20-1-update/index.html
@@ -1,6 +1,6 @@
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.20.1 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.20.1 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-20-1-update"><meta property="og:title" content="Jina 3.20.1 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/20230811_143532_0000.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-20-1-update"><meta property="twitter:title" content="Jina 3.20.1 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/20230811_143532_0000.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 11, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3201">Release Note (<code>3.20.1</code>)</h2><p>This release contains 2 bug fixes and 2 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Multimodal AI services &amp; pipelines with cloud-native stack: gRPC, Kubernetes, Docker, OpenTelemetry, Prometheus, Jaeger, etc.</div><div class="kg-bookmark-description">🔮 Multimodal AI services &amp;amp; pipelines with cloud-native stack: gRPC, Kubernetes, Docker, OpenTelemetry, Prometheus, Jaeger, etc. - GitHub - jina-ai/jina: 🔮 Multimodal AI services &amp;amp; pipelines…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/09d66a57-001b-4834-b685-c72e3dc3e1ba" alt=""></div></a></figure><h2 id="%F0%9F%90%9Ebug-fixes">🐞Bug Fixes</h2><h3 id="make-gateway-load-balancer-stream-results-6024">Make Gateway load balancer stream results (<a href="https://github.com/jina-ai/jina/pull/6024?ref=jina-ai-gmbh.ghost.io">#6024</a>)</h3><p><a href="https://docs.jina.ai/concepts/serving/executor/add-endpoints/?ref=jina-ai-gmbh.ghost.io#streaming-endpoints" rel="nofollow">Streaming endpoints</a> in Executors can be deployed behind a Gateway (when using <code>include_gateway=True</code> in <code>Deployment</code>).</p><p>In this case, the Gateway acts as a load balancer. However, prior to this release, when the <code>HTTP</code> protocol is used, the Gateway would wait until all chunks of the responses had been streamed from the Executor.</p><p>Only when all the chunks were received would it send them back to the client. This resulted in delays and suppressed the desired behavior of a streaming endpoint (namely, displaying tokens streamed from an LLM with a typewriter effect).</p><p>This release fixes this issue by making the Gateway stream chunks of responses from the forwarded request as soon as they are received from the Executor.</p><p>No matter whether you are setting <code>include_gateway</code> to <code>True</code> or <code>False</code> in <code>Deployment</code>, streaming endpoints should give the same desired behavior.</p><h3 id="fix-deeply-nested-schemas-support-in-executors-and-flows-6021">Fix deeply nested Schemas support in Executors and Flows (<a href="https://github.com/jina-ai/jina/pull/6021?ref=jina-ai-gmbh.ghost.io">#6021</a>)</h3><p>When a deeply nested schema (DocArray schema with 2+ levels of nesting) was specified as an input or output of an Executor endpoint, and the Executor was deployed in a Flow, the Gateway would fail to fetch information about the endpoints and their input/output schemas:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> typing <span class="hljs-keyword">import</span> <span class="hljs-type">List</span>, <span class="hljs-type">Optional</span>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 11, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3201">Release Note (<code>3.20.1</code>)</h2><p>This release contains 2 bug fixes and 2 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Multimodal AI services &amp; pipelines with cloud-native stack: gRPC, Kubernetes, Docker, OpenTelemetry, Prometheus, Jaeger, etc.</div><div class="kg-bookmark-description">🔮 Multimodal AI services &amp;amp; pipelines with cloud-native stack: gRPC, Kubernetes, Docker, OpenTelemetry, Prometheus, Jaeger, etc. - GitHub - jina-ai/jina: 🔮 Multimodal AI services &amp;amp; pipelines…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/09d66a57-001b-4834-b685-c72e3dc3e1ba" alt=""></div></a></figure><h2 id="%F0%9F%90%9Ebug-fixes">🐞Bug Fixes</h2><h3 id="make-gateway-load-balancer-stream-results-6024">Make Gateway load balancer stream results (<a href="https://github.com/jina-ai/jina/pull/6024?ref=jina-ai-gmbh.ghost.io">#6024</a>)</h3><p><a href="https://docs.jina.ai/concepts/serving/executor/add-endpoints/?ref=jina-ai-gmbh.ghost.io#streaming-endpoints" rel="nofollow">Streaming endpoints</a> in Executors can be deployed behind a Gateway (when using <code>include_gateway=True</code> in <code>Deployment</code>).</p><p>In this case, the Gateway acts as a load balancer. However, prior to this release, when the <code>HTTP</code> protocol is used, the Gateway would wait until all chunks of the responses had been streamed from the Executor.</p><p>Only when all the chunks were received would it send them back to the client. This resulted in delays and suppressed the desired behavior of a streaming endpoint (namely, displaying tokens streamed from an LLM with a typewriter effect).</p><p>This release fixes this issue by making the Gateway stream chunks of responses from the forwarded request as soon as they are received from the Executor.</p><p>No matter whether you are setting <code>include_gateway</code> to <code>True</code> or <code>False</code> in <code>Deployment</code>, streaming endpoints should give the same desired behavior.</p><h3 id="fix-deeply-nested-schemas-support-in-executors-and-flows-6021">Fix deeply nested Schemas support in Executors and Flows (<a href="https://github.com/jina-ai/jina/pull/6021?ref=jina-ai-gmbh.ghost.io">#6021</a>)</h3><p>When a deeply nested schema (DocArray schema with 2+ levels of nesting) was specified as an input or output of an Executor endpoint, and the Executor was deployed in a Flow, the Gateway would fail to fetch information about the endpoints and their input/output schemas:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> typing <span class="hljs-keyword">import</span> <span class="hljs-type">List</span>, <span class="hljs-type">Optional</span>
 <span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc, DocList
 <span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, Flow, requests
 
@@ -43,4 +43,4 @@
         on=<span class="hljs-string">'/endpoint'</span>, inputs=RootDoc(text=<span class="hljs-string">'hello'</span>), return_type=DocList[RootDoc]
     )</code></pre><pre><code class="hljs language-python-repl"><span class="hljs-meta prompt_">...</span>
 2023-08-07 02:49:32,529 topology_graph.py[608] WARNING Getting endpoints failed: 'definitions'. Waiting for another trial
-</code></pre><p>This was due to an internal utility function failing to convert such deeply nested JSON schemas to DocArray models.</p><p>This release fixes the issue by propagating global schema definitions when generating models for nested schemas.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Remove extra backtick in <code>create-app.md</code> (<a href="https://github.com/jina-ai/jina/pull/6023?ref=jina-ai-gmbh.ghost.io">#6023</a>)</li><li>Fix streaming endpoint reference in README (<a href="https://github.com/jina-ai/jina/pull/6017?ref=jina-ai-gmbh.ghost.io">#6017</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Saba Sturua (<a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a>)</li><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Naymul Islam (<a href="https://github.com/ai-naymul?ref=jina-ai-gmbh.ghost.io">@ai-naymul</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-20-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
+</code></pre><p>This was due to an internal utility function failing to convert such deeply nested JSON schemas to DocArray models.</p><p>This release fixes the issue by propagating global schema definitions when generating models for nested schemas.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Remove extra backtick in <code>create-app.md</code> (<a href="https://github.com/jina-ai/jina/pull/6023?ref=jina-ai-gmbh.ghost.io">#6023</a>)</li><li>Fix streaming endpoint reference in README (<a href="https://github.com/jina-ai/jina/pull/6017?ref=jina-ai-gmbh.ghost.io">#6017</a>)</li></ul><h2 id="%F0%9F%A4%98-contributors">🤘 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Saba Sturua (<a href="https://github.com/jupyterjazz?ref=jina-ai-gmbh.ghost.io">@jupyterjazz</a>)</li><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Naymul Islam (<a href="https://github.com/ai-naymul?ref=jina-ai-gmbh.ghost.io">@ai-naymul</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-20-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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diff --git a/news/jina-3-20-2-update/index.html b/news/jina-3-20-2-update/index.html
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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.20.2 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.20.2 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-20-2-update"><meta property="og:title" content="Jina 3.20.2 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Jina-core--2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-20-2-update"><meta property="twitter:title" content="Jina 3.20.2 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Jina-core--2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.20.2 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.20.2 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-20-2-update"><meta property="og:title" content="Jina 3.20.2 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Jina-core--2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-20-2-update"><meta property="twitter:title" content="Jina 3.20.2 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Jina-core--2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.20.2 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 06, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3202">Release Note (<code>3.20.2</code>)</h2><p>This release contains 1 bug fix and 1 refactoring.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Multimodal AI services &amp; pipelines with cloud-native stack: gRPC, Kubernetes, Docker, OpenTelemetry, Prometheus, Jaeger, etc.</div><div class="kg-bookmark-description">🔮 Multimodal AI services &amp;amp; pipelines with cloud-native stack: gRPC, Kubernetes, Docker, OpenTelemetry, Prometheus, Jaeger, etc. - GitHub - jina-ai/jina: 🔮 Multimodal AI services &amp;amp; pipelines…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/09d66a57-001b-4834-b685-c72e3dc3e1ba" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-install-issue-6037">Fix install issue (<a href="https://github.com/jina-ai/jina/pull/6037?ref=jina-ai-gmbh.ghost.io">#6037</a>)</h3><p>Fix an installation issue that appeared because a new release of <code>opentelemetry-sdk</code> prevented <code>pip</code> from finding compatible libraries.</p><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="refactor-the-setuppy-file-6038">Refactor the setup.py file (<a href="https://github.com/jina-ai/jina/pull/6038?ref=jina-ai-gmbh.ghost.io">#6038</a>)</h3><p>Some hard-coded strings were replaced with constants to improve code readability. </p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a> )</li><li>Naymul Islam (<a href="https://github.com/ai-naymul?ref=jina-ai-gmbh.ghost.io">@ai-naymul</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-20-2-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.20.2 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 06, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3202">Release Note (<code>3.20.2</code>)</h2><p>This release contains 1 bug fix and 1 refactoring.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Multimodal AI services &amp; pipelines with cloud-native stack: gRPC, Kubernetes, Docker, OpenTelemetry, Prometheus, Jaeger, etc.</div><div class="kg-bookmark-description">🔮 Multimodal AI services &amp;amp; pipelines with cloud-native stack: gRPC, Kubernetes, Docker, OpenTelemetry, Prometheus, Jaeger, etc. - GitHub - jina-ai/jina: 🔮 Multimodal AI services &amp;amp; pipelines…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/09d66a57-001b-4834-b685-c72e3dc3e1ba" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-install-issue-6037">Fix install issue (<a href="https://github.com/jina-ai/jina/pull/6037?ref=jina-ai-gmbh.ghost.io">#6037</a>)</h3><p>Fix an installation issue that appeared because a new release of <code>opentelemetry-sdk</code> prevented <code>pip</code> from finding compatible libraries.</p><h2 id="%E2%9A%99-refactoring">⚙ Refactoring</h2><h3 id="refactor-the-setuppy-file-6038">Refactor the setup.py file (<a href="https://github.com/jina-ai/jina/pull/6038?ref=jina-ai-gmbh.ghost.io">#6038</a>)</h3><p>Some hard-coded strings were replaced with constants to improve code readability. </p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a> )</li><li>Naymul Islam (<a href="https://github.com/ai-naymul?ref=jina-ai-gmbh.ghost.io">@ai-naymul</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-20-2-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.20.3 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.20.3 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-20-3-update"><meta property="og:title" content="Jina 3.20.3 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Jina-core--3-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-20-3-update"><meta property="twitter:title" content="Jina 3.20.3 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Jina-core--3-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.20.3 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.20.3 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-20-3-update"><meta property="og:title" content="Jina 3.20.3 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Jina-core--3-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-20-3-update"><meta property="twitter:title" content="Jina 3.20.3 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Jina-core--3-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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We have fixed this by securing access to <code>__fields__</code> when dynamically creating these pydantic models.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Narek Amirbekian (<a href="https://github.com/NarekA?ref=jina-ai-gmbh.ghost.io">@NarekA</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-20-3-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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\ No newline at end of file
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.20.3 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 07, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3203">Release Note (<code>3.20.3</code>)</h2><p>This release contains 1 bug fix.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.20.3?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.20.3 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.20.3) Release time: 2023-09-07 08:46:43 This release contains 1 bug fix.🐞 Bug FixesSkip doc attributes in annotations but not in fields (#6035)When deploying an Executor insi…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/14f7bbdbfe0b51a6e9a063fbd6b02ff83a7be18f62409ca98fe22a6004eb8a94/jina-ai/jina/releases/tag/v3.20.3" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="skip-doc-attributes-in-annotations-but-not-in-fields-6035">Skip doc attributes in annotations but not in fields (<a href="https://github.com/jina-ai/jina/pull/6035?ref=jina-ai-gmbh.ghost.io">#6035</a>)</h3><p>When deploying an Executor inside a Flow with a <code>BaseDoc</code> model that has any attribute with a <code>ClassVar</code> value, the service would fail to initialize because the Gateway could not properly create the schemas. We have fixed this by securing access to <code>__fields__</code> when dynamically creating these pydantic models.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Narek Amirbekian (<a href="https://github.com/NarekA?ref=jina-ai-gmbh.ghost.io">@NarekA</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-20-3-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.20 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.20 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-20-update"><meta property="og:title" content="Jina 3.20 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Jina-core--5-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-20-update"><meta property="twitter:title" content="Jina 3.20 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Jina-core--5-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 04, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3200">Release Note (<code>3.20.0</code>)</h2><p>This release contains 5 new features, 3 bug fixes and 8 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.20.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.20.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.20.0) Release time: 2023-08-04 08:58:38This release contains 5 new features 3 bug fixes and 8 documentation improvements. 🆕 FeaturesExecutor can work on single documents (#5991)…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/9a337b40558f051a422eed6da1fe44dfcde78f0b06ca059279329e9adeb9450e/jina-ai/jina/releases/tag/v3.20.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="executor-can-work-on-single-documents-5991">Executor can work on single documents (<a href="https://github.com/jina-ai/jina/pull/5991?ref=jina-ai-gmbh.ghost.io">#5991</a>)</h3><p>Executors no longer need to work solely on a <code>DocList</code>, but can expose endpoints for working on single documents.</p><p>For this, the method decorated by <code>requests</code> must take a <code>doc</code> argument and an annotation for the input and output types:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.20 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 04, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3200">Release Note (<code>3.20.0</code>)</h2><p>This release contains 5 new features, 3 bug fixes and 8 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.20.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.20.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.20.0) Release time: 2023-08-04 08:58:38This release contains 5 new features 3 bug fixes and 8 documentation improvements. 🆕 FeaturesExecutor can work on single documents (#5991)…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/9a337b40558f051a422eed6da1fe44dfcde78f0b06ca059279329e9adeb9450e/jina-ai/jina/releases/tag/v3.20.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="executor-can-work-on-single-documents-5991">Executor can work on single documents (<a href="https://github.com/jina-ai/jina/pull/5991?ref=jina-ai-gmbh.ghost.io">#5991</a>)</h3><p>Executors no longer need to work solely on a <code>DocList</code>, but can expose endpoints for working on single documents.</p><p>For this, the method decorated by <code>requests</code> must take a <code>doc</code> argument and an annotation for the input and output types:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, requests
 <span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDoc
 
 <span class="hljs-keyword">class</span> <span class="hljs-title class_">MyInputDocument</span>(<span class="hljs-title class_ inherited__">BaseDoc</span>):
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.21.0 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.21.0 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-21-0-update"><meta property="og:title" content="Jina 3.21.0 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Image-Jina-dark.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-21-0-update"><meta property="twitter:title" content="Jina 3.21.0 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Image-Jina-dark.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 26, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3210">Release Note (<code>3.21.0</code>)</h2><p>This release contains 1 new feature, 4 bug fixes, and 1 documentation improvement.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.21.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.21.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.21.0) Release time: 2023-09-26 15:54:28 This release contains 1 new feature, 4 bug fixes, and 1 documentation improvement.🆕 FeaturesAdd return_type parameter to gateway streamer…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/1877d2f667bb48c4e89982137b897330112ecd4c21a092cf9058fce5791e4474/jina-ai/jina/releases/tag/v3.21.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="add-returntype-parameter-to-gateway-streamer-methods-6027">Add <code>return_type</code> parameter to gateway streamer methods (<a href="https://github.com/jina-ai/jina/pull/6027?ref=jina-ai-gmbh.ghost.io">#6027</a>)</h3><p>By default, <code>GatewayStreamer</code> will fetch executor input and output schemas and reconstruct docarray models dynamically. The output schemas will be used to cast the responses at the gateway level.</p><p>Although the cast responses are nearly identical to the original schemas defined at the executor level, they might fail some checks. For example, if the gateway receives a document <code>doc</code> from an executor with output <code>MyDoc</code>, the following check will fail:</p><pre><code class="language-Python">assert isinstance(doc, MyDoc)</code></pre><p>Similarly, adding <code>doc</code> to a <code>DocList[MyDoc]</code> will fail the type checks.</p><p>To prevent this, the user of a <code>GatewayStreamer</code> can now use the <code>return_type</code> parameter to explicitly specify the type that will be used to cast the response. Output responses received from gateway streamer methods will always match the specified return type.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-topology-schema-validation-6057">Fix topology schema validation (<a href="https://github.com/jina-ai/jina/pull/6057?ref=jina-ai-gmbh.ghost.io">#6057</a>)</h3><p>Previously, if the endpoint model schemas of different Executors in a Flow did not match exactly, the Flow would fail to start, Even if the difference was as small as a different default value, it would still give rise to this error.</p><p>We have fixed this bug by relaxing the model schema checking to only verify that the types of properties match.</p><h3 id="fix-consensus-module-memory-leak-6054">Fix consensus module memory leak (<a href="https://github.com/jina-ai/jina/pull/6054?ref=jina-ai-gmbh.ghost.io">#6054</a>)</h3><p>In the consensus <code>golang</code> module, some allocated strings were not being properly released. We have repaired this.</p><h3 id="document-casting-in-flow-gateway-6032">Document casting in Flow gateway (<a href="https://github.com/jina-ai/jina/pull/6032?ref=jina-ai-gmbh.ghost.io">#6032</a>)</h3><p>This bug is related to <a href="https://github.com/jina-ai/jina/pull/6027?ref=jina-ai-gmbh.ghost.io">#6027</a>. We now use the <code>return_type</code> parameter in <code>GatewayStreamer</code> to ensure that Documents received at the gateway level are properly cast to the correct schema. This prevents validation and serialization errors that previously occurred.</p><h3 id="remove-sandbox-6047">Remove sandbox (<a href="https://github.com/jina-ai/jina/pull/6047?ref=jina-ai-gmbh.ghost.io">#6047</a>)</h3><p>Remove support for deploying Executors in the Jina Cloud sandbox, since the sandbox has been deprecated.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Make example copy-pastable (<a href="https://github.com/jina-ai/jina/pull/6052?ref=jina-ai-gmbh.ghost.io">#6052</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Naymul Islam (<a href="https://github.com/ai-naymul?ref=jina-ai-gmbh.ghost.io">@ai-naymul</a>)</li><li>Deepankar Mahapatro (<a href="https://github.com/deepankarm?ref=jina-ai-gmbh.ghost.io">@deepankarm</a>)</li><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Han Xiao (<a href="https://github.com/hanxiao?ref=jina-ai-gmbh.ghost.io">@hanxiao</a>)</li><li>XXIV (<a href="https://github.com/thechampagne?ref=jina-ai-gmbh.ghost.io">@thechampagne</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-21-0-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 26, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3210">Release Note (<code>3.21.0</code>)</h2><p>This release contains 1 new feature, 4 bug fixes, and 1 documentation improvement.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.21.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.21.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.21.0) Release time: 2023-09-26 15:54:28 This release contains 1 new feature, 4 bug fixes, and 1 documentation improvement.🆕 FeaturesAdd return_type parameter to gateway streamer…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/1877d2f667bb48c4e89982137b897330112ecd4c21a092cf9058fce5791e4474/jina-ai/jina/releases/tag/v3.21.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="add-returntype-parameter-to-gateway-streamer-methods-6027">Add <code>return_type</code> parameter to gateway streamer methods (<a href="https://github.com/jina-ai/jina/pull/6027?ref=jina-ai-gmbh.ghost.io">#6027</a>)</h3><p>By default, <code>GatewayStreamer</code> will fetch executor input and output schemas and reconstruct docarray models dynamically. The output schemas will be used to cast the responses at the gateway level.</p><p>Although the cast responses are nearly identical to the original schemas defined at the executor level, they might fail some checks. For example, if the gateway receives a document <code>doc</code> from an executor with output <code>MyDoc</code>, the following check will fail:</p><pre><code class="language-Python">assert isinstance(doc, MyDoc)</code></pre><p>Similarly, adding <code>doc</code> to a <code>DocList[MyDoc]</code> will fail the type checks.</p><p>To prevent this, the user of a <code>GatewayStreamer</code> can now use the <code>return_type</code> parameter to explicitly specify the type that will be used to cast the response. Output responses received from gateway streamer methods will always match the specified return type.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-topology-schema-validation-6057">Fix topology schema validation (<a href="https://github.com/jina-ai/jina/pull/6057?ref=jina-ai-gmbh.ghost.io">#6057</a>)</h3><p>Previously, if the endpoint model schemas of different Executors in a Flow did not match exactly, the Flow would fail to start, Even if the difference was as small as a different default value, it would still give rise to this error.</p><p>We have fixed this bug by relaxing the model schema checking to only verify that the types of properties match.</p><h3 id="fix-consensus-module-memory-leak-6054">Fix consensus module memory leak (<a href="https://github.com/jina-ai/jina/pull/6054?ref=jina-ai-gmbh.ghost.io">#6054</a>)</h3><p>In the consensus <code>golang</code> module, some allocated strings were not being properly released. We have repaired this.</p><h3 id="document-casting-in-flow-gateway-6032">Document casting in Flow gateway (<a href="https://github.com/jina-ai/jina/pull/6032?ref=jina-ai-gmbh.ghost.io">#6032</a>)</h3><p>This bug is related to <a href="https://github.com/jina-ai/jina/pull/6027?ref=jina-ai-gmbh.ghost.io">#6027</a>. We now use the <code>return_type</code> parameter in <code>GatewayStreamer</code> to ensure that Documents received at the gateway level are properly cast to the correct schema. This prevents validation and serialization errors that previously occurred.</p><h3 id="remove-sandbox-6047">Remove sandbox (<a href="https://github.com/jina-ai/jina/pull/6047?ref=jina-ai-gmbh.ghost.io">#6047</a>)</h3><p>Remove support for deploying Executors in the Jina Cloud sandbox, since the sandbox has been deprecated.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Make example copy-pastable (<a href="https://github.com/jina-ai/jina/pull/6052?ref=jina-ai-gmbh.ghost.io">#6052</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Naymul Islam (<a href="https://github.com/ai-naymul?ref=jina-ai-gmbh.ghost.io">@ai-naymul</a>)</li><li>Deepankar Mahapatro (<a href="https://github.com/deepankarm?ref=jina-ai-gmbh.ghost.io">@deepankarm</a>)</li><li>AlaeddineAbdessalem (<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">@alaeddine-13</a>)</li><li>Han Xiao (<a href="https://github.com/hanxiao?ref=jina-ai-gmbh.ghost.io">@hanxiao</a>)</li><li>XXIV (<a href="https://github.com/thechampagne?ref=jina-ai-gmbh.ghost.io">@thechampagne</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-21-0-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.21.1 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.21.1 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-21-1-update"><meta property="og:title" content="Jina 3.21.1 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Image-Jina-dark-1.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-21-1-update"><meta property="twitter:title" content="Jina 3.21.1 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Image-Jina-dark-1.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.21.1 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.21.1 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-21-1-update"><meta property="og:title" content="Jina 3.21.1 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Image-Jina-dark-1.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-21-1-update"><meta property="twitter:title" content="Jina 3.21.1 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Image-Jina-dark-1.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="6ab50bb3-d9c8-495e-8bb8-41ea4463cf64" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="6ab50bb3-d9c8-495e-8bb8-41ea4463cf64" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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This has been fixed by making sure that only one model instance is served for each model name.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-21-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 29, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3211">Release Note (<code>3.21.1</code>)</h2><p>This release contains 1 bug fix.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-issue-with-same-doc-type-in-different-containerized-executors-6062">Fix issue with same doc type in different containerized Executors (<a href="https://github.com/jina-ai/jina/pull/6062?ref=jina-ai-gmbh.ghost.io">#6062</a>)</h3><p>When multiple Executors inside a Flow had the same model name and they were used as docker containers or had set the environment variable <code>JINA_MP_START_METHOD=spawn</code>, there was a problem serving them via HTTP. This has been fixed by making sure that only one model instance is served for each model name.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-21-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
diff --git a/news/jina-3-22-0-update/index.html b/news/jina-3-22-0-update/index.html
index ba9b9c7412f..0622fdc4f6d 100644
--- a/news/jina-3-22-0-update/index.html
+++ b/news/jina-3-22-0-update/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.22.0 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.22.0 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-22-0-update"><meta property="og:title" content="Jina 3.22.0 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-1.jpeg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-22-0-update"><meta property="twitter:title" content="Jina 3.22.0 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-1.jpeg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.22.0 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.22.0 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-22-0-update"><meta property="og:title" content="Jina 3.22.0 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-1.jpeg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-22-0-update"><meta property="twitter:title" content="Jina 3.22.0 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-1.jpeg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><script src="https://jina-ai-gmbh.ghost.io/public/cards.min.js" async=""></script><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 04, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3220"><br>Release Note (<code>3.22.0</code>)</h2><p>This release contains 1 new feature and 2 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.22.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.22.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.22.0) Release time: 2023-10-04 12:16:53 This release contains 1 new feature and 2 documentation improvements.🆕 FeaturesChange the way dynamic batching is handled (#6066)This re…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/da0df8f748c732c06c623f112cf1a035f2119229a4e0c4af7a7a4bc13da78b7e/jina-ai/jina/releases/tag/v3.22.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="change-the-way-dynamic-batching-is-handled-6066">Change the way dynamic batching is handled (<a href="https://github.com/jina-ai/jina/pull/6066?ref=jina-ai-gmbh.ghost.io">#6066</a>)</h3><p>This release implements some changes in the way we handle dynamic batching:</p><ul><li>Jina guarantees that all the batches passed to Executors contain no more than <code>preferred_batch_size</code> documents.</li><li>Requests are returned to the client as they are processed without waiting for other requests to be ready.</li></ul><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Fix dynamic batching documentation (<a href="https://github.com/jina-ai/jina/pull/6068?ref=jina-ai-gmbh.ghost.io">#6068</a>)</li><li>Fix line explaining dynamic batching in YAML (<a href="https://github.com/jina-ai/jina/pull/6065?ref=jina-ai-gmbh.ghost.io">#6065</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-22-0-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 04, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3220"><br>Release Note (<code>3.22.0</code>)</h2><p>This release contains 1 new feature and 2 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.22.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Release v3.22.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.22.0) Release time: 2023-10-04 12:16:53 This release contains 1 new feature and 2 documentation improvements.🆕 FeaturesChange the way dynamic batching is handled (#6066)This re…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/da0df8f748c732c06c623f112cf1a035f2119229a4e0c4af7a7a4bc13da78b7e/jina-ai/jina/releases/tag/v3.22.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="change-the-way-dynamic-batching-is-handled-6066">Change the way dynamic batching is handled (<a href="https://github.com/jina-ai/jina/pull/6066?ref=jina-ai-gmbh.ghost.io">#6066</a>)</h3><p>This release implements some changes in the way we handle dynamic batching:</p><ul><li>Jina guarantees that all the batches passed to Executors contain no more than <code>preferred_batch_size</code> documents.</li><li>Requests are returned to the client as they are processed without waiting for other requests to be ready.</li></ul><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Fix dynamic batching documentation (<a href="https://github.com/jina-ai/jina/pull/6068?ref=jina-ai-gmbh.ghost.io">#6068</a>)</li><li>Fix line explaining dynamic batching in YAML (<a href="https://github.com/jina-ai/jina/pull/6065?ref=jina-ai-gmbh.ghost.io">#6065</a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Johannes Messner (<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">@JohannesMessner</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-22-0-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.22.1 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.22.1 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-22-1-update"><meta property="og:title" content="Jina 3.22.1 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-22-1-update"><meta property="twitter:title" content="Jina 3.22.1 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.22.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 06, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3221"><br>Release Note (<code>3.22.1</code>)</h2><p>This release contains 1 bug fix.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.22.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.22.1 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.22.1) Release time: 2023-10-06 13:52:45 This release contains 1 bug fix.🐞 Bug FixesFix timeout issue with dynamic batching (#6071)When using dynamic batching (either with the @…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/f8312759ade3440797e5ebe9a8b57877d5e0cf47ed60c32fad174d1e51ee2f1e/jina-ai/jina/releases/tag/v3.22.1" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-timeout-issue-with-dynamic-batching-6071">Fix timeout issue with dynamic batching (<a href="https://github.com/jina-ai/jina/pull/6071?ref=jina-ai-gmbh.ghost.io">#6071</a>)</h3><p>When using dynamic batching (either with the <code>@dynamic_batching</code> decorator on an <code>Executor</code> endpoint or by setting the <code>uses_dynamic_batching</code> parameter on a <code>Deployment</code>, timeouts were not being properly taken into account because the timer might not be triggered until a previous batch finished. This has been fixed.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-22-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.22.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 06, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3221"><br>Release Note (<code>3.22.1</code>)</h2><p>This release contains 1 bug fix.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.22.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.22.1 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.22.1) Release time: 2023-10-06 13:52:45 This release contains 1 bug fix.🐞 Bug FixesFix timeout issue with dynamic batching (#6071)When using dynamic batching (either with the @…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/pinned-octocat.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/f8312759ade3440797e5ebe9a8b57877d5e0cf47ed60c32fad174d1e51ee2f1e/jina-ai/jina/releases/tag/v3.22.1" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-timeout-issue-with-dynamic-batching-6071">Fix timeout issue with dynamic batching (<a href="https://github.com/jina-ai/jina/pull/6071?ref=jina-ai-gmbh.ghost.io">#6071</a>)</h3><p>When using dynamic batching (either with the <code>@dynamic_batching</code> decorator on an <code>Executor</code> endpoint or by setting the <code>uses_dynamic_batching</code> parameter on a <code>Deployment</code>, timeouts were not being properly taken into account because the timer might not be triggered until a previous batch finished. This has been fixed.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a> )</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-22-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.22.2 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.22.2 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-22-2-update"><meta property="og:title" content="Jina 3.22.2 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-1.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-22-2-update"><meta property="twitter:title" content="Jina 3.22.2 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-1.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 20, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3222">Release Note (<code>3.22.2</code>)</h2><p>This release contains 1 bug fix and 5 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.22.2?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.22.2 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.22.2) Release time: 2023-10-20 14:42:15 This release contains 1 bug fix and 5 documentation improvements.
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina 3.22.2 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 20, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3222">Release Note (<code>3.22.2</code>)</h2><p>This release contains 1 bug fix and 5 documentation improvements.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.22.2?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.22.2 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.22.2) Release time: 2023-10-20 14:42:15 This release contains 1 bug fix and 5 documentation improvements.
 🐞 Bug Fixes
 Fix check graph compatibility nested types (#6085)
-A bug was…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/4b64ab24771105198f1dd2fd80fda882c9f93774e44c7f831d779620eef7ae30/jina-ai/jina/releases/tag/v3.22.2" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-check-graph-compatibility-nested-types-6085">Fix check graph compatibility nested types (<a href="https://github.com/jina-ai/jina/pull/6085?ref=jina-ai-gmbh.ghost.io">#6085</a>)</h3><p>A bug was found that prevented Flows from starting when they had Executors with different but compatible schemas. This is now fixed.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Add Jina deployment docs (<a href="https://github.com/jina-ai/jina/pull/6079?ref=jina-ai-gmbh.ghost.io"><u>#6079</u></a>)</li><li>Fix typos inside docs/cloud-nativeness (<a href="https://github.com/jina-ai/jina/pull/6080?ref=jina-ai-gmbh.ghost.io"><u>#6080</u></a>)</li><li>Fix typos inside docs/concepts directory (<a href="https://github.com/jina-ai/jina/pull/6082?ref=jina-ai-gmbh.ghost.io"><u>#6082</u></a>)</li><li>Fix typo inside docs/tutorials (<a href="https://github.com/jina-ai/jina/pull/6083?ref=jina-ai-gmbh.ghost.io"><u>#6083</u></a>)</li><li>Fix readme code (<a href="https://github.com/jina-ai/jina/pull/6075?ref=jina-ai-gmbh.ghost.io"><u>#6075</u></a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Deepankar Mahapatro (<a href="https://github.com/deepankarm?ref=jina-ai-gmbh.ghost.io">@deepankarm</a>&nbsp;)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>&nbsp;)</li><li>Parikshit Adhikari (<a href="https://github.com/parikshitadhikari?ref=jina-ai-gmbh.ghost.io">@parikshitadhikari</a>&nbsp;)</li><li>Subba Reddy Veeramreddy (<a href="https://github.com/subbuv26?ref=jina-ai-gmbh.ghost.io">@subbuv26</a>&nbsp;)</li><li>Антон (<a href="https://github.com/BouFFaNTCRiB?ref=jina-ai-gmbh.ghost.io">@BouFFaNTCRiB</a>&nbsp;)</li><li>Abhijit (<a href="https://github.com/AbhiGaunker?ref=jina-ai-gmbh.ghost.io">@AbhiGaunker</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-22-2-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+A bug was…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/4b64ab24771105198f1dd2fd80fda882c9f93774e44c7f831d779620eef7ae30/jina-ai/jina/releases/tag/v3.22.2" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-check-graph-compatibility-nested-types-6085">Fix check graph compatibility nested types (<a href="https://github.com/jina-ai/jina/pull/6085?ref=jina-ai-gmbh.ghost.io">#6085</a>)</h3><p>A bug was found that prevented Flows from starting when they had Executors with different but compatible schemas. This is now fixed.</p><h2 id="%F0%9F%93%97-documentation-improvements">📗 Documentation Improvements</h2><ul><li>Add Jina deployment docs (<a href="https://github.com/jina-ai/jina/pull/6079?ref=jina-ai-gmbh.ghost.io"><u>#6079</u></a>)</li><li>Fix typos inside docs/cloud-nativeness (<a href="https://github.com/jina-ai/jina/pull/6080?ref=jina-ai-gmbh.ghost.io"><u>#6080</u></a>)</li><li>Fix typos inside docs/concepts directory (<a href="https://github.com/jina-ai/jina/pull/6082?ref=jina-ai-gmbh.ghost.io"><u>#6082</u></a>)</li><li>Fix typo inside docs/tutorials (<a href="https://github.com/jina-ai/jina/pull/6083?ref=jina-ai-gmbh.ghost.io"><u>#6083</u></a>)</li><li>Fix readme code (<a href="https://github.com/jina-ai/jina/pull/6075?ref=jina-ai-gmbh.ghost.io"><u>#6075</u></a>)</li></ul><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Deepankar Mahapatro (<a href="https://github.com/deepankarm?ref=jina-ai-gmbh.ghost.io">@deepankarm</a>&nbsp;)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>&nbsp;)</li><li>Parikshit Adhikari (<a href="https://github.com/parikshitadhikari?ref=jina-ai-gmbh.ghost.io">@parikshitadhikari</a>&nbsp;)</li><li>Subba Reddy Veeramreddy (<a href="https://github.com/subbuv26?ref=jina-ai-gmbh.ghost.io">@subbuv26</a>&nbsp;)</li><li>Антон (<a href="https://github.com/BouFFaNTCRiB?ref=jina-ai-gmbh.ghost.io">@BouFFaNTCRiB</a>&nbsp;)</li><li>Abhijit (<a href="https://github.com/AbhiGaunker?ref=jina-ai-gmbh.ghost.io">@AbhiGaunker</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-22-2-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.22.3 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.22.3 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-22-3-update"><meta property="og:title" content="Jina 3.22.3 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-2.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-22-3-update"><meta property="twitter:title" content="Jina 3.22.3 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-2.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.22.3 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.22.3 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-22-3-update"><meta property="og:title" content="Jina 3.22.3 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-2.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-22-3-update"><meta property="twitter:title" content="Jina 3.22.3 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-2.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="cece0cc3-c022-4557-96f4-18a25c93ba6a" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="cece0cc3-c022-4557-96f4-18a25c93ba6a" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 25, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3223">Release Note (<code>3.22.3</code>)</h2><p>This release contains 1 bug fix.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.22.3?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.22.3 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.22.3) Release time: 2023-10-25 12:03:58 This release contains 1 bug fix.
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="4b8c949b-731b-4a48-9970-21d656c4037d" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="4b8c949b-731b-4a48-9970-21d656c4037d" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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 🐞 Bug Fixes
 Add and use POST endpoint for streaming (#6093)
-HTTP streaming when using a GET endpoint only…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/bbf622e38936bd97688a794004636257a997cf3b42c4e080c2308a580498fffe/jina-ai/jina/releases/tag/v3.22.3" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="add-and-use-post-endpoint-for-streaming-6093">Add and use POST endpoint for streaming (<a href="https://github.com/jina-ai/jina/pull/6093?ref=jina-ai-gmbh.ghost.io">#6093</a>)</h3><p>HTTP streaming when using a&nbsp;<code>GET</code>&nbsp;endpoint only allows Documents whose schemas contain only&nbsp;<code>str</code>,&nbsp;<code>int</code>, and&nbsp;<code>float</code>&nbsp;fields.</p><p>By adding a&nbsp;<code>POST</code>&nbsp;endpoint and modifying the Jina Client to use it, it is now possible to send Documents with complex nested document schemas over streaming HTTP.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Peter Willemsen (<a href="https://github.com/peterwilli?ref=jina-ai-gmbh.ghost.io">@peterwilli</a>&nbsp;)</li><li>Narek Amirbekian (<a href="https://github.com/NarekA?ref=jina-ai-gmbh.ghost.io">@NarekA</a>&nbsp;)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-22-3-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+HTTP streaming when using a GET endpoint only…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/bbf622e38936bd97688a794004636257a997cf3b42c4e080c2308a580498fffe/jina-ai/jina/releases/tag/v3.22.3" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="add-and-use-post-endpoint-for-streaming-6093">Add and use POST endpoint for streaming (<a href="https://github.com/jina-ai/jina/pull/6093?ref=jina-ai-gmbh.ghost.io">#6093</a>)</h3><p>HTTP streaming when using a&nbsp;<code>GET</code>&nbsp;endpoint only allows Documents whose schemas contain only&nbsp;<code>str</code>,&nbsp;<code>int</code>, and&nbsp;<code>float</code>&nbsp;fields.</p><p>By adding a&nbsp;<code>POST</code>&nbsp;endpoint and modifying the Jina Client to use it, it is now possible to send Documents with complex nested document schemas over streaming HTTP.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Peter Willemsen (<a href="https://github.com/peterwilli?ref=jina-ai-gmbh.ghost.io">@peterwilli</a>&nbsp;)</li><li>Narek Amirbekian (<a href="https://github.com/NarekA?ref=jina-ai-gmbh.ghost.io">@NarekA</a>&nbsp;)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-22-3-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.22.4 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.22.4 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-22-4-update"><meta property="og:title" content="Jina 3.22.4 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-3.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-22-4-update"><meta property="twitter:title" content="Jina 3.22.4 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-3.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.22.4 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.22.4 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-22-4-update"><meta property="og:title" content="Jina 3.22.4 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-3.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-22-4-update"><meta property="twitter:title" content="Jina 3.22.4 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Image-Jina-dark-3.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="931c3332-3abe-41e4-85ee-dc5099c9df75" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="931c3332-3abe-41e4-85ee-dc5099c9df75" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 31, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3224">Release Note (<code>3.22.4</code>)</h2><p>This release contains 1 bug fix.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.22.4?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.22.4 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.22.4) Release time: 2023-10-31 14:33:21 This release contains 1 bug fix.
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="57a6292f-3806-4496-8130-7995717b937b" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="57a6292f-3806-4496-8130-7995717b937b" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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 🐞 Bug Fixes
 Add option to use body for streaming instead of params (#6098)
-In order to allow complex neste…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/39a4535a750f8cf9c61cd33bd367faa5bb713422cddd112641a36c1a99333c4f/jina-ai/jina/releases/tag/v3.22.4" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="add-option-to-use-body-for-streaming-instead-of-params-6098">Add option to use body for streaming instead of params (<a href="https://github.com/jina-ai/jina/pull/6098?ref=jina-ai-gmbh.ghost.io">#6098</a>)</h3><p>In order to allow complex nested documents to pass through streaming endpoints, the&nbsp;<code>GET</code>&nbsp;endpoint can now get the data from the body or the parameters of the HTTP request.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Narek Amirbekian (<a href="https://github.com/NarekA?ref=jina-ai-gmbh.ghost.io">@NarekA</a>&nbsp;)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-22-4-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+In order to allow complex neste…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/39a4535a750f8cf9c61cd33bd367faa5bb713422cddd112641a36c1a99333c4f/jina-ai/jina/releases/tag/v3.22.4" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="add-option-to-use-body-for-streaming-instead-of-params-6098">Add option to use body for streaming instead of params (<a href="https://github.com/jina-ai/jina/pull/6098?ref=jina-ai-gmbh.ghost.io">#6098</a>)</h3><p>In order to allow complex nested documents to pass through streaming endpoints, the&nbsp;<code>GET</code>&nbsp;endpoint can now get the data from the body or the parameters of the HTTP request.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Narek Amirbekian (<a href="https://github.com/NarekA?ref=jina-ai-gmbh.ghost.io">@NarekA</a>&nbsp;)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-22-4-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.23.0 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.23.0 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-23-0-update"><meta property="og:title" content="Jina 3.23.0 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Image-Jina-dark.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-23-0-update"><meta property="twitter:title" content="Jina 3.23.0 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Image-Jina-dark.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.23.0 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.23.0 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-23-0-update"><meta property="og:title" content="Jina 3.23.0 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Image-Jina-dark.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-23-0-update"><meta property="twitter:title" content="Jina 3.23.0 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Image-Jina-dark.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 20, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3230">Release Note (<code>3.23.0</code>)</h2><p>This release contains 1 new feature and 1 bug fix.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.23.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.23.0 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.23.0) Release time: 2023-11-20 10:02:37 This release contains 1 new feature and 1 bug fix.
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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 🆕 Features
 Call extend rest interface in worker (#6108)
 When running a Deployment with H…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/1e01faf8fa1f5ed07a44184f9998e6cc26cea7da380da0ed5c663d6859928bca/jina-ai/jina/releases/tag/v3.23.0" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="call-extend-rest-interface-in-worker-6108">Call extend rest interface in worker (<a href="https://github.com/jina-ai/jina/pull/6108?ref=jina-ai-gmbh.ghost.io">#6108</a>)</h3><p>When running a&nbsp;<code>Deployment</code>&nbsp;with HTTP locally without&nbsp;<code>docker</code>&nbsp;you can now extend the API by using&nbsp;<code>extend_rest_interface</code>, the same as with&nbsp;<code>Flow</code>.</p><pre><code class="language-Python hljs">    <span class="hljs-keyword">import</span> jina
@@ -29,4 +29,4 @@
     <span class="hljs-keyword">with</span> d:
         response = requests.get(<span class="hljs-string">f'http://localhost:8080/hello'</span>)
         <span class="hljs-keyword">assert</span> response.status_code == <span class="hljs-number">200</span>
-        <span class="hljs-keyword">assert</span> response.json() == {<span class="hljs-string">'msg'</span>: <span class="hljs-string">'hello world'</span>}</code></pre><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="read-csv-with-escaped-chars-6102">Read CSV with escaped chars (<a href="https://github.com/jina-ai/jina/pull/6102?ref=jina-ai-gmbh.ghost.io">#6102</a>)</h3><p>There was an issue when using Jina to do batch transformations on SageMaker. Parsing texts with escape characters was not working properly.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals Martinez (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Deepankar Mahapatro (<a href="https://github.com/deepankarm?ref=jina-ai-gmbh.ghost.io">@deepankarm</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-23-0-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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\ No newline at end of file
+        <span class="hljs-keyword">assert</span> response.json() == {<span class="hljs-string">'msg'</span>: <span class="hljs-string">'hello world'</span>}</code></pre><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="read-csv-with-escaped-chars-6102">Read CSV with escaped chars (<a href="https://github.com/jina-ai/jina/pull/6102?ref=jina-ai-gmbh.ghost.io">#6102</a>)</h3><p>There was an issue when using Jina to do batch transformations on SageMaker. Parsing texts with escape characters was not working properly.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals Martinez (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li><li>Deepankar Mahapatro (<a href="https://github.com/deepankarm?ref=jina-ai-gmbh.ghost.io">@deepankarm</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-23-0-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.23.1 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.23.1 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-23-1-update"><meta property="og:title" content="Jina 3.23.1 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-23-1-update"><meta property="twitter:title" content="Jina 3.23.1 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 01, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3231">Release Note (<code>3.23.1</code>)</h2><p>This release contains 1 bug fix.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.23.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.23.1 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.23.1) Release time: 2023-12-01 09:24:22 This release contains 1 bug fix.
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 01, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3231">Release Note (<code>3.23.1</code>)</h2><p>This release contains 1 bug fix.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.23.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.23.1 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.23.1) Release time: 2023-12-01 09:24:22 This release contains 1 bug fix.
 🐞 Bug Fixes
 Fix dependency on OpenTelemetry Exporter Prometheus (#6118)
-We fixed the dependency version wi…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/bbfee09be3e253af0418f345fc17cff01a66ed9575027c8c932d25cf7cb4fb6f/jina-ai/jina/releases/tag/v3.23.1" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-dependency-on-opentelemetry-exporter-prometheus-6118">Fix dependency on OpenTelemetry Exporter Prometheus (<a href="https://github.com/jina-ai/jina/pull/6118?ref=jina-ai-gmbh.ghost.io">#6118</a>)</h3><p>We fixed the dependency version with&nbsp;<code>opentelemetry-exporter-prometheus</code>&nbsp;to avoid using deprecated versions.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-23-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Image-Jina-dark.jpg" style="object-fit: cover; 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+We fixed the dependency version wi…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/bbfee09be3e253af0418f345fc17cff01a66ed9575027c8c932d25cf7cb4fb6f/jina-ai/jina/releases/tag/v3.23.1" alt=""></div></a></figure><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="fix-dependency-on-opentelemetry-exporter-prometheus-6118">Fix dependency on OpenTelemetry Exporter Prometheus (<a href="https://github.com/jina-ai/jina/pull/6118?ref=jina-ai-gmbh.ghost.io">#6118</a>)</h3><p>We fixed the dependency version with&nbsp;<code>opentelemetry-exporter-prometheus</code>&nbsp;to avoid using deprecated versions.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-23-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; 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\ No newline at end of file
diff --git a/news/jina-3-23-2-update/index.html b/news/jina-3-23-2-update/index.html
index 01f89920efa..375d25e19ff 100644
--- a/news/jina-3-23-2-update/index.html
+++ b/news/jina-3-23-2-update/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.23.2 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.23.2 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-23-2-update"><meta property="og:title" content="Jina 3.23.2 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-23-2-update"><meta property="twitter:title" content="Jina 3.23.2 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina 3.23.2 Update</title><meta charset="utf-8"><meta name="title" content="Jina 3.23.2 Update"><meta name="description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-3-23-2-update"><meta property="og:title" content="Jina 3.23.2 Update"><meta property="og:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-3-23-2-update"><meta property="twitter:title" content="Jina 3.23.2 Update"><meta property="twitter:description" content="Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><script src="https://jina-ai-gmbh.ghost.io/public/cards.min.js" async=""></script><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 14, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3232">Release Note (<code>3.23.2</code>)</h2><p>This release contains 1 dependency update and 2 bug fixes.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.23.2?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.23.2 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.23.2) Release time: 2023-12-14 15:28:24 This release contains 1 dependency update and 2 bug fixes.
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 14, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="release-note-3232">Release Note (<code>3.23.2</code>)</h2><p>This release contains 1 dependency update and 2 bug fixes.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/releases/tag/v3.23.2?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release 💫 Patch v3.23.2 · jina-ai/jina</div><div class="kg-bookmark-description">Release Note (3.23.2) Release time: 2023-12-14 15:28:24 This release contains 1 dependency update and 2 bug fixes.
 ⚙ Dependency update
 Update GRPC version requirements (#6110)
-The grpc version re…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/66a744fcace7275ba964cb292fb9e91fd04678aa02883dd2f72c0c8ef1b2bc4a/jina-ai/jina/releases/tag/v3.23.2" alt=""></div></a></figure><h2 id="%E2%9A%99-dependency-update">⚙ Dependency update</h2><h3 id="update-grpc-version-requirements-6110">Update GRPC version requirements (<a href="https://github.com/jina-ai/jina/pull/6110?ref=jina-ai-gmbh.ghost.io">#6110</a>)</h3><p>The&nbsp;<code>grpc</code>&nbsp;version requirements have been updated to allow&nbsp;<code>grpcio&lt;=1.57.0</code>.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="better-handling-of-exceptions-in-dynamic-batching-6128">Better handling of Exceptions in dynamic batching (<a href="https://github.com/jina-ai/jina/pull/6128?ref=jina-ai-gmbh.ghost.io">#6128</a>)</h3><p>An issue was identified when a dynamic batch raises an Exception that could affect some unrelated requests.</p><h3 id="load-balancing-streaming-based-on-response-type-6122">Load-balancing streaming based on response type (<a href="https://github.com/jina-ai/jina/pull/6122?ref=jina-ai-gmbh.ghost.io">#6122</a>)</h3><p>When using&nbsp;<code>Deployment</code>&nbsp;locally with multiple replicas, a load-balancing process is added in front of the replicas. </p><p>The load balancer assumed all&nbsp;<code>GET</code>&nbsp;requests to be streaming, but this may not be true for user-added FastAPI endpoints. We have fixed this assumption and now use the response type to determine if a request is streaming.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Narek Amirbekian (<a href="https://github.com/NarekA?ref=jina-ai-gmbh.ghost.io">@NarekA</a>&nbsp;)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>&nbsp;)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-23-2-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; 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+The grpc version re…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/66a744fcace7275ba964cb292fb9e91fd04678aa02883dd2f72c0c8ef1b2bc4a/jina-ai/jina/releases/tag/v3.23.2" alt=""></div></a></figure><h2 id="%E2%9A%99-dependency-update">⚙ Dependency update</h2><h3 id="update-grpc-version-requirements-6110">Update GRPC version requirements (<a href="https://github.com/jina-ai/jina/pull/6110?ref=jina-ai-gmbh.ghost.io">#6110</a>)</h3><p>The&nbsp;<code>grpc</code>&nbsp;version requirements have been updated to allow&nbsp;<code>grpcio&lt;=1.57.0</code>.</p><h2 id="%F0%9F%90%9E-bug-fixes">🐞 Bug Fixes</h2><h3 id="better-handling-of-exceptions-in-dynamic-batching-6128">Better handling of Exceptions in dynamic batching (<a href="https://github.com/jina-ai/jina/pull/6128?ref=jina-ai-gmbh.ghost.io">#6128</a>)</h3><p>An issue was identified when a dynamic batch raises an Exception that could affect some unrelated requests.</p><h3 id="load-balancing-streaming-based-on-response-type-6122">Load-balancing streaming based on response type (<a href="https://github.com/jina-ai/jina/pull/6122?ref=jina-ai-gmbh.ghost.io">#6122</a>)</h3><p>When using&nbsp;<code>Deployment</code>&nbsp;locally with multiple replicas, a load-balancing process is added in front of the replicas. </p><p>The load balancer assumed all&nbsp;<code>GET</code>&nbsp;requests to be streaming, but this may not be true for user-added FastAPI endpoints. We have fixed this assumption and now use the response type to determine if a request is streaming.</p><h2 id="%F0%9F%A4%9F-contributors">🤟 Contributors</h2><p>We would like to thank all contributors to this release:</p><ul><li>Narek Amirbekian (<a href="https://github.com/NarekA?ref=jina-ai-gmbh.ghost.io">@NarekA</a>&nbsp;)</li><li>Joan Fontanals (<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">@JoanFM</a>&nbsp;)</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-3-23-2-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="72ff9bfe-db42-48e1-a147-0dcd0db3cf78" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="72ff9bfe-db42-48e1-a147-0dcd0db3cf78" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina AI’s 8K Embedding Models Hit AWS Marketplace for On-Prem Deployment</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI launches 8K token length embedding v2 models on AWS marketplace, elevating enterprise AI deployments with EU-engineered innovation and a commitment to data sovereignty.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 20, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><strong>Berlin, Germany - November 20, 2023 </strong>- Catering to enterprise customers, Jina AI has released <a href="https://jina.ai/news/jina-ai-launches-worlds-first-open-source-8k-text-embedding-rivaling-openai/?ref=jina-ai-gmbh.ghost.io">Embeddings v2</a> on AWS SageMaker, a milestone in accessible, top-tier AI solutions. Enterprise users can now search for <code>jina-embeddings-v2-base/small</code> on the AWS Marketplace and deploy them directly to their own AWS accounts. As a part of the AWS Startups program, this release underscores the collaboration between Jina AI's innovation and AWS's commitment to supporting groundbreaking startups, marking a significant advancement in AI development.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://aws.amazon.com/marketplace/seller-profile?id=seller-stch2ludm6vgy&amp;ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-60.png" class="kg-image" alt="" width="2000" height="1556" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-60.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-60.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-60.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-60.png 2134w" sizes="(min-width: 720px) 720px"></a><figcaption><span style="white-space: pre-wrap;">Enterprise users can now search jina-embeddings-v2-base/small on the AWS marketplace and deploy them directly on their own AWS account.</span></figcaption></figure><h2 id="superior-models-on-a-robust-platform">Superior Models on a Robust Platform</h2><ul><li><em>SageMaker Integration</em>: With global availability on the AWS SageMaker Marketplace, Jina AI underscores its dedication to enterprise users, providing them with an effortless way to build applications using our advanced embedding models.</li><li><em>Seamless Deployment</em>: Enterprises can now easily deploy Jina Embedding v2 models as SageMaker endpoints, bypassing the complexity associated with custom infrastructure setups.</li><li><em>Cost-Effective Licensing</em>: The English <a href="https://aws.amazon.com/marketplace/pp/prodview-egsf72y46ursa?ref=jina-ai-gmbh.ghost.io">base</a> and <a href="https://aws.amazon.com/marketplace/pp/prodview-jwbhofu3iesos?ref=jina-ai-gmbh.ghost.io">small</a> models are available <em>without licensing fees</em>. Clients incur costs only for their AWS instances, ensuring a privacy-first, cost-effective solution within their VPC.</li></ul><h3 id="tailored-solutions-for-varied-use-cases">Tailored Solutions for Varied Use Cases</h3><ul><li><em>Model Diversity</em>: With a <a href="https://aws.amazon.com/marketplace/pp/prodview-egsf72y46ursa?ref=jina-ai-gmbh.ghost.io">0.27GB base model</a> and a <a href="https://aws.amazon.com/marketplace/pp/prodview-jwbhofu3iesos?ref=jina-ai-gmbh.ghost.io">0.07GB small model</a>, Jina AI provides tailored solutions for various needs, from in-depth analytics to lightweight applications.</li><li><em>Use Cases</em>: The base model is designed for comprehensive semantic representation, ideal for enterprise search and content discovery, while the small model caters to mobile and edge devices, optimizing for speed and efficiency.</li></ul><p>Commenting on this significant milestone, Dr. Han Xiao, CEO of Jina AI, offered the following insights:</p><blockquote>Launching Jina AI's 8K Context Length v2 Embedding Models on AWS Marketplace, we advance industry standards for private AI solutions. Developed in Germany, this pivotal release emphasizes data sovereignty and customer-centric innovation, addressing today's needs and shaping future secure, private AI deployments.</blockquote><p>Jina AI aims to make continuous strides towards privacy-aware, state-of-the-art AI, as evident from its plans.  </p><h2 id="why-jina-embeddings-v2-a-leap-in-ai-capability">Why Jina Embeddings v2: A Leap in AI Capability</h2><ul><li><em>Extended Context Length</em>: Jina Embeddings v2 models support an <a href="https://arxiv.org/abs/2310.19923?ref=jina-ai-gmbh.ghost.io">unprecedented 8K</a> (8192 tokens) context length, allowing for a full understanding of longer documents.</li><li><em>Open Source Pioneer</em>: Jina AI takes pride in offering the only open-source model with a context length that matches OpenAI’s proprietary models, broadening access to advanced AI.</li><li><em>Benchmark Leadership</em>: On the Massive Text Embedding Benchmark (MTEB) <a href="https://huggingface.co/spaces/mteb/leaderboard?ref=jina-ai-gmbh.ghost.io">leaderboard</a>, our models boast performance on par with industry-leading models, attesting to our commitment to excellence.</li></ul><h3 id="performance-vs-openais-text-embedding-ada002">Performance vs. OpenAI's text-embedding-ada002</h3><p>Below is a comparative performance snapshot that showcases the robust capabilities of Jina Embeddings v2:</p>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina AI’s 8K Embedding Models Hit AWS Marketplace for On-Prem Deployment</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI launches 8K token length embedding v2 models on AWS marketplace, elevating enterprise AI deployments with EU-engineered innovation and a commitment to data sovereignty.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 20, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><strong>Berlin, Germany - November 20, 2023 </strong>- Catering to enterprise customers, Jina AI has released <a href="https://jina.ai/news/jina-ai-launches-worlds-first-open-source-8k-text-embedding-rivaling-openai/?ref=jina-ai-gmbh.ghost.io">Embeddings v2</a> on AWS SageMaker, a milestone in accessible, top-tier AI solutions. Enterprise users can now search for <code>jina-embeddings-v2-base/small</code> on the AWS Marketplace and deploy them directly to their own AWS accounts. As a part of the AWS Startups program, this release underscores the collaboration between Jina AI's innovation and AWS's commitment to supporting groundbreaking startups, marking a significant advancement in AI development.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://aws.amazon.com/marketplace/seller-profile?id=seller-stch2ludm6vgy&amp;ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-60.png" class="kg-image" alt="" width="2000" height="1556" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-60.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-60.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/image-60.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-60.png 2134w" sizes="(min-width: 720px) 720px"></a><figcaption><span style="white-space: pre-wrap;">Enterprise users can now search jina-embeddings-v2-base/small on the AWS marketplace and deploy them directly on their own AWS account.</span></figcaption></figure><h2 id="superior-models-on-a-robust-platform">Superior Models on a Robust Platform</h2><ul><li><em>SageMaker Integration</em>: With global availability on the AWS SageMaker Marketplace, Jina AI underscores its dedication to enterprise users, providing them with an effortless way to build applications using our advanced embedding models.</li><li><em>Seamless Deployment</em>: Enterprises can now easily deploy Jina Embedding v2 models as SageMaker endpoints, bypassing the complexity associated with custom infrastructure setups.</li><li><em>Cost-Effective Licensing</em>: The English <a href="https://aws.amazon.com/marketplace/pp/prodview-egsf72y46ursa?ref=jina-ai-gmbh.ghost.io">base</a> and <a href="https://aws.amazon.com/marketplace/pp/prodview-jwbhofu3iesos?ref=jina-ai-gmbh.ghost.io">small</a> models are available <em>without licensing fees</em>. Clients incur costs only for their AWS instances, ensuring a privacy-first, cost-effective solution within their VPC.</li></ul><h3 id="tailored-solutions-for-varied-use-cases">Tailored Solutions for Varied Use Cases</h3><ul><li><em>Model Diversity</em>: With a <a href="https://aws.amazon.com/marketplace/pp/prodview-egsf72y46ursa?ref=jina-ai-gmbh.ghost.io">0.27GB base model</a> and a <a href="https://aws.amazon.com/marketplace/pp/prodview-jwbhofu3iesos?ref=jina-ai-gmbh.ghost.io">0.07GB small model</a>, Jina AI provides tailored solutions for various needs, from in-depth analytics to lightweight applications.</li><li><em>Use Cases</em>: The base model is designed for comprehensive semantic representation, ideal for enterprise search and content discovery, while the small model caters to mobile and edge devices, optimizing for speed and efficiency.</li></ul><p>Commenting on this significant milestone, Dr. Han Xiao, CEO of Jina AI, offered the following insights:</p><blockquote>Launching Jina AI's 8K Context Length v2 Embedding Models on AWS Marketplace, we advance industry standards for private AI solutions. Developed in Germany, this pivotal release emphasizes data sovereignty and customer-centric innovation, addressing today's needs and shaping future secure, private AI deployments.</blockquote><p>Jina AI aims to make continuous strides towards privacy-aware, state-of-the-art AI, as evident from its plans.  </p><h2 id="why-jina-embeddings-v2-a-leap-in-ai-capability">Why Jina Embeddings v2: A Leap in AI Capability</h2><ul><li><em>Extended Context Length</em>: Jina Embeddings v2 models support an <a href="https://arxiv.org/abs/2310.19923?ref=jina-ai-gmbh.ghost.io">unprecedented 8K</a> (8192 tokens) context length, allowing for a full understanding of longer documents.</li><li><em>Open Source Pioneer</em>: Jina AI takes pride in offering the only open-source model with a context length that matches OpenAI’s proprietary models, broadening access to advanced AI.</li><li><em>Benchmark Leadership</em>: On the Massive Text Embedding Benchmark (MTEB) <a href="https://huggingface.co/spaces/mteb/leaderboard?ref=jina-ai-gmbh.ghost.io">leaderboard</a>, our models boast performance on par with industry-leading models, attesting to our commitment to excellence.</li></ul><h3 id="performance-vs-openais-text-embedding-ada002">Performance vs. OpenAI's text-embedding-ada002</h3><p>Below is a comparative performance snapshot that showcases the robust capabilities of Jina Embeddings v2:</p>
 
 <table id="e6f57e0d-fe4c-414f-8c0f-5081d4ad007d" class="simple-table"><tbody><tr id="29fae3d0-ca66-462f-8966-b3c1b74c9a86"><td id="bT<r" class="">Model</td><td id="hcDn" class="">text-embedding-ada-002</td><td id="gMgn" class="">jina-embeddings-v2-base-en</td></tr><tr id="5cff5519-ba19-40a8-9900-4488689c0a84"><td id="bT<r" class="">Rank</td><td id="hcDn" class=""><strong>18</strong></td><td id="gMgn" class="">21</td></tr><tr id="f01a5da8-92d0-4a76-8e1c-8fb77c9ac6c8"><td id="bT<r" class="">Model Size (GB)</td><td id="hcDn" class="">Unknown</td><td id="gMgn" class="">0.27</td></tr><tr id="56cc4ec4-a35e-44f4-8f2a-5243a8c4331b"><td id="bT<r" class="">Average (56 datasets)</td><td id="hcDn" class=""><strong>60.99</strong></td><td id="gMgn" class="">60.38</td></tr><tr id="ca2d0ce9-9157-46c5-a9c7-9179edea43ee"><td id="bT<r" class="">Embedding Dimensions</td><td id="hcDn" class="">1536</td><td id="gMgn" class=""><strong>768</strong></td></tr><tr id="8c7ecb47-1d30-4c32-8a23-89dadfbbfc38"><td id="bT<r" class="">Sequence Length</td><td id="hcDn" class="">8191</td><td id="gMgn" class="">8192</td></tr><tr id="a0398e1a-3144-4ec4-bb36-8768488b3d8a"><td id="bT<r" class="">Classification Average (12 datasets)</td><td id="hcDn" class="">70.93</td><td id="gMgn" class=""><strong>73.45</strong></td></tr><tr id="d5a7ccfb-7769-4d58-bad4-a219481876ff"><td id="bT<r" class="">Pair Classification Average (3 datasets)</td><td id="hcDn" class="">84.89</td><td id="gMgn" class=""><strong>85.38</strong></td></tr><tr id="461eb054-e39a-4ec5-8c33-cc880cb9f2ac"><td id="bT<r" class="">Summarization Average (1 dataset)</td><td id="hcDn" class="">30.8</td><td id="gMgn" class=""><strong>31.6</strong></td></tr><tr id="5f55e5e5-a6dc-4a4a-b67d-4ffed0084989"><td id="bT<r" class="">Retrieval Average (15 datasets)</td><td id="hcDn" class=""><strong>49.25</strong></td><td id="gMgn" class="">47.87</td></tr></tbody></table>
 
-<p>Jina AI's base model excels particularly in Classification and Pair Classification tasks, underscoring its value in diverse applications ranging from document analysis to recommendation systems.</p><h2 id="get-started-with-jina-embeddings-v2-on-aws">Get Started with Jina Embeddings v2 on AWS</h2><p>To begin using Jina Embeddings v2, visit the <a href="https://aws.amazon.com/marketplace/seller-profile?id=seller-stch2ludm6vgy&amp;ref=jina-ai-gmbh.ghost.io">AWS Marketplace listings</a> and select the model that best fits your needs.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aws.amazon.com/marketplace/seller-profile?id=seller-stch2ludm6vgy&amp;ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">AWS Marketplace: Jina AI</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://d32gc0xr2ho6pa.cloudfront.net/img/general/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://d32gc0xr2ho6pa.cloudfront.net/img/general/v2/socialPreview.png" alt=""></div></a></figure><p>These sample notebooks can help users get started with Jina Embeddings v2 models:</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina-sagemaker/blob/main/notebooks/Real-time%20inference.ipynb?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">jina-sagemaker/notebooks/Real-time inference.ipynb at main · jina-ai/jina-sagemaker</div><div class="kg-bookmark-description">Jina Embedding Models on AWS SageMaker. Contribute to jina-ai/jina-sagemaker development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/91499715ca0bec59273499acfddecae62d0a3833146f7ceaf9968656007b16f0/jina-ai/jina-sagemaker" alt=""></div></a><figcaption><p dir="ltr"><span style="white-space: pre-wrap;">Real-time inference on SageMaker</span></p></figcaption></figure><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina-sagemaker/blob/main/notebooks/Batch%20transform.ipynb?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">jina-sagemaker/notebooks/Batch transform.ipynb at main · jina-ai/jina-sagemaker</div><div class="kg-bookmark-description">Jina Embedding Models on AWS SageMaker. Contribute to jina-ai/jina-sagemaker development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/91499715ca0bec59273499acfddecae62d0a3833146f7ceaf9968656007b16f0/jina-ai/jina-sagemaker" alt=""></div></a><figcaption><p dir="ltr"><span style="white-space: pre-wrap;">Embedding multiple sentences in a batch with SageMaker</span></p></figcaption></figure><h2 id="coming-soon-multilingual-embeddings-and-more">Coming Soon: Multilingual Embeddings and More</h2><p>Looking ahead, Jina AI is already deep in developing multilingual embedding models, making them available to its enterprise clients for private deployment on various cloud service providers (CSPs). With the imminent launch of these models, Jina AI is set to bridge language barriers, unlocking global opportunities for its clients.</p><h2 id="about-jina-ai-gmbh">About Jina AI GmbH</h2><p>Located at <a href="https://maps.app.goo.gl/rAZ1QiqoKp49KZAg6?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</a>, Jina AI is at the vanguard of reshaping the landscape of multimodal artificial intelligence. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-ai-launches-worlds-first-open-source-8k-text-embedding-rivaling-openai" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">October 25, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels--11-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+<p>Jina AI's base model excels particularly in Classification and Pair Classification tasks, underscoring its value in diverse applications ranging from document analysis to recommendation systems.</p><h2 id="get-started-with-jina-embeddings-v2-on-aws">Get Started with Jina Embeddings v2 on AWS</h2><p>To begin using Jina Embeddings v2, visit the <a href="https://aws.amazon.com/marketplace/seller-profile?id=seller-stch2ludm6vgy&amp;ref=jina-ai-gmbh.ghost.io">AWS Marketplace listings</a> and select the model that best fits your needs.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aws.amazon.com/marketplace/seller-profile?id=seller-stch2ludm6vgy&amp;ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">AWS Marketplace: Jina AI</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://d32gc0xr2ho6pa.cloudfront.net/img/general/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://d32gc0xr2ho6pa.cloudfront.net/img/general/v2/socialPreview.png" alt=""></div></a></figure><p>These sample notebooks can help users get started with Jina Embeddings v2 models:</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina-sagemaker/blob/main/notebooks/Real-time%20inference.ipynb?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">jina-sagemaker/notebooks/Real-time inference.ipynb at main · jina-ai/jina-sagemaker</div><div class="kg-bookmark-description">Jina Embedding Models on AWS SageMaker. Contribute to jina-ai/jina-sagemaker development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/91499715ca0bec59273499acfddecae62d0a3833146f7ceaf9968656007b16f0/jina-ai/jina-sagemaker" alt=""></div></a><figcaption><p dir="ltr"><span style="white-space: pre-wrap;">Real-time inference on SageMaker</span></p></figcaption></figure><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina-sagemaker/blob/main/notebooks/Batch%20transform.ipynb?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">jina-sagemaker/notebooks/Batch transform.ipynb at main · jina-ai/jina-sagemaker</div><div class="kg-bookmark-description">Jina Embedding Models on AWS SageMaker. Contribute to jina-ai/jina-sagemaker development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.githubassets.com/assets/pinned-octocat-093da3e6fa40.svg" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/91499715ca0bec59273499acfddecae62d0a3833146f7ceaf9968656007b16f0/jina-ai/jina-sagemaker" alt=""></div></a><figcaption><p dir="ltr"><span style="white-space: pre-wrap;">Embedding multiple sentences in a batch with SageMaker</span></p></figcaption></figure><h2 id="coming-soon-multilingual-embeddings-and-more">Coming Soon: Multilingual Embeddings and More</h2><p>Looking ahead, Jina AI is already deep in developing multilingual embedding models, making them available to its enterprise clients for private deployment on various cloud service providers (CSPs). With the imminent launch of these models, Jina AI is set to bridge language barriers, unlocking global opportunities for its clients.</p><h2 id="about-jina-ai-gmbh">About Jina AI GmbH</h2><p>Located at <a href="https://maps.app.goo.gl/rAZ1QiqoKp49KZAg6?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</a>, Jina AI is at the vanguard of reshaping the landscape of multimodal artificial intelligence. For inquiries, please reach out at&nbsp;<a>contact@jina.ai</a>.<br></p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Press release</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-ai-8k-embedding-models-hit-aws-marketplace-for-on-prem-deployment%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-ai-launches-worlds-first-open-source-8k-text-embedding-rivaling-openai" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">October 25, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels--11-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="7e44bf99-f270-4517-85be-d3656e1f4f66" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="7e44bf99-f270-4517-85be-d3656e1f4f66" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Tech Talk and Cheer: Celebrating the Holidays at Our 2022 Annual Christmas Party</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The holiday season is upon us! As we reflect on this past year, we made a huge difference together with the support from our team, community members, and our partners.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 08, 2022 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The holiday season is upon us! As we reflect on this past year, we made a huge difference together with the support from our team, community members, and our partners. In spring, we released Jina 3, aiming for increased simplicity and consistency. We embraced generative AI in summer by launching <a href="https://github.com/jina-ai/dalle-flow?ref=jina-ai-gmbh.ghost.io">Dalle-Flow</a> and <a href="https://github.com/jina-ai/discoart?ref=jina-ai-gmbh.ghost.io">DiscoArt</a>, which became the trending project on GitHub multiple times. In addition, we were listed on CB Insight AI100 for the second time as one of the most innovative AI start-ups. By autumn, we were grateful to have broadened our horizons over the multimodal AI landscape, while at the same time, evolving offerings to become a powerful ML Ops framework. And this winter, as a contributor of open source, we donated DocArray to the Linux Foundation and became a member of it. </p><p>We also took the opportunity to gather our beloved developer community, partners, and friends to celebrate the memories we’ve created and outlook for a greater upcoming 2023!</p><p>Let's look back on the highlights of the last event we held, the Jina AI Annual Event 2022:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00006-2.jpg" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00006-2.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00006-2.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00006-2.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_00006-2.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00042.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00042.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00042.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00042.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_00042.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00201.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00201.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00201.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00201.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_00201.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00320.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00320.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00320.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00320.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_00320.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00306.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00306.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00306.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00306.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_00306.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00646.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00646.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00646.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00646.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_00646.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Some moments from the Jina AI Annual Event</figcaption></figure><p>We had impressive tech talks, the release of our first new book, inspiring panel discussions, and last but not least, the Christmas party!</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://lh3.googleusercontent.com/qKAqHhKWhPa5BLG2RCD5bZjff5xCLcJ0oggDYdcGDMEZwDhEwCk846btWJjgbnqG8Zbe9-7Pm9dsR_3nXIhB8HLTMbc-Czr4Pb2xdGxKD5KrHXFHZ6AlO9agfNTyZHIotmIZH16XjvmyzlK0nzQT0PY7fQjVPKr2P9tP6DId3DG-nIzImgE9ZN-XhHvnew" class="kg-image" alt="" width="641" height="427"><figcaption>Founder and CEO of Jina AI, Dr. Han Xiao is giving an opening speech</figcaption></figure><p><br>Dr. Han Xiao, founder, and CEO of Jina AI gave an opening speech with the topic <em>Unlock the Business Value of Multimodal Data</em>. In this talk, Han described the benefits of using an MLOps platform for multimodal AI applications in production and how that helps to unlock the business value of your multimodal data. Multimodal AI is a new type of AI that can take in data from multiple modalities (images, text, audio, etc.) and learn from it to make predictions. This makes it very powerful for applications like neural search and creative AI (e.g., DALLE and StableDiffusion). Multimodal AI also presents new challenges for engineering. In particular, it can be difficult to deploy and manage multimodal AI models and pipelines and make them scalable in production. This is where MLOps platforms come in to resolve this problem. </p><p>Read our blog to learn more about what MLOps do.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">The Paradigm Shift Towards Multimodal AI</div><div class="kg-bookmark-description">We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they’re right at the starting line of this paradigm shift, and build the applications of the future today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/9.png" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://lh3.googleusercontent.com/nWOFbOkEiuOH6q_GeLgFKM3_hP_BqMCtME14TBh9Od5ytEYlgsJQo3f5-kCB0NRgX6RG5Lg2FqTodk0sOiLE73Wzl4v8dNCbJg8u0ZsSX6QnlxWRsN8XKmWq8iJegtKtYHwANDIOHpeyL_8MCjlDg8hd7hmmT5Vq56rkOQuq998_M8pfnp0WtJ75Iq7kBw" class="kg-image" alt="" width="474" height="315"><figcaption>Authors of the book - <em>Neural Search - From Prototype to Production with Jina</em></figcaption></figure><p>Following the insightful speech by Han, we were excited to announce the release of our first book <em>Neural Search - From Prototype to Production with Jina</em> - a must-have starter pack for understanding neural search and building useful applications on top... Two of the authors, Susana Guzmán and Bo Wang, shared their experiences writing the book and the reason why it is a <em>must-read</em>. Please check the article for an inside scoop on Neural Search with our new book! </p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://jina.ai/news/neural-search-from-prototype-to-production-with-jina/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Get the Inside Scoop on Neural Search with Our New Book!</div><div class="kg-bookmark-description">If you’re an AI engineer building search systems for any kind of data type – text, Q+A, image, audio, PDF, 3D models, etc. – or a Python developer interested in search or state-of-the-art deep learning techniques, then our new book “Neural Search - From Prototype to Production with Jina” is for you.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--30--3.png" alt=""></div></a><figcaption>The book is available on Amazon</figcaption></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_01447.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_01447.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_01447.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_01447.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_01447.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_01494.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_01494.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_01494.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_01494.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_01494.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_01573.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_01573.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_01573.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_01573.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_01573.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_01620.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_01620.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_01620.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_01620.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_01620.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>From top left to bottom right: Sami Jaghouar, Leon Wolf, Girish Chandrashekar, Georgios Mastrapas</figcaption></figure><p>The engineer’s lightning talk was an essential part of this event! The team presented exciting progress on our product offerings and feature updates. Find out more in our recent blogs:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/docarray-0-20-update?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">DocArray 0.20 Update</div><div class="kg-bookmark-description">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--9-.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/donate-docarray-lf-for-inclusive-standard-multimodal-data-model/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">We’re Donating DocArray to LF for an Inclusive and Standard Multimodal Data Model</div><div class="kg-bookmark-description">DocArray is now hosted under the Linux Foundation AI &amp; Data - a neutral home to build and support an open AI and data community. This is the start of a new day for DocArray.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--37-.png" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/BeFunky-collage.png" class="kg-image" alt="" width="2000" height="1181" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/BeFunky-collage.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/BeFunky-collage.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/BeFunky-collage.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/BeFunky-collage.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Left to right: <a href="https://www.linkedin.com/in/gfissore/?ref=jina-ai-gmbh.ghost.io">Giancarlo Fissore</a>, <a href="https://www.linkedin.com/in/codebuffet/?ref=jina-ai-gmbh.ghost.io">Peter Willemsen</a> &amp; <a href="https://www.linkedin.com/in/moritz-feuerpfeil/?ref=jina-ai-gmbh.ghost.io">Moritz Feuerpfeil</a>&nbsp;</figcaption></figure><p>We are dedicated to supporting the open-source community and the contributions that make our product stronger. We are thrilled to have invited Giancarlo Fissore and Peter Willemsen, two valued members of the Jina community, to share their experiences and insights. In addition, Moritz Feuerpiel from Kern.ai brought up a thought-provoking talk on the origins and costs of labeling errors. Our community would not be the same without them!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://jina.ai/slack/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Become a member of our community</a></div><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://lh5.googleusercontent.com/Fr2KLHUbi_Iw4YCH8BPaXvTv39Asu2GrZUNUM4tTDFb-uJwQiun1MR5Y8d0nYSrxfGbkTNT50Srf8zFX70TGh9tKkzmv6JABVpnuQTwFkDki7yvEMzSKC9xOMcZLv3lVL1Ts0yCINVVACIh7kXc06Oq0INeeYjuyUCSY0FLjfmpPm5PoA1UUDS8SzIGd-A" class="kg-image" alt="" width="624" height="416"><figcaption>Panel Discussion: How to build an engaging tech community?</figcaption></figure><p>In the last panel session, tech community leaders Dania Meira (Director of AI Guild), Stephen Batifol (organizer of the MLOps local community), and Dr. Larysa Visengeriyeva (senior consultant at INNQ) joined our Head of Engineering, Maximilian Werk, shared their experiences and insights on how to build an engaging community.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://lh4.googleusercontent.com/emob7SJLl91Fcgx5I9tLb_-4Te6nd608vxnwoQSS36op6VAv7PfVAi_rx60EC2qFNPmfWJswXfaZBXGj1clMWSQ8AJLIkIo-pvAjrLvnbZOlPEY0OipkHivaXK9yOC6oDpeYKMnDoYJ_eHja9KVngX6fcIN_aYMHnTG7hptMtEQ-5CQlpolUM7S0Td1d2A" class="kg-image" alt="" width="624" height="416"><figcaption>Jina AI team together with their own Santa Claus</figcaption></figure><p>We're honored and humbled to know that so many of you are using Jina AI to build amazing things and contributing your energy and expertise back to our open-source projects. We are already working on upcoming events and creating more memorable moments with you, our community, so sign up to our newsletter and stay tuned!</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/35hmBwYHYikAAAAC/the-office-bow.gif" class="kg-image" alt="" width="300" height="168"><figcaption>Thank you to our community for being awesome!</figcaption></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-ai-annual-event%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Tech Talk and Cheer: Celebrating the Holidays at Our 2022 Annual Christmas Party</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The holiday season is upon us! As we reflect on this past year, we made a huge difference together with the support from our team, community members, and our partners.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 08, 2022 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The holiday season is upon us! As we reflect on this past year, we made a huge difference together with the support from our team, community members, and our partners. In spring, we released Jina 3, aiming for increased simplicity and consistency. We embraced generative AI in summer by launching <a href="https://github.com/jina-ai/dalle-flow?ref=jina-ai-gmbh.ghost.io">Dalle-Flow</a> and <a href="https://github.com/jina-ai/discoart?ref=jina-ai-gmbh.ghost.io">DiscoArt</a>, which became the trending project on GitHub multiple times. In addition, we were listed on CB Insight AI100 for the second time as one of the most innovative AI start-ups. By autumn, we were grateful to have broadened our horizons over the multimodal AI landscape, while at the same time, evolving offerings to become a powerful ML Ops framework. And this winter, as a contributor of open source, we donated DocArray to the Linux Foundation and became a member of it. </p><p>We also took the opportunity to gather our beloved developer community, partners, and friends to celebrate the memories we’ve created and outlook for a greater upcoming 2023!</p><p>Let's look back on the highlights of the last event we held, the Jina AI Annual Event 2022:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00006-2.jpg" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00006-2.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00006-2.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00006-2.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_00006-2.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00042.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00042.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00042.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00042.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_00042.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00201.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00201.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00201.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00201.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_00201.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00320.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00320.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00320.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00320.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_00320.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00306.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00306.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00306.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00306.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_00306.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_00646.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_00646.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_00646.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_00646.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_00646.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Some moments from the Jina AI Annual Event</figcaption></figure><p>We had impressive tech talks, the release of our first new book, inspiring panel discussions, and last but not least, the Christmas party!</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://lh3.googleusercontent.com/qKAqHhKWhPa5BLG2RCD5bZjff5xCLcJ0oggDYdcGDMEZwDhEwCk846btWJjgbnqG8Zbe9-7Pm9dsR_3nXIhB8HLTMbc-Czr4Pb2xdGxKD5KrHXFHZ6AlO9agfNTyZHIotmIZH16XjvmyzlK0nzQT0PY7fQjVPKr2P9tP6DId3DG-nIzImgE9ZN-XhHvnew" class="kg-image" alt="" width="641" height="427"><figcaption>Founder and CEO of Jina AI, Dr. Han Xiao is giving an opening speech</figcaption></figure><p><br>Dr. Han Xiao, founder, and CEO of Jina AI gave an opening speech with the topic <em>Unlock the Business Value of Multimodal Data</em>. In this talk, Han described the benefits of using an MLOps platform for multimodal AI applications in production and how that helps to unlock the business value of your multimodal data. Multimodal AI is a new type of AI that can take in data from multiple modalities (images, text, audio, etc.) and learn from it to make predictions. This makes it very powerful for applications like neural search and creative AI (e.g., DALLE and StableDiffusion). Multimodal AI also presents new challenges for engineering. In particular, it can be difficult to deploy and manage multimodal AI models and pipelines and make them scalable in production. This is where MLOps platforms come in to resolve this problem. </p><p>Read our blog to learn more about what MLOps do.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">The Paradigm Shift Towards Multimodal AI</div><div class="kg-bookmark-description">We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they’re right at the starting line of this paradigm shift, and build the applications of the future today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/9.png" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://lh3.googleusercontent.com/nWOFbOkEiuOH6q_GeLgFKM3_hP_BqMCtME14TBh9Od5ytEYlgsJQo3f5-kCB0NRgX6RG5Lg2FqTodk0sOiLE73Wzl4v8dNCbJg8u0ZsSX6QnlxWRsN8XKmWq8iJegtKtYHwANDIOHpeyL_8MCjlDg8hd7hmmT5Vq56rkOQuq998_M8pfnp0WtJ75Iq7kBw" class="kg-image" alt="" width="474" height="315"><figcaption>Authors of the book - <em>Neural Search - From Prototype to Production with Jina</em></figcaption></figure><p>Following the insightful speech by Han, we were excited to announce the release of our first book <em>Neural Search - From Prototype to Production with Jina</em> - a must-have starter pack for understanding neural search and building useful applications on top... Two of the authors, Susana Guzmán and Bo Wang, shared their experiences writing the book and the reason why it is a <em>must-read</em>. Please check the article for an inside scoop on Neural Search with our new book! </p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://jina.ai/news/neural-search-from-prototype-to-production-with-jina/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Get the Inside Scoop on Neural Search with Our New Book!</div><div class="kg-bookmark-description">If you’re an AI engineer building search systems for any kind of data type – text, Q+A, image, audio, PDF, 3D models, etc. – or a Python developer interested in search or state-of-the-art deep learning techniques, then our new book “Neural Search - From Prototype to Production with Jina” is for you.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--30--3.png" alt=""></div></a><figcaption>The book is available on Amazon</figcaption></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_01447.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_01447.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_01447.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_01447.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_01447.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_01494.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_01494.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_01494.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_01494.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_01494.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_01573.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_01573.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_01573.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_01573.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_01573.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.49925 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/2022-12-02-Jina-AI_01620.jpg" width="2000" height="1334" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/2022-12-02-Jina-AI_01620.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/2022-12-02-Jina-AI_01620.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/2022-12-02-Jina-AI_01620.jpg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/2022-12-02-Jina-AI_01620.jpg 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>From top left to bottom right: Sami Jaghouar, Leon Wolf, Girish Chandrashekar, Georgios Mastrapas</figcaption></figure><p>The engineer’s lightning talk was an essential part of this event! The team presented exciting progress on our product offerings and feature updates. Find out more in our recent blogs:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/docarray-0-20-update?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">DocArray 0.20 Update</div><div class="kg-bookmark-description">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--9-.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/donate-docarray-lf-for-inclusive-standard-multimodal-data-model/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">We’re Donating DocArray to LF for an Inclusive and Standard Multimodal Data Model</div><div class="kg-bookmark-description">DocArray is now hosted under the Linux Foundation AI &amp; Data - a neutral home to build and support an open AI and data community. This is the start of a new day for DocArray.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--37-.png" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/BeFunky-collage.png" class="kg-image" alt="" width="2000" height="1181" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/BeFunky-collage.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/BeFunky-collage.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/BeFunky-collage.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/BeFunky-collage.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Left to right: <a href="https://www.linkedin.com/in/gfissore/?ref=jina-ai-gmbh.ghost.io">Giancarlo Fissore</a>, <a href="https://www.linkedin.com/in/codebuffet/?ref=jina-ai-gmbh.ghost.io">Peter Willemsen</a> &amp; <a href="https://www.linkedin.com/in/moritz-feuerpfeil/?ref=jina-ai-gmbh.ghost.io">Moritz Feuerpfeil</a>&nbsp;</figcaption></figure><p>We are dedicated to supporting the open-source community and the contributions that make our product stronger. We are thrilled to have invited Giancarlo Fissore and Peter Willemsen, two valued members of the Jina community, to share their experiences and insights. In addition, Moritz Feuerpiel from Kern.ai brought up a thought-provoking talk on the origins and costs of labeling errors. Our community would not be the same without them!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://jina.ai/slack/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Become a member of our community</a></div><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://lh5.googleusercontent.com/Fr2KLHUbi_Iw4YCH8BPaXvTv39Asu2GrZUNUM4tTDFb-uJwQiun1MR5Y8d0nYSrxfGbkTNT50Srf8zFX70TGh9tKkzmv6JABVpnuQTwFkDki7yvEMzSKC9xOMcZLv3lVL1Ts0yCINVVACIh7kXc06Oq0INeeYjuyUCSY0FLjfmpPm5PoA1UUDS8SzIGd-A" class="kg-image" alt="" width="624" height="416"><figcaption>Panel Discussion: How to build an engaging tech community?</figcaption></figure><p>In the last panel session, tech community leaders Dania Meira (Director of AI Guild), Stephen Batifol (organizer of the MLOps local community), and Dr. Larysa Visengeriyeva (senior consultant at INNQ) joined our Head of Engineering, Maximilian Werk, shared their experiences and insights on how to build an engaging community.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://lh4.googleusercontent.com/emob7SJLl91Fcgx5I9tLb_-4Te6nd608vxnwoQSS36op6VAv7PfVAi_rx60EC2qFNPmfWJswXfaZBXGj1clMWSQ8AJLIkIo-pvAjrLvnbZOlPEY0OipkHivaXK9yOC6oDpeYKMnDoYJ_eHja9KVngX6fcIN_aYMHnTG7hptMtEQ-5CQlpolUM7S0Td1d2A" class="kg-image" alt="" width="624" height="416"><figcaption>Jina AI team together with their own Santa Claus</figcaption></figure><p>We're honored and humbled to know that so many of you are using Jina AI to build amazing things and contributing your energy and expertise back to our open-source projects. We are already working on upcoming events and creating more memorable moments with you, our community, so sign up to our newsletter and stay tuned!</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/35hmBwYHYikAAAAC/the-office-bow.gif" class="kg-image" alt="" width="300" height="168"><figcaption>Thank you to our community for being awesome!</figcaption></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-ai-annual-event%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina AI Cloud Alpha Launch</title><meta charset="utf-8"><meta name="title" content="Jina AI Cloud Alpha Launch"><meta name="description" content="Announcing the alpha launch of Jina AI Cloud, designed to streamline and simplify deployment and management of your multimodal applications"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-ai-cloud-alpha"><meta property="og:title" content="Jina AI Cloud Alpha Launch"><meta property="og:description" content="Announcing the alpha launch of Jina AI Cloud, designed to streamline and simplify deployment and management of your multimodal applications"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--15-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-ai-cloud-alpha"><meta property="twitter:title" content="Jina AI Cloud Alpha Launch"><meta property="twitter:description" content="Announcing the alpha launch of Jina AI Cloud, designed to streamline and simplify deployment and management of your multimodal applications"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--15-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina AI Cloud Alpha Launch</title><meta charset="utf-8"><meta name="title" content="Jina AI Cloud Alpha Launch"><meta name="description" content="Announcing the alpha launch of Jina AI Cloud, designed to streamline and simplify deployment and management of your multimodal applications"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-ai-cloud-alpha"><meta property="og:title" content="Jina AI Cloud Alpha Launch"><meta property="og:description" content="Announcing the alpha launch of Jina AI Cloud, designed to streamline and simplify deployment and management of your multimodal applications"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--15-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-ai-cloud-alpha"><meta property="twitter:title" content="Jina AI Cloud Alpha Launch"><meta property="twitter:description" content="Announcing the alpha launch of Jina AI Cloud, designed to streamline and simplify deployment and management of your multimodal applications"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--15-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina AI Cloud Alpha Launch</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Announcing the alpha launch of Jina AI Cloud, designed to streamline and simplify deployment and management of your multimodal applications</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 24, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina AI is all about building an open-source ecosystem around every task related to multimodal AI and AI-powered search. We’re happy to announce our alpha launch of Jina AI Cloud, designed to streamline and simplify deployment and management of your multimodal applications. Now you can spend more time building amazing products instead of getting bogged down in Kubernetes, deployments, and all those other nuts and bolts.</p><h2 id="activity-at-a-glance-with-the-dashboard">Activity at a Glance with the Dashboard</h2><p>The new <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">dashboard</a> shows you all activity at a glance, giving a clear understanding of the status of your Flows, Apps and deployments. Get an overview of important metrics such as the number of requests served, active Flows, and recently completed Finetuner runs. You can also quickly identify any potential issues or areas that require attention.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.17.51--1-.png" class="kg-image" alt="" width="2000" height="1137" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.17.51--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.17.51--1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.17.51--1-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/01/Screenshot-2023-01-23-at-14.17.51--1-.png 2400w" sizes="(min-width: 720px) 720px"></figure><h2 id="deploy-multimodal-search-apps">Deploy Multimodal Search Apps</h2><p>With this release, you can create awesome <a href="https://cloud.jina.ai/user/apps?ref=jina-ai-gmbh.ghost.io">multi-modal search applications</a> with just a few clicks! Upload your dataset, choose the fields you want to search and filter, and voilà, you’ve got a production-ready search application that you can integrate into your business using RESTful APIs. <a href="https://cloud.jina.ai/user/apps?ref=jina-ai-gmbh.ghost.io">Try it out</a> and tell us what you think!</p><figure class="kg-card kg-video-card kg-width-wide"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/deploy_search_apps-1.mp4" poster="https://img.spacergif.org/v1/4054x2160/0a/spacer.png" width="4054" height="2160" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember430.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="on-demand-ai-models-with-inference-api">On-Demand AI Models with Inference API</h2><p>The <a href="https://cloud.jina.ai/user/inference-api?ref=jina-ai-gmbh.ghost.io">Inference API</a> takes care of all your AI model hosting and deployment needs. Just choose the state-of-the-art model for your task and start sending queries! No more painful GPU costs or wondering how you can optimize and finetune your CLIP deployment.</p><p>Right now, the Inference API offers access to a variety of CLIP model variations. Going further, we plan to expand our offering beyond CLIP and let you offload all your model-hosting requirements to us! Stay tuned for more news in the coming weeks (or <a href="http://eepurl.com/hb-r_L?ref=jina-ai-gmbh.ghost.io">subscribe to our newsletter</a>!)</p><figure class="kg-card kg-video-card kg-width-wide"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/Screen-2023-01-24-093144--1-.mp4" poster="https://img.spacergif.org/v1/2876x1532/0a/spacer.png" width="2876" height="1532" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember664.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="streamlined-finetuning-via-finetuner-api">Streamlined Finetuning via Finetuner API</h2><p>Easily enhance pre-trained models with Jina AI's Finetuner and boost your performance with a low budget and few training samples - all in a simple yet powerful platform. With Jina AI Cloud, you can view, manage and create <a href="https://cloud.jina.ai/user/finetuner-api?ref=jina-ai-gmbh.ghost.io">Finetuner runs</a> directly in the browser. </p><p>You can not only track all your previous runs with detailed information, but also see how to implement the resulting model. </p><p>In Finetuner, you can easily configure hyper-parameters to increase the accuracy of the model. Finetuner is perfect for neural model task optimization, allowing you to get the best results with the least amount of effort.</p><figure class="kg-card kg-video-card kg-width-wide"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/Finetuner-UI.mp4" poster="https://img.spacergif.org/v1/4054x2160/0a/spacer.png" width="4054" height="2160" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember442.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="monitor-jcloud-flows">Monitor JCloud Flows</h2><p>Our CLI tool <code>jc</code> is great to get information about running Flows in JCloud (Jina AI’s cloud hosting service), but the command line can be a bit limiting at times.</p><p>The Jina AI Cloud platform lets you <a href="https://cloud.jina.ai/user/flows?ref=jina-ai-gmbh.ghost.io">navigate between Flows and see all details quickly</a>. You can also monitor dashboards and logs directly in the UI, to make sure everything is going as planned.</p><figure class="kg-card kg-video-card kg-width-wide"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/flows-trimmed-cropped3.mp4" poster="https://img.spacergif.org/v1/1402x736/0a/spacer.png" width="1402" height="736" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember112.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="manage-your-docarrays">Manage your DocArrays</h2><p><a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray</a> is an open source multimodal data storage library that lets you store all kinds of data in a unified format. Use the <a href="https://cloud.jina.ai/user/storage?ref=jina-ai-gmbh.ghost.io">storage view</a> to view and share your DocArrays, and then use them in all our services. DocArray is the perfect way to pass data through the Jina AI ecosystem.</p><figure class="kg-card kg-video-card kg-width-wide"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/Docarray.mp4" poster="https://img.spacergif.org/v1/2876x1532/0a/spacer.png" width="2876" height="1532" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember458.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="manage-personal-access-tokens">Manage Personal Access Tokens</h2><p><a href="https://cloud.jina.ai/settings/tokens?ref=jina-ai-gmbh.ghost.io">Personal access tokens</a> make the Jina AI World go round. Use these tokens to access the Jina AI Cloud via your code, authenticate your applications and utilize our great features!</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/PATs.png" class="kg-image" alt="" width="1573" height="681" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/PATs.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/PATs.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/PATs.png 1573w" sizes="(min-width: 720px) 720px"></figure><h2 id="built-in-chat-support">Built-in Chat Support</h2><p>With our integrated chat, you can get direct help regarding any issues or questions about the Jina AI Cloud or ecosystem.</p><h2 id="get-started-now">Get Started Now</h2><p>Looking to build your search solution? Get started today with Jina AI and try our services for free!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Go to Jina AI Cloud</a></div><p>Want to explore how Jina AI can enhance your business or still have questions?Reach out and book a meeting today by emailing <a href="mailto:hello@jina.ai">hello@jina.ai</a>.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-ai-cloud-alpha%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina AI Cloud Alpha Launch</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Announcing the alpha launch of Jina AI Cloud, designed to streamline and simplify deployment and management of your multimodal applications</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 24, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina AI is all about building an open-source ecosystem around every task related to multimodal AI and AI-powered search. We’re happy to announce our alpha launch of Jina AI Cloud, designed to streamline and simplify deployment and management of your multimodal applications. Now you can spend more time building amazing products instead of getting bogged down in Kubernetes, deployments, and all those other nuts and bolts.</p><h2 id="activity-at-a-glance-with-the-dashboard">Activity at a Glance with the Dashboard</h2><p>The new <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">dashboard</a> shows you all activity at a glance, giving a clear understanding of the status of your Flows, Apps and deployments. Get an overview of important metrics such as the number of requests served, active Flows, and recently completed Finetuner runs. You can also quickly identify any potential issues or areas that require attention.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Screenshot-2023-01-23-at-14.17.51--1-.png" class="kg-image" alt="" width="2000" height="1137" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/Screenshot-2023-01-23-at-14.17.51--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/Screenshot-2023-01-23-at-14.17.51--1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/Screenshot-2023-01-23-at-14.17.51--1-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/01/Screenshot-2023-01-23-at-14.17.51--1-.png 2400w" sizes="(min-width: 720px) 720px"></figure><h2 id="deploy-multimodal-search-apps">Deploy Multimodal Search Apps</h2><p>With this release, you can create awesome <a href="https://cloud.jina.ai/user/apps?ref=jina-ai-gmbh.ghost.io">multi-modal search applications</a> with just a few clicks! Upload your dataset, choose the fields you want to search and filter, and voilà, you’ve got a production-ready search application that you can integrate into your business using RESTful APIs. <a href="https://cloud.jina.ai/user/apps?ref=jina-ai-gmbh.ghost.io">Try it out</a> and tell us what you think!</p><figure class="kg-card kg-video-card kg-width-wide"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/deploy_search_apps-1.mp4" poster="https://img.spacergif.org/v1/4054x2160/0a/spacer.png" width="4054" height="2160" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember430.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="on-demand-ai-models-with-inference-api">On-Demand AI Models with Inference API</h2><p>The <a href="https://cloud.jina.ai/user/inference-api?ref=jina-ai-gmbh.ghost.io">Inference API</a> takes care of all your AI model hosting and deployment needs. Just choose the state-of-the-art model for your task and start sending queries! No more painful GPU costs or wondering how you can optimize and finetune your CLIP deployment.</p><p>Right now, the Inference API offers access to a variety of CLIP model variations. Going further, we plan to expand our offering beyond CLIP and let you offload all your model-hosting requirements to us! Stay tuned for more news in the coming weeks (or <a href="http://eepurl.com/hb-r_L?ref=jina-ai-gmbh.ghost.io">subscribe to our newsletter</a>!)</p><figure class="kg-card kg-video-card kg-width-wide"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/Screen-2023-01-24-093144--1-.mp4" poster="https://img.spacergif.org/v1/2876x1532/0a/spacer.png" width="2876" height="1532" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember664.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="streamlined-finetuning-via-finetuner-api">Streamlined Finetuning via Finetuner API</h2><p>Easily enhance pre-trained models with Jina AI's Finetuner and boost your performance with a low budget and few training samples - all in a simple yet powerful platform. With Jina AI Cloud, you can view, manage and create <a href="https://cloud.jina.ai/user/finetuner-api?ref=jina-ai-gmbh.ghost.io">Finetuner runs</a> directly in the browser. </p><p>You can not only track all your previous runs with detailed information, but also see how to implement the resulting model. </p><p>In Finetuner, you can easily configure hyper-parameters to increase the accuracy of the model. Finetuner is perfect for neural model task optimization, allowing you to get the best results with the least amount of effort.</p><figure class="kg-card kg-video-card kg-width-wide"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/Finetuner-UI.mp4" poster="https://img.spacergif.org/v1/4054x2160/0a/spacer.png" width="4054" height="2160" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember442.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="monitor-jcloud-flows">Monitor JCloud Flows</h2><p>Our CLI tool <code>jc</code> is great to get information about running Flows in JCloud (Jina AI’s cloud hosting service), but the command line can be a bit limiting at times.</p><p>The Jina AI Cloud platform lets you <a href="https://cloud.jina.ai/user/flows?ref=jina-ai-gmbh.ghost.io">navigate between Flows and see all details quickly</a>. You can also monitor dashboards and logs directly in the UI, to make sure everything is going as planned.</p><figure class="kg-card kg-video-card kg-width-wide"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/flows-trimmed-cropped3.mp4" poster="https://img.spacergif.org/v1/1402x736/0a/spacer.png" width="1402" height="736" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember112.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="manage-your-docarrays">Manage your DocArrays</h2><p><a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray</a> is an open source multimodal data storage library that lets you store all kinds of data in a unified format. Use the <a href="https://cloud.jina.ai/user/storage?ref=jina-ai-gmbh.ghost.io">storage view</a> to view and share your DocArrays, and then use them in all our services. DocArray is the perfect way to pass data through the Jina AI ecosystem.</p><figure class="kg-card kg-video-card kg-width-wide"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/Docarray.mp4" poster="https://img.spacergif.org/v1/2876x1532/0a/spacer.png" width="2876" height="1532" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember458.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="manage-personal-access-tokens">Manage Personal Access Tokens</h2><p><a href="https://cloud.jina.ai/settings/tokens?ref=jina-ai-gmbh.ghost.io">Personal access tokens</a> make the Jina AI World go round. Use these tokens to access the Jina AI Cloud via your code, authenticate your applications and utilize our great features!</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/PATs.png" class="kg-image" alt="" width="1573" height="681" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/PATs.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/PATs.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/PATs.png 1573w" sizes="(min-width: 720px) 720px"></figure><h2 id="built-in-chat-support">Built-in Chat Support</h2><p>With our integrated chat, you can get direct help regarding any issues or questions about the Jina AI Cloud or ecosystem.</p><h2 id="get-started-now">Get Started Now</h2><p>Looking to build your search solution? Get started today with Jina AI and try our services for free!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Go to Jina AI Cloud</a></div><p>Want to explore how Jina AI can enhance your business or still have questions?Reach out and book a meeting today by emailing <a href="mailto:hello@jina.ai">hello@jina.ai</a>.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-ai-cloud-alpha%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina AI Cloud: Production-ready Scalable Multimodal AI</title><meta charset="utf-8"><meta name="title" content="Jina AI Cloud: Production-ready Scalable Multimodal AI"><meta name="description" content="Jina AI Cloud is the most advanced MLOps platform for building multimodal AI applications in the cloud. Users can translate their data and a few lines of code into a production-ready service without dealing with infrastructure complexity or scaling hassles."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-ai-cloud-production-ready-scalable-multimodal-ai"><meta property="og:title" content="Jina AI Cloud: Production-ready Scalable Multimodal AI"><meta property="og:description" content="Jina AI Cloud is the most advanced MLOps platform for building multimodal AI applications in the cloud. Users can translate their data and a few lines of code into a production-ready service without dealing with infrastructure complexity or scaling hassles."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/banner-JAC.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-ai-cloud-production-ready-scalable-multimodal-ai"><meta property="twitter:title" content="Jina AI Cloud: Production-ready Scalable Multimodal AI"><meta property="twitter:description" content="Jina AI Cloud is the most advanced MLOps platform for building multimodal AI applications in the cloud. Users can translate their data and a few lines of code into a production-ready service without dealing with infrastructure complexity or scaling hassles."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/banner-JAC.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina AI Cloud: Production-ready Scalable Multimodal AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI Cloud is the most advanced MLOps platform for building multimodal AI applications in the cloud. Users can translate their data and a few lines of code into a production-ready service without dealing with infrastructure complexity or scaling hassles.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Wolf_Leon-web-square.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Leon Wolf, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 09, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>We are excited to announce the launch of Jina AI Cloud: The central place for creating, launching, and managing neural search, creative AI, and multimodal AI applications.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">The most advanced MLOps platform for multimodal AI, neural search and creative AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a></figure><p>Jina AI Cloud is a platform for quick access to all the information you need to develop, adapt and integrate AI into your business. It provides an intuitive and easy-to-use experience with accessible onboarding while letting experienced users efficiently set up, monitor, and manage AI services.</p><p>With Jina AI Cloud, you can access real-time logs, <a href="https://grafana.com/grafana/dashboards/?ref=jina-ai-gmbh.ghost.io">Grafana dashboards</a>, and detailed itemization of resource usage for your services. The platform anchors Jina AI’s entire ecosystem of tools to accelerate AI application development.</p><p>Features:</p><ul><li>Build out-of-the-box <a href="https://cloud.jina.ai/user/search?ref=jina-ai-gmbh.ghost.io">multimodal search applications</a>.</li><li>Offload costly AI hosting and maintenance to our <a href="https://cloud.jina.ai/user/inference?ref=jina-ai-gmbh.ghost.io">Inference service</a></li><li><a href="https://finetunerplus.jina.ai/?ref=jina-ai-gmbh.ghost.io">Fine-tune AI models</a> to maximize quality</li><li>View detailed information about application performance with <a href="https://docs.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Flows</a></li><li>Direct support via live chat</li></ul><p>Our <a href="https://cloud.jina.ai/pricing?ref=jina-ai-gmbh.ghost.io">flexible pricing system</a> scales smoothly with your demand, so you only pay for the resources you need. With our business-friendly <strong>Pro plan</strong>, you use as many credits as you need and receive an invoice at the end of each month.</p><p>If you have a high-demand service, <a href="mailto:cloud@jina.ai">contact us</a> about our <strong>Enterprise plan</strong>, which offers tailored solutions and volume discounts!</p><p>If you want to try Jina AI Cloud out to see if it’s for you, our <strong>Free plan</strong> provides enough access to experiment, learn and create prototype applications at your own pace without paying anything!</p><p>At Jina AI, we are committed to making multimodal AI accessible to everyone, not just AI experts and people with expensive hardware. Jina AI Cloud enables that by providing users with an intuitive, empowering, and reasonably priced cloud platform for building multimodal AI applications.</p><p>For more information, visit our website at <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">https://cloud.jina.ai/</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">The most advanced MLOps platform for multimodal AI, neural search and creative AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-ai-cloud-production-ready-scalable-multimodal-ai%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina AI Cloud: Production-ready Scalable Multimodal AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI Cloud is the most advanced MLOps platform for building multimodal AI applications in the cloud. Users can translate their data and a few lines of code into a production-ready service without dealing with infrastructure complexity or scaling hassles.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Wolf_Leon-web-square.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Leon Wolf, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 09, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>We are excited to announce the launch of Jina AI Cloud: The central place for creating, launching, and managing neural search, creative AI, and multimodal AI applications.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">The most advanced MLOps platform for multimodal AI, neural search and creative AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a></figure><p>Jina AI Cloud is a platform for quick access to all the information you need to develop, adapt and integrate AI into your business. It provides an intuitive and easy-to-use experience with accessible onboarding while letting experienced users efficiently set up, monitor, and manage AI services.</p><p>With Jina AI Cloud, you can access real-time logs, <a href="https://grafana.com/grafana/dashboards/?ref=jina-ai-gmbh.ghost.io">Grafana dashboards</a>, and detailed itemization of resource usage for your services. The platform anchors Jina AI’s entire ecosystem of tools to accelerate AI application development.</p><p>Features:</p><ul><li>Build out-of-the-box <a href="https://cloud.jina.ai/user/search?ref=jina-ai-gmbh.ghost.io">multimodal search applications</a>.</li><li>Offload costly AI hosting and maintenance to our <a href="https://cloud.jina.ai/user/inference?ref=jina-ai-gmbh.ghost.io">Inference service</a></li><li><a href="https://finetunerplus.jina.ai/?ref=jina-ai-gmbh.ghost.io">Fine-tune AI models</a> to maximize quality</li><li>View detailed information about application performance with <a href="https://docs.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Flows</a></li><li>Direct support via live chat</li></ul><p>Our <a href="https://cloud.jina.ai/pricing?ref=jina-ai-gmbh.ghost.io">flexible pricing system</a> scales smoothly with your demand, so you only pay for the resources you need. With our business-friendly <strong>Pro plan</strong>, you use as many credits as you need and receive an invoice at the end of each month.</p><p>If you have a high-demand service, <a href="mailto:cloud@jina.ai">contact us</a> about our <strong>Enterprise plan</strong>, which offers tailored solutions and volume discounts!</p><p>If you want to try Jina AI Cloud out to see if it’s for you, our <strong>Free plan</strong> provides enough access to experiment, learn and create prototype applications at your own pace without paying anything!</p><p>At Jina AI, we are committed to making multimodal AI accessible to everyone, not just AI experts and people with expensive hardware. Jina AI Cloud enables that by providing users with an intuitive, empowering, and reasonably priced cloud platform for building multimodal AI applications.</p><p>For more information, visit our website at <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">https://cloud.jina.ai/</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">The most advanced MLOps platform for multimodal AI, neural search and creative AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-ai-cloud-production-ready-scalable-multimodal-ai%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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diff --git a/news/jina-ai-is-coming-to-pycon-us-2023/index.html b/news/jina-ai-is-coming-to-pycon-us-2023/index.html
index da5b4b2a1c5..d8c143beab0 100644
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+++ b/news/jina-ai-is-coming-to-pycon-us-2023/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina AI is Coming to PyCon US 2023</title><meta charset="utf-8"><meta name="title" content="Jina AI is Coming to PyCon US 2023"><meta name="description" content="Jina AI senior software engineer Johannes Messner is delivering a sold-out presentation at PyCon US 2023 titled “Modern Typed Python for (Multimodal) ML: From Training to Deployment.”"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-ai-is-coming-to-pycon-us-2023"><meta property="og:title" content="Jina AI is Coming to PyCon US 2023"><meta property="og:description" content="Jina AI senior software engineer Johannes Messner is delivering a sold-out presentation at PyCon US 2023 titled “Modern Typed Python for (Multimodal) ML: From Training to Deployment.”"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/B.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-ai-is-coming-to-pycon-us-2023"><meta property="twitter:title" content="Jina AI is Coming to PyCon US 2023"><meta property="twitter:description" content="Jina AI senior software engineer Johannes Messner is delivering a sold-out presentation at PyCon US 2023 titled “Modern Typed Python for (Multimodal) ML: From Training to Deployment.”"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/B.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina AI is Coming to PyCon US 2023</title><meta charset="utf-8"><meta name="title" content="Jina AI is Coming to PyCon US 2023"><meta name="description" content="Jina AI senior software engineer Johannes Messner is delivering a sold-out presentation at PyCon US 2023 titled “Modern Typed Python for (Multimodal) ML: From Training to Deployment.”"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-ai-is-coming-to-pycon-us-2023"><meta property="og:title" content="Jina AI is Coming to PyCon US 2023"><meta property="og:description" content="Jina AI senior software engineer Johannes Messner is delivering a sold-out presentation at PyCon US 2023 titled “Modern Typed Python for (Multimodal) ML: From Training to Deployment.”"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/B.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-ai-is-coming-to-pycon-us-2023"><meta property="twitter:title" content="Jina AI is Coming to PyCon US 2023"><meta property="twitter:description" content="Jina AI senior software engineer Johannes Messner is delivering a sold-out presentation at PyCon US 2023 titled “Modern Typed Python for (Multimodal) ML: From Training to Deployment.”"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/B.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI senior software engineer Johannes Messner is delivering a sold-out presentation at PyCon US 2023 titled “Modern Typed Python for (Multimodal) ML: From Training to Deployment.”</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/avatar.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jocelyn Matthews</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 30, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="featured-presentation-topic-type-hints-in-python-for-multimodal-ml">Featured Presentation Topic: Type Hints in Python for Multimodal ML</h2><p>Jina AI senior software engineer Johannes Messner is delivering a sold-out presentation at PyCon US 2023 titled “<a href="https://us.pycon.org/2023/schedule/presentation/131/?ref=jina-ai-gmbh.ghost.io">Modern Typed Python for (Multimodal) ML: From Training to Deployment</a>.” The one-hour talk is in Room 251D of the Salt Palace Convention Center at 9:30am CT, April 20. Johannes is a core maintainer of DocArray and Jina, ML engineer at Jina AI, fan of multimodal AI and SSL, enjoyer of good food, and a man of the mountains. He staunchly believes that beautiful code is good code.</p><p>In his talk, Johannes will explore the benefits of Python type hints and also show how they are infiltrating the next big domain: machine learning.</p><p>The introduction of Johannes’ talk is an overview of typing in Python: its history, utility, and the tooling landscape. The main part of his talk focuses on Python type hints as specific to ML. This second section covers why typing is useful in ML; tensor shapes and multimodal data; getting the most out of ML tools like jaxtyping and DocArray; data organization a keeping track of tensor shapes with type hints; &nbsp;and how typing-focused libraries can bridge the gap between training and deployment.</p><p>“<a href="https://us.pycon.org/2023/schedule/presentation/131/?ref=jina-ai-gmbh.ghost.io">Modern Typed Python for (Multimodal) ML: From Training to Deployment</a>” is for anyone who would like to know more about Python type hints that can be helpful in their code base, and is especially well-suited for machine learning practitioners focusing on model training and/or model deployment and serving.</p><p>Audience members will leave the talk with three actionable takeaways: an understanding of why Python-type hints are useful; why they’re particularly useful in the ML domain; and how libraries like DocArray can be leveraged in practice.</p><h2 id="about-pycon-us-2023">About PyCon US 2023</h2><p>Boasting over 2,000 attendees, <a href="https://us.pycon.org/?ref=jina-ai-gmbh.ghost.io">PyCon US 2023</a> will take place April 19-27 at the Salt Palace Convention Center in Salt Lake City, Utah. Attendees will find an amazing program filled with pre-conference tutorials and sponsor presentations; 90+ of the Python community’s best talks; speakers; a lively Expo Hall; and lightning talks on each main conference day. Four days of sprints follow the main conoference, that are free and open to the public. PyCon US offers a whole host of events such as the Job Fair, Summits, Open Spaces, the PyLadies Auction, and the always-popular “hallway track,” which brings together Python users from around the world.</p><h2 id="visit-us-onsite">Visit us onsite!</h2><p>Jina AI is a Partner-level sponsor at PyCon’s 20th Anniversary Special. The Jina AI booth is #405, located in the back right corner of the <a href="https://us.pycon.org/2023/expo/expo-hall/?ref=jina-ai-gmbh.ghost.io">expo hall</a>. Please swing by! 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI senior software engineer Johannes Messner is delivering a sold-out presentation at PyCon US 2023 titled “Modern Typed Python for (Multimodal) ML: From Training to Deployment.”</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/avatar.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jocelyn Matthews</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 30, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="featured-presentation-topic-type-hints-in-python-for-multimodal-ml">Featured Presentation Topic: Type Hints in Python for Multimodal ML</h2><p>Jina AI senior software engineer Johannes Messner is delivering a sold-out presentation at PyCon US 2023 titled “<a href="https://us.pycon.org/2023/schedule/presentation/131/?ref=jina-ai-gmbh.ghost.io">Modern Typed Python for (Multimodal) ML: From Training to Deployment</a>.” The one-hour talk is in Room 251D of the Salt Palace Convention Center at 9:30am CT, April 20. Johannes is a core maintainer of DocArray and Jina, ML engineer at Jina AI, fan of multimodal AI and SSL, enjoyer of good food, and a man of the mountains. He staunchly believes that beautiful code is good code.</p><p>In his talk, Johannes will explore the benefits of Python type hints and also show how they are infiltrating the next big domain: machine learning.</p><p>The introduction of Johannes’ talk is an overview of typing in Python: its history, utility, and the tooling landscape. The main part of his talk focuses on Python type hints as specific to ML. This second section covers why typing is useful in ML; tensor shapes and multimodal data; getting the most out of ML tools like jaxtyping and DocArray; data organization a keeping track of tensor shapes with type hints; &nbsp;and how typing-focused libraries can bridge the gap between training and deployment.</p><p>“<a href="https://us.pycon.org/2023/schedule/presentation/131/?ref=jina-ai-gmbh.ghost.io">Modern Typed Python for (Multimodal) ML: From Training to Deployment</a>” is for anyone who would like to know more about Python type hints that can be helpful in their code base, and is especially well-suited for machine learning practitioners focusing on model training and/or model deployment and serving.</p><p>Audience members will leave the talk with three actionable takeaways: an understanding of why Python-type hints are useful; why they’re particularly useful in the ML domain; and how libraries like DocArray can be leveraged in practice.</p><h2 id="about-pycon-us-2023">About PyCon US 2023</h2><p>Boasting over 2,000 attendees, <a href="https://us.pycon.org/?ref=jina-ai-gmbh.ghost.io">PyCon US 2023</a> will take place April 19-27 at the Salt Palace Convention Center in Salt Lake City, Utah. Attendees will find an amazing program filled with pre-conference tutorials and sponsor presentations; 90+ of the Python community’s best talks; speakers; a lively Expo Hall; and lightning talks on each main conference day. Four days of sprints follow the main conoference, that are free and open to the public. PyCon US offers a whole host of events such as the Job Fair, Summits, Open Spaces, the PyLadies Auction, and the always-popular “hallway track,” which brings together Python users from around the world.</p><h2 id="visit-us-onsite">Visit us onsite!</h2><p>Jina AI is a Partner-level sponsor at PyCon’s 20th Anniversary Special. The Jina AI booth is #405, located in the back right corner of the <a href="https://us.pycon.org/2023/expo/expo-hall/?ref=jina-ai-gmbh.ghost.io">expo hall</a>. Please swing by! 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI</title><meta charset="utf-8"><meta name="title" content="Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI"><meta name="description" content="Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-ai-launches-worlds-first-open-source-8k-text-embedding-rivaling-openai"><meta property="og:title" content="Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI"><meta property="og:description" content="Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels--11-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-ai-launches-worlds-first-open-source-8k-text-embedding-rivaling-openai"><meta property="twitter:title" content="Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI"><meta property="twitter:description" content="Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels--11-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI</title><meta charset="utf-8"><meta name="title" content="Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI"><meta name="description" content="Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-ai-launches-worlds-first-open-source-8k-text-embedding-rivaling-openai"><meta property="og:title" content="Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI"><meta property="og:description" content="Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels--11-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-ai-launches-worlds-first-open-source-8k-text-embedding-rivaling-openai"><meta property="twitter:title" content="Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI"><meta property="twitter:description" content="Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels--11-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 25, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><strong>Berlin, Germany - October 25, 2023</strong> – Jina AI, the Berlin-based artificial intelligence company, is thrilled to announce the launch of its second-generation text embedding model: <code><strong>jina-embeddings-v2</strong></code>. This cutting-edge model is now the only open-source offering that supports an impressive 8K (8192 tokens) context length, putting it on par with OpenAI's proprietary model, <code>text-embedding-ada-002</code>, in terms of both capabilities and performance <a href="https://huggingface.co/spaces/mteb/leaderboard?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">on the Massive Text Embedding Benchmark (MTEB) leaderboard.</a></p><h2 id="benchmarking-against-the-best-8k-model-from-open-ai"><strong>Benchmarking Against the Best 8K Model from Open AI</strong></h2><p>When directly compared with OpenAI's 8K model <code>text-embedding-ada-002</code>, <code>jina-embeddings-v2</code> showcases its mettle. Below is a performance comparison table, highlighting areas where <code>jina-embeddings-v2</code> particularly excels:</p>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI introduces jina-embeddings-v2, the world's first open-source model boasting an 8K context length. Matching the prowess of OpenAI's proprietary models, this innovation is now publicly accessible on Huggingface, signaling a significant milestone in the landscape of text embeddings.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 25, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><strong>Berlin, Germany - October 25, 2023</strong> – Jina AI, the Berlin-based artificial intelligence company, is thrilled to announce the launch of its second-generation text embedding model: <code><strong>jina-embeddings-v2</strong></code>. This cutting-edge model is now the only open-source offering that supports an impressive 8K (8192 tokens) context length, putting it on par with OpenAI's proprietary model, <code>text-embedding-ada-002</code>, in terms of both capabilities and performance <a href="https://huggingface.co/spaces/mteb/leaderboard?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">on the Massive Text Embedding Benchmark (MTEB) leaderboard.</a></p><h2 id="benchmarking-against-the-best-8k-model-from-open-ai"><strong>Benchmarking Against the Best 8K Model from Open AI</strong></h2><p>When directly compared with OpenAI's 8K model <code>text-embedding-ada-002</code>, <code>jina-embeddings-v2</code> showcases its mettle. Below is a performance comparison table, highlighting areas where <code>jina-embeddings-v2</code> particularly excels:</p>
 
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-<p>Notably, <code>jina-embedding-v2</code> outperforms its OpenAI counterpart in Classification Average, Reranking Average, Retrieval Average, and Summarization Average.</p><h2 id="features-and-benefits"><strong>Features and Benefits</strong></h2><p>Jina AI’s dedication to innovation is evident in this latest offering:</p><ul><li><strong>From Scratch to Superiority</strong>: The <code>jina-embeddings-v2</code> was built from the ground up. Over<strong> </strong>the last three months, the team at Jina AI engaged in intensive R&amp;D, data collection, and tuning. The outcome is a model that marks a significant leap from its predecessor.</li><li><strong>Unlocking Extended Context Potential with 8K</strong>: <code>jina-embeddings-v2</code> isn’t just a technical feat; its 8K context length opens doors to new industry applications:<ul><li><strong>Legal Document Analysis</strong>: Ensure every detail in extensive legal texts is captured and analyzed.</li><li><strong>Medical Research</strong>: Embed scientific papers holistically for advanced analytics and discovery.</li><li><strong>Literary Analysis</strong>: Dive deep into long-form content, capturing nuanced thematic elements.</li><li><strong>Financial Forecasting</strong>: Attain superior insights from detailed financial reports.</li><li><strong>Conversational AI</strong>: Improve chatbot responses to intricate user queries.</li></ul></li></ul><p>Benchmarking shows that in several datasets, this extended context enabled <code>jina-embeddings-v2</code> to outperform other leading base embedding models, emphasizing the practical advantages of longer context capabilities.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Screenshot-from-2023-10-23-17-41-40.png" class="kg-image" alt="" width="2000" height="647" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Screenshot-from-2023-10-23-17-41-40.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/Screenshot-from-2023-10-23-17-41-40.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/10/Screenshot-from-2023-10-23-17-41-40.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Screenshot-from-2023-10-23-17-41-40.png 2359w" sizes="(min-width: 720px) 720px"></figure><ul><li><strong>Availability</strong>: Both models are freely available for download on Huggingface:<ul><li><strong>Base Model</strong> (0.27G) - Designed for heavy-duty tasks requiring higher accuracy, like academic research or business analytics.</li><li><strong>Small Model</strong> (0.07G) - Crafted for lightweight applications such as mobile apps or devices with limited computing resources.</li></ul></li><li><strong>Size Options for Different Needs</strong>: Understanding the diverse needs of the AI community, Jina AI offers two versions of the model:</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/jinaai/jina-embeddings-v2-base-en?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">jinaai/jina-embeddings-v2-base-en · Hugging Face</div><div class="kg-bookmark-description">We’re on a journey to advance and democratize artificial intelligence through open source and open science.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/models/jinaai/jina-embeddings-v2-base-en.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/jinaai/jina-embeddings-v2-small-en?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">jinaai/jina-embeddings-v2-small-en · Hugging Face</div><div class="kg-bookmark-description">We’re on a journey to advance and democratize artificial intelligence through open source and open science.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/models/jinaai/jina-embeddings-v2-small-en.png" alt=""></div></a></figure><p>In reflecting on the journey and significance of this launch, Dr. Han Xiao, CEO of Jina AI, shared his thoughts:</p><blockquote><em>"In the ever-evolving world of AI, staying ahead and ensuring open access to breakthroughs is paramount. With <code>jina-embeddings-v2</code>, we've achieved a significant milestone. Not only have we developed <strong>the world's first open-source 8K context length model</strong>, but we have also brought it to a performance level on par with industry giants like OpenAI. Our mission at Jina AI is clear: we aim to democratize AI and empower the community with tools that were once confined to proprietary ecosystems. Today, I am proud to say, we have taken a giant leap towards that vision."</em></blockquote><p>This pioneering spirit is evident in Jina AI's forward-looking plans.</p><h2 id="a-glimpse-into-the-future"><strong>A Glimpse into the Future</strong></h2><p>Jina AI is committed to leading the forefront of innovation in AI. Here’s what’s next on their roadmap:</p><ul><li><strong>Academic Insights</strong>: An academic paper detailing the technical intricacies and benchmarks of <code>jina-embeddings-v2</code> will soon be published, allowing the AI community to gain deeper insights.</li><li><strong>API Development</strong>: The team is in the advanced stages of developing an OpenAI-like embeddings API platform. This will provide users with the capability to effortlessly scale the embedding model according to their needs.</li><li><strong>Language Expansion</strong>: Venturing into multilingual embeddings, Jina AI is setting its sights on launching German-English models, further expanding its repertoire.</li></ul><hr><p>About Jina AI GmbH:<br>Located at Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany, Jina AI is at the vanguard of reshaping the landscape of multimodal artificial intelligence. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina AI’s 8K Embedding Models Hit AWS Marketplace for On-Prem Deployment</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina AI launches 8K token length embedding v2 models on AWS marketplace, elevating enterprise AI deployments with EU-engineered innovation and a commitment to data sovereignty.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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+<p>Notably, <code>jina-embedding-v2</code> outperforms its OpenAI counterpart in Classification Average, Reranking Average, Retrieval Average, and Summarization Average.</p><h2 id="features-and-benefits"><strong>Features and Benefits</strong></h2><p>Jina AI’s dedication to innovation is evident in this latest offering:</p><ul><li><strong>From Scratch to Superiority</strong>: The <code>jina-embeddings-v2</code> was built from the ground up. Over<strong> </strong>the last three months, the team at Jina AI engaged in intensive R&amp;D, data collection, and tuning. The outcome is a model that marks a significant leap from its predecessor.</li><li><strong>Unlocking Extended Context Potential with 8K</strong>: <code>jina-embeddings-v2</code> isn’t just a technical feat; its 8K context length opens doors to new industry applications:<ul><li><strong>Legal Document Analysis</strong>: Ensure every detail in extensive legal texts is captured and analyzed.</li><li><strong>Medical Research</strong>: Embed scientific papers holistically for advanced analytics and discovery.</li><li><strong>Literary Analysis</strong>: Dive deep into long-form content, capturing nuanced thematic elements.</li><li><strong>Financial Forecasting</strong>: Attain superior insights from detailed financial reports.</li><li><strong>Conversational AI</strong>: Improve chatbot responses to intricate user queries.</li></ul></li></ul><p>Benchmarking shows that in several datasets, this extended context enabled <code>jina-embeddings-v2</code> to outperform other leading base embedding models, emphasizing the practical advantages of longer context capabilities.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Screenshot-from-2023-10-23-17-41-40.png" class="kg-image" alt="" width="2000" height="647" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/10/Screenshot-from-2023-10-23-17-41-40.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/10/Screenshot-from-2023-10-23-17-41-40.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/10/Screenshot-from-2023-10-23-17-41-40.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/10/Screenshot-from-2023-10-23-17-41-40.png 2359w" sizes="(min-width: 720px) 720px"></figure><ul><li><strong>Availability</strong>: Both models are freely available for download on Huggingface:<ul><li><strong>Base Model</strong> (0.27G) - Designed for heavy-duty tasks requiring higher accuracy, like academic research or business analytics.</li><li><strong>Small Model</strong> (0.07G) - Crafted for lightweight applications such as mobile apps or devices with limited computing resources.</li></ul></li><li><strong>Size Options for Different Needs</strong>: Understanding the diverse needs of the AI community, Jina AI offers two versions of the model:</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/jinaai/jina-embeddings-v2-base-en?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">jinaai/jina-embeddings-v2-base-en · Hugging Face</div><div class="kg-bookmark-description">We’re on a journey to advance and democratize artificial intelligence through open source and open science.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/models/jinaai/jina-embeddings-v2-base-en.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/jinaai/jina-embeddings-v2-small-en?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">jinaai/jina-embeddings-v2-small-en · Hugging Face</div><div class="kg-bookmark-description">We’re on a journey to advance and democratize artificial intelligence through open source and open science.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/models/jinaai/jina-embeddings-v2-small-en.png" alt=""></div></a></figure><p>In reflecting on the journey and significance of this launch, Dr. Han Xiao, CEO of Jina AI, shared his thoughts:</p><blockquote><em>"In the ever-evolving world of AI, staying ahead and ensuring open access to breakthroughs is paramount. With <code>jina-embeddings-v2</code>, we've achieved a significant milestone. Not only have we developed <strong>the world's first open-source 8K context length model</strong>, but we have also brought it to a performance level on par with industry giants like OpenAI. Our mission at Jina AI is clear: we aim to democratize AI and empower the community with tools that were once confined to proprietary ecosystems. Today, I am proud to say, we have taken a giant leap towards that vision."</em></blockquote><p>This pioneering spirit is evident in Jina AI's forward-looking plans.</p><h2 id="a-glimpse-into-the-future"><strong>A Glimpse into the Future</strong></h2><p>Jina AI is committed to leading the forefront of innovation in AI. Here’s what’s next on their roadmap:</p><ul><li><strong>Academic Insights</strong>: An academic paper detailing the technical intricacies and benchmarks of <code>jina-embeddings-v2</code> will soon be published, allowing the AI community to gain deeper insights.</li><li><strong>API Development</strong>: The team is in the advanced stages of developing an OpenAI-like embeddings API platform. This will provide users with the capability to effortlessly scale the embedding model according to their needs.</li><li><strong>Language Expansion</strong>: Venturing into multilingual embeddings, Jina AI is setting its sights on launching German-English models, further expanding its repertoire.</li></ul><hr><p>About Jina AI GmbH:<br>Located at Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany, Jina AI is at the vanguard of reshaping the landscape of multimodal artificial intelligence. For inquiries, please reach out at <a>contact@jina.ai</a>. </p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Press release</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-ai-launches-worlds-first-open-source-8k-text-embedding-rivaling-openai%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina AI’s 8K Embedding Models Hit AWS Marketplace for On-Prem Deployment</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina AI launches 8K token length embedding v2 models on AWS marketplace, elevating enterprise AI deployments with EU-engineered innovation and a commitment to data sovereignty.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--17-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/how-to-manage-jina-resources-with-namespaces" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">How to Manage Jina Resources with Namespace</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">With Jina AI Cloud's user namespaces, all users can have their own DocumentArrays and Executors with the same name, with no fear of naming conflicts.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/492616.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Degi</div><div class="q-item__label q-item__label--caption text-caption">November 16, 2022 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--35-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/benchmark-vector-search-databases-with-one-million-data" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Benchmark Vector Search Databases with One Million Data</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">In DocArray, Documents inside a DocumentArray can live in a document store instead of in memory. External store provides longer persistence and faster retrieval. Ever wonder about which one is best for your use case? Here's a comprehensive benchmark to help guide you.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">November 15, 2022 • 33 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--33-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina AI’s PyCon US 2023 Ticket Giveaway Challenge</title><meta charset="utf-8"><meta name="title" content="Jina AI’s PyCon US 2023 Ticket Giveaway Challenge"><meta name="description" content="We’re giving away chances to win full conference passes to PyCon US, valued at 750 USD"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-ais-pycon-us-2023-ticket-giveaway"><meta property="og:title" content="Jina AI’s PyCon US 2023 Ticket Giveaway Challenge"><meta property="og:description" content="We’re giving away chances to win full conference passes to PyCon US, valued at 750 USD"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina-AI-s-PyCon-US-2023-Ticket-Giveaway-Challenge-2.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-ais-pycon-us-2023-ticket-giveaway"><meta property="twitter:title" content="Jina AI’s PyCon US 2023 Ticket Giveaway Challenge"><meta property="twitter:description" content="We’re giving away chances to win full conference passes to PyCon US, valued at 750 USD"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina-AI-s-PyCon-US-2023-Ticket-Giveaway-Challenge-2.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="ffc7bfac-a114-4fb4-a834-ddc5cad55a30" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="ffc7bfac-a114-4fb4-a834-ddc5cad55a30" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina AI’s PyCon US 2023 Ticket Giveaway Challenge</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">We’re giving away chances to win full conference passes to PyCon US, valued at 750 USD</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/avatar.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jocelyn Matthews</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 22, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="you-could-win-a-full-conference-pass-for-pycon-us"><a href="https://docs.google.com/forms/d/18DMVRSnRE230aTCZ078gCgfrqB6tBW7ucHq8QGNH5jA?ref=jina-ai-gmbh.ghost.io">You could win a full conference pass for PyCon US!</a></h2><p>Jina AI is a Partner sponsor at PyCon’s 20th anniversary event this April 19-27 in Salt Lake City, Utah. To celebrate, we’re giving away chances to win full conference passes to the event, valued at 750 USD. Winners will also receive a cool Jina t-shirt from our swag store and have the opportunity to meet our engineer Johannes Messner, a featured speaker at the event.</p><p>We want these tickets and tees to go to our most diehard advocates and our emerging community members - so we’ve created some flexible ways to express your enthusiasm for Jina - just share your best Jina social post or pledge to volunteer in our booth. Our favorite entrants will receive full conference passes to PyCon US.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://docs.google.com/forms/d/18DMVRSnRE230aTCZ078gCgfrqB6tBW7ucHq8QGNH5jA?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Enter here!</a></div><p><strong>The deadline for this giveaway is 11:59 pm Pacific time, March 29, 2023.</strong></p><p>Winners will be notified by March 30, 2023, and Jina will supply winners with a discount code for a free ticket.</p><p>Can’t make it to Salt Lake City, Utah? No worries! We know our community is global, and we’ve got you covered. Stay tuned for our next giveaway, featuring five online passes to the event.</p><h2 id="about-pycon-2023">About PyCon 2023</h2><p>“By the community, for the community”</p><p>PyCon US is the largest and longest-running annual gathering for the community using and developing the open-source Python programming language.</p><p>At PyCon US 2023, you will find an amazing program filled with pre-conference tutorials and sponsor presentations, 90+ of the community’s best talks, which includes the Charlas track, brilliant keynote speakers, a lively Expo Hall filled with incredible Sponsors’ booths, and PyCon's famed lightning talks on each main conference day. Following the conference days, there are four days of sprints that are free and open to the public, and offer an opportunity for anyone to collaborate and contribute to a project, even if it is their first time.</p><p>PyCon US offers a whole host of events such as the Job Fair, Summits, Open Spaces, and PyLadies Auction, and don’t forget about the “hallway” track, which brings together Python users from around the world.</p><h3 id="pycon-us-2023-dates"><strong>PyCon US 2023 Dates</strong></h3><ul><li><strong>Tutorials</strong> - April 19-20, 2023</li><li><strong>Sponsor Presentations</strong> - April 20, 2023</li><li><strong>Opening Reception</strong> April 20, 2023</li><li><strong>Main Conference and Online</strong> - April 21-23, 2023</li><li><strong>Job Fair</strong> - April 23, 2022</li><li><strong>Sprints</strong> - April 24-27, 2023</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-ais-pycon-us-2023-ticket-giveaway%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina-AI-s-PyCon-US-2023-Ticket-Giveaway-Challenge-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina AI’s PyCon US 2023 Ticket Giveaway Challenge</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">We’re giving away chances to win full conference passes to PyCon US, valued at 750 USD</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/avatar.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jocelyn Matthews</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 22, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="you-could-win-a-full-conference-pass-for-pycon-us"><a href="https://docs.google.com/forms/d/18DMVRSnRE230aTCZ078gCgfrqB6tBW7ucHq8QGNH5jA?ref=jina-ai-gmbh.ghost.io">You could win a full conference pass for PyCon US!</a></h2><p>Jina AI is a Partner sponsor at PyCon’s 20th anniversary event this April 19-27 in Salt Lake City, Utah. To celebrate, we’re giving away chances to win full conference passes to the event, valued at 750 USD. Winners will also receive a cool Jina t-shirt from our swag store and have the opportunity to meet our engineer Johannes Messner, a featured speaker at the event.</p><p>We want these tickets and tees to go to our most diehard advocates and our emerging community members - so we’ve created some flexible ways to express your enthusiasm for Jina - just share your best Jina social post or pledge to volunteer in our booth. Our favorite entrants will receive full conference passes to PyCon US.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://docs.google.com/forms/d/18DMVRSnRE230aTCZ078gCgfrqB6tBW7ucHq8QGNH5jA?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Enter here!</a></div><p><strong>The deadline for this giveaway is 11:59 pm Pacific time, March 29, 2023.</strong></p><p>Winners will be notified by March 30, 2023, and Jina will supply winners with a discount code for a free ticket.</p><p>Can’t make it to Salt Lake City, Utah? No worries! We know our community is global, and we’ve got you covered. Stay tuned for our next giveaway, featuring five online passes to the event.</p><h2 id="about-pycon-2023">About PyCon 2023</h2><p>“By the community, for the community”</p><p>PyCon US is the largest and longest-running annual gathering for the community using and developing the open-source Python programming language.</p><p>At PyCon US 2023, you will find an amazing program filled with pre-conference tutorials and sponsor presentations, 90+ of the community’s best talks, which includes the Charlas track, brilliant keynote speakers, a lively Expo Hall filled with incredible Sponsors’ booths, and PyCon's famed lightning talks on each main conference day. Following the conference days, there are four days of sprints that are free and open to the public, and offer an opportunity for anyone to collaborate and contribute to a project, even if it is their first time.</p><p>PyCon US offers a whole host of events such as the Job Fair, Summits, Open Spaces, and PyLadies Auction, and don’t forget about the “hallway” track, which brings together Python users from around the world.</p><h3 id="pycon-us-2023-dates"><strong>PyCon US 2023 Dates</strong></h3><ul><li><strong>Tutorials</strong> - April 19-20, 2023</li><li><strong>Sponsor Presentations</strong> - April 20, 2023</li><li><strong>Opening Reception</strong> April 20, 2023</li><li><strong>Main Conference and Online</strong> - April 21-23, 2023</li><li><strong>Job Fair</strong> - April 23, 2022</li><li><strong>Sprints</strong> - April 24-27, 2023</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-ais-pycon-us-2023-ticket-giveaway%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina AI Virtual Ticket Giveaway for PyCon 2023 Online</title><meta charset="utf-8"><meta name="title" content="Jina AI Virtual Ticket Giveaway for PyCon 2023 Online"><meta name="description" content="Jina AI's giving away PyCon US Online passes. Deadline April 10."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-ap-virtual-ticket-giveaway-for-pycon-2023"><meta property="og:title" content="Jina AI Virtual Ticket Giveaway for PyCon 2023 Online"><meta property="og:description" content="Jina AI's giving away PyCon US Online passes. Deadline April 10."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/virtual-ticket-promo.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-ap-virtual-ticket-giveaway-for-pycon-2023"><meta property="twitter:title" content="Jina AI Virtual Ticket Giveaway for PyCon 2023 Online"><meta property="twitter:description" content="Jina AI's giving away PyCon US Online passes. Deadline April 10."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/virtual-ticket-promo.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/virtual-ticket-promo.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI's giving away PyCon US Online passes. Deadline April 10.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/avatar.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jocelyn Matthews</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 03, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p></p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">🏆</div><div class="kg-callout-text">The Jina AI team would like to congratulate the winner of last week's giveaway of a conference pass to the in-person event at Salt Palace. Community member <strong>Giancarlo Fissore</strong> will join us onsite and in the booth. Congratulations, Giancarlo!&nbsp;</div></div><h2 id="jina-ai-wants-you-to-join-pycon%E2%80%99s-20th-anniversary-celebration-online">Jina AI wants you to join PyCon’s 20th Anniversary celebration online!</h2><p>Jina AI is giving away virtual conference passes for the online portion of PyCon US 2023. As a proud Partner level sponsor, we’re looking forward to connecting with our community both online and in person.</p><h3 id="enter-the-giveaway">Enter the giveaway</h3><p>Winners will receive a virtual conference pass for <a href="https://us.pycon.org/2023/attend/pycon-online/?ref=jina-ai-gmbh.ghost.io">PyCon US 2023 Online</a>, bragging rights, and a cool Jina AI t-shirt.</p><p>We’re seeking submissions that highlight your creativity and enthusiasm for Jina and Python. Our judges will give preference to entries which are thought-provoking, innovative and insightful. Whether you’re at the start of your learning curve or a seasoned ML engineer, we want to hear from you!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://docs.google.com/forms/d/11CXcKKzhh4U_BEfosgYZqhhK-d4yrmgz2dM-2QqDy-o/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Enter to Win!</a></div><p><strong>The deadline for this giveaway is 11:59 pm Pacific time, April 10, 2023.</strong><br>Winners will be notified by April 18, 2023. Jina AI will provide winners with a discount code redeemable for a free ticket via their own <a href="http://python.org/?ref=jina-ai-gmbh.ghost.io">python.org</a> account</p><p>Online registration includes livestreaming of:</p><ul><li>Keynotes</li><li>Lightning Talks</li><li>Charlas Track (en español)</li><li>Talk Tracks</li></ul><h3 id="about-pycon-us-2023-online">About PyCon US 2023 Online</h3><p>PyCon US is the largest and longest-running annual gathering for the community using and developing the open-source Python programming language. It is produced and underwritten by the <a href="https://www.python.org/psf-landing/?ref=jina-ai-gmbh.ghost.io">Python Software Foundation</a>, the 501(c)(3) nonprofit organization dedicated to advancing and promoting Python. Through PyCon US, the PSF advances its mission of growing the international community of Python programmers.</p><p>The online event is for those who cannot join the event in person. Online attendees may join PyCon US 2023 online to watch a live stream of the General Sessions and Talk tracks during the main conference days (Fri., April 21, 2023 - Sun., April 23, 2023). Online registrants will access the PyCon US live stream through the Hubilo platform.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-ap-virtual-ticket-giveaway-for-pycon-2023%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/virtual-ticket-promo.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina AI Virtual Ticket Giveaway for PyCon 2023 Online</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI's giving away PyCon US Online passes. Deadline April 10.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/avatar.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jocelyn Matthews</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 03, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p></p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">🏆</div><div class="kg-callout-text">The Jina AI team would like to congratulate the winner of last week's giveaway of a conference pass to the in-person event at Salt Palace. Community member <strong>Giancarlo Fissore</strong> will join us onsite and in the booth. Congratulations, Giancarlo!&nbsp;</div></div><h2 id="jina-ai-wants-you-to-join-pycon%E2%80%99s-20th-anniversary-celebration-online">Jina AI wants you to join PyCon’s 20th Anniversary celebration online!</h2><p>Jina AI is giving away virtual conference passes for the online portion of PyCon US 2023. As a proud Partner level sponsor, we’re looking forward to connecting with our community both online and in person.</p><h3 id="enter-the-giveaway">Enter the giveaway</h3><p>Winners will receive a virtual conference pass for <a href="https://us.pycon.org/2023/attend/pycon-online/?ref=jina-ai-gmbh.ghost.io">PyCon US 2023 Online</a>, bragging rights, and a cool Jina AI t-shirt.</p><p>We’re seeking submissions that highlight your creativity and enthusiasm for Jina and Python. Our judges will give preference to entries which are thought-provoking, innovative and insightful. Whether you’re at the start of your learning curve or a seasoned ML engineer, we want to hear from you!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://docs.google.com/forms/d/11CXcKKzhh4U_BEfosgYZqhhK-d4yrmgz2dM-2QqDy-o/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Enter to Win!</a></div><p><strong>The deadline for this giveaway is 11:59 pm Pacific time, April 10, 2023.</strong><br>Winners will be notified by April 18, 2023. Jina AI will provide winners with a discount code redeemable for a free ticket via their own <a href="http://python.org/?ref=jina-ai-gmbh.ghost.io">python.org</a> account</p><p>Online registration includes livestreaming of:</p><ul><li>Keynotes</li><li>Lightning Talks</li><li>Charlas Track (en español)</li><li>Talk Tracks</li></ul><h3 id="about-pycon-us-2023-online">About PyCon US 2023 Online</h3><p>PyCon US is the largest and longest-running annual gathering for the community using and developing the open-source Python programming language. It is produced and underwritten by the <a href="https://www.python.org/psf-landing/?ref=jina-ai-gmbh.ghost.io">Python Software Foundation</a>, the 501(c)(3) nonprofit organization dedicated to advancing and promoting Python. Through PyCon US, the PSF advances its mission of growing the international community of Python programmers.</p><p>The online event is for those who cannot join the event in person. Online attendees may join PyCon US 2023 online to watch a live stream of the General Sessions and Talk tracks during the main conference days (Fri., April 21, 2023 - Sun., April 23, 2023). Online registrants will access the PyCon US live stream through the Hubilo platform.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-ap-virtual-ticket-giveaway-for-pycon-2023%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina Core's New Logo: A Creative Spin on Planetary Design</title><meta charset="utf-8"><meta name="title" content="Jina Core's New Logo: A Creative Spin on Planetary Design"><meta name="description" content="It’s time to give Jina Core a makeover. And that all starts with our new logo."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-cores-new-logo-a-creative-spin-on-planetary-design"><meta property="og:title" content="Jina Core's New Logo: A Creative Spin on Planetary Design"><meta property="og:description" content="It’s time to give Jina Core a makeover. And that all starts with our new logo."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/banner---jina_logo_design--1-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-cores-new-logo-a-creative-spin-on-planetary-design"><meta property="twitter:title" content="Jina Core's New Logo: A Creative Spin on Planetary Design"><meta property="twitter:description" content="It’s time to give Jina Core a makeover. And that all starts with our new logo."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/banner---jina_logo_design--1-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina Core's New Logo: A Creative Spin on Planetary Design</title><meta charset="utf-8"><meta name="title" content="Jina Core's New Logo: A Creative Spin on Planetary Design"><meta name="description" content="It’s time to give Jina Core a makeover. And that all starts with our new logo."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-cores-new-logo-a-creative-spin-on-planetary-design"><meta property="og:title" content="Jina Core's New Logo: A Creative Spin on Planetary Design"><meta property="og:description" content="It’s time to give Jina Core a makeover. And that all starts with our new logo."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/banner---jina_logo_design--1-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-cores-new-logo-a-creative-spin-on-planetary-design"><meta property="twitter:title" content="Jina Core's New Logo: A Creative Spin on Planetary Design"><meta property="twitter:description" content="It’s time to give Jina Core a makeover. And that all starts with our new logo."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/05/banner---jina_logo_design--1-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina Core's New Logo: A Creative Spin on Planetary Design</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">It’s time to give Jina Core a makeover. And that all starts with our new logo.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Untitled-design--14-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G, Tianshi Kan</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 08, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Once upon a time, many moons ago, Jina AI launched with the aim of building <em>the</em> neural search solution. Back then we only had one product: the imaginatively-titled Jina, a framework for building <a href="https://jina.ai/news/what-is-neural-search-and-learn-to-build-a-neural-search-engine/?ref=jina-ai-gmbh.ghost.io">neural search</a> solutions.</p><p>Time, however, marches on. We’ve now got a lot more products under our belt, and our core product has been refocused on <a href="https://jina.ai/news/what-is-multimodal-deep-learning-and-what-are-the-applications/?ref=jina-ai-gmbh.ghost.io">multimodal AI</a> services with cloud-native technologies.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Build multimodal AI services via cloud native technologies</div><div class="kg-bookmark-description">🔮 Build multimodal AI services via cloud native technologies - GitHub - jina-ai/jina: 🔮 Build multimodal AI services via cloud native technologies</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/09d66a57-001b-4834-b685-c72e3dc3e1ba" alt=""></div></a></figure><p>Kinda makes our magnifying glass logo a bit disconnected from reality. </p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Dark--1-.png" class="kg-image" alt="" width="1200" height="600" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/Dark--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/Dark--1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/Dark--1-.png 1200w" sizes="(min-width: 720px) 720px"></figure><p>After all, magnifying glasses are usually associated with search, and that’s just not who <em>are</em> nowadays, y’know.</p><p>You know what that means. It’s time to give Jina a glow-up. And that starts with our new logo.</p><p>Let’s hope we did a better job than these folks:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.creativebloq.com/news/worst-logo-fails-2022?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">The most unbelievable logo fails of 2022</div><div class="kg-bookmark-description">These terrible logo designs will stay with us.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://vanilla.futurecdn.net/creativebloq/676264/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">Creative Bloq</span><span class="kg-bookmark-publisher">Joseph Foley</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn.mos.cms.futurecdn.net/rA5dHnPSS92voa3c9XTXsL-1200-80.jpg" alt=""></div></a></figure><p>Our designer, Tianshi, will take it from here, answering all the burning questions around the new look.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Light--1-.png" class="kg-image" alt="" width="2000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/Light--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/Light--1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/05/Light--1-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/05/Light--1-.png 2400w" sizes="(min-width: 720px) 720px"></figure><h2 id="what-does-the-new-logo-represent">What does the new logo represent?</h2><p>The new logo has got this cool blue planet hugged by a ribbon, which is all about flowing data. You know, data is like the lifeblood of the digital era, and it's pretty much everywhere. So, this swirling data ribbon suggests that when you get your data act together and set it in motion, the sky's the limit!</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Core-Animation.gif" class="kg-image" alt="" width="1080" height="608" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/Core-Animation.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/Core-Animation.gif 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/Core-Animation.gif 1080w" sizes="(min-width: 720px) 720px"></figure><h2 id="what-are-the-meanings-behind-the-colors-in-the-new-logo">What are the meanings behind the colors in the new logo?</h2><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/StoryBoard.png" class="kg-image" alt="" width="2000" height="1336" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/StoryBoard.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/StoryBoard.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/05/StoryBoard.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/StoryBoard.png 2053w" sizes="(min-width: 720px) 720px"></figure><p>So, the new logo has a mix of green, red, and yellow. Green is all about tech, trustworthiness, and life itself, showing off Jina's dedication to diving deep into the data seas and playing the long game. Red brings in some zest and a youthful vibe, celebrating our fiery passion for the digital age. And then there's yellow, which is like a big ol' nod to the future, 'cause we're always chasing after the latest tech goodies to make the world a better place.</p><h2 id="how-does-the-new-logo-reflect-jina-cores-brand-personality">How does the new logo reflect Jina Core's brand personality?</h2><p>By mashing up these three colors and their oh-so-deep meanings, the new logo manages to capture its essence in a funky, modern way. The logo's got this tech-savvy, youthful, and lively vibe going on, but at the same time, it feels like a warm hug, showing that we really care about making a difference for our customers and the world around us.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/----1-.png" class="kg-image" alt="" width="1601" height="901" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/----1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/----1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/05/----1-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/----1-.png 1601w" sizes="(min-width: 720px) 720px"></figure><h2 id="how-does-jina-core-facilitate-a-smooth-pythonic-experience-for-developers">How does Jina Core facilitate a smooth Pythonic experience for developers?</h2><p>Jina Core aims to provide a seamless experience for developers transitioning from local deployment to advanced orchestration frameworks such as Docker-Compose, Kubernetes, or Jina AI Cloud. It handles infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to all developers.</p><h2 id="what-tools-did-you-use-to-create-the-logo-why-these-ones">What tools did you use to create the logo? Why these ones?</h2><p>When it comes to designing logos, my go-to tools are <a href="https://www.sketch.com/?ref=jina-ai-gmbh.ghost.io">Sketch</a> and <a href="https://www.figma.com/?ref=jina-ai-gmbh.ghost.io">Figma</a>. Sketch is not only handy for creating user interfaces, but its canvas and palette features make it super easy to check out inspiration, whip up storyboards, and compare design options.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/image-1.png" class="kg-image" alt="" width="2000" height="1242" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/image-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/05/image-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/05/image-1.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>And because my colleagues are scattered all over the world, Figma's collaborative workspace is a real lifesaver. I can give feedback and comments on the spot and make changes in real-time, avoiding the agony of exporting and uploading PNGs, begging for feedback, and repeating the whole process until we're satisfied with the final version.</p><h2 id="what%E2%80%99s-your-working-process-like-how-do-you-even-get-started-with-designing-a-cool-logo">What’s your working process like? How do you even get started with designing a cool logo?</h2><p>So, let me break it down for you. We're a company that's all about AI technology, and our stuff is pretty abstract and tricky to understand. My job? Well, it's to take all that brainy functionality and turn it into a symbol that anyone can grasp. As someone who's not a tech genius, I have to chat with the engineers to get a handle on what the product actually does. Then, I put it into words that even I can understand, and I come up with a bunch of different ideas to get inspired. After that, it's time to get down to business and sketch out some concepts. At the next meeting, I usually whip out 3-4 versions of my sketches and we all pick a couple to fine-tune and tweak. It's like magic - except with more brainpower and way less rabbits.</p><h2 id="what-ideas-did-you-reject-early-on-what-was-your-craziest-or-silliest-idea">What ideas did you reject early on? What was your craziest or silliest idea?</h2><p>You wanna talk design ideas? Well, let me tell you, I've learned that clients always have these grandiose, picturesque ideas that are just missing something. It's like trying to make out a blurry face with some details - sure, you can kind of visualize it, but it might not be the best approach. I try to steer them away from totally unrealistic or just plain ridiculous concepts from the get-go.</p><p>But, if you really wanna know my craziest design idea, it's actually something pretty simple. I've always wanted to put on a little exhibition of my work. I mean, come on, isn't that every designer or artist's dream? The only problem is, I'm a bit of a wuss when it comes to criticism. So, until virtual reality tech gets good enough for me to showcase my stuff in the digital world, I guess I'll just keep dreaming.</p><p>And oh boy, I'll never forget the silliest thing I ever designed. I drew this goofy little boat on the logo for Jina magnifier version. </p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/image.png" class="kg-image" alt="" width="370" height="434"></figure><p>It looked like something a kid would draw, and honestly, I thought it was pretty silly. But, to my surprise, everyone else seemed to love it too.</p><h2 id="wrapping-up">Wrapping up</h2><p>Our new logo and rebranding at Jina Core really show off our love for innovation, excitement for all things tech, and dedication to the digital world. The design and colors capture what we're all about, giving us a fresh and engaging look. As we keep creating user-friendly software and diving into the data universe, our updated logo is the perfect symbol of our dreams and our non-stop quest to be the best in the business.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-cores-new-logo-a-creative-spin-on-planetary-design%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina Core's New Logo: A Creative Spin on Planetary Design</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">It’s time to give Jina Core a makeover. And that all starts with our new logo.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Untitled-design--14-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G, Tianshi Kan</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">May 08, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Once upon a time, many moons ago, Jina AI launched with the aim of building <em>the</em> neural search solution. Back then we only had one product: the imaginatively-titled Jina, a framework for building <a href="https://jina.ai/news/what-is-neural-search-and-learn-to-build-a-neural-search-engine/?ref=jina-ai-gmbh.ghost.io">neural search</a> solutions.</p><p>Time, however, marches on. We’ve now got a lot more products under our belt, and our core product has been refocused on <a href="https://jina.ai/news/what-is-multimodal-deep-learning-and-what-are-the-applications/?ref=jina-ai-gmbh.ghost.io">multimodal AI</a> services with cloud-native technologies.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Build multimodal AI services via cloud native technologies</div><div class="kg-bookmark-description">🔮 Build multimodal AI services via cloud native technologies - GitHub - jina-ai/jina: 🔮 Build multimodal AI services via cloud native technologies</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/09d66a57-001b-4834-b685-c72e3dc3e1ba" alt=""></div></a></figure><p>Kinda makes our magnifying glass logo a bit disconnected from reality. </p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Dark--1-.png" class="kg-image" alt="" width="1200" height="600" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/Dark--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/Dark--1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/Dark--1-.png 1200w" sizes="(min-width: 720px) 720px"></figure><p>After all, magnifying glasses are usually associated with search, and that’s just not who <em>are</em> nowadays, y’know.</p><p>You know what that means. It’s time to give Jina a glow-up. And that starts with our new logo.</p><p>Let’s hope we did a better job than these folks:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.creativebloq.com/news/worst-logo-fails-2022?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">The most unbelievable logo fails of 2022</div><div class="kg-bookmark-description">These terrible logo designs will stay with us.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://vanilla.futurecdn.net/creativebloq/676264/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">Creative Bloq</span><span class="kg-bookmark-publisher">Joseph Foley</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn.mos.cms.futurecdn.net/rA5dHnPSS92voa3c9XTXsL-1200-80.jpg" alt=""></div></a></figure><p>Our designer, Tianshi, will take it from here, answering all the burning questions around the new look.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Light--1-.png" class="kg-image" alt="" width="2000" height="1000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/Light--1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/Light--1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/05/Light--1-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/05/Light--1-.png 2400w" sizes="(min-width: 720px) 720px"></figure><h2 id="what-does-the-new-logo-represent">What does the new logo represent?</h2><p>The new logo has got this cool blue planet hugged by a ribbon, which is all about flowing data. You know, data is like the lifeblood of the digital era, and it's pretty much everywhere. So, this swirling data ribbon suggests that when you get your data act together and set it in motion, the sky's the limit!</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/Core-Animation.gif" class="kg-image" alt="" width="1080" height="608" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/Core-Animation.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/Core-Animation.gif 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/Core-Animation.gif 1080w" sizes="(min-width: 720px) 720px"></figure><h2 id="what-are-the-meanings-behind-the-colors-in-the-new-logo">What are the meanings behind the colors in the new logo?</h2><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/StoryBoard.png" class="kg-image" alt="" width="2000" height="1336" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/StoryBoard.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/StoryBoard.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/05/StoryBoard.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/StoryBoard.png 2053w" sizes="(min-width: 720px) 720px"></figure><p>So, the new logo has a mix of green, red, and yellow. Green is all about tech, trustworthiness, and life itself, showing off Jina's dedication to diving deep into the data seas and playing the long game. Red brings in some zest and a youthful vibe, celebrating our fiery passion for the digital age. And then there's yellow, which is like a big ol' nod to the future, 'cause we're always chasing after the latest tech goodies to make the world a better place.</p><h2 id="how-does-the-new-logo-reflect-jina-cores-brand-personality">How does the new logo reflect Jina Core's brand personality?</h2><p>By mashing up these three colors and their oh-so-deep meanings, the new logo manages to capture its essence in a funky, modern way. The logo's got this tech-savvy, youthful, and lively vibe going on, but at the same time, it feels like a warm hug, showing that we really care about making a difference for our customers and the world around us.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/----1-.png" class="kg-image" alt="" width="1601" height="901" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/----1-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/----1-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/05/----1-.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/05/----1-.png 1601w" sizes="(min-width: 720px) 720px"></figure><h2 id="how-does-jina-core-facilitate-a-smooth-pythonic-experience-for-developers">How does Jina Core facilitate a smooth Pythonic experience for developers?</h2><p>Jina Core aims to provide a seamless experience for developers transitioning from local deployment to advanced orchestration frameworks such as Docker-Compose, Kubernetes, or Jina AI Cloud. It handles infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to all developers.</p><h2 id="what-tools-did-you-use-to-create-the-logo-why-these-ones">What tools did you use to create the logo? Why these ones?</h2><p>When it comes to designing logos, my go-to tools are <a href="https://www.sketch.com/?ref=jina-ai-gmbh.ghost.io">Sketch</a> and <a href="https://www.figma.com/?ref=jina-ai-gmbh.ghost.io">Figma</a>. Sketch is not only handy for creating user interfaces, but its canvas and palette features make it super easy to check out inspiration, whip up storyboards, and compare design options.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/image-1.png" class="kg-image" alt="" width="2000" height="1242" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/05/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/05/image-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/05/image-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/05/image-1.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>And because my colleagues are scattered all over the world, Figma's collaborative workspace is a real lifesaver. I can give feedback and comments on the spot and make changes in real-time, avoiding the agony of exporting and uploading PNGs, begging for feedback, and repeating the whole process until we're satisfied with the final version.</p><h2 id="what%E2%80%99s-your-working-process-like-how-do-you-even-get-started-with-designing-a-cool-logo">What’s your working process like? How do you even get started with designing a cool logo?</h2><p>So, let me break it down for you. We're a company that's all about AI technology, and our stuff is pretty abstract and tricky to understand. My job? Well, it's to take all that brainy functionality and turn it into a symbol that anyone can grasp. As someone who's not a tech genius, I have to chat with the engineers to get a handle on what the product actually does. Then, I put it into words that even I can understand, and I come up with a bunch of different ideas to get inspired. After that, it's time to get down to business and sketch out some concepts. At the next meeting, I usually whip out 3-4 versions of my sketches and we all pick a couple to fine-tune and tweak. It's like magic - except with more brainpower and way less rabbits.</p><h2 id="what-ideas-did-you-reject-early-on-what-was-your-craziest-or-silliest-idea">What ideas did you reject early on? What was your craziest or silliest idea?</h2><p>You wanna talk design ideas? Well, let me tell you, I've learned that clients always have these grandiose, picturesque ideas that are just missing something. It's like trying to make out a blurry face with some details - sure, you can kind of visualize it, but it might not be the best approach. I try to steer them away from totally unrealistic or just plain ridiculous concepts from the get-go.</p><p>But, if you really wanna know my craziest design idea, it's actually something pretty simple. I've always wanted to put on a little exhibition of my work. I mean, come on, isn't that every designer or artist's dream? The only problem is, I'm a bit of a wuss when it comes to criticism. So, until virtual reality tech gets good enough for me to showcase my stuff in the digital world, I guess I'll just keep dreaming.</p><p>And oh boy, I'll never forget the silliest thing I ever designed. I drew this goofy little boat on the logo for Jina magnifier version. </p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/05/image.png" class="kg-image" alt="" width="370" height="434"></figure><p>It looked like something a kid would draw, and honestly, I thought it was pretty silly. But, to my surprise, everyone else seemed to love it too.</p><h2 id="wrapping-up">Wrapping up</h2><p>Our new logo and rebranding at Jina Core really show off our love for innovation, excitement for all things tech, and dedication to the digital world. The design and colors capture what we're all about, giving us a fresh and engaging look. As we keep creating user-friendly software and diving into the data universe, our updated logo is the perfect symbol of our dreams and our non-stop quest to be the best in the business.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-cores-new-logo-a-creative-spin-on-planetary-design%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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diff --git a/news/jina-embeddings-2-the-best-solution-for-embedding-long-documents/index.html b/news/jina-embeddings-2-the-best-solution-for-embedding-long-documents/index.html
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@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina Embeddings 2: The Best Solution for Embedding Long Documents</title><meta charset="utf-8"><meta name="title" content="Jina Embeddings 2: The Best Solution for Embedding Long Documents"><meta name="description" content="With Jina Embeddings 2 models you get high-quality embeddings from an open-source, downloadable model with an input size of 8,192 tokens."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-embeddings-2-the-best-solution-for-embedding-long-documents"><meta property="og:title" content="Jina Embeddings 2: The Best Solution for Embedding Long Documents"><meta property="og:description" content="With Jina Embeddings 2 models you get high-quality embeddings from an open-source, downloadable model with an input size of 8,192 tokens."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Blog-images--7-.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-embeddings-2-the-best-solution-for-embedding-long-documents"><meta property="twitter:title" content="Jina Embeddings 2: The Best Solution for Embedding Long Documents"><meta property="twitter:description" content="With Jina Embeddings 2 models you get high-quality embeddings from an open-source, downloadable model with an input size of 8,192 tokens."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Blog-images--7-.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina Embeddings 2: The Best Solution for Embedding Long Documents</title><meta charset="utf-8"><meta name="title" content="Jina Embeddings 2: The Best Solution for Embedding Long Documents"><meta name="description" content="With Jina Embeddings 2 models you get high-quality embeddings from an open-source, downloadable model with an input size of 8,192 tokens."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-embeddings-2-the-best-solution-for-embedding-long-documents"><meta property="og:title" content="Jina Embeddings 2: The Best Solution for Embedding Long Documents"><meta property="og:description" content="With Jina Embeddings 2 models you get high-quality embeddings from an open-source, downloadable model with an input size of 8,192 tokens."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Blog-images--7-.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-embeddings-2-the-best-solution-for-embedding-long-documents"><meta property="twitter:title" content="Jina Embeddings 2: The Best Solution for Embedding Long Documents"><meta property="twitter:description" content="With Jina Embeddings 2 models you get high-quality embeddings from an open-source, downloadable model with an input size of 8,192 tokens."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Blog-images--7-.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina Embeddings 2: The Best Solution for Embedding Long Documents</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With Jina Embeddings 2 models you get high-quality embeddings from an open-source, downloadable model with an input size of 8,192 tokens.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 02, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Text embeddings are the backbone of AI language processing, powering text clustering, information retrieval, sentiment analysis, text-to-image processing, and information extraction, among other core tasks. But there’s a catch: Until now, text embedding models have been trained for very short text segments, typically a few hundred tokens at most. <a href="https://arxiv.org/abs/2307.11224?ref=jina-ai-gmbh.ghost.io">Jina Embeddings 1 models</a>, based on the <a href="https://huggingface.co/docs/transformers/model_doc/t5?ref=jina-ai-gmbh.ghost.io">T5 models</a>, are limited to 512 tokens. Tokens don’t <em>quite</em> match up to words one-to-one, but this means the largest texts that they can support are just a few short paragraphs.</p><p>But not anymore!</p><p>With <a href="https://arxiv.org/abs/2310.19923?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Jina Embeddings 2 models</a>, you can get high-quality embeddings from an open-source, Apache 2-licensed model with an input size of 8,192 tokens — more than sixteen times as much as Jina Embeddings 1 and the widely used <a href="https://www.sbert.net/?ref=jina-ai-gmbh.ghost.io">SBERT</a> models!</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2310.19923?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents</div><div class="kg-bookmark-description">Text embedding models have emerged as powerful tools for transforming
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With Jina Embeddings 2 models you get high-quality embeddings from an open-source, downloadable model with an input size of 8,192 tokens.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 02, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Text embeddings are the backbone of AI language processing, powering text clustering, information retrieval, sentiment analysis, text-to-image processing, and information extraction, among other core tasks. But there’s a catch: Until now, text embedding models have been trained for very short text segments, typically a few hundred tokens at most. <a href="https://arxiv.org/abs/2307.11224?ref=jina-ai-gmbh.ghost.io">Jina Embeddings 1 models</a>, based on the <a href="https://huggingface.co/docs/transformers/model_doc/t5?ref=jina-ai-gmbh.ghost.io">T5 models</a>, are limited to 512 tokens. Tokens don’t <em>quite</em> match up to words one-to-one, but this means the largest texts that they can support are just a few short paragraphs.</p><p>But not anymore!</p><p>With <a href="https://arxiv.org/abs/2310.19923?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Jina Embeddings 2 models</a>, you can get high-quality embeddings from an open-source, Apache 2-licensed model with an input size of 8,192 tokens — more than sixteen times as much as Jina Embeddings 1 and the widely used <a href="https://www.sbert.net/?ref=jina-ai-gmbh.ghost.io">SBERT</a> models!</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2310.19923?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents</div><div class="kg-bookmark-description">Text embedding models have emerged as powerful tools for transforming
 sentences into fixed-sized feature vectors that encapsulate semantic
 information. While these models are essential for tasks like information
 retrieval, semantic clustering, and text re-ranking, most existing open-source
-models, e…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Michael Günther</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Read the Jina Embeddings 2 paper on arXiv</span></p></figcaption></figure><p>Few other embedding models offer input sizes exceeding 512 tokens, and at present, the <em>only </em>one that accepts over 8,000 tokens is neither open-source nor available for download. Jina Embeddings 2 models not only give you a larger input size than all other open-source models, but they also rival the performance of the closed-source alternative.</p><p>Check for yourself on the <a href="https://huggingface.co/spaces/mteb/leaderboard?ref=jina-ai-gmbh.ghost.io">HuggingFace MTEB leaderboard</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/spaces/mteb/leaderboard?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">MTEB Leaderboard - a Hugging Face Space by mteb</div><div class="kg-bookmark-description">Discover amazing ML apps made by the community</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""><span class="kg-bookmark-author">a Hugging Face Space by mteb</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/spaces/mteb/leaderboard.png" alt=""></div></a></figure><h2 id="how-jina-embeddings-2-supports-long-documents">How Jina Embeddings 2 Supports Long Documents</h2><p>Jina AI has implemented the <a href="https://arxiv.org/abs/2108.12409?ref=jina-ai-gmbh.ghost.io">ALiBi approach</a>, the first embedding model to do so. ALiBi is an alternative to the positional encoding system first proposed in the famous “<a href="https://dl.acm.org/doi/10.5555/3295222.3295349?ref=jina-ai-gmbh.ghost.io">Attention is all you need</a>” paper. This scheme makes it possible to train embedding models on short texts and still get high-quality results on longer texts.</p><p>For Jina Embeddings 2, Jina AI has taken the BERT architecture and grafted it into ALiBi.</p><p>ALiBi was originally proposed for text generators (like ChatGPT) that only care about dependencies on previous words. This means that the last tokens in the input matter more than earlier ones because a text generator’s task is to produce the next word after the input. This makes no sense for an embedding model that tries to create a representation of the whole text input, so Jina Embeddings 2 models implement a bi-directional version of ALiBi.</p><p>This architectural change, however, means that we can’t use the pre-training of the original BERT model and have to completely retrain the model from scratch.</p><h2 id="english-only-for-now-german-and-chinese-soon">English-Only for Now, German and Chinese Soon</h2><p>Although there are plenty of multilingual text embedding models out there, there are known issues with providing universal language support. Not all languages are equal when it comes to embedding quality, and <a href="https://aclanthology.org/2023.sigtyp-1.16.pdf?ref=jina-ai-gmbh.ghost.io">recent research</a> shows that models tend to be biased towards structures that parallel English ones, distorting embeddings.</p><p>In short, multilingual models have an “accent”, usually an English one due to the majority of English data in the training.</p><p>For superior language-specific performance, and more compact, easier-to-train models, Jina Embeddings are currently English-only. We’re planning German and Chinese models for the near future.</p><h2 id="training-jina-embeddings-2-for-top-performance-up-to-8192-tokens">Training Jina Embeddings 2 for Top Performance up to 8,192 Tokens</h2><p>Using ALiBi means that even though Jina Embeddings 2 models support larger input sizes, the models don’t have to be trained with larger input data. The training learned for short sequences scales up to larger ones automatically.</p><p>Our training is similar to the way other embedding models are trained. We start with <a href="https://aclanthology.org/N19-1423.pdf?ref=jina-ai-gmbh.ghost.io">masked word pre-training</a> using the circa 170 billion word English-only <a href="https://huggingface.co/datasets/c4?ref=jina-ai-gmbh.ghost.io">C4 dataset</a>. Then, we do <a href="https://arxiv.org/abs/1607.08085?ref=jina-ai-gmbh.ghost.io">pairwise contrastive training</a>. This means taking pairs of texts that are known to be similar or dissimilar and adjusting the weights of the embedding model so that similar inputs are closer together, and dissimilar ones are farther apart. We used a new corpus of text pairs, curated by Jina AI, based on the one <a href="https://arxiv.org/abs/2307.11224?ref=jina-ai-gmbh.ghost.io">used to train the Jina Embeddings 1 models</a>.</p><p>Finally, we fine-tuned the model using <a href="https://finetuner.jina.ai/advanced-topics/negative-mining/?ref=jina-ai-gmbh.ghost.io">text triplets and negative mining</a>, with an in-house training dataset specially augmented with sentences of opposite grammatical polarity. Embedding models have typically had trouble with negative polarity sentences: A sentence like “The dog is in the car” will often have an embedding close to “The dog is outside the car,” even though these are naturally opposite in meaning.</p><p>We added a collection of positive and negative pairs like this to the training data, using the same methods <a href="https://arxiv.org/abs/2307.11224?ref=jina-ai-gmbh.ghost.io">employed for the Jina Embeddings 1 models</a> to specifically improve performance on this kind of language.</p><h2 id="three-models-to-better-fit-your-use-case">Three Models To Better Fit Your Use Case</h2><p>The Jina Embeddings 2 models come in three sizes, providing high-quality embeddings for users with different requirements and capabilities. All three support 8,192 input tokens.</p><ul><li><a href="https://huggingface.co/jinaai/jina-embeddings-v2-small-en?ref=jina-ai-gmbh.ghost.io" rel="noreferrer"><code>jina-embeddings-v2-small-en</code></a>: 33 million parameters, 512-dimension embeddings.</li><li><a href="https://huggingface.co/jinaai/jina-embeddings-v2-base-en?ref=jina-ai-gmbh.ghost.io" rel="noreferrer"><code>jina-embeddings-v2-base-en</code></a>: 137 million parameters, 768-dimension embeddings.</li><li><code>jina-embeddings-v2-large-en</code>: 435 million parameters, 1,024-dimension embeddings.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image.png" class="kg-image" alt="" width="1296" height="946" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image.png 1296w" sizes="(min-width: 720px) 720px"></figure><p>The <code>jina-embeddings-v2-large-en</code> model is not yet available to download but will be released in the immediate future.</p><h2 id="bigger-inputs-leaner-models-peak-performance">Bigger Inputs, Leaner Models, Peak Performance</h2><p>We tested the Jina Embeddings 2 models against the <a href="https://arxiv.org/abs/2210.07316?ref=jina-ai-gmbh.ghost.io">MTEB benchmark suite</a> and at the time of writing:</p><ul><li><code>jina-embeddings-v2-base-en</code> scores roughly on par with the best models on most benchmarks, and generally better than similarly sized ones.</li><li><code>jina-embeddings-v2-small-en</code> ranks near the top for models with sizes under 100MB.</li></ul><p>The <code>jina-embeddings-v2-large-en</code> model is not yet available for testing.</p><p>However, among models that take more than 512 tokens in input, there is only one that compares to the Jina Embeddings 2 models: OpenAI’s <code>text-embedding-ada-002</code>. This model is not publicly available and can only be accessed via a paid web-based API. Its size is unknown.</p><figure class="kg-card kg-image-card kg-width-wide kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-14.png" class="kg-image" alt="" width="1184" height="375" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-14.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-14.png 1184w"><figcaption><span style="white-space: pre-wrap;">jina-embeddings-v2-base-en compared with OpenAI’s text-embedding-ada-002 on the English MTEB benchmark</span></figcaption></figure><p><code>jina-embeddings-v2-base-en</code> is comparable in performance with <code>text-embedding-ada-002</code> on all benchmarks and even exceeds it in several tasks. Furthermore, the Jina Embeddings 2 models all produce smaller embedding vectors than <code>text-embedding-ada-002</code> which produces 1,536-dimensional output, compared to 512, 768, and 1,024 dimensions for our three model sizes respectively. This means considerable savings in computing time and memory for applications. Storing shorter vectors takes less space in memory and storage, speeds up database retrieval, and calculating the distance between them is proportionately fast.</p><figure class="kg-card kg-image-card kg-width-wide kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-15.png" class="kg-image" alt="" width="1204" height="376" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-15.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-15.png 1204w" sizes="(min-width: 1200px) 1200px"><figcaption><span style="white-space: pre-wrap;">Jina Embeddings 2 compared to other leading AI embedding models</span></figcaption></figure><p>Jina AI’s base and small model compared to other leading embedding models</p><p>Furthermore, <code>jina-embeddings-v2-small-en</code> is the only model under 100MB that supports more than 512 input tokens.</p><p>Even if we set aside support for larger inputs, Jina Embeddings offers performance on par with the most common embedding foundation models, while remaining roughly the same size or even significantly smaller.</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-16.png" class="kg-image" alt="" width="1000" height="433" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-16.png 1000w"></figure><p>This gives Jina Embeddings 2 models an impressive advantage in terms of accessibility, economic use of computing power, and cost to users.</p><h2 id="integration">Integration</h2><p>Jina Embeddings 2 models are already integrated into:</p><ul><li><a href="https://github.com/huggingface/text-embeddings-inference?ref=jina-ai-gmbh.ghost.io#supported-models">HuggingFace Text Embeddings Inference API</a></li><li><a href="https://github.com/run-llama/llama_index/blob/main/docs/examples/embeddings/jina_embeddings.ipynb?ref=jina-ai-gmbh.ghost.io">LlamaIndex</a></li><li><a href="https://twitter.com/xenovacom/status/1717904546481992094?ref=jina-ai-gmbh.ghost.io">Transformers.js</a></li><li><a href="https://github.com/simonw/llm-embed-jina?ref=jina-ai-gmbh.ghost.io">LLM</a></li></ul><p>More integrations are coming soon, both from Jina AI and our open-source user community.</p><h2 id="try-it-out-yourself-right-now">Try It Out Yourself Right Now</h2><p>Go to <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io#enterprises">https://jina.ai/#enterprises</a> to get an access key for Jina AI's online Embedding API with ten thousand free tokens for you to embed. You'll find the key on the upper right:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-4.png" class="kg-image" alt="" width="1289" height="712" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-4.png 1289w" sizes="(min-width: 720px) 720px"></figure><p>You can access Jina Embeddings 2 models hosted at Jina AI via any standard HTTP interface. Use the drop-down menus to select between the <code>jina-embeddings-v2-base-en</code> and <code>jina-embeddings-v2-small-en</code> models, and to get code snippets to use the Embeddings API.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-6.png" class="kg-image" alt="" width="1309" height="737" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-6.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-6.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-6.png 1309w" sizes="(min-width: 720px) 720px"></figure><p>You can also get example code snippets in a variety of languages and frameworks to help integrate Jina Embeddings directly into your project:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-7.png" class="kg-image" alt="" width="1307" height="972" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-7.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-7.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-7.png 1307w" sizes="(min-width: 720px) 720px"></figure><p>And if you need to add tokens to your API key, just click the "Top Up" tab.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-8.png" class="kg-image" alt="" width="1281" height="1155" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-8.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-8.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-8.png 1281w" sizes="(min-width: 720px) 720px"></figure><h2 id="future-jina-embeddings-models">Future Jina Embeddings Models</h2><p>Jina AI will be rolling out a larger model, <code>jina-embeddings-v2-large-en</code>, in the immediate future, which we expect to exceed the performance of the other Jina Embeddings 2 models and compete with the highest-scoring large embedding models.</p><p>In the near future, we are expanding our offerings to include German and Chinese embedding models, which we expect will match or exceed state-of-the-art performance in both languages.</p><p>These benchmark results prove the robustness of Jina AI’s contrastive training methodology, and we are always investigating improved model design and AI techniques. Our mission is to put more intelligence and higher performance into more compact open-access models that you can affordably access via our API, or easily run on your hardware and in your cloud instances.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-embeddings-2-the-best-solution-for-embedding-long-documents%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; 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+models, e…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Michael Günther</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Read the Jina Embeddings 2 paper on arXiv</span></p></figcaption></figure><p>Few other embedding models offer input sizes exceeding 512 tokens, and at present, the <em>only </em>one that accepts over 8,000 tokens is neither open-source nor available for download. Jina Embeddings 2 models not only give you a larger input size than all other open-source models, but they also rival the performance of the closed-source alternative.</p><p>Check for yourself on the <a href="https://huggingface.co/spaces/mteb/leaderboard?ref=jina-ai-gmbh.ghost.io">HuggingFace MTEB leaderboard</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/spaces/mteb/leaderboard?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">MTEB Leaderboard - a Hugging Face Space by mteb</div><div class="kg-bookmark-description">Discover amazing ML apps made by the community</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""><span class="kg-bookmark-author">a Hugging Face Space by mteb</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/spaces/mteb/leaderboard.png" alt=""></div></a></figure><h2 id="how-jina-embeddings-2-supports-long-documents">How Jina Embeddings 2 Supports Long Documents</h2><p>Jina AI has implemented the <a href="https://arxiv.org/abs/2108.12409?ref=jina-ai-gmbh.ghost.io">ALiBi approach</a>, the first embedding model to do so. ALiBi is an alternative to the positional encoding system first proposed in the famous “<a href="https://dl.acm.org/doi/10.5555/3295222.3295349?ref=jina-ai-gmbh.ghost.io">Attention is all you need</a>” paper. This scheme makes it possible to train embedding models on short texts and still get high-quality results on longer texts.</p><p>For Jina Embeddings 2, Jina AI has taken the BERT architecture and grafted it into ALiBi.</p><p>ALiBi was originally proposed for text generators (like ChatGPT) that only care about dependencies on previous words. This means that the last tokens in the input matter more than earlier ones because a text generator’s task is to produce the next word after the input. This makes no sense for an embedding model that tries to create a representation of the whole text input, so Jina Embeddings 2 models implement a bi-directional version of ALiBi.</p><p>This architectural change, however, means that we can’t use the pre-training of the original BERT model and have to completely retrain the model from scratch.</p><h2 id="english-only-for-now-german-and-chinese-soon">English-Only for Now, German and Chinese Soon</h2><p>Although there are plenty of multilingual text embedding models out there, there are known issues with providing universal language support. Not all languages are equal when it comes to embedding quality, and <a href="https://aclanthology.org/2023.sigtyp-1.16.pdf?ref=jina-ai-gmbh.ghost.io">recent research</a> shows that models tend to be biased towards structures that parallel English ones, distorting embeddings.</p><p>In short, multilingual models have an “accent”, usually an English one due to the majority of English data in the training.</p><p>For superior language-specific performance, and more compact, easier-to-train models, Jina Embeddings are currently English-only. We’re planning German and Chinese models for the near future.</p><h2 id="training-jina-embeddings-2-for-top-performance-up-to-8192-tokens">Training Jina Embeddings 2 for Top Performance up to 8,192 Tokens</h2><p>Using ALiBi means that even though Jina Embeddings 2 models support larger input sizes, the models don’t have to be trained with larger input data. The training learned for short sequences scales up to larger ones automatically.</p><p>Our training is similar to the way other embedding models are trained. We start with <a href="https://aclanthology.org/N19-1423.pdf?ref=jina-ai-gmbh.ghost.io">masked word pre-training</a> using the circa 170 billion word English-only <a href="https://huggingface.co/datasets/c4?ref=jina-ai-gmbh.ghost.io">C4 dataset</a>. Then, we do <a href="https://arxiv.org/abs/1607.08085?ref=jina-ai-gmbh.ghost.io">pairwise contrastive training</a>. This means taking pairs of texts that are known to be similar or dissimilar and adjusting the weights of the embedding model so that similar inputs are closer together, and dissimilar ones are farther apart. We used a new corpus of text pairs, curated by Jina AI, based on the one <a href="https://arxiv.org/abs/2307.11224?ref=jina-ai-gmbh.ghost.io">used to train the Jina Embeddings 1 models</a>.</p><p>Finally, we fine-tuned the model using <a href="https://finetuner.jina.ai/advanced-topics/negative-mining/?ref=jina-ai-gmbh.ghost.io">text triplets and negative mining</a>, with an in-house training dataset specially augmented with sentences of opposite grammatical polarity. Embedding models have typically had trouble with negative polarity sentences: A sentence like “The dog is in the car” will often have an embedding close to “The dog is outside the car,” even though these are naturally opposite in meaning.</p><p>We added a collection of positive and negative pairs like this to the training data, using the same methods <a href="https://arxiv.org/abs/2307.11224?ref=jina-ai-gmbh.ghost.io">employed for the Jina Embeddings 1 models</a> to specifically improve performance on this kind of language.</p><h2 id="three-models-to-better-fit-your-use-case">Three Models To Better Fit Your Use Case</h2><p>The Jina Embeddings 2 models come in three sizes, providing high-quality embeddings for users with different requirements and capabilities. All three support 8,192 input tokens.</p><ul><li><a href="https://huggingface.co/jinaai/jina-embeddings-v2-small-en?ref=jina-ai-gmbh.ghost.io" rel="noreferrer"><code>jina-embeddings-v2-small-en</code></a>: 33 million parameters, 512-dimension embeddings.</li><li><a href="https://huggingface.co/jinaai/jina-embeddings-v2-base-en?ref=jina-ai-gmbh.ghost.io" rel="noreferrer"><code>jina-embeddings-v2-base-en</code></a>: 137 million parameters, 768-dimension embeddings.</li><li><code>jina-embeddings-v2-large-en</code>: 435 million parameters, 1,024-dimension embeddings.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image.png" class="kg-image" alt="" width="1296" height="946" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image.png 1296w" sizes="(min-width: 720px) 720px"></figure><p>The <code>jina-embeddings-v2-large-en</code> model is not yet available to download but will be released in the immediate future.</p><h2 id="bigger-inputs-leaner-models-peak-performance">Bigger Inputs, Leaner Models, Peak Performance</h2><p>We tested the Jina Embeddings 2 models against the <a href="https://arxiv.org/abs/2210.07316?ref=jina-ai-gmbh.ghost.io">MTEB benchmark suite</a> and at the time of writing:</p><ul><li><code>jina-embeddings-v2-base-en</code> scores roughly on par with the best models on most benchmarks, and generally better than similarly sized ones.</li><li><code>jina-embeddings-v2-small-en</code> ranks near the top for models with sizes under 100MB.</li></ul><p>The <code>jina-embeddings-v2-large-en</code> model is not yet available for testing.</p><p>However, among models that take more than 512 tokens in input, there is only one that compares to the Jina Embeddings 2 models: OpenAI’s <code>text-embedding-ada-002</code>. This model is not publicly available and can only be accessed via a paid web-based API. Its size is unknown.</p><figure class="kg-card kg-image-card kg-width-wide kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-14.png" class="kg-image" alt="" width="1184" height="375" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-14.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-14.png 1184w"><figcaption><span style="white-space: pre-wrap;">jina-embeddings-v2-base-en compared with OpenAI’s text-embedding-ada-002 on the English MTEB benchmark</span></figcaption></figure><p><code>jina-embeddings-v2-base-en</code> is comparable in performance with <code>text-embedding-ada-002</code> on all benchmarks and even exceeds it in several tasks. Furthermore, the Jina Embeddings 2 models all produce smaller embedding vectors than <code>text-embedding-ada-002</code> which produces 1,536-dimensional output, compared to 512, 768, and 1,024 dimensions for our three model sizes respectively. This means considerable savings in computing time and memory for applications. Storing shorter vectors takes less space in memory and storage, speeds up database retrieval, and calculating the distance between them is proportionately fast.</p><figure class="kg-card kg-image-card kg-width-wide kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-15.png" class="kg-image" alt="" width="1204" height="376" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-15.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-15.png 1204w" sizes="(min-width: 1200px) 1200px"><figcaption><span style="white-space: pre-wrap;">Jina Embeddings 2 compared to other leading AI embedding models</span></figcaption></figure><p>Jina AI’s base and small model compared to other leading embedding models</p><p>Furthermore, <code>jina-embeddings-v2-small-en</code> is the only model under 100MB that supports more than 512 input tokens.</p><p>Even if we set aside support for larger inputs, Jina Embeddings offers performance on par with the most common embedding foundation models, while remaining roughly the same size or even significantly smaller.</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-16.png" class="kg-image" alt="" width="1000" height="433" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-16.png 1000w"></figure><p>This gives Jina Embeddings 2 models an impressive advantage in terms of accessibility, economic use of computing power, and cost to users.</p><h2 id="integration">Integration</h2><p>Jina Embeddings 2 models are already integrated into:</p><ul><li><a href="https://github.com/huggingface/text-embeddings-inference?ref=jina-ai-gmbh.ghost.io#supported-models">HuggingFace Text Embeddings Inference API</a></li><li><a href="https://github.com/run-llama/llama_index/blob/main/docs/examples/embeddings/jina_embeddings.ipynb?ref=jina-ai-gmbh.ghost.io">LlamaIndex</a></li><li><a href="https://twitter.com/xenovacom/status/1717904546481992094?ref=jina-ai-gmbh.ghost.io">Transformers.js</a></li><li><a href="https://github.com/simonw/llm-embed-jina?ref=jina-ai-gmbh.ghost.io">LLM</a></li></ul><p>More integrations are coming soon, both from Jina AI and our open-source user community.</p><h2 id="try-it-out-yourself-right-now">Try It Out Yourself Right Now</h2><p>Go to <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io#enterprises">https://jina.ai/#enterprises</a> to get an access key for Jina AI's online Embedding API with ten thousand free tokens for you to embed. You'll find the key on the upper right:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-4.png" class="kg-image" alt="" width="1289" height="712" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-4.png 1289w" sizes="(min-width: 720px) 720px"></figure><p>You can access Jina Embeddings 2 models hosted at Jina AI via any standard HTTP interface. Use the drop-down menus to select between the <code>jina-embeddings-v2-base-en</code> and <code>jina-embeddings-v2-small-en</code> models, and to get code snippets to use the Embeddings API.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-6.png" class="kg-image" alt="" width="1309" height="737" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-6.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-6.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-6.png 1309w" sizes="(min-width: 720px) 720px"></figure><p>You can also get example code snippets in a variety of languages and frameworks to help integrate Jina Embeddings directly into your project:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-7.png" class="kg-image" alt="" width="1307" height="972" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-7.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-7.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-7.png 1307w" sizes="(min-width: 720px) 720px"></figure><p>And if you need to add tokens to your API key, just click the "Top Up" tab.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-8.png" class="kg-image" alt="" width="1281" height="1155" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-8.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-8.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-8.png 1281w" sizes="(min-width: 720px) 720px"></figure><h2 id="future-jina-embeddings-models">Future Jina Embeddings Models</h2><p>Jina AI will be rolling out a larger model, <code>jina-embeddings-v2-large-en</code>, in the immediate future, which we expect to exceed the performance of the other Jina Embeddings 2 models and compete with the highest-scoring large embedding models.</p><p>In the near future, we are expanding our offerings to include German and Chinese embedding models, which we expect will match or exceed state-of-the-art performance in both languages.</p><p>These benchmark results prove the robustness of Jina AI’s contrastive training methodology, and we are always investigating improved model design and AI techniques. 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diff --git a/news/jina-embeddings-v2-and-mongodb-atlas/index.html b/news/jina-embeddings-v2-and-mongodb-atlas/index.html
index a14e77a0bf0..475e6dfa97b 100644
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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina Embeddings v2 and MongoDB Atlas</title><meta charset="utf-8"><meta name="title" content="Jina Embeddings v2 and MongoDB Atlas"><meta name="description" content="Supercharge MongoDB Atlas multi-cloud vector search solutions with Jina AI’s industry-leading embeddings!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-embeddings-v2-and-mongodb-atlas"><meta property="og:title" content="Jina Embeddings v2 and MongoDB Atlas"><meta property="og:description" content="Supercharge MongoDB Atlas multi-cloud vector search solutions with Jina AI’s industry-leading embeddings!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Blog-images--8-.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-embeddings-v2-and-mongodb-atlas"><meta property="twitter:title" content="Jina Embeddings v2 and MongoDB Atlas"><meta property="twitter:description" content="Supercharge MongoDB Atlas multi-cloud vector search solutions with Jina AI’s industry-leading embeddings!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Blog-images--8-.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Jina Embeddings v2 and MongoDB Atlas</title><meta charset="utf-8"><meta name="title" content="Jina Embeddings v2 and MongoDB Atlas"><meta name="description" content="Supercharge MongoDB Atlas multi-cloud vector search solutions with Jina AI’s industry-leading embeddings!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/jina-embeddings-v2-and-mongodb-atlas"><meta property="og:title" content="Jina Embeddings v2 and MongoDB Atlas"><meta property="og:description" content="Supercharge MongoDB Atlas multi-cloud vector search solutions with Jina AI’s industry-leading embeddings!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Blog-images--8-.jpg"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/jina-embeddings-v2-and-mongodb-atlas"><meta property="twitter:title" content="Jina Embeddings v2 and MongoDB Atlas"><meta property="twitter:description" content="Supercharge MongoDB Atlas multi-cloud vector search solutions with Jina AI’s industry-leading embeddings!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Blog-images--8-.jpg"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><script src="https://jina-ai-gmbh.ghost.io/public/cards.min.js" async=""></script><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Jina Embeddings v2 and MongoDB Atlas</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Supercharge MongoDB Atlas multi-cloud vector search solutions with Jina AI’s industry-leading embeddings!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens, Saahil Ognawala</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 06, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina AI and <a href="https://www.mongodb.com/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">MongoDB</a> have collaborated to bring you a tutorial on using <a href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Jina Embeddings v2</a> to bring state-of-the-art semantic search to MongoDB Atlas. Follow the link below to MongoDB's website to see how you can supercharge MongoDB’s multi-cloud vector search solutions with Jina AI’s industry-leading embeddings!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.mongodb.com/developer/products/atlas/jina-ai-semantic-search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Semantic search with Jina Embeddings v2 and MongoDB Atlas | MongoDB</div><div class="kg-bookmark-description">Follow along with this tutorial on using Jina Embeddings v2 with MongoDB Atlas for vector search.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.mongodb.com/developer/favicon.ico" alt=""><span class="kg-bookmark-author">MongoDB</span><span class="kg-bookmark-publisher">Scott Martens, Saahil Ognawala</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://images.contentstack.io/v3/assets/blt39790b633ee0d5a7/blt3d996d2aa8d9ece9/647a2f77f7b1280bb15174b7/Technical_SOFTWARE_Terminal(4)_Spot_BS_ForestGreen.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Embedding API</div><div class="kg-bookmark-description">Top-performing, 8192-token length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/banner-embedding-api.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-embeddings-v2-and-mongodb-atlas%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Scott Martens, Saahil Ognawala</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 06, 2023 • 1 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina AI and <a href="https://www.mongodb.com/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">MongoDB</a> have collaborated to bring you a tutorial on using <a href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Jina Embeddings v2</a> to bring state-of-the-art semantic search to MongoDB Atlas. Follow the link below to MongoDB's website to see how you can supercharge MongoDB’s multi-cloud vector search solutions with Jina AI’s industry-leading embeddings!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.mongodb.com/developer/products/atlas/jina-ai-semantic-search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Semantic search with Jina Embeddings v2 and MongoDB Atlas | MongoDB</div><div class="kg-bookmark-description">Follow along with this tutorial on using Jina Embeddings v2 with MongoDB Atlas for vector search.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.mongodb.com/developer/favicon.ico" alt=""><span class="kg-bookmark-author">MongoDB</span><span class="kg-bookmark-publisher">Scott Martens, Saahil Ognawala</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://images.contentstack.io/v3/assets/blt39790b633ee0d5a7/blt3d996d2aa8d9ece9/647a2f77f7b1280bb15174b7/Technical_SOFTWARE_Terminal(4)_Spot_BS_ForestGreen.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/embeddings/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Embedding API</div><div class="kg-bookmark-description">Top-performing, 8192-token length, $100 for 1.25B tokens, seamless OpenAI alternative, free trial</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/banner-embedding-api.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjina-embeddings-v2-and-mongodb-atlas%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.385%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-meetup" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="mailto:support@jina.ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">email</i></span></a></div><div class="row col-12 col-md-6 items-center text-caption justify-center"><div class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--stretch inline" no-caps=""><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch text-caption" tabindex="0" href="/legal/#privacy-policy" style="padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">Privacy Policy</span></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch text-caption" tabindex="0" href="/legal/#terms-and-conditions" style="padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">Terms and Conditions</span></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch text-caption" tabindex="0" href="javascript:UC_UI.showSecondLayer();" style="padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">Privacy Settings</span></span></a></div></div></div></footer></div></div><div id="q-notify" data-v-app=""><div class="q-notifications"><div class="q-notifications__list q-notifications__list--top fixed column no-wrap items-start"></div><div class="q-notifications__list q-notifications__list--top fixed column no-wrap items-end"></div><div class="q-notifications__list q-notifications__list--bottom fixed column no-wrap items-start"></div><div class="q-notifications__list q-notifications__list--bottom fixed column no-wrap items-end"></div><div class="q-notifications__list q-notifications__list--top fixed column no-wrap items-center"></div><div class="q-notifications__list q-notifications__list--bottom fixed column no-wrap items-center"></div><div class="q-notifications__list q-notifications__list--center fixed column no-wrap items-start justify-center"></div><div class="q-notifications__list q-notifications__list--center fixed column no-wrap items-end justify-center"></div><div class="q-notifications__list q-notifications__list--center fixed column no-wrap flex-center"></div></div></div></body></html>
\ No newline at end of file
diff --git a/news/join-berlin-ai-summit-on-oct-4-6-and-meet-our-team/index.html b/news/join-berlin-ai-summit-on-oct-4-6-and-meet-our-team/index.html
index 2da0c34ba33..a02c12db1fa 100644
--- a/news/join-berlin-ai-summit-on-oct-4-6-and-meet-our-team/index.html
+++ b/news/join-berlin-ai-summit-on-oct-4-6-and-meet-our-team/index.html
@@ -10,9 +10,9 @@
 
 🎤 Keynote: Unlock the Business Value of Multimodal Data via Jina AI
 
-Multimodal AI is a new type of AI that can take in data from multiple modalities (images, tex"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/2-1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+Multimodal AI is a new type of AI that can take in data from multiple modalities (images, tex"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/09/2-1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">On Oct. 5th, our Founder and CEO Han Xiao will give a keynote speech at Berlin AI Summit. He will introduce the Jina AI platform and talk about unlocking the business value of multimodal data in the enterprise. Our team will also be there for open discussion. Feel free to say hi to us and understand more about our mission and vision.
 
 🎤 Keynote: Unlock the Business Value of Multimodal Data via Jina AI
 
-Multimodal AI is a new type of AI that can take in data from multiple modalities (images, tex</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 28, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p></p><p>On Oct. 5th, our Founder and CEO Han Xiao will give a keynote speech at Berlin AI Summit. He will introduce the Jina AI platform and talk about unlocking the business value of multimodal data in the enterprise. Our team will also be there for open discussion. Feel free to say hi to us and understand more about our mission and vision.</p><div class="kg-card kg-toggle-card" data-kg-toggle-state="close"><div class="kg-toggle-heading"><h4 class="kg-toggle-heading-text">🎤 Keynote: Unlock the Business Value of Multimodal Data via Jina AI</h4><button class="kg-toggle-card-icon"><svg id="Regular" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path class="cls-1" d="M23.25,7.311,12.53,18.03a.749.749,0,0,1-1.06,0L.75,7.311"></path></svg></button></div><div class="kg-toggle-content"><p>Multimodal AI is a new type of AI that can take in data from multiple modalities (images, text, audio, etc.) and learn from it to make predictions. This makes it very powerful for applications like neural search and creative AI (DALLE and StableDiffusion). Multimodal AI also presents new challenges for engineering. In particular, it can be difficult to deploy and manage multimodal AI models and pipelines and make them scalable in production. This is where MLOps platforms come in. In this talk, Han will discuss the benefits of using an MLOps platform for multimodal AI applications in production and help to unlock the business value of your multimodal data.</p></div></div><p>One can find more information and registration below:</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://www.re-work.co/events/deep-learning-summit-berlin-2022/schedule?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Schedule | Deep Learning Summit Berlin</div><div class="kg-bookmark-description">We create and organise globally renowned summits, workshops and dinners, bringing together the brightest minds in AI from both industry and academia. At each RE•WORK event, we combine the latest technological innovation with real-world applications and practical case studies. Learn from global pione…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.re-work.co/assets/favIcon.png" alt=""><span class="kg-bookmark-author">RE•WORK</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://s3.amazonaws.com/re-work-production/calendar_images/495/large.jpg?1638361357" alt=""></div></a><figcaption>Han's talk will be on Oct 5th 9:40AM</figcaption></figure><h2 id="about-jina-ai">About Jina AI</h2><p>Jina AI is a commercial open-source software company founded in February 2020. It provides businesses and developers an MLOps platform for building multimodal applications on the cloud, including neural search, creative AI, etc. The company has raised 37.5 million USD backed by top investors such as Canaan Partners, GGV Capital, Yunqi Partners, SAP.io, and Mango Capital. The company is headquartered in Berlin, Germany with offices in San Jose, Beijing, and Shenzhen; its distributed team model includes members from all around the world. </p><h2 id="about-berlin-ai-summit">About Berlin AI Summit</h2><p>Berlin AI Summit is organized by RE•WORK. This event brings together the latest technological advancements as well as practical examples to apply AI to solve challenges in business and society. The unique mix of academia and industry enables you to meet with AI pioneers at the forefront of research, as well as exploring real-world case studies to discover the business value of AI.</p><p>Bringing together the smartest minds in AI since 2013, RE•WORK created a community of thought leaders with both technical and business expertise, providing the highest quality learning and networking opportunities.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjoin-berlin-ai-summit-on-oct-4-6-and-meet-our-team%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; 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+Multimodal AI is a new type of AI that can take in data from multiple modalities (images, tex</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 28, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p></p><p>On Oct. 5th, our Founder and CEO Han Xiao will give a keynote speech at Berlin AI Summit. He will introduce the Jina AI platform and talk about unlocking the business value of multimodal data in the enterprise. Our team will also be there for open discussion. Feel free to say hi to us and understand more about our mission and vision.</p><div class="kg-card kg-toggle-card" data-kg-toggle-state="close"><div class="kg-toggle-heading"><h4 class="kg-toggle-heading-text">🎤 Keynote: Unlock the Business Value of Multimodal Data via Jina AI</h4><button class="kg-toggle-card-icon"><svg id="Regular" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path class="cls-1" d="M23.25,7.311,12.53,18.03a.749.749,0,0,1-1.06,0L.75,7.311"></path></svg></button></div><div class="kg-toggle-content"><p>Multimodal AI is a new type of AI that can take in data from multiple modalities (images, text, audio, etc.) and learn from it to make predictions. This makes it very powerful for applications like neural search and creative AI (DALLE and StableDiffusion). Multimodal AI also presents new challenges for engineering. In particular, it can be difficult to deploy and manage multimodal AI models and pipelines and make them scalable in production. This is where MLOps platforms come in. In this talk, Han will discuss the benefits of using an MLOps platform for multimodal AI applications in production and help to unlock the business value of your multimodal data.</p></div></div><p>One can find more information and registration below:</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://www.re-work.co/events/deep-learning-summit-berlin-2022/schedule?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Schedule | Deep Learning Summit Berlin</div><div class="kg-bookmark-description">We create and organise globally renowned summits, workshops and dinners, bringing together the brightest minds in AI from both industry and academia. At each RE•WORK event, we combine the latest technological innovation with real-world applications and practical case studies. Learn from global pione…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.re-work.co/assets/favIcon.png" alt=""><span class="kg-bookmark-author">RE•WORK</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://s3.amazonaws.com/re-work-production/calendar_images/495/large.jpg?1638361357" alt=""></div></a><figcaption>Han's talk will be on Oct 5th 9:40AM</figcaption></figure><h2 id="about-jina-ai">About Jina AI</h2><p>Jina AI is a commercial open-source software company founded in February 2020. It provides businesses and developers an MLOps platform for building multimodal applications on the cloud, including neural search, creative AI, etc. The company has raised 37.5 million USD backed by top investors such as Canaan Partners, GGV Capital, Yunqi Partners, SAP.io, and Mango Capital. The company is headquartered in Berlin, Germany with offices in San Jose, Beijing, and Shenzhen; its distributed team model includes members from all around the world. </p><h2 id="about-berlin-ai-summit">About Berlin AI Summit</h2><p>Berlin AI Summit is organized by RE•WORK. This event brings together the latest technological advancements as well as practical examples to apply AI to solve challenges in business and society. The unique mix of academia and industry enables you to meet with AI pioneers at the forefront of research, as well as exploring real-world case studies to discover the business value of AI.</p><p>Bringing together the smartest minds in AI since 2013, RE•WORK created a community of thought leaders with both technical and business expertise, providing the highest quality learning and networking opportunities.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjoin-berlin-ai-summit-on-oct-4-6-and-meet-our-team%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Join Jina AI for Multimodal AI innovation through Google Summer of Code 2023</title><meta charset="utf-8"><meta name="title" content="Join Jina AI for Multimodal AI innovation through Google Summer of Code 2023"><meta name="description" content="Jina AI's GSoC 2023: Multimodal AI at your fingertips and world-class mentors by your side. Join us now! "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/join-jina-ai-for-multimodal-ai-innovation-through-gsoc-2023"><meta property="og:title" content="Join Jina AI for Multimodal AI innovation through Google Summer of Code 2023"><meta property="og:description" content="Jina AI's GSoC 2023: Multimodal AI at your fingertips and world-class mentors by your side. Join us now! "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Banner-of-GSoC--4-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/join-jina-ai-for-multimodal-ai-innovation-through-gsoc-2023"><meta property="twitter:title" content="Join Jina AI for Multimodal AI innovation through Google Summer of Code 2023"><meta property="twitter:description" content="Jina AI's GSoC 2023: Multimodal AI at your fingertips and world-class mentors by your side. Join us now! "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Banner-of-GSoC--4-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Join Jina AI for Multimodal AI innovation through Google Summer of Code 2023</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI's GSoC 2023: Multimodal AI at your fingertips and world-class mentors by your side. Join us now! </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/SaZhang.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Sa Zhang</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 14, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina AI has been selected as one of 19 organizations in Infrastructure and Cloud for Google Summer of Code 2023! Google Summer of Code is an open-source internship program offering <a href="https://developers.google.com/open-source/gsoc/help/student-stipends?ref=jina-ai-gmbh.ghost.io">paid remote work</a>. Presently, it is recognized as the world's pre-eminent remunerated open-source programming event and contributes significantly to the advancement of global open-source ecology.</p><p><strong>Almost anyone in the world over 18 years of age</strong> who loves coding and wants to explore the incredible world of open source can join us as a GSoC 2023 contributor.</p><h2 id="why-participate-in-jina-ais-gsoc-2023">Why participate in Jina AI's GSoC 2023?</h2><p><a href="https://github.com/jina-ai/gsoc/?ref=jina-ai-gmbh.ghost.io">Jina AI's GSoC</a> includes diverse and challenging tasks, ambiguous goals to stimulate creativity, authentic challenges consistent with<strong> </strong>realistic projects, and flexible collaboration between potential contributors and mentors.</p><p>We offer a <strong>diverse</strong> range of challenging tasks that encourage creativity among our participants. The program includes projects that range from developing new features, improving existing ones, conducting research, and practical implementation.</p><p>To foster <strong>creativity</strong>, our mentors encourage a broad approach to the projects, allowing contributors to explore different ideas and possibilities, without being confined to rigid boundaries.</p><p><strong>Authenticity</strong> is at the heart of Jina AI's GSoC program. The program participants will work on real-world projects driven by the open-source community.</p><p>The program is also highly <strong>flexible</strong>, encouraging contributors and mentors to work together to develop proposals that deliver the best possible outcomes, leading to innovative results.</p><h2 id="jina-ais-gsoc-projects">Jina AI's GSoC Projects</h2><h3 id="1-build-executor-model-ui-in-jina">1. <a href="https://github.com/jina-ai/GSoC/issues/16?ref=jina-ai-gmbh.ghost.io">Build Executor (model) UI in jina</a></h3><table role="table" style="box-sizing: border-box; border-spacing: 0px; border-collapse: collapse; margin-top: 0px; margin-bottom: 16px; display: block; width: max-content; max-width: 100%; overflow: auto; color: rgb(36, 41, 47); font-family: -apple-system, &quot;system-ui&quot;, &quot;Segoe UI&quot;, &quot;Noto Sans&quot;, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><thead style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">info</th><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">details</th></tr></thead><tbody style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Skills needed</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Python</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Project size</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">175 hours</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Difficulty level</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Easy</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Mentors</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">@<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Alaeddine Abdessalem</a>, @<a href="https://www.linkedin.com/in/philipvollet?ref=jina-ai-gmbh.ghost.io" rel="nofollow" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none; margin-bottom: 0px;">Philip Vollet</a></td></tr></tbody></table><p><strong>Project Description:</strong></p><p>Jina <a href="https://docs.jina.ai/concepts/executor/?ref=jina-ai-gmbh.ghost.io">Executors</a> are components that perform certain tasks and expose them as services using gRPC. Executors accept <a href="https://docs.docarray.org/fundamentals/documentarray/?ref=jina-ai-gmbh.ghost.io">DocumentArrays</a> as input and output. However, with <a href="https://github.com/docarray/docarray/tree/feat-rewrite-v2?ref=jina-ai-gmbh.ghost.io">DocArray V2</a> focusing on type annotations and enabling annotation of Executor endpoints, it becomes possible for Executors to describe their services and input/output in the same way as OpenAPI schemas. This allows us to offer built-in UIs for Executors, enabling people to easily use their services with multimodal data. The goal is to build this feature in Jina using Gradio.</p><p><strong>Expected outcomes:</strong></p><ul><li>Submit one or more Pull Requests (PRs) to the <a href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io">Jina</a> repository that enables providing a built-in Executor UI for Executors. </li><li>The UI can be built using Gradio and should be able to infer information about the Executor service using type annotations.</li></ul><h3 id="2-docarray-wrap-ann-libraries">2. <a href="https://github.com/jina-ai/GSoC/issues/17?ref=jina-ai-gmbh.ghost.io">DocArray wrap ANN libraries</a></h3><table role="table" style="box-sizing: border-box; border-spacing: 0px; border-collapse: collapse; margin-top: 0px; margin-bottom: 16px; display: block; width: max-content; max-width: 100%; overflow: auto; color: rgb(36, 41, 47); font-family: -apple-system, &quot;system-ui&quot;, &quot;Segoe UI&quot;, &quot;Noto Sans&quot;, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><thead style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">Info</th><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">details</th></tr></thead><tbody style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Skills needed</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Python, ANN Search experience</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Project size</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">175 hours</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Difficulty level</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Medium</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Mentors</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">@<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Johannes Messner</a>, @<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Sami Jaghouar</a>, @<a href="https://www.linkedin.com/in/philipvollet?ref=jina-ai-gmbh.ghost.io" rel="nofollow" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none; margin-bottom: 0px;">Philip Vollet</a></td></tr></tbody></table><p><strong>Project Description:</strong></p><p>In DocArray, we have been concentrating on developing production-ready Vector DBs for large-scale searches. However, there are many ANN libraries without scalability layers that can be integrated into DocArray, making it accessible to academia and production teams with small-to-medium amounts of data, without the need for external services.</p><p>DocArray v2 will have a concept called Document Index. This is an abstraction that lets a user store their Documents (on disk or in a database), and retrieve them using ANN search. As such, there can be multiple Document Indexes backed by different backends: Elastic, Qdrant, Weaviate, etc, but all following the same basic API.</p><p>The idea behind this project is to take an ANN library and use it to implement a Document Index. There is already an implementation using HNSWLib that you can find here: <a href="https://github.com/docarray/docarray/pull/1124?ref=jina-ai-gmbh.ghost.io">feat: hnswlib document index</a>, But there is space to create similar backends using other libraries: Annoy, Faiss, etc. The goal is to provide user choice.</p><p>If there is interest, someone could also implement a backend using a vector database. We already have Qdrant, Weaviate, and Elastic covered, but Milvus, Redis, and some others could also be interesting. You can find a design doc for Document Index <a href="https://lightning-scent-57a.notion.site/Document-Stores-v2-design-doc-f11d6fe6ecee43f49ef88e0f1bf80b7f?ref=jina-ai-gmbh.ghost.io" rel="nofollow">here</a>.</p><p><strong>Expected Outcomes:</strong></p><ul><li>We have a set of Document Store implementations in DocArray that support the most popular ANN libraries, such as FAISS, Annoy, and Hnswlib.</li></ul><h3 id="3-research-about-deploying-llm-with-jina">3. <a href="https://github.com/jina-ai/GSoC/issues/18?ref=jina-ai-gmbh.ghost.io">Research about deploying LLM with Jina</a></h3><table role="table" style="box-sizing: border-box; border-spacing: 0px; border-collapse: collapse; margin-top: 0px; margin-bottom: 16px; display: block; width: max-content; max-width: 100%; overflow: auto; color: rgb(36, 41, 47); font-family: -apple-system, &quot;system-ui&quot;, &quot;Segoe UI&quot;, &quot;Noto Sans&quot;, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><thead style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">info</th><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">details</th></tr></thead><tbody style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Skills needed</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Python, Pytorch, CUDA, Docker, Kubernetes</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Project size</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">350 hours</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Difficulty level</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Hard</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Mentors</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">@<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Alaeddine Abdessalem</a>, @<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none; margin-bottom: 0px;">Joan Martínez</a></td></tr></tbody></table><p><strong>Project Description: </strong></p><p>This project aims to demonstrate the capability of deploying and scaling Large Language Models (LLMs) using Jina. LLMs have gained significant attention for their ability to generate text and solve various tasks. However, deploying LLMs requires technologies to enable scalability when using GPU resources. This project will assess the capability of deploying LLMs with Jina and explore integrations with existing libraries such as <a href="https://github.com/microsoft/DeepSpeed?ref=jina-ai-gmbh.ghost.io">DeepSpeed</a>, <a href="https://github.com/FMInference/FlexGen?ref=jina-ai-gmbh.ghost.io">Accelerate</a>, and <a href="https://github.com/FMInference/FlexGen?ref=jina-ai-gmbh.ghost.io">FlexGen</a> that provide optimizations for model deployment. The goal is to build demos and showcases hosting LLMs using Jina and the integrated libraries. This will demonstrate Jina's ability to deploy and scale LLMs in a cost-efficient manner.</p><p><strong>Expected Outcomes: </strong></p><ul><li>Implementation of LLM deployment using Jina and assessing scalability with GPU resources.</li><li>Documentation and example code demonstrating the use of Jina for LLM deployment and inference.</li><li>Building integrations with the mentioned libraries in order to use them within Jina.</li><li>Evaluation of the cost-efficiency of deploying and scaling LLMs with Jina compared to other technologies.</li></ul><h3 id="4-expand-annlite-capabilities-with-bm25-to-build-hybrid-search">4. <a href="https://github.com/jina-ai/GSoC/issues/19?ref=jina-ai-gmbh.ghost.io">Expand ANNLite capabilities with BM25 to build Hybrid Search</a></h3><table role="table" style="box-sizing: border-box; border-spacing: 0px; border-collapse: collapse; margin-top: 0px; margin-bottom: 16px; display: block; width: max-content; max-width: 100%; overflow: auto; color: rgb(36, 41, 47); font-family: -apple-system, &quot;system-ui&quot;, &quot;Segoe UI&quot;, &quot;Noto Sans&quot;, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><thead style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">info</th><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">details</th></tr></thead><tbody style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Skills needed</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Python, C++, Lucene, ANN, Inverted Index</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Project size</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">350 hours</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Difficulty level</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Hard</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Mentors</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">@<a href="https://github.com/numb3r3?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Felix Wang</a><span>&nbsp;</span>@<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Joan Martínez</a><span>&nbsp;</span>@<a href="https://github.com/girishc13?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none; margin-bottom: 0px;">Girish Chandrashekar</a></td></tr></tbody></table><p><strong>Project Description: </strong></p><p>This project aims to evaluate and implement <a href="https://jina.ai/news/hype-and-hybrids-multimodal-search-means-more-than-keywords-and-vectors-2/?ref=jina-ai-gmbh.ghost.io">Hybrid Search</a> approaches on top of <a href="https://github.com/jina-ai/annlite?ref=jina-ai-gmbh.ghost.io">ANNLite</a>, a Vector search library developed by Jina using <a href="https://github.com/naver/splade?ref=jina-ai-gmbh.ghost.io">HNSW</a> as the algorithm for searches. The incorporation of <a href="https://www.elastic.co/blog/practical-bm25-part-2-the-bm25-algorithm-and-its-variables?ref=jina-ai-gmbh.ghost.io" rel="nofollow">BM25</a> and Hybrid Search will enable Jina to create scalable solutions for Hybrid Search in the cloud. While ANNLite allows the filtering of documents, combining Vector Search algorithms with traditional text-search ones will help improve performance in search systems. Through this project, we will investigate the benefits of Hybrid Search and try to deploy it with ANNLite to create powerful default search solutions for Jina.</p><p><strong>Expected Outcomes: </strong></p><ul><li>ANNLite is ready to be used as a default library to solve Hybrid Search applications.</li></ul><h3 id="5-make-annlite-the-go-to-vector-search-library-to-be-scaled-by-jina-using-the-statefulexecutor-feature">5. <a href="https://github.com/jina-ai/GSoC/issues/20?ref=jina-ai-gmbh.ghost.io">Make ANNLite the go-to Vector Search library to be scaled by Jina using the StatefulExecutor feature</a></h3><table role="table" style="box-sizing: border-box; border-spacing: 0px; border-collapse: collapse; margin-top: 0px; margin-bottom: 16px; display: block; width: max-content; max-width: 100%; overflow: auto; color: rgb(36, 41, 47); font-family: -apple-system, &quot;system-ui&quot;, &quot;Segoe UI&quot;, &quot;Noto Sans&quot;, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><thead style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">info</th><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">details</th></tr></thead><tbody style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Skills needed</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">ANN, C++, Python, Databases</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Project size</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">350 hours</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Difficulty level</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Hard</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Mentors</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">@<a href="https://github.com/numb3r3?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Felix Wang</a><span>&nbsp;</span>@<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none; margin-bottom: 0px;">Joan Martínez</a></td></tr></tbody></table><p><strong>Project Description: </strong></p><p>Jina is developing a stateful Executor feature that enables Deployments with a state to be replicated and scaled. This opens the door to having a Vector Database in our ecosystem effectively and robustly. Iterating on ANNLite to act as the "Lucene" for Jina would be a great opportunity.</p><p><strong>Expected Outcomes: </strong></p><ul><li>Prove and come up with an Executor in our <a href="https://cloud.jina.ai/executors?ref=jina-ai-gmbh.ghost.io">Executor Hub</a> that uses ANNlite or DocArray with ANNLite as a backend to be the default Vector Databases for all our examples for mid-sized data requirements.</li></ul><h3 id="6-jax-support-in-docarray-v2">6. <a href="https://github.com/jina-ai/GSoC/issues/21?ref=jina-ai-gmbh.ghost.io">JAX support in DocArray v2</a></h3><table role="table" style="box-sizing: border-box; border-spacing: 0px; border-collapse: collapse; margin-top: 0px; margin-bottom: 16px; display: block; width: max-content; max-width: 100%; overflow: auto; color: rgb(36, 41, 47); font-family: -apple-system, &quot;system-ui&quot;, &quot;Segoe UI&quot;, &quot;Noto Sans&quot;, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><thead style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">Info</th><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">details</th></tr></thead><tbody style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Skills needed</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Python, Deep Learning, JAX</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Project size</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">175 hours</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Difficulty level</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Hard</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Mentors</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">@<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none; margin-bottom: 0px;">Sami Jaghouar</a></td></tr></tbody></table><p><strong>Project Description: </strong></p><p>DocArray is a library for representing, sending, and storing multi-modal data, with a focus on applications in Machine Learning and Neural Search. It currently supports several deep learning frameworks, including <a href="https://cloud.jina.ai/executors?ref=jina-ai-gmbh.ghost.io">PyTorch and TensorFlow</a>. <a href="https://jax.readthedocs.io/?ref=jina-ai-gmbh.ghost.io">Google JAX</a> is becoming increasingly popular for deep learning, so we want to integrate it into DocArray.</p><p>The project we propose is to add JAX as a backend for DocArray, alongside PyTorch and TensorFlow. The first part would involve rewriting and translating all of the computational backend functions of DocArray with the JAX framework. Then, we would battle-test the implementation against a real JAX use case, such as integrating DocArray with JAX support for model training and serving.</p><p><strong>Expected Outcomes: </strong></p><ul><li>We aim to provide JAX with the same level of support in DocArray as we do for PyTorch, Numpy, and TensorFlow. The integration should be thoroughly tested and documented.</li></ul><h2 id="meet-the-jina-ai-mentor-team">Meet the Jina AI mentor team</h2><ul><li><a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">Joan Martínez</a>, Head of Engineering</li><li><a href="https://github.com/numb3r3?ref=jina-ai-gmbh.ghost.io">Felix Wang</a>, Engineering Manager</li><li><a href="https://www.linkedin.com/in/philipvollet?ref=jina-ai-gmbh.ghost.io">Philip Vollet</a>, Head of Developer Experience</li><li><a href="https://github.com/girishc13?ref=jina-ai-gmbh.ghost.io">Girish Chandrashekar</a>, Senior Software Engineer</li><li><a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">Johannes Messner</a>, Senior Software Engineer</li><li><a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">Sami Jaghouar</a>, Senior Software Engineer</li><li><a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">Alaeddine Abdessalem</a>, Software Engineer</li></ul><h2 id="how-to-apply-for-jina-ais-gsoc">How to apply for Jina AI's GSoC</h2><ol><li>Read through <a href="https://github.com/jina-ai/gsoc?ref=jina-ai-gmbh.ghost.io">Jina AI's GSoC</a> page and <a href="https://google.github.io/gsocguides/student/?ref=jina-ai-gmbh.ghost.io">Google Summer of Code guides</a>.</li><li>Identify project ideas on <a href="https://github.com/jina-ai/gsoc/issues?ref=jina-ai-gmbh.ghost.io">Jina AI's GSoC issues.</a></li><li>Fill out the <a href="https://10sw1tcpld4.typeform.com/to/chrdIltW?ref=jina-ai-gmbh.ghost.io">Survey</a> so mentors can understand your background and relevant experience.</li><li>Interact with the <a href="https://jina.ai/community/?ref=jina-ai-gmbh.ghost.io">Jina community</a>: join channels, introduce yourself, ask thoughtful questions, and help others with issues you have experience with.</li><li>Try out the project ideas: Try on the local environment, Read the <a href="https://docs.jina.ai/?ref=jina-ai-gmbh.ghost.io">documentation</a>, Reproduce <a href="https://jina.ai/news/?tag=tech-blog&amp;ref=jina-ai-gmbh.ghost.io">tech blogs' examples</a> to get hands-on experience, Solve issues you encounter, and Ask questions if stuck.</li><li>Make contributions: Try to fix some <a href="https://github.com/docarray/docarray/issues?q=is%3Aissue+is%3Aopen&amp;ref=jina-ai-gmbh.ghost.io">good first issues</a>, write tutorials, or share interesting projects you build with Jina or DocArray.</li><li>Preparing a well-crafted proposal aligned with project goals. Submit applications through <a href="Google's application system">Google's system</a> from March 20 to April 4.</li></ol><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/timeline.png" class="kg-image" alt="" width="2000" height="2288" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/timeline.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/timeline.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/03/timeline.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/timeline.png 2000w" sizes="(min-width: 720px) 720px"><figcaption><a href="https://summerofcode.withgoogle.com/organizations/jina-ai-sb/programs/2023/timeline?ref=jina-ai-gmbh.ghost.io">Timeline</a></figcaption></figure><h2 id="gsoc-x-jina-ai-webinar">GSoC x Jina AI Webinar</h2><p>We will be hosting a <a href="https://www.meetup.com/jina-community-meetup/events/292210036/?ref=jina-ai-gmbh.ghost.io">GSoC x Jina AI webinar</a> on March 23rd, 14:00-15:00 PM (CET). Join us as our experienced mentors provide an overview of their GSoC projects and answer any questions you have about the project requirements and expectations. This is a great opportunity for students, developers, and tech enthusiasts to learn more about these exciting projects and get involved in the open-source community.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.meetup.com/jina-community-meetup/events/292210036/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">From Idea to Reality: Dive into Jina AI’s GSoC projects, Thu, Mar 23, 2023, 2:00 PM | Meetup</div><div class="kg-bookmark-description">👋 Google Summer of Code (GSoC) is an annual program that offers students the opportunity to work on open-source projects with experienced mentors. [Jina AI](https://github</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://secure.meetupstatic.com/next/images/general/m_swarm_196x196.png" alt=""><span class="kg-bookmark-author">Meetup</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://secure.meetupstatic.com/photos/event/d/8/c/1/600_511315489.jpeg" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjoin-jina-ai-for-multimodal-ai-innovation-through-gsoc-2023%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI's GSoC 2023: Multimodal AI at your fingertips and world-class mentors by your side. Join us now! </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/SaZhang.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Sa Zhang</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 14, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina AI has been selected as one of 19 organizations in Infrastructure and Cloud for Google Summer of Code 2023! Google Summer of Code is an open-source internship program offering <a href="https://developers.google.com/open-source/gsoc/help/student-stipends?ref=jina-ai-gmbh.ghost.io">paid remote work</a>. Presently, it is recognized as the world's pre-eminent remunerated open-source programming event and contributes significantly to the advancement of global open-source ecology.</p><p><strong>Almost anyone in the world over 18 years of age</strong> who loves coding and wants to explore the incredible world of open source can join us as a GSoC 2023 contributor.</p><h2 id="why-participate-in-jina-ais-gsoc-2023">Why participate in Jina AI's GSoC 2023?</h2><p><a href="https://github.com/jina-ai/gsoc/?ref=jina-ai-gmbh.ghost.io">Jina AI's GSoC</a> includes diverse and challenging tasks, ambiguous goals to stimulate creativity, authentic challenges consistent with<strong> </strong>realistic projects, and flexible collaboration between potential contributors and mentors.</p><p>We offer a <strong>diverse</strong> range of challenging tasks that encourage creativity among our participants. The program includes projects that range from developing new features, improving existing ones, conducting research, and practical implementation.</p><p>To foster <strong>creativity</strong>, our mentors encourage a broad approach to the projects, allowing contributors to explore different ideas and possibilities, without being confined to rigid boundaries.</p><p><strong>Authenticity</strong> is at the heart of Jina AI's GSoC program. The program participants will work on real-world projects driven by the open-source community.</p><p>The program is also highly <strong>flexible</strong>, encouraging contributors and mentors to work together to develop proposals that deliver the best possible outcomes, leading to innovative results.</p><h2 id="jina-ais-gsoc-projects">Jina AI's GSoC Projects</h2><h3 id="1-build-executor-model-ui-in-jina">1. <a href="https://github.com/jina-ai/GSoC/issues/16?ref=jina-ai-gmbh.ghost.io">Build Executor (model) UI in jina</a></h3><table role="table" style="box-sizing: border-box; border-spacing: 0px; border-collapse: collapse; margin-top: 0px; margin-bottom: 16px; display: block; width: max-content; max-width: 100%; overflow: auto; color: rgb(36, 41, 47); font-family: -apple-system, &quot;system-ui&quot;, &quot;Segoe UI&quot;, &quot;Noto Sans&quot;, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><thead style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">info</th><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">details</th></tr></thead><tbody style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Skills needed</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Python</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Project size</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">175 hours</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Difficulty level</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Easy</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Mentors</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">@<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Alaeddine Abdessalem</a>, @<a href="https://www.linkedin.com/in/philipvollet?ref=jina-ai-gmbh.ghost.io" rel="nofollow" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none; margin-bottom: 0px;">Philip Vollet</a></td></tr></tbody></table><p><strong>Project Description:</strong></p><p>Jina <a href="https://docs.jina.ai/concepts/executor/?ref=jina-ai-gmbh.ghost.io">Executors</a> are components that perform certain tasks and expose them as services using gRPC. Executors accept <a href="https://docs.docarray.org/fundamentals/documentarray/?ref=jina-ai-gmbh.ghost.io">DocumentArrays</a> as input and output. However, with <a href="https://github.com/docarray/docarray/tree/feat-rewrite-v2?ref=jina-ai-gmbh.ghost.io">DocArray V2</a> focusing on type annotations and enabling annotation of Executor endpoints, it becomes possible for Executors to describe their services and input/output in the same way as OpenAPI schemas. This allows us to offer built-in UIs for Executors, enabling people to easily use their services with multimodal data. The goal is to build this feature in Jina using Gradio.</p><p><strong>Expected outcomes:</strong></p><ul><li>Submit one or more Pull Requests (PRs) to the <a href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io">Jina</a> repository that enables providing a built-in Executor UI for Executors. </li><li>The UI can be built using Gradio and should be able to infer information about the Executor service using type annotations.</li></ul><h3 id="2-docarray-wrap-ann-libraries">2. <a href="https://github.com/jina-ai/GSoC/issues/17?ref=jina-ai-gmbh.ghost.io">DocArray wrap ANN libraries</a></h3><table role="table" style="box-sizing: border-box; border-spacing: 0px; border-collapse: collapse; margin-top: 0px; margin-bottom: 16px; display: block; width: max-content; max-width: 100%; overflow: auto; color: rgb(36, 41, 47); font-family: -apple-system, &quot;system-ui&quot;, &quot;Segoe UI&quot;, &quot;Noto Sans&quot;, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><thead style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">Info</th><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">details</th></tr></thead><tbody style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Skills needed</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Python, ANN Search experience</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Project size</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">175 hours</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Difficulty level</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Medium</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Mentors</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">@<a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Johannes Messner</a>, @<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Sami Jaghouar</a>, @<a href="https://www.linkedin.com/in/philipvollet?ref=jina-ai-gmbh.ghost.io" rel="nofollow" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none; margin-bottom: 0px;">Philip Vollet</a></td></tr></tbody></table><p><strong>Project Description:</strong></p><p>In DocArray, we have been concentrating on developing production-ready Vector DBs for large-scale searches. However, there are many ANN libraries without scalability layers that can be integrated into DocArray, making it accessible to academia and production teams with small-to-medium amounts of data, without the need for external services.</p><p>DocArray v2 will have a concept called Document Index. This is an abstraction that lets a user store their Documents (on disk or in a database), and retrieve them using ANN search. As such, there can be multiple Document Indexes backed by different backends: Elastic, Qdrant, Weaviate, etc, but all following the same basic API.</p><p>The idea behind this project is to take an ANN library and use it to implement a Document Index. There is already an implementation using HNSWLib that you can find here: <a href="https://github.com/docarray/docarray/pull/1124?ref=jina-ai-gmbh.ghost.io">feat: hnswlib document index</a>, But there is space to create similar backends using other libraries: Annoy, Faiss, etc. The goal is to provide user choice.</p><p>If there is interest, someone could also implement a backend using a vector database. We already have Qdrant, Weaviate, and Elastic covered, but Milvus, Redis, and some others could also be interesting. You can find a design doc for Document Index <a href="https://lightning-scent-57a.notion.site/Document-Stores-v2-design-doc-f11d6fe6ecee43f49ef88e0f1bf80b7f?ref=jina-ai-gmbh.ghost.io" rel="nofollow">here</a>.</p><p><strong>Expected Outcomes:</strong></p><ul><li>We have a set of Document Store implementations in DocArray that support the most popular ANN libraries, such as FAISS, Annoy, and Hnswlib.</li></ul><h3 id="3-research-about-deploying-llm-with-jina">3. <a href="https://github.com/jina-ai/GSoC/issues/18?ref=jina-ai-gmbh.ghost.io">Research about deploying LLM with Jina</a></h3><table role="table" style="box-sizing: border-box; border-spacing: 0px; border-collapse: collapse; margin-top: 0px; margin-bottom: 16px; display: block; width: max-content; max-width: 100%; overflow: auto; color: rgb(36, 41, 47); font-family: -apple-system, &quot;system-ui&quot;, &quot;Segoe UI&quot;, &quot;Noto Sans&quot;, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><thead style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">info</th><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">details</th></tr></thead><tbody style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Skills needed</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Python, Pytorch, CUDA, Docker, Kubernetes</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Project size</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">350 hours</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Difficulty level</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Hard</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Mentors</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">@<a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Alaeddine Abdessalem</a>, @<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none; margin-bottom: 0px;">Joan Martínez</a></td></tr></tbody></table><p><strong>Project Description: </strong></p><p>This project aims to demonstrate the capability of deploying and scaling Large Language Models (LLMs) using Jina. LLMs have gained significant attention for their ability to generate text and solve various tasks. However, deploying LLMs requires technologies to enable scalability when using GPU resources. This project will assess the capability of deploying LLMs with Jina and explore integrations with existing libraries such as <a href="https://github.com/microsoft/DeepSpeed?ref=jina-ai-gmbh.ghost.io">DeepSpeed</a>, <a href="https://github.com/FMInference/FlexGen?ref=jina-ai-gmbh.ghost.io">Accelerate</a>, and <a href="https://github.com/FMInference/FlexGen?ref=jina-ai-gmbh.ghost.io">FlexGen</a> that provide optimizations for model deployment. The goal is to build demos and showcases hosting LLMs using Jina and the integrated libraries. This will demonstrate Jina's ability to deploy and scale LLMs in a cost-efficient manner.</p><p><strong>Expected Outcomes: </strong></p><ul><li>Implementation of LLM deployment using Jina and assessing scalability with GPU resources.</li><li>Documentation and example code demonstrating the use of Jina for LLM deployment and inference.</li><li>Building integrations with the mentioned libraries in order to use them within Jina.</li><li>Evaluation of the cost-efficiency of deploying and scaling LLMs with Jina compared to other technologies.</li></ul><h3 id="4-expand-annlite-capabilities-with-bm25-to-build-hybrid-search">4. <a href="https://github.com/jina-ai/GSoC/issues/19?ref=jina-ai-gmbh.ghost.io">Expand ANNLite capabilities with BM25 to build Hybrid Search</a></h3><table role="table" style="box-sizing: border-box; border-spacing: 0px; border-collapse: collapse; margin-top: 0px; margin-bottom: 16px; display: block; width: max-content; max-width: 100%; overflow: auto; color: rgb(36, 41, 47); font-family: -apple-system, &quot;system-ui&quot;, &quot;Segoe UI&quot;, &quot;Noto Sans&quot;, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><thead style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">info</th><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">details</th></tr></thead><tbody style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Skills needed</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Python, C++, Lucene, ANN, Inverted Index</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Project size</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">350 hours</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Difficulty level</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Hard</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Mentors</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">@<a href="https://github.com/numb3r3?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Felix Wang</a><span>&nbsp;</span>@<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Joan Martínez</a><span>&nbsp;</span>@<a href="https://github.com/girishc13?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none; margin-bottom: 0px;">Girish Chandrashekar</a></td></tr></tbody></table><p><strong>Project Description: </strong></p><p>This project aims to evaluate and implement <a href="https://jina.ai/news/hype-and-hybrids-multimodal-search-means-more-than-keywords-and-vectors-2/?ref=jina-ai-gmbh.ghost.io">Hybrid Search</a> approaches on top of <a href="https://github.com/jina-ai/annlite?ref=jina-ai-gmbh.ghost.io">ANNLite</a>, a Vector search library developed by Jina using <a href="https://github.com/naver/splade?ref=jina-ai-gmbh.ghost.io">HNSW</a> as the algorithm for searches. The incorporation of <a href="https://www.elastic.co/blog/practical-bm25-part-2-the-bm25-algorithm-and-its-variables?ref=jina-ai-gmbh.ghost.io" rel="nofollow">BM25</a> and Hybrid Search will enable Jina to create scalable solutions for Hybrid Search in the cloud. While ANNLite allows the filtering of documents, combining Vector Search algorithms with traditional text-search ones will help improve performance in search systems. Through this project, we will investigate the benefits of Hybrid Search and try to deploy it with ANNLite to create powerful default search solutions for Jina.</p><p><strong>Expected Outcomes: </strong></p><ul><li>ANNLite is ready to be used as a default library to solve Hybrid Search applications.</li></ul><h3 id="5-make-annlite-the-go-to-vector-search-library-to-be-scaled-by-jina-using-the-statefulexecutor-feature">5. <a href="https://github.com/jina-ai/GSoC/issues/20?ref=jina-ai-gmbh.ghost.io">Make ANNLite the go-to Vector Search library to be scaled by Jina using the StatefulExecutor feature</a></h3><table role="table" style="box-sizing: border-box; border-spacing: 0px; border-collapse: collapse; margin-top: 0px; margin-bottom: 16px; display: block; width: max-content; max-width: 100%; overflow: auto; color: rgb(36, 41, 47); font-family: -apple-system, &quot;system-ui&quot;, &quot;Segoe UI&quot;, &quot;Noto Sans&quot;, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><thead style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">info</th><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">details</th></tr></thead><tbody style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Skills needed</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">ANN, C++, Python, Databases</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Project size</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">350 hours</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Difficulty level</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Hard</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Mentors</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">@<a href="https://github.com/numb3r3?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none;">Felix Wang</a><span>&nbsp;</span>@<a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none; margin-bottom: 0px;">Joan Martínez</a></td></tr></tbody></table><p><strong>Project Description: </strong></p><p>Jina is developing a stateful Executor feature that enables Deployments with a state to be replicated and scaled. This opens the door to having a Vector Database in our ecosystem effectively and robustly. Iterating on ANNLite to act as the "Lucene" for Jina would be a great opportunity.</p><p><strong>Expected Outcomes: </strong></p><ul><li>Prove and come up with an Executor in our <a href="https://cloud.jina.ai/executors?ref=jina-ai-gmbh.ghost.io">Executor Hub</a> that uses ANNlite or DocArray with ANNLite as a backend to be the default Vector Databases for all our examples for mid-sized data requirements.</li></ul><h3 id="6-jax-support-in-docarray-v2">6. <a href="https://github.com/jina-ai/GSoC/issues/21?ref=jina-ai-gmbh.ghost.io">JAX support in DocArray v2</a></h3><table role="table" style="box-sizing: border-box; border-spacing: 0px; border-collapse: collapse; margin-top: 0px; margin-bottom: 16px; display: block; width: max-content; max-width: 100%; overflow: auto; color: rgb(36, 41, 47); font-family: -apple-system, &quot;system-ui&quot;, &quot;Segoe UI&quot;, &quot;Noto Sans&quot;, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;; font-size: 14px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><thead style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">Info</th><th style="box-sizing: border-box; padding: 6px 13px; font-weight: var(--base-text-weight-semibold, 600); border: 1px solid var(--color-border-default);">details</th></tr></thead><tbody style="box-sizing: border-box;"><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Skills needed</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Python, Deep Learning, JAX</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Project size</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">175 hours</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-default); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Difficulty level</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Hard</td></tr><tr style="box-sizing: border-box; background-color: var(--color-canvas-subtle); border-top: 1px solid var(--color-border-muted);"><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">Mentors</td><td style="box-sizing: border-box; padding: 6px 13px; border: 1px solid var(--color-border-default);">@<a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io" style="box-sizing: border-box; background-color: transparent; color: var(--color-accent-fg); text-decoration: none; margin-bottom: 0px;">Sami Jaghouar</a></td></tr></tbody></table><p><strong>Project Description: </strong></p><p>DocArray is a library for representing, sending, and storing multi-modal data, with a focus on applications in Machine Learning and Neural Search. It currently supports several deep learning frameworks, including <a href="https://cloud.jina.ai/executors?ref=jina-ai-gmbh.ghost.io">PyTorch and TensorFlow</a>. <a href="https://jax.readthedocs.io/?ref=jina-ai-gmbh.ghost.io">Google JAX</a> is becoming increasingly popular for deep learning, so we want to integrate it into DocArray.</p><p>The project we propose is to add JAX as a backend for DocArray, alongside PyTorch and TensorFlow. The first part would involve rewriting and translating all of the computational backend functions of DocArray with the JAX framework. Then, we would battle-test the implementation against a real JAX use case, such as integrating DocArray with JAX support for model training and serving.</p><p><strong>Expected Outcomes: </strong></p><ul><li>We aim to provide JAX with the same level of support in DocArray as we do for PyTorch, Numpy, and TensorFlow. The integration should be thoroughly tested and documented.</li></ul><h2 id="meet-the-jina-ai-mentor-team">Meet the Jina AI mentor team</h2><ul><li><a href="https://github.com/JoanFM?ref=jina-ai-gmbh.ghost.io">Joan Martínez</a>, Head of Engineering</li><li><a href="https://github.com/numb3r3?ref=jina-ai-gmbh.ghost.io">Felix Wang</a>, Engineering Manager</li><li><a href="https://www.linkedin.com/in/philipvollet?ref=jina-ai-gmbh.ghost.io">Philip Vollet</a>, Head of Developer Experience</li><li><a href="https://github.com/girishc13?ref=jina-ai-gmbh.ghost.io">Girish Chandrashekar</a>, Senior Software Engineer</li><li><a href="https://github.com/JohannesMessner?ref=jina-ai-gmbh.ghost.io">Johannes Messner</a>, Senior Software Engineer</li><li><a href="https://github.com/samsja?ref=jina-ai-gmbh.ghost.io">Sami Jaghouar</a>, Senior Software Engineer</li><li><a href="https://github.com/alaeddine-13?ref=jina-ai-gmbh.ghost.io">Alaeddine Abdessalem</a>, Software Engineer</li></ul><h2 id="how-to-apply-for-jina-ais-gsoc">How to apply for Jina AI's GSoC</h2><ol><li>Read through <a href="https://github.com/jina-ai/gsoc?ref=jina-ai-gmbh.ghost.io">Jina AI's GSoC</a> page and <a href="https://google.github.io/gsocguides/student/?ref=jina-ai-gmbh.ghost.io">Google Summer of Code guides</a>.</li><li>Identify project ideas on <a href="https://github.com/jina-ai/gsoc/issues?ref=jina-ai-gmbh.ghost.io">Jina AI's GSoC issues.</a></li><li>Fill out the <a href="https://10sw1tcpld4.typeform.com/to/chrdIltW?ref=jina-ai-gmbh.ghost.io">Survey</a> so mentors can understand your background and relevant experience.</li><li>Interact with the <a href="https://jina.ai/community/?ref=jina-ai-gmbh.ghost.io">Jina community</a>: join channels, introduce yourself, ask thoughtful questions, and help others with issues you have experience with.</li><li>Try out the project ideas: Try on the local environment, Read the <a href="https://docs.jina.ai/?ref=jina-ai-gmbh.ghost.io">documentation</a>, Reproduce <a href="https://jina.ai/news/?tag=tech-blog&amp;ref=jina-ai-gmbh.ghost.io">tech blogs' examples</a> to get hands-on experience, Solve issues you encounter, and Ask questions if stuck.</li><li>Make contributions: Try to fix some <a href="https://github.com/docarray/docarray/issues?q=is%3Aissue+is%3Aopen&amp;ref=jina-ai-gmbh.ghost.io">good first issues</a>, write tutorials, or share interesting projects you build with Jina or DocArray.</li><li>Preparing a well-crafted proposal aligned with project goals. Submit applications through <a href="Google's application system">Google's system</a> from March 20 to April 4.</li></ol><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/timeline.png" class="kg-image" alt="" width="2000" height="2288" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/timeline.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/timeline.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/03/timeline.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/timeline.png 2000w" sizes="(min-width: 720px) 720px"><figcaption><a href="https://summerofcode.withgoogle.com/organizations/jina-ai-sb/programs/2023/timeline?ref=jina-ai-gmbh.ghost.io">Timeline</a></figcaption></figure><h2 id="gsoc-x-jina-ai-webinar">GSoC x Jina AI Webinar</h2><p>We will be hosting a <a href="https://www.meetup.com/jina-community-meetup/events/292210036/?ref=jina-ai-gmbh.ghost.io">GSoC x Jina AI webinar</a> on March 23rd, 14:00-15:00 PM (CET). Join us as our experienced mentors provide an overview of their GSoC projects and answer any questions you have about the project requirements and expectations. This is a great opportunity for students, developers, and tech enthusiasts to learn more about these exciting projects and get involved in the open-source community.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.meetup.com/jina-community-meetup/events/292210036/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">From Idea to Reality: Dive into Jina AI’s GSoC projects, Thu, Mar 23, 2023, 2:00 PM | Meetup</div><div class="kg-bookmark-description">👋 Google Summer of Code (GSoC) is an annual program that offers students the opportunity to work on open-source projects with experienced mentors. [Jina AI](https://github</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://secure.meetupstatic.com/next/images/general/m_swarm_196x196.png" alt=""><span class="kg-bookmark-author">Meetup</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://secure.meetupstatic.com/photos/event/d/8/c/1/600_511315489.jpeg" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fjoin-jina-ai-for-multimodal-ai-innovation-through-gsoc-2023%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Langchain-serve: Bringing LangChain Apps Closer to Your Users</title><meta charset="utf-8"><meta name="title" content="Langchain-serve: Bringing LangChain Apps Closer to Your Users"><meta name="description" content="Langchain-serve makes deployment and delivery of LangChain apps simple, taking one less hassle out of producing your AI applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/langchain-serve-bringing-langchain-apps-closer-to-your-users"><meta property="og:title" content="Langchain-serve: Bringing LangChain Apps Closer to Your Users"><meta property="og:description" content="Langchain-serve makes deployment and delivery of LangChain apps simple, taking one less hassle out of producing your AI applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_3cN_qz9pICgmDlpubzMLIw.webp"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/langchain-serve-bringing-langchain-apps-closer-to-your-users"><meta property="twitter:title" content="Langchain-serve: Bringing LangChain Apps Closer to Your Users"><meta property="twitter:description" content="Langchain-serve makes deployment and delivery of LangChain apps simple, taking one less hassle out of producing your AI applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_3cN_qz9pICgmDlpubzMLIw.webp"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="73122ef7-835c-46b5-a47e-b120ed76ff2e" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="73122ef7-835c-46b5-a47e-b120ed76ff2e" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Langchain-serve: Bringing LangChain Apps Closer to Your Users</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Langchain-serve makes deployment and delivery of LangChain apps simple, taking one less hassle out of producing your AI applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/deepankar.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Deepankar Mahapatro, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 27, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>It is exciting to witness the growing community of developers building innovative, sophisticated LLM-powered applications using LangChain. This dynamic ecosystem promotes rapid development and innovation and also unveils unlimited potential for a wide array of use cases.</p><p>Amidst this, <strong><strong>Langchain-serve</strong></strong> plays an important role by making LangChain applications readily available and accessible to end-users. It streamlines deployment and delivery for LangChain applications and makes it easy for application developers to reach their target audience.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/langchain-serve?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-description">⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀 - GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/087bd996b490447dee3e56163ebe3116d1a8f433589968ceae25747de28f6934/jina-ai/langchain-serve" alt=""></div></a></figure><h2 id="features">Features</h2><p>With Langchain-serve, deploying and distributing LangChain applications becomes a breeze. It has a feature set designed to streamline the deployment process:</p><ul><li><strong><strong>API Management</strong></strong>: Define your APIs in Python using the <code>@serving</code> decorator, ensuring a secure interaction with Bearer tokens. This seamlessly integrates your local LangChain applications with external applications, broadening its reach and functionality.</li><li><strong><strong>LLM-powered Slack Bots</strong></strong>: Build, deploy, and distribute Slack bots thanks to the simple <code>@slackbot</code> decorator. This puts your LangChain application where your users are, providing them with access to your application within their Slack workspace.</li><li><strong><strong>Interactivity and Collaboration</strong></strong>: Enable real-time interactions with LLMs via WebSockets, optionally keeping humans in the loop.</li><li><strong><strong>FastAPI Integration</strong></strong>: Wrap your LangChain apps with FastAPI endpoints and deploy them with a single command.</li></ul><p>Furthermore, <strong>Langchain-serve takes care of all your infrastructure headaches</strong>, enabling you to focus solely on developing and refining your applications.</p><ul><li><strong><strong>Secure and Scalable</strong></strong>: Enjoy secure, serverless, scalable, and highly available applications on <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">Jina AI Cloud</a>.</li><li><strong><strong>Hardware Configuration</strong></strong>: Easily configure the hardware resources for your application with a single command.</li><li><strong><strong>Persistent Storage</strong></strong>: Use the built-in persistent storage for LLM caching, file storage, and more.</li><li><strong><strong>Observability</strong></strong>: Monitor your applications with built-in logs, metrics, and traces.</li><li><strong>Availability: </strong>Your app remains responsive and available, regardless of the traffic volume.</li></ul><p>Alternatively, you can<strong><strong> </strong>s<strong>elf-host your apps</strong>.</strong> With a single command, you can export your apps as Kubernetes or Docker Compose YAMLs so that you can host your applications on your own infrastructure.</p><h2 id="langchain-serve-in-action">Langchain-serve in action</h2><p>Before diving into the examples, please make sure you have the <code>langchain-serve</code> package installed. It is available as a PyPI package and you can install it with <code>pip</code>:</p><pre><code class="language-bash hljs">pip install langchain-serve</code></pre><p>Now, let’s see how to quickly deploy a simple LangChain agent as an HTTP endpoint with some examples of building and deploying Slack bots. These examples provide a practical demonstration of Langchain-serve's features and show you how straightforward it is to get your LangChain applications up and running.</p><h2 id="wrap-and-deploy-a-simple-agent-as-a-restful-api">Wrap and deploy a simple agent as a RESTful API</h2><p>Let’s start with a simple example using <code>ZeroShotAgent</code> with a <code>Search</code> tool to ask a question. We will use the <code>@serving</code> decorator to define a <code>POST /ask </code>endpoint that accepts an <code>input</code> parameter and returns an answer.</p><p>This involves four simple steps:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.4771 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_EGmaxmjPuQEOovOYrSD-4Q.webp" width="2000" height="1354" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_EGmaxmjPuQEOovOYrSD-4Q.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_EGmaxmjPuQEOovOYrSD-4Q.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/1_EGmaxmjPuQEOovOYrSD-4Q.webp 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/1_EGmaxmjPuQEOovOYrSD-4Q.webp 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.09529 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_iHH2qCU0sOo1kOfNdJTYmA.webp" width="2000" height="1826" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_iHH2qCU0sOo1kOfNdJTYmA.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_iHH2qCU0sOo1kOfNdJTYmA.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/1_iHH2qCU0sOo1kOfNdJTYmA.webp 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/1_iHH2qCU0sOo1kOfNdJTYmA.webp 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Before and After</figcaption></figure><ol><li>Refactor your code to one or more functions in a new file <code>app.py</code> and add the <code>@serving</code> decorator. (See above for an example.)</li><li>Create a <code>requirements.txt</code> file with all the dependencies.</li><li>Run <code>lc-serve deploy local app</code> to deploy and use the app locally.</li><li>Run <code>lc-serve deploy jcloud app</code> to deploy and use the app on <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">Jina AI Cloud</a>.</li></ol><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_P4l-Uo7FvLCJ1qXBDGvGsQ.webp" class="kg-image" alt="" width="1400" height="748" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_P4l-Uo7FvLCJ1qXBDGvGsQ.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_P4l-Uo7FvLCJ1qXBDGvGsQ.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_P4l-Uo7FvLCJ1qXBDGvGsQ.webp 1400w" sizes="(min-width: 720px) 720px"><figcaption>Usage example</figcaption></figure><p>The <code>@serving</code> decorator also enables real-time streaming and human-in-the-loop integration using WebSockets. Optionally, the endpoints can also be protected with bearer tokens for secure interactions. Follow the readme to go through more elaborate examples to deploy your LangChain APIs on Jina AI Cloud.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/langchain-serve?ref=jina-ai-gmbh.ghost.io#-langchain-apps-on-production-with-jina--fastapi-"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-description">⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀 - GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/087bd996b490447dee3e56163ebe3116d1a8f433589968ceae25747de28f6934/jina-ai/langchain-serve" alt=""></div></a></figure><h2 id="build-deploy-and-distribute-slack-bots">Build, deploy, and distribute Slack bots</h2><p>Slack has become an indispensable tool in many modern workplaces, helping teams to communicate and collaborate effectively. With the integration of LLM-powered Slack bots, you can infuse the reasoning power of LLMs into your workspace, providing rich contextual understanding and intelligent responses.</p><p>From moderator bots that enrich brainstorming sessions with the knowledge and reasoning capacity of LLMs, to project management bots that provide smart recommendations and summarize key points, the use cases for these Slack bots are endless. By leveraging LangChain and Langchain-serve, these bots can enhance the efficiency and productivity of digital workspaces.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.671537 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_sp10s1RCilbUSpztxA17NA.webp" width="1333" height="1985" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_sp10s1RCilbUSpztxA17NA.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_sp10s1RCilbUSpztxA17NA.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_sp10s1RCilbUSpztxA17NA.webp 1333w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.671537 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_xXvzwxqjyNjUgmU8X1hjNg.webp" width="1333" height="1985" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_xXvzwxqjyNjUgmU8X1hjNg.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_xXvzwxqjyNjUgmU8X1hjNg.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_xXvzwxqjyNjUgmU8X1hjNg.webp 1333w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.671537 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_mY2V90CD8C62bL5FarYS5A-1.webp" width="1333" height="1985" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_mY2V90CD8C62bL5FarYS5A-1.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_mY2V90CD8C62bL5FarYS5A-1.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_mY2V90CD8C62bL5FarYS5A-1.webp 1333w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.671537 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_HJY7n-GeIXJyEjhNUUArEQ-1.webp" width="1333" height="1985" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_HJY7n-GeIXJyEjhNUUArEQ-1.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_HJY7n-GeIXJyEjhNUUArEQ-1.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_HJY7n-GeIXJyEjhNUUArEQ-1.webp 1333w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>A brainstorming bot having elaborate discussions with a team to decide their platform strategy. Reading order: Top-left (1), top-right (2), bottom-left (3), bottom-right (4).</figcaption></figure><p>Langchain-serve provides a decorator <code>@slackbot</code> to help build and deploy Slack bots on <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">Jina AI Cloud</a>. Here’s a step-by-step guide that takes you through creating and configuring a Slack app and deploying a demo bot integrated with Langchain-serve:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/langchain-serve/tree/main/lcserve/apps/slackbot?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">langchain-serve/lcserve/apps/slackbot at main · jina-ai/langchain-serve</div><div class="kg-bookmark-description">⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀 - langchain-serve/lcserve/apps/slackbot at main · jina-ai/langchain-serve</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/087bd996b490447dee3e56163ebe3116d1a8f433589968ceae25747de28f6934/jina-ai/langchain-serve" alt=""></div></a></figure><p>Let’s delve deeper into the Slack bot demo code and understand how it works so you can modify it for custom applications. We’ll also go through the<code>@slackbot</code> decorator, as it shapes the bot’s behavior.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_j2ObJaLN_tZkfEupDyN_uw.webp" class="kg-image" alt="" width="1374" height="1638" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_j2ObJaLN_tZkfEupDyN_uw.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_j2ObJaLN_tZkfEupDyN_uw.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_j2ObJaLN_tZkfEupDyN_uw.webp 1374w" sizes="(min-width: 720px) 720px"><figcaption>A function decorated by <code>@slackbot</code> defines the entry point for the bot. This is expected to listen to two types of events: “app-mention” and “DM”</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_yeJTwz5SBMJeqWuDTNZvxw.webp" class="kg-image" alt="" width="1400" height="352" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_yeJTwz5SBMJeqWuDTNZvxw.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_yeJTwz5SBMJeqWuDTNZvxw.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_yeJTwz5SBMJeqWuDTNZvxw.webp 1400w" sizes="(min-width: 720px) 720px"><figcaption>Slack bot decorator arguments</figcaption></figure><p><strong><strong>Prompt: </strong></strong>We use a <a href="https://github.com/jina-ai/langchain-serve/blob/98a586254cfe0b01409a5ce7e6d4af23d57bff32/lcserve/backend/slackbot/slackbot.py?ref=jina-ai-gmbh.ghost.io#L303" rel="noopener ugc nofollow">predefined prompt template</a> to make the agent act as a Slack bot. This can be easily modified/extended to fit your application.</p><p><strong><strong>Memory: </strong></strong>Since Slack threads are routinely longer than the token limits for LLMs, we use <code>memory</code> modules defined in LangChain to store the conversation history. Langchain-serve's <a href="https://github.com/jina-ai/langchain-serve/blob/98a586254cfe0b01409a5ce7e6d4af23d57bff32/lcserve/backend/slackbot/memory.py?ref=jina-ai-gmbh.ghost.io#L29" rel="noopener ugc nofollow"><code>get_memory</code></a> function is designed to generate memory objects from a conversation history. However, you can also use custom memory objects like <a href="https://github.com/jerryjliu/llama_index/blob/main/examples/langchain_demo/LangchainDemo.ipynb?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">LlamaIndex's memory wrappers</a>.</p><p><strong><strong>Tools: </strong></strong>Likewise, we have a pre-defined tool for Slack: A <a href="https://github.com/jina-ai/langchain-serve/blob/98a586254cfe0b01409a5ce7e6d4af23d57bff32/lcserve/backend/slackbot/slackbot.py?ref=jina-ai-gmbh.ghost.io#L147" rel="noopener ugc nofollow">Slack thread parser</a> that extracts the conversation history from a thread URL. This is very useful when you share a different thread with the bot.</p><p><strong><strong>Workspace: </strong></strong>Every bot deployed on Jina AI Cloud gets a persistent storage path. This can be used to cache LLM calls to speed up the response time. This can also be used to store other files that the bot needs to access.</p><p><strong><strong>Reply: </strong></strong>The <code>reply</code> function is used to send a reply back to the user. It takes a single argument - <code>message</code> - which is the reply message to be sent to the user.</p><p>After customizing the bot to fit your needs, you can deploy it on Jina AI Cloud with the following command, where the <code>.env</code> should contain the Slack bot token, signing secret, and other required environment variables.</p><pre><code class="language-bash hljs">lc-serve deploy jcloud app --<span class="hljs-built_in">env</span> .<span class="hljs-built_in">env</span></code></pre><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_Ffg_qCBzqFl3qnV0ns5coQ.webp" class="kg-image" alt="" width="1400" height="507" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_Ffg_qCBzqFl3qnV0ns5coQ.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_Ffg_qCBzqFl3qnV0ns5coQ.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_Ffg_qCBzqFl3qnV0ns5coQ.webp 1400w" sizes="(min-width: 720px) 720px"><figcaption>Jina AI Cloud deployment log. The Slack Events URL here denotes the URL to be used as “Requests URL” in the Slack app configuration to enable event subscriptions for your bot.</figcaption></figure><p>Once the bot is integrated and tested in your workspace, it’s ready to be rolled out to the workspaces of your end users. For further information on how to distribute your bot globally, you can refer to this <a href="https://api.slack.com/start/distributing?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">guide</a>.</p><h2 id="looking-ahead">Looking ahead</h2><p>We’ve seen how Langchain-serve makes deploying LangChain applications a breeze. We’ve seen it in action, turning a simple agent into a RESTful API and transforming LLM-powered apps into interactive Slack bots. As we continue to evolve, our sights are set on the next milestone: bringing the intelligence of LangChain to Discord with <code>discordbot</code>.</p><p>We’re eager to see the diverse Slackbots and APIs you’ll be shipping for your users, bridging the gap between a local demo and practical, user-friendly applications that harness the full potential of LLMs in the real world.</p><h2 id="learn-more-about-langchain-serve">Learn more about Langchain-serve</h2><p>For more information about Langchain-serve, visit the <a href="https://github.com/jina-ai/langchain-serve?ref=jina-ai-gmbh.ghost.io">project page at GitHub</a>, and visit the <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI website</a> for more about the Jina ecosystem.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/langchain-serve?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-description">⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀 - GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/087bd996b490447dee3e56163ebe3116d1a8f433589968ceae25747de28f6934/jina-ai/langchain-serve" alt=""></div></a></figure><h2 id="get-in-touch">Get in touch</h2><p>Talk to us and keep the conversation going by joining the Jina AI Discord!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://discord.com/channels/1106542220112302130/1106544066692390942?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Jina AI Discord</a></div><p></p><p></p><p></p><p></p><p><br></p><p></p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Flangchain-serve-bringing-langchain-apps-closer-to-your-users%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Langchain-serve: Bringing LangChain Apps Closer to Your Users</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Langchain-serve makes deployment and delivery of LangChain apps simple, taking one less hassle out of producing your AI applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/deepankar.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Deepankar Mahapatro, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 27, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>It is exciting to witness the growing community of developers building innovative, sophisticated LLM-powered applications using LangChain. This dynamic ecosystem promotes rapid development and innovation and also unveils unlimited potential for a wide array of use cases.</p><p>Amidst this, <strong><strong>Langchain-serve</strong></strong> plays an important role by making LangChain applications readily available and accessible to end-users. It streamlines deployment and delivery for LangChain applications and makes it easy for application developers to reach their target audience.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/langchain-serve?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-description">⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀 - GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/087bd996b490447dee3e56163ebe3116d1a8f433589968ceae25747de28f6934/jina-ai/langchain-serve" alt=""></div></a></figure><h2 id="features">Features</h2><p>With Langchain-serve, deploying and distributing LangChain applications becomes a breeze. It has a feature set designed to streamline the deployment process:</p><ul><li><strong><strong>API Management</strong></strong>: Define your APIs in Python using the <code>@serving</code> decorator, ensuring a secure interaction with Bearer tokens. This seamlessly integrates your local LangChain applications with external applications, broadening its reach and functionality.</li><li><strong><strong>LLM-powered Slack Bots</strong></strong>: Build, deploy, and distribute Slack bots thanks to the simple <code>@slackbot</code> decorator. This puts your LangChain application where your users are, providing them with access to your application within their Slack workspace.</li><li><strong><strong>Interactivity and Collaboration</strong></strong>: Enable real-time interactions with LLMs via WebSockets, optionally keeping humans in the loop.</li><li><strong><strong>FastAPI Integration</strong></strong>: Wrap your LangChain apps with FastAPI endpoints and deploy them with a single command.</li></ul><p>Furthermore, <strong>Langchain-serve takes care of all your infrastructure headaches</strong>, enabling you to focus solely on developing and refining your applications.</p><ul><li><strong><strong>Secure and Scalable</strong></strong>: Enjoy secure, serverless, scalable, and highly available applications on <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">Jina AI Cloud</a>.</li><li><strong><strong>Hardware Configuration</strong></strong>: Easily configure the hardware resources for your application with a single command.</li><li><strong><strong>Persistent Storage</strong></strong>: Use the built-in persistent storage for LLM caching, file storage, and more.</li><li><strong><strong>Observability</strong></strong>: Monitor your applications with built-in logs, metrics, and traces.</li><li><strong>Availability: </strong>Your app remains responsive and available, regardless of the traffic volume.</li></ul><p>Alternatively, you can<strong><strong> </strong>s<strong>elf-host your apps</strong>.</strong> With a single command, you can export your apps as Kubernetes or Docker Compose YAMLs so that you can host your applications on your own infrastructure.</p><h2 id="langchain-serve-in-action">Langchain-serve in action</h2><p>Before diving into the examples, please make sure you have the <code>langchain-serve</code> package installed. It is available as a PyPI package and you can install it with <code>pip</code>:</p><pre><code class="language-bash hljs">pip install langchain-serve</code></pre><p>Now, let’s see how to quickly deploy a simple LangChain agent as an HTTP endpoint with some examples of building and deploying Slack bots. These examples provide a practical demonstration of Langchain-serve's features and show you how straightforward it is to get your LangChain applications up and running.</p><h2 id="wrap-and-deploy-a-simple-agent-as-a-restful-api">Wrap and deploy a simple agent as a RESTful API</h2><p>Let’s start with a simple example using <code>ZeroShotAgent</code> with a <code>Search</code> tool to ask a question. We will use the <code>@serving</code> decorator to define a <code>POST /ask </code>endpoint that accepts an <code>input</code> parameter and returns an answer.</p><p>This involves four simple steps:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.4771 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_EGmaxmjPuQEOovOYrSD-4Q.webp" width="2000" height="1354" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_EGmaxmjPuQEOovOYrSD-4Q.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_EGmaxmjPuQEOovOYrSD-4Q.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/1_EGmaxmjPuQEOovOYrSD-4Q.webp 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/1_EGmaxmjPuQEOovOYrSD-4Q.webp 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.09529 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_iHH2qCU0sOo1kOfNdJTYmA.webp" width="2000" height="1826" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_iHH2qCU0sOo1kOfNdJTYmA.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_iHH2qCU0sOo1kOfNdJTYmA.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/1_iHH2qCU0sOo1kOfNdJTYmA.webp 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/1_iHH2qCU0sOo1kOfNdJTYmA.webp 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Before and After</figcaption></figure><ol><li>Refactor your code to one or more functions in a new file <code>app.py</code> and add the <code>@serving</code> decorator. (See above for an example.)</li><li>Create a <code>requirements.txt</code> file with all the dependencies.</li><li>Run <code>lc-serve deploy local app</code> to deploy and use the app locally.</li><li>Run <code>lc-serve deploy jcloud app</code> to deploy and use the app on <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">Jina AI Cloud</a>.</li></ol><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_P4l-Uo7FvLCJ1qXBDGvGsQ.webp" class="kg-image" alt="" width="1400" height="748" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_P4l-Uo7FvLCJ1qXBDGvGsQ.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_P4l-Uo7FvLCJ1qXBDGvGsQ.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_P4l-Uo7FvLCJ1qXBDGvGsQ.webp 1400w" sizes="(min-width: 720px) 720px"><figcaption>Usage example</figcaption></figure><p>The <code>@serving</code> decorator also enables real-time streaming and human-in-the-loop integration using WebSockets. Optionally, the endpoints can also be protected with bearer tokens for secure interactions. Follow the readme to go through more elaborate examples to deploy your LangChain APIs on Jina AI Cloud.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/langchain-serve?ref=jina-ai-gmbh.ghost.io#-langchain-apps-on-production-with-jina--fastapi-"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-description">⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀 - GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/087bd996b490447dee3e56163ebe3116d1a8f433589968ceae25747de28f6934/jina-ai/langchain-serve" alt=""></div></a></figure><h2 id="build-deploy-and-distribute-slack-bots">Build, deploy, and distribute Slack bots</h2><p>Slack has become an indispensable tool in many modern workplaces, helping teams to communicate and collaborate effectively. With the integration of LLM-powered Slack bots, you can infuse the reasoning power of LLMs into your workspace, providing rich contextual understanding and intelligent responses.</p><p>From moderator bots that enrich brainstorming sessions with the knowledge and reasoning capacity of LLMs, to project management bots that provide smart recommendations and summarize key points, the use cases for these Slack bots are endless. By leveraging LangChain and Langchain-serve, these bots can enhance the efficiency and productivity of digital workspaces.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.671537 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_sp10s1RCilbUSpztxA17NA.webp" width="1333" height="1985" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_sp10s1RCilbUSpztxA17NA.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_sp10s1RCilbUSpztxA17NA.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_sp10s1RCilbUSpztxA17NA.webp 1333w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.671537 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_xXvzwxqjyNjUgmU8X1hjNg.webp" width="1333" height="1985" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_xXvzwxqjyNjUgmU8X1hjNg.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_xXvzwxqjyNjUgmU8X1hjNg.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_xXvzwxqjyNjUgmU8X1hjNg.webp 1333w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.671537 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_mY2V90CD8C62bL5FarYS5A-1.webp" width="1333" height="1985" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_mY2V90CD8C62bL5FarYS5A-1.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_mY2V90CD8C62bL5FarYS5A-1.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_mY2V90CD8C62bL5FarYS5A-1.webp 1333w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.671537 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_HJY7n-GeIXJyEjhNUUArEQ-1.webp" width="1333" height="1985" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_HJY7n-GeIXJyEjhNUUArEQ-1.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_HJY7n-GeIXJyEjhNUUArEQ-1.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_HJY7n-GeIXJyEjhNUUArEQ-1.webp 1333w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>A brainstorming bot having elaborate discussions with a team to decide their platform strategy. Reading order: Top-left (1), top-right (2), bottom-left (3), bottom-right (4).</figcaption></figure><p>Langchain-serve provides a decorator <code>@slackbot</code> to help build and deploy Slack bots on <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">Jina AI Cloud</a>. Here’s a step-by-step guide that takes you through creating and configuring a Slack app and deploying a demo bot integrated with Langchain-serve:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/langchain-serve/tree/main/lcserve/apps/slackbot?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">langchain-serve/lcserve/apps/slackbot at main · jina-ai/langchain-serve</div><div class="kg-bookmark-description">⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀 - langchain-serve/lcserve/apps/slackbot at main · jina-ai/langchain-serve</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/087bd996b490447dee3e56163ebe3116d1a8f433589968ceae25747de28f6934/jina-ai/langchain-serve" alt=""></div></a></figure><p>Let’s delve deeper into the Slack bot demo code and understand how it works so you can modify it for custom applications. We’ll also go through the<code>@slackbot</code> decorator, as it shapes the bot’s behavior.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_j2ObJaLN_tZkfEupDyN_uw.webp" class="kg-image" alt="" width="1374" height="1638" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_j2ObJaLN_tZkfEupDyN_uw.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_j2ObJaLN_tZkfEupDyN_uw.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_j2ObJaLN_tZkfEupDyN_uw.webp 1374w" sizes="(min-width: 720px) 720px"><figcaption>A function decorated by <code>@slackbot</code> defines the entry point for the bot. This is expected to listen to two types of events: “app-mention” and “DM”</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_yeJTwz5SBMJeqWuDTNZvxw.webp" class="kg-image" alt="" width="1400" height="352" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_yeJTwz5SBMJeqWuDTNZvxw.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_yeJTwz5SBMJeqWuDTNZvxw.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_yeJTwz5SBMJeqWuDTNZvxw.webp 1400w" sizes="(min-width: 720px) 720px"><figcaption>Slack bot decorator arguments</figcaption></figure><p><strong><strong>Prompt: </strong></strong>We use a <a href="https://github.com/jina-ai/langchain-serve/blob/98a586254cfe0b01409a5ce7e6d4af23d57bff32/lcserve/backend/slackbot/slackbot.py?ref=jina-ai-gmbh.ghost.io#L303" rel="noopener ugc nofollow">predefined prompt template</a> to make the agent act as a Slack bot. This can be easily modified/extended to fit your application.</p><p><strong><strong>Memory: </strong></strong>Since Slack threads are routinely longer than the token limits for LLMs, we use <code>memory</code> modules defined in LangChain to store the conversation history. Langchain-serve's <a href="https://github.com/jina-ai/langchain-serve/blob/98a586254cfe0b01409a5ce7e6d4af23d57bff32/lcserve/backend/slackbot/memory.py?ref=jina-ai-gmbh.ghost.io#L29" rel="noopener ugc nofollow"><code>get_memory</code></a> function is designed to generate memory objects from a conversation history. However, you can also use custom memory objects like <a href="https://github.com/jerryjliu/llama_index/blob/main/examples/langchain_demo/LangchainDemo.ipynb?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">LlamaIndex's memory wrappers</a>.</p><p><strong><strong>Tools: </strong></strong>Likewise, we have a pre-defined tool for Slack: A <a href="https://github.com/jina-ai/langchain-serve/blob/98a586254cfe0b01409a5ce7e6d4af23d57bff32/lcserve/backend/slackbot/slackbot.py?ref=jina-ai-gmbh.ghost.io#L147" rel="noopener ugc nofollow">Slack thread parser</a> that extracts the conversation history from a thread URL. This is very useful when you share a different thread with the bot.</p><p><strong><strong>Workspace: </strong></strong>Every bot deployed on Jina AI Cloud gets a persistent storage path. This can be used to cache LLM calls to speed up the response time. This can also be used to store other files that the bot needs to access.</p><p><strong><strong>Reply: </strong></strong>The <code>reply</code> function is used to send a reply back to the user. It takes a single argument - <code>message</code> - which is the reply message to be sent to the user.</p><p>After customizing the bot to fit your needs, you can deploy it on Jina AI Cloud with the following command, where the <code>.env</code> should contain the Slack bot token, signing secret, and other required environment variables.</p><pre><code class="language-bash hljs">lc-serve deploy jcloud app --<span class="hljs-built_in">env</span> .<span class="hljs-built_in">env</span></code></pre><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_Ffg_qCBzqFl3qnV0ns5coQ.webp" class="kg-image" alt="" width="1400" height="507" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1_Ffg_qCBzqFl3qnV0ns5coQ.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/1_Ffg_qCBzqFl3qnV0ns5coQ.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1_Ffg_qCBzqFl3qnV0ns5coQ.webp 1400w" sizes="(min-width: 720px) 720px"><figcaption>Jina AI Cloud deployment log. The Slack Events URL here denotes the URL to be used as “Requests URL” in the Slack app configuration to enable event subscriptions for your bot.</figcaption></figure><p>Once the bot is integrated and tested in your workspace, it’s ready to be rolled out to the workspaces of your end users. For further information on how to distribute your bot globally, you can refer to this <a href="https://api.slack.com/start/distributing?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">guide</a>.</p><h2 id="looking-ahead">Looking ahead</h2><p>We’ve seen how Langchain-serve makes deploying LangChain applications a breeze. We’ve seen it in action, turning a simple agent into a RESTful API and transforming LLM-powered apps into interactive Slack bots. As we continue to evolve, our sights are set on the next milestone: bringing the intelligence of LangChain to Discord with <code>discordbot</code>.</p><p>We’re eager to see the diverse Slackbots and APIs you’ll be shipping for your users, bridging the gap between a local demo and practical, user-friendly applications that harness the full potential of LLMs in the real world.</p><h2 id="learn-more-about-langchain-serve">Learn more about Langchain-serve</h2><p>For more information about Langchain-serve, visit the <a href="https://github.com/jina-ai/langchain-serve?ref=jina-ai-gmbh.ghost.io">project page at GitHub</a>, and visit the <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI website</a> for more about the Jina ecosystem.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/langchain-serve?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-description">⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀 - GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/087bd996b490447dee3e56163ebe3116d1a8f433589968ceae25747de28f6934/jina-ai/langchain-serve" alt=""></div></a></figure><h2 id="get-in-touch">Get in touch</h2><p>Talk to us and keep the conversation going by joining the Jina AI Discord!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://discord.com/channels/1106542220112302130/1106544066692390942?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Jina AI Discord</a></div><p></p><p></p><p></p><p></p><p><br></p><p></p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Flangchain-serve-bringing-langchain-apps-closer-to-your-users%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>LangChain-serve: Powering your Slack with LangChain</title><meta charset="utf-8"><meta name="title" content="LangChain-serve: Powering your Slack with LangChain"><meta name="description" content="Langchain-serve makes deployment and delivery of LangChain apps simple, taking one less hassle out of producing your AI applications."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/langchain-serve-powering-your-slack-with-langchain"><meta property="og:title" content="LangChain-serve: Powering your Slack with LangChain"><meta property="og:description" content="Langchain-serve makes deployment and delivery of LangChain apps simple, taking one less hassle out of producing your AI applications."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/1_DCu2jG_kw7R8f1h86BAdeQ.webp"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/langchain-serve-powering-your-slack-with-langchain"><meta property="twitter:title" content="LangChain-serve: Powering your Slack with LangChain"><meta property="twitter:description" content="Langchain-serve makes deployment and delivery of LangChain apps simple, taking one less hassle out of producing your AI applications."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/1_DCu2jG_kw7R8f1h86BAdeQ.webp"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">LangChain-serve: Powering your Slack with LangChain</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Langchain-serve makes deployment and delivery of LangChain apps simple, taking one less hassle out of producing your AI applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/deepankar.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Deepankar Mahapatro, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 06, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Slack is an essential tool for business that has transformed the way teams communicate and collaborate. Introducing LangChain-powered chatbots adds a layer of intelligence to your Slack workspace. These bots don’t just passively respond to commands. They’re like virtual colleagues, capable of understanding context and providing useful feedback.</p><p>LangChain-powered chatbots are more than just message handlers. They are like an interactive consultant, fielding questions about your company’s internal data, and putting a wealth of information at your fingertips. The result? A workspace that’s not just connected, but also informed, fostering a more engaged and knowledgeable team.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/langchain-serve?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-description">⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀 - GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/7342025836ed5851d33c2ae5fe8f11fe1c2ea6fd7981067f72b1e8faa4a9020b/jina-ai/langchain-serve" alt=""></div></a></figure><p>As a starting point, you can download a demo chatbot from Langchain-serve's repository. Follow <a href="https://github.com/jina-ai/langchain-serve/tree/main/lcserve/apps/slackbot?ref=jina-ai-gmbh.ghost.io#-langchain-slack-bots-on-jina-ai-cloud" rel="noopener ugc nofollow">this step-by-step guide</a> to create an app in your workspace and deploy it to <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">Jina AI Cloud</a>. </p><pre><code class="language-bash hljs">pip install langchain-serve
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">LangChain-serve: Powering your Slack with LangChain</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Langchain-serve makes deployment and delivery of LangChain apps simple, taking one less hassle out of producing your AI applications.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/deepankar.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Deepankar Mahapatro, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 06, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Slack is an essential tool for business that has transformed the way teams communicate and collaborate. Introducing LangChain-powered chatbots adds a layer of intelligence to your Slack workspace. These bots don’t just passively respond to commands. They’re like virtual colleagues, capable of understanding context and providing useful feedback.</p><p>LangChain-powered chatbots are more than just message handlers. They are like an interactive consultant, fielding questions about your company’s internal data, and putting a wealth of information at your fingertips. The result? A workspace that’s not just connected, but also informed, fostering a more engaged and knowledgeable team.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/langchain-serve?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-description">⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀 - GitHub - jina-ai/langchain-serve: ⚡ Langchain Apps on Production with Jina &amp; FastAPI 🚀</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/7342025836ed5851d33c2ae5fe8f11fe1c2ea6fd7981067f72b1e8faa4a9020b/jina-ai/langchain-serve" alt=""></div></a></figure><p>As a starting point, you can download a demo chatbot from Langchain-serve's repository. Follow <a href="https://github.com/jina-ai/langchain-serve/tree/main/lcserve/apps/slackbot?ref=jina-ai-gmbh.ghost.io#-langchain-slack-bots-on-jina-ai-cloud" rel="noopener ugc nofollow">this step-by-step guide</a> to create an app in your workspace and deploy it to <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">Jina AI Cloud</a>. </p><pre><code class="language-bash hljs">pip install langchain-serve
 <span class="hljs-built_in">echo</span> <span class="hljs-string">'SLACK_SIGNING_SECRET=&lt;your-signing-secret&gt;'</span> &gt;&gt; .<span class="hljs-built_in">env</span>
 <span class="hljs-built_in">echo</span> <span class="hljs-string">'SLACK_BOT_TOKEN=&lt;your-bot-token&gt;'</span> &gt;&gt; .<span class="hljs-built_in">env</span>
 <span class="hljs-built_in">echo</span> <span class="hljs-string">'OPENAI_API_TOKEN=&lt;your-openai-api-token&gt;'</span> &gt;&gt; .<span class="hljs-built_in">env</span>
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Supercharge Your LangChain Workflow with Jina AI’s Inference: Seamless Integration for Powerful Applications</title><meta charset="utf-8"><meta name="title" content="Supercharge Your LangChain Workflow with Jina AI’s Inference: Seamless Integration for Powerful Applications"><meta name="description" content="How Jina AI's Inference integrates with LangChain, allowing developers to build cutting-edge applications with ease"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/langchain_jina_inference"><meta property="og:title" content="Supercharge Your LangChain Workflow with Jina AI’s Inference: Seamless Integration for Powerful Applications"><meta property="og:description" content="How Jina AI's Inference integrates with LangChain, allowing developers to build cutting-edge applications with ease"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Blog-images--2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/langchain_jina_inference"><meta property="twitter:title" content="Supercharge Your LangChain Workflow with Jina AI’s Inference: Seamless Integration for Powerful Applications"><meta property="twitter:description" content="How Jina AI's Inference integrates with LangChain, allowing developers to build cutting-edge applications with ease"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Blog-images--2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Supercharge Your LangChain Workflow with Jina AI’s Inference: Seamless Integration for Powerful Applications</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">How Jina AI's Inference integrates with LangChain, allowing developers to build cutting-edge applications with ease</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 121.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/profile-option-2.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/fwang.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Saahil Ognawala, Felix Wang</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 03, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP) and opened up a myriad of possibilities for various applications. With the recent rise in popularity of the <a href="https://langchain.readthedocs.io/en/latest/index.html?ref=jina-ai-gmbh.ghost.io">LangChain framework</a>, developers are now able to create powerful end-to-end user-facing applications by chaining different steps in a workflow.</p><p>In this blog post, we'll show how <a href="https://cloud.jina.ai/user/inference?ref=jina-ai-gmbh.ghost.io">Jina AI's Inference</a>, a robust SaaS serving highly curated models for the most common machine learning tasks, <a href="https://python.langchain.com/en/latest/ecosystem/jina.html?ref=jina-ai-gmbh.ghost.io">seamlessly integrates</a> with LangChain, allowing developers to build cutting-edge applications with unparalleled ease.</p><h2 id="langchain-and-inference-a-match-made-in-heaven">LangChain and Inference: A match made in heaven</h2><p>Given the enormous value proposition of LangChain in terms of ease of use across several use cases, we are proud to announce that Inference is now fully compatible with LangChain. Existing users that have already created Inference APIs can, starting now, completely integrate these APIs into their LangChain workflow, and enjoy numerous benefits, including:</p><ol><li><strong>Simplified workflow</strong>: By integrating Inference with LangChain, developers can easily access and utilize the power of <a href="https://cloud.jina.ai/user/inference/model/63dca9df5a0da83009d519cd?ref=jina-ai-gmbh.ghost.io">CLIP</a> embeddings without having to train or deploy neural networks. This reduces time spent on complex setup and management.</li><li><strong>Scalability</strong>: Inference allows developers to generate embeddings for their input documents on demand, ensuring that their applications can scale with ease.</li><li><strong>Flexibility</strong>: The compatibility between Inference and LangChain enables developers to mix and match different components in their applications. This allows for the creation of customized solutions tailored to specific needs.</li><li><strong>Cost-effective</strong>: With Inference’s highly competitive <a href="https://cloud.jina.ai/pricing?ref=jina-ai-gmbh.ghost.io">pay-per-document pricing model</a>, developers only pay for the embeddings they generate, making it a cost-effective option for projects of any size.</li></ol><h2 id="invoking-inference-from-langchain-extracting-passages-from-a-pdf-document">Invoking Inference from LangChain: Extracting passages from a PDF document</h2><p>Follow the steps below to create a simple application that processes text from a PDF document, generates embeddings using Inference, and uses them to extract the most relevant passages from the document given a user’s question:</p><p>Follow the steps below to create a simple application that processes text from a PDF document, generates embeddings using Inference, and uses them to extract the most relevant passages from the document given a user’s question:</p><h3 id="step-1-sign-up-on-jina-ai-cloud">Step 1: Sign up on Jina AI Cloud</h3><p>Visit <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a> to sign up. </p><h3 id="step-2-generate-a-new-token">Step 2: Generate a new token</h3><p>If you’re a first-time user of Inference, you will need a personalized user token that you can create under the <a href="https://cloud.jina.ai/settings/tokens?ref=jina-ai-gmbh.ghost.io">Tokens section</a> . You will need this token in step 7. </p><h3 id="step-3-create-an-inference-api">Step 3: Create an Inference API</h3><p>You can now create a personalized <a href="https://cloud.jina.ai/user/inference?ref=jina-ai-gmbh.ghost.io">Inference API</a> from the several models and variants offered on our platform. Before creating an API, you can try out the several tasks supported by a model, such as CLIP.<br><br>Click on a model type, e.g. CLIP, then click on <code>Details</code> to see technical details of the provided models and their variants.<br><br>Click on <code>Create</code> on the top right of the details page, to start the creation process. <br><br>Enter the name of your API, e.g. “<code>my-first-inference-api</code>”. <br><br>Now, based on your requirements for <a href="https://clip-as-service.jina.ai/user-guides/benchmark/?ref=jina-ai-gmbh.ghost.io">query throughput and encoding performance</a>, select a model variant such as <code>ViT-B-32::openai</code>. You will use the name of this model in step 7. <br><br>Finally, click on <code>Create</code>.</p><h3 id="step-4-install-packages">Step 4: Install packages</h3><p>To get started, you’ll need to install the required packages for LangChain and Jina AI’s Inference. The following command will install these packages for you:</p><pre><code class="language-bash hljs">pip install <span class="hljs-string">"langchain&gt;=0.0.124"</span> jina==3.14.1 chromadb unstructured</code></pre><p><a href="https://www.trychroma.com/?ref=jina-ai-gmbh.ghost.io">Chroma</a> is an in-memory vector database, that is especially useful for this tutorial because it means you don’t need to have a running installation of a vector database on your system or remotely.</p><h3 id="step-5-import-libraries">Step 5: Import libraries</h3><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> langchain.embeddings <span class="hljs-keyword">import</span> JinaEmbeddings
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Supercharge Your LangChain Workflow with Jina AI’s Inference: Seamless Integration for Powerful Applications</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">How Jina AI's Inference integrates with LangChain, allowing developers to build cutting-edge applications with ease</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 121.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/profile-option-2.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/fwang.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Saahil Ognawala, Felix Wang</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 03, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP) and opened up a myriad of possibilities for various applications. With the recent rise in popularity of the <a href="https://langchain.readthedocs.io/en/latest/index.html?ref=jina-ai-gmbh.ghost.io">LangChain framework</a>, developers are now able to create powerful end-to-end user-facing applications by chaining different steps in a workflow.</p><p>In this blog post, we'll show how <a href="https://cloud.jina.ai/user/inference?ref=jina-ai-gmbh.ghost.io">Jina AI's Inference</a>, a robust SaaS serving highly curated models for the most common machine learning tasks, <a href="https://python.langchain.com/en/latest/ecosystem/jina.html?ref=jina-ai-gmbh.ghost.io">seamlessly integrates</a> with LangChain, allowing developers to build cutting-edge applications with unparalleled ease.</p><h2 id="langchain-and-inference-a-match-made-in-heaven">LangChain and Inference: A match made in heaven</h2><p>Given the enormous value proposition of LangChain in terms of ease of use across several use cases, we are proud to announce that Inference is now fully compatible with LangChain. Existing users that have already created Inference APIs can, starting now, completely integrate these APIs into their LangChain workflow, and enjoy numerous benefits, including:</p><ol><li><strong>Simplified workflow</strong>: By integrating Inference with LangChain, developers can easily access and utilize the power of <a href="https://cloud.jina.ai/user/inference/model/63dca9df5a0da83009d519cd?ref=jina-ai-gmbh.ghost.io">CLIP</a> embeddings without having to train or deploy neural networks. This reduces time spent on complex setup and management.</li><li><strong>Scalability</strong>: Inference allows developers to generate embeddings for their input documents on demand, ensuring that their applications can scale with ease.</li><li><strong>Flexibility</strong>: The compatibility between Inference and LangChain enables developers to mix and match different components in their applications. This allows for the creation of customized solutions tailored to specific needs.</li><li><strong>Cost-effective</strong>: With Inference’s highly competitive <a href="https://cloud.jina.ai/pricing?ref=jina-ai-gmbh.ghost.io">pay-per-document pricing model</a>, developers only pay for the embeddings they generate, making it a cost-effective option for projects of any size.</li></ol><h2 id="invoking-inference-from-langchain-extracting-passages-from-a-pdf-document">Invoking Inference from LangChain: Extracting passages from a PDF document</h2><p>Follow the steps below to create a simple application that processes text from a PDF document, generates embeddings using Inference, and uses them to extract the most relevant passages from the document given a user’s question:</p><p>Follow the steps below to create a simple application that processes text from a PDF document, generates embeddings using Inference, and uses them to extract the most relevant passages from the document given a user’s question:</p><h3 id="step-1-sign-up-on-jina-ai-cloud">Step 1: Sign up on Jina AI Cloud</h3><p>Visit <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a> to sign up. </p><h3 id="step-2-generate-a-new-token">Step 2: Generate a new token</h3><p>If you’re a first-time user of Inference, you will need a personalized user token that you can create under the <a href="https://cloud.jina.ai/settings/tokens?ref=jina-ai-gmbh.ghost.io">Tokens section</a> . You will need this token in step 7. </p><h3 id="step-3-create-an-inference-api">Step 3: Create an Inference API</h3><p>You can now create a personalized <a href="https://cloud.jina.ai/user/inference?ref=jina-ai-gmbh.ghost.io">Inference API</a> from the several models and variants offered on our platform. Before creating an API, you can try out the several tasks supported by a model, such as CLIP.<br><br>Click on a model type, e.g. CLIP, then click on <code>Details</code> to see technical details of the provided models and their variants.<br><br>Click on <code>Create</code> on the top right of the details page, to start the creation process. <br><br>Enter the name of your API, e.g. “<code>my-first-inference-api</code>”. <br><br>Now, based on your requirements for <a href="https://clip-as-service.jina.ai/user-guides/benchmark/?ref=jina-ai-gmbh.ghost.io">query throughput and encoding performance</a>, select a model variant such as <code>ViT-B-32::openai</code>. You will use the name of this model in step 7. <br><br>Finally, click on <code>Create</code>.</p><h3 id="step-4-install-packages">Step 4: Install packages</h3><p>To get started, you’ll need to install the required packages for LangChain and Jina AI’s Inference. The following command will install these packages for you:</p><pre><code class="language-bash hljs">pip install <span class="hljs-string">"langchain&gt;=0.0.124"</span> jina==3.14.1 chromadb unstructured</code></pre><p><a href="https://www.trychroma.com/?ref=jina-ai-gmbh.ghost.io">Chroma</a> is an in-memory vector database, that is especially useful for this tutorial because it means you don’t need to have a running installation of a vector database on your system or remotely.</p><h3 id="step-5-import-libraries">Step 5: Import libraries</h3><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> langchain.embeddings <span class="hljs-keyword">import</span> JinaEmbeddings
 <span class="hljs-keyword">from</span> langchain.vectorstores <span class="hljs-keyword">import</span> Chroma
 <span class="hljs-keyword">from</span> langchain.text_splitter <span class="hljs-keyword">import</span> CharacterTextSplitter
 <span class="hljs-keyword">from</span> langchain.document_loaders <span class="hljs-keyword">import</span> UnstructuredPDFLoader
diff --git a/news/look-up-in-the-sky-using-scenexplain-to-classify-land-use-from-satellite-data/index.html b/news/look-up-in-the-sky-using-scenexplain-to-classify-land-use-from-satellite-data/index.html
index 9b1fa8edd13..85662534a9d 100644
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@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Look, Up in the Sky! Using SceneXplain To Classify Land Use From Satellite Data</title><meta charset="utf-8"><meta name="title" content="Look, Up in the Sky! Using SceneXplain To Classify Land Use From Satellite Data"><meta name="description" content="Unlock the Secrets of the Satellites: Leverage SceneXplain's powerful 'Extract JSON from Image' feature for land use classification"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/look-up-in-the-sky-using-scenexplain-to-classify-land-use-from-satellite-data"><meta property="og:title" content="Look, Up in the Sky! Using SceneXplain To Classify Land Use From Satellite Data"><meta property="og:description" content="Unlock the Secrets of the Satellites: Leverage SceneXplain's powerful 'Extract JSON from Image' feature for land use classification"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Release-banner-DocArray.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/look-up-in-the-sky-using-scenexplain-to-classify-land-use-from-satellite-data"><meta property="twitter:title" content="Look, Up in the Sky! Using SceneXplain To Classify Land Use From Satellite Data"><meta property="twitter:description" content="Unlock the Secrets of the Satellites: Leverage SceneXplain's powerful 'Extract JSON from Image' feature for land use classification"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Release-banner-DocArray.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Look, Up in the Sky! Using SceneXplain To Classify Land Use From Satellite Data</title><meta charset="utf-8"><meta name="title" content="Look, Up in the Sky! Using SceneXplain To Classify Land Use From Satellite Data"><meta name="description" content="Unlock the Secrets of the Satellites: Leverage SceneXplain's powerful 'Extract JSON from Image' feature for land use classification"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/look-up-in-the-sky-using-scenexplain-to-classify-land-use-from-satellite-data"><meta property="og:title" content="Look, Up in the Sky! Using SceneXplain To Classify Land Use From Satellite Data"><meta property="og:description" content="Unlock the Secrets of the Satellites: Leverage SceneXplain's powerful 'Extract JSON from Image' feature for land use classification"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Release-banner-DocArray.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/look-up-in-the-sky-using-scenexplain-to-classify-land-use-from-satellite-data"><meta property="twitter:title" content="Look, Up in the Sky! Using SceneXplain To Classify Land Use From Satellite Data"><meta property="twitter:description" content="Unlock the Secrets of the Satellites: Leverage SceneXplain's powerful 'Extract JSON from Image' feature for land use classification"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Release-banner-DocArray.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Using SceneXplain To Classify Land Use From Satellite Data</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Unlock the Secrets of the Satellites: Leverage SceneXplain's powerful 'Extract JSON from Image' feature for land use classification</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 06, 2023 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Is it a bird? Is it a plane? Is it a dense residential area? Or maybe even a chaparral? Worry not readers. SceneXplain is here to let you know. We don't even have to jump into a phone booth to change first.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">🌱</div><div class="kg-callout-text">A <a href="https://en.wikipedia.org/wiki/Chaparral?ref=jina-ai-gmbh.ghost.io">chaparral</a> is a shrubland plant community found primarily in California, in southern Oregon and in the northern portion of the Baja California Peninsula in Mexico. <br><br>You'll see why this is relevant later.</div></div><p>In this blog post, we'll talk about our experiments using SceneXplain to look at satellite imagery and classify it based on what the land is used for. We'll go through three different datasets and explain how we did what we did.</p><h2 id="what-is-land-use-classification-and-what-is-it-used-for">What is land use classification and what is it used for?</h2><p>Using satellite data for classifying land use involves working out what a section of the Earth is used for, such as agriculture, city, forest, or body of water. The focus here is on using optical satellite imagery as the data source, which is then analyzed through AI image models to determine the land use. It's often used for:</p><ul><li>Resource Management: Knowing how land is being used aids in allocating and managing resources, such as water for irrigation.</li><li>Urban Planning: Good land use maps are invaluable to city planners so that they can know what types of land use exist in and around urban areas to make informed decisions on infrastructure development.</li><li>Environmental Protection: By identifying sensitive or critical ecological zones, conservationists can better protect and manage them.</li><li>Disaster Management: Land use classification can help to identify vulnerable areas that require priority during emergencies.</li><li>Climate Change Studies: Monitoring land use over time can offer insights into climate change impacts, such as the rate of deforestation.</li><li>Research and Education: Scientists and educators across disciplines use this data for various kinds of research, from ecology to social sciences.</li></ul><h2 id="up-up-and-away-how-we-classify-land-usage-in-scenexplain">Up, up, and away! How we classify land usage in SceneXplain</h2><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">🐍</div><div class="kg-callout-text">You can find a link to the notebook <a href="https://colab.research.google.com/github/alexcg1/scenex-geospatial/blob/main/notebook.ipynb?ref=jina-ai-gmbh.ghost.io">here</a>.</div></div><h3 id="datasets">Datasets</h3><p>We used three datasets for our testing:</p><ul><li><a href="http://weegee.vision.ucmerced.edu/datasets/landuse.html?ref=jina-ai-gmbh.ghost.io">UC Merced land use classification</a></li><li><a href="https://captain-whu.github.io/AID/?ref=jina-ai-gmbh.ghost.io">AID (Aerial Image Dataset)</a></li><li><a href="https://www.tensorflow.org/datasets/catalog/resisc45?ref=jina-ai-gmbh.ghost.io">RESISC45 (Remote Sensing Image Scene Classification)</a></li></ul><p>Each of these consists of satellite and aerial images of different sections of Earth, labeled by what they are used for, e.g. <code>dense_residential</code>, <code>round_farm</code>, <code>intersection</code>, etc.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/airport_10.jpg" width="600" height="600" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/2023/11/airport_10.jpg 600w"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/denseresidential10.jpg" width="256" height="256" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/chaparral_010.jpg" width="256" height="256" alt=""></div></div></div><figcaption><p><code spellcheck="false" style="white-space: pre-wrap;"><span>airport</span></code><span style="white-space: pre-wrap;"> from AID dataset, </span><code spellcheck="false" style="white-space: pre-wrap;"><span>denseresidential</span></code><span style="white-space: pre-wrap;"> from UC Merced dataset, </span><code spellcheck="false" style="white-space: pre-wrap;"><span>chaparral</span></code><span style="white-space: pre-wrap;"> from RESISC45 dataset</span></p></figcaption></figure><h3 id="scenexplain">SceneXplain</h3><p>We used SceneXplain's <a href="https://www.notion.so/Look-Up-in-the-Sky-Using-SceneXplain-To-Classify-Land-Use-From-Satellite-Data-e46f7ee6e503425fba837e09fb03b26f?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">"Extract JSON from image" feature</a> with the Flash algorithm to extract one label per input image. After testing with several algorithms, we saw the Flash algorithm offered the fastest performance, and precision on par with more recent algorithms like <a href="https://www.notion.so/Look-Up-in-the-Sky-Using-SceneXplain-To-Classify-Land-Use-From-Satellite-Data-e46f7ee6e503425fba837e09fb03b26f?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">Jelly</a>.</p><p>Rather than manually uploading each image via the web UI, we used SceneXplain's API to upload and analyze images one at a time.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">We could speed this up by (ab)using SceneXplain's cid feature when batching and giving each image a unique ID. The ID would contain the image's "official" category, so (after processing) we could extract that and compare it to the category assigned by SceneXplain.</div></div><h3 id="json-schema">JSON Schema</h3><p>Why even use a JSON schema? Why not just let SceneXplain interpret the images directly? Say, by looking at an aerial view of a baseball diamond from the UC Merced dataset?</p><p>Here's why:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--39-.png" class="kg-image" alt="" width="441" height="666"><figcaption><a href="https://scenex.jina.ai/share?thread=qjW5p1gZBYK2HONbNsOE&amp;ref=jina-ai-gmbh.ghost.io" rel="noreferrer"><span style="white-space: pre-wrap;">Link to this scene on SceneXplain</span></a></figcaption></figure><p>It’s a clear description, but nowhere does it mention <code>baseballdiamond</code>, which (since we’re doing classification) is the label we want.</p><p>We could also try asking it a question using visual question answering (VQA):</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--40-.png" class="kg-image" alt="" width="444" height="798"><figcaption><a href="https://scenex.jina.ai/share?thread=VW4xcmLawvG8lWInwwAa&amp;ref=jina-ai-gmbh.ghost.io" rel="noreferrer"><span style="white-space: pre-wrap;">Link to this scene on SceneXplain</span></a></figcaption></figure><p>That answer is slightly better, but still throws in a lot more superfluous words. If we were to bulk classify images using this method we would have to search each answer for the category label, since there would be no consistent wording between them. And what would happen if an image were ambiguous and SceneXplain tried to assign it two categories or more?</p><p>For this reason, we used SceneXplain’s “<a href="https://jina.ai/news/scenexplains-image-json-extract-structured-data-images-precision/?ref=jina-ai-gmbh.ghost.io">Extract JSON from image</a>” feature, where we specify a JSON Schema and can thus get highly structured, standardized output:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--41-.png" class="kg-image" alt="" width="612" height="1389" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/Untitled--41-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--41-.png 612w"><figcaption><a href="https://scenex.jina.ai/share?thread=agnPj7H47wl87kDiEjM6&amp;ref=jina-ai-gmbh.ghost.io" rel="noreferrer"><span style="white-space: pre-wrap;">Link to this scene on SceneXplain</span></a></figcaption></figure><p>We used the following JSON schema:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
-  <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"object"</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-attr">"properties"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-    <span class="hljs-attr">"category"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-      <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"array"</span><span class="hljs-punctuation">,</span>
-      <span class="hljs-attr">"description"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"Which single main category of geospatial imagery does this image belong to?"</span><span class="hljs-punctuation">,</span>
-      <span class="hljs-attr">"enum"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span>&lt;categories from dataset&gt;<span class="hljs-punctuation">]</span><span class="hljs-punctuation">,</span>
-      <span class="hljs-attr">"maxContains"</span><span class="hljs-punctuation">:</span> <span class="hljs-number">1</span>
-    <span class="hljs-punctuation">}</span>
-  <span class="hljs-punctuation">}</span>
-<span class="hljs-punctuation">}</span>
-</code></pre><p>Since each dataset has different (albeit similar) categories, we generated the list dynamically for each dataset.</p><h2 id="does-it-work">Does it work?</h2><p>Sometimes! Like at least 60% of the time! In some randomized tests we got close to 80% (or occasionally as low as 50%).</p><p>Several factors can cause it to fail:</p><ul><li>Some categories can look very similar, e.g. <code>sparse_residential</code>, <code>medium_residential</code>, <code>dense_residential</code>. SceneXplain often picks the wrong one. This can also be seen in cases like <code>road</code> vs <code>runway</code>.</li><li>Occasionally it hallucinates a new category not specified in the <code>enum</code>, for example <code>residential</code> (as opposed to <code>denseresidential</code>). Occasionally it glitches and assigns a category like <code>A</code>.</li><li>Some category names like <code>chaparral</code> are uncommon words and/or concepts. It seems unlikely that many pictures of (or references to) chaparrals are in its training datasets. With so little data, the model barely knows what a chaparral is or what it looks like. (Before reading this post, did you?)</li><li>Aerial view geospatial images are under-represented in the training corpora relative to other images. This means that to a general-purpose tool like SceneXplain, an aerial view of a chaparral may look more like mold or dirt on a surface.</li></ul><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--42-.png" width="1200" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/Untitled--42-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/Untitled--42-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--42-.png 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/chaparral01.jpg" width="256" height="256" alt=""></div></div></div><figcaption><p><span style="white-space: pre-wrap;">One of these is mold. The other is chaparral. Sorry, California.</span></p></figcaption></figure><h2 id="why-not-use-a-dedicated-model">Why not use a dedicated model?</h2><p>Most land-use classification is indeed done with dedicated models, specifically trained on aerial-view land use imagery. This makes them perfect for that particular task while not being so hot at general image classification.</p><p>So, why not just use one of those?</p><h3 id="self-hosting-is-a-drag">Self-hosting is a drag</h3><p>Even self-hosting something like Resnet (which has <a href="https://awsdocs-neuron.readthedocs-hosted.com/en/latest/src/examples/pytorch/torch-neuronx/resnet50-inference-on-trn1-tutorial.html?ref=jina-ai-gmbh.ghost.io">decent tutorials</a>) is a drag. You need to set up AWS, install dependencies, compile the model, and so on. It’s not as easy as using an existing software-as-a-service like SceneXplain.</p><h3 id="academic-models-are-pure-kryptonite">Academic models are pure kryptonite</h3><p>Let's look at the <a href="https://captain-whu.github.io/AID/?ref=jina-ai-gmbh.ghost.io">AID dataset</a> and see how we can replicate what they did in their paper:</p><p>First of all, we have to download the code from OneDrive or Baidu Pan. Dang, the file no longer exists on OneDrive, and Baidu Pan wants me to install a random RPM or DEB file just to download the dataset. Blech.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--43-.png" class="kg-image" alt="" width="1238" height="602" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/Untitled--43-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/Untitled--43-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--43-.png 1238w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Parents: Please check your children's Halloween candy. I just found a Baidu Pan installation RPM in my kid's bag. Disgusting.</span></figcaption></figure><p>Assuming we have a friend in China who downloads the code and sends it to us (thanks Kelly!), we can extract it and check the <code>readme.txt</code> (Did you assume the readme would be in a repo somewhere, you sweet innocent summer child?)</p><p>Checking the file dates with <code>ls -l</code>, we see the files were last modified in 2016. Great.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--44-.png" class="kg-image" alt="" width="741" height="338" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/Untitled--44-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--44-.png 741w" sizes="(min-width: 720px) 720px"></figure><p>Now we download the pre-trained model from the <a href="https://www.vlfeat.org/matconvnet/pretrained/?ref=jina-ai-gmbh.ghost.io">URL in the readme</a>. Good news! The link works! Bad news! There are lots of CNNs there and the readme doesn't say which one to download!</p><p>To quote the readme, the next step is to: <code>Compile vlfeat, gist, matconvnet and liblinear, and place them under &lt;libs&gt;</code>. We didn't actually try this, but I'm <em>sure</em> compiling software from over five years ago will go without a hitch. I just need to use version...um. There's no version specified. It's sheer dumb luck I guess!</p><p>The final step: We've put so much work into the other steps that now we can finally reap the fruits of our labor. We just need to install MatLab. Which is 860 EUR per year. Wonderful.</p><p>I'm sure setting up the model was worth the effort for whoever wrote the paper. But if I'm just trying things out, that's a lot of work and money.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💢</div><div class="kg-callout-text">On the verge of giving up, I checked the directory structure of the code. Reading the readme, I assumed I had to <i><em class="italic" style="white-space: pre-wrap;">download</em></i> the libs. But the libs folder already exists. Already (supposedly) populated with what I need. Turns out I can't even trust the readme (or perhaps myself, to be honest)</div></div><h3 id="i-got-ninety-nine-problems-but-a-chaparral-aint-one">I got ninety-nine problems, but a chaparral ain't one</h3><p>Even assuming pre-trained models were simple to use, the categories are baked in already. Since most of the training data was (I assume) taken from California, chaparrals are all over the place, but there aren't so many medieval castles. So if I wanted to apply the same model to Europe, I'd be stuck with those categories.</p><p>On the other hand, SceneXplain is a general-purpose tool. This means it may not have extensive chaparral knowledge (seriously, outside of Californians, who among us does?), but it has enough general-purpose knowledge that it can more reliably classify what you're specifically looking for.</p><p>Let's just say that specialist data can be kryptonite to a general-purpose image classification/captioning model. AI models aren’t (and can’t be) all things to all people, after all.</p><p>When you think of the data used to train general-purpose image models, very little would be aerial views of the landscape taken from satellites and labels for such data (<code>road</code>, <code>residential</code>, etc.) would far more commonly be applied to pictures of those phenomena taken from a more human-centric angle.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.5 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--45-.png" width="1125" height="750" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/Untitled--45-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/Untitled--45-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--45-.png 1125w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/denseresidential10-1.jpg" width="256" height="256" alt=""></div></div></div><figcaption><p><span style="white-space: pre-wrap;">Dense residential (L: How it's represented in most models, R: how it's represented in UC Merced dataset)</span></p></figcaption></figure><h2 id="why-not-use-scenexplain">Why NOT use SceneXplain?</h2><p>While using dedicated models has its downsides, there are some advantages:</p><h3 id="you-only-care-about-chaparrals">You only care about chaparrals</h3><p>Good for you buddy. Good for you.</p><h3 id="scenexplain-isnt-as-accurate-as-pre-trained-models">SceneXplain isn't as accurate as pre-trained models</h3><p>While a pain to set up, pre-trained models offer superior accuracy when it comes to this very specific domain. Those models were trained specifically on aerial imagery and thus offer accuracy rates of 85-95% when using high-level methods (see final table in the <a href="https://captain-whu.github.io/AID/?ref=jina-ai-gmbh.ghost.io">AID dataset paper</a>), compared to SceneXplain's accuracy of about 60%.</p><h2 id="next-steps">Next steps</h2><p>Large language models and image-to-text models aren’t specially trained to recognize landscape types from satellite imagery. There’s enough in their training data to make a stab at it, and it’s not totally useless, but zero-shot detection is just not good. Some categories are (by their nature) going to be tough to recognize, even for a human. If we can’t tell from 30,000 feet how many people live on a city block, then how could we expect SceneXplain to tell <code>sparseresidential</code> from <code>mediumresidential</code>?</p><p>Specially trained and fine-tuned models perform well enough to be a hard bar to beat.</p><p>But often you hit upon a problem that <strong>doesn’t</strong> have a specialized dataset that can be used for training a dedicated model. That means that a general-purpose tool, like SceneXplain, may be your best bet. Our next steps are trying to see how much better we can make SceneX with the least effort, so that our users can always get the best performance possible for the least added effort.</p><p>Even if no one ever uses SceneXplain to catalog land use, learning to make it better at this task teaches us how to make it better for something else that it’s never specially learned to do.</p><p>To test out SceneXplain for our own use case, create a free account and start playing! Let us know how you're doing on our <a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Discord</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Unlock the Secrets of the Satellites: Leverage SceneXplain's powerful 'Extract JSON from Image' feature for land use classification</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 06, 2023 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Is it a bird? Is it a plane? Is it a dense residential area? Or maybe even a chaparral? Worry not readers. SceneXplain is here to let you know. We don't even have to jump into a phone booth to change first.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">🌱</div><div class="kg-callout-text">A <a href="https://en.wikipedia.org/wiki/Chaparral?ref=jina-ai-gmbh.ghost.io">chaparral</a> is a shrubland plant community found primarily in California, in southern Oregon and in the northern portion of the Baja California Peninsula in Mexico. <br><br>You'll see why this is relevant later.</div></div><p>In this blog post, we'll talk about our experiments using SceneXplain to look at satellite imagery and classify it based on what the land is used for. We'll go through three different datasets and explain how we did what we did.</p><h2 id="what-is-land-use-classification-and-what-is-it-used-for">What is land use classification and what is it used for?</h2><p>Using satellite data for classifying land use involves working out what a section of the Earth is used for, such as agriculture, city, forest, or body of water. The focus here is on using optical satellite imagery as the data source, which is then analyzed through AI image models to determine the land use. It's often used for:</p><ul><li>Resource Management: Knowing how land is being used aids in allocating and managing resources, such as water for irrigation.</li><li>Urban Planning: Good land use maps are invaluable to city planners so that they can know what types of land use exist in and around urban areas to make informed decisions on infrastructure development.</li><li>Environmental Protection: By identifying sensitive or critical ecological zones, conservationists can better protect and manage them.</li><li>Disaster Management: Land use classification can help to identify vulnerable areas that require priority during emergencies.</li><li>Climate Change Studies: Monitoring land use over time can offer insights into climate change impacts, such as the rate of deforestation.</li><li>Research and Education: Scientists and educators across disciplines use this data for various kinds of research, from ecology to social sciences.</li></ul><h2 id="up-up-and-away-how-we-classify-land-usage-in-scenexplain">Up, up, and away! How we classify land usage in SceneXplain</h2><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">🐍</div><div class="kg-callout-text">You can find a link to the notebook <a href="https://colab.research.google.com/github/alexcg1/scenex-geospatial/blob/main/notebook.ipynb?ref=jina-ai-gmbh.ghost.io">here</a>.</div></div><h3 id="datasets">Datasets</h3><p>We used three datasets for our testing:</p><ul><li><a href="http://weegee.vision.ucmerced.edu/datasets/landuse.html?ref=jina-ai-gmbh.ghost.io">UC Merced land use classification</a></li><li><a href="https://captain-whu.github.io/AID/?ref=jina-ai-gmbh.ghost.io">AID (Aerial Image Dataset)</a></li><li><a href="https://www.tensorflow.org/datasets/catalog/resisc45?ref=jina-ai-gmbh.ghost.io">RESISC45 (Remote Sensing Image Scene Classification)</a></li></ul><p>Each of these consists of satellite and aerial images of different sections of Earth, labeled by what they are used for, e.g. <code>dense_residential</code>, <code>round_farm</code>, <code>intersection</code>, etc.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/airport_10.jpg" width="600" height="600" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/2023/11/airport_10.jpg 600w"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/denseresidential10.jpg" width="256" height="256" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/chaparral_010.jpg" width="256" height="256" alt=""></div></div></div><figcaption><p><code spellcheck="false" style="white-space: pre-wrap;"><span>airport</span></code><span style="white-space: pre-wrap;"> from AID dataset, </span><code spellcheck="false" style="white-space: pre-wrap;"><span>denseresidential</span></code><span style="white-space: pre-wrap;"> from UC Merced dataset, </span><code spellcheck="false" style="white-space: pre-wrap;"><span>chaparral</span></code><span style="white-space: pre-wrap;"> from RESISC45 dataset</span></p></figcaption></figure><h3 id="scenexplain">SceneXplain</h3><p>We used SceneXplain's <a href="https://www.notion.so/Look-Up-in-the-Sky-Using-SceneXplain-To-Classify-Land-Use-From-Satellite-Data-e46f7ee6e503425fba837e09fb03b26f?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">"Extract JSON from image" feature</a> with the Flash algorithm to extract one label per input image. After testing with several algorithms, we saw the Flash algorithm offered the fastest performance, and precision on par with more recent algorithms like <a href="https://www.notion.so/Look-Up-in-the-Sky-Using-SceneXplain-To-Classify-Land-Use-From-Satellite-Data-e46f7ee6e503425fba837e09fb03b26f?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">Jelly</a>.</p><p>Rather than manually uploading each image via the web UI, we used SceneXplain's API to upload and analyze images one at a time.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">We could speed this up by (ab)using SceneXplain's cid feature when batching and giving each image a unique ID. The ID would contain the image's "official" category, so (after processing) we could extract that and compare it to the category assigned by SceneXplain.</div></div><h3 id="json-schema">JSON Schema</h3><p>Why even use a JSON schema? Why not just let SceneXplain interpret the images directly? Say, by looking at an aerial view of a baseball diamond from the UC Merced dataset?</p><p>Here's why:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--39-.png" class="kg-image" alt="" width="441" height="666"><figcaption><a href="https://scenex.jina.ai/share?thread=qjW5p1gZBYK2HONbNsOE&amp;ref=jina-ai-gmbh.ghost.io" rel="noreferrer"><span style="white-space: pre-wrap;">Link to this scene on SceneXplain</span></a></figcaption></figure><p>It’s a clear description, but nowhere does it mention <code>baseballdiamond</code>, which (since we’re doing classification) is the label we want.</p><p>We could also try asking it a question using visual question answering (VQA):</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--40-.png" class="kg-image" alt="" width="444" height="798"><figcaption><a href="https://scenex.jina.ai/share?thread=VW4xcmLawvG8lWInwwAa&amp;ref=jina-ai-gmbh.ghost.io" rel="noreferrer"><span style="white-space: pre-wrap;">Link to this scene on SceneXplain</span></a></figcaption></figure><p>That answer is slightly better, but still throws in a lot more superfluous words. If we were to bulk classify images using this method we would have to search each answer for the category label, since there would be no consistent wording between them. And what would happen if an image were ambiguous and SceneXplain tried to assign it two categories or more?</p><p>For this reason, we used SceneXplain’s “<a href="https://jina.ai/news/scenexplains-image-json-extract-structured-data-images-precision/?ref=jina-ai-gmbh.ghost.io">Extract JSON from image</a>” feature, where we specify a JSON Schema and can thus get highly structured, standardized output:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--41-.png" class="kg-image" alt="" width="612" height="1389" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/Untitled--41-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--41-.png 612w"><figcaption><a href="https://scenex.jina.ai/share?thread=agnPj7H47wl87kDiEjM6&amp;ref=jina-ai-gmbh.ghost.io" rel="noreferrer"><span style="white-space: pre-wrap;">Link to this scene on SceneXplain</span></a></figcaption></figure><p>We used the following JSON schema:</p><pre><code class="language-json">{
+  "type": "object",
+  "properties": {
+    "category": {
+      "type": "array",
+      "description": "Which single main category of geospatial imagery does this image belong to?",
+      "enum": [&lt;categories from dataset&gt;],
+      "maxContains": 1
+    }
+  }
+}
+</code></pre><p>Since each dataset has different (albeit similar) categories, we generated the list dynamically for each dataset.</p><h2 id="does-it-work">Does it work?</h2><p>Sometimes! Like at least 60% of the time! In some randomized tests we got close to 80% (or occasionally as low as 50%).</p><p>Several factors can cause it to fail:</p><ul><li>Some categories can look very similar, e.g. <code>sparse_residential</code>, <code>medium_residential</code>, <code>dense_residential</code>. SceneXplain often picks the wrong one. This can also be seen in cases like <code>road</code> vs <code>runway</code>.</li><li>Occasionally it hallucinates a new category not specified in the <code>enum</code>, for example <code>residential</code> (as opposed to <code>denseresidential</code>). Occasionally it glitches and assigns a category like <code>A</code>.</li><li>Some category names like <code>chaparral</code> are uncommon words and/or concepts. It seems unlikely that many pictures of (or references to) chaparrals are in its training datasets. With so little data, the model barely knows what a chaparral is or what it looks like. (Before reading this post, did you?)</li><li>Aerial view geospatial images are under-represented in the training corpora relative to other images. This means that to a general-purpose tool like SceneXplain, an aerial view of a chaparral may look more like mold or dirt on a surface.</li></ul><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--42-.png" width="1200" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/Untitled--42-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/Untitled--42-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--42-.png 1200w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/chaparral01.jpg" width="256" height="256" alt=""></div></div></div><figcaption><p><span style="white-space: pre-wrap;">One of these is mold. The other is chaparral. Sorry, California.</span></p></figcaption></figure><h2 id="why-not-use-a-dedicated-model">Why not use a dedicated model?</h2><p>Most land-use classification is indeed done with dedicated models, specifically trained on aerial-view land use imagery. This makes them perfect for that particular task while not being so hot at general image classification.</p><p>So, why not just use one of those?</p><h3 id="self-hosting-is-a-drag">Self-hosting is a drag</h3><p>Even self-hosting something like Resnet (which has <a href="https://awsdocs-neuron.readthedocs-hosted.com/en/latest/src/examples/pytorch/torch-neuronx/resnet50-inference-on-trn1-tutorial.html?ref=jina-ai-gmbh.ghost.io">decent tutorials</a>) is a drag. You need to set up AWS, install dependencies, compile the model, and so on. It’s not as easy as using an existing software-as-a-service like SceneXplain.</p><h3 id="academic-models-are-pure-kryptonite">Academic models are pure kryptonite</h3><p>Let's look at the <a href="https://captain-whu.github.io/AID/?ref=jina-ai-gmbh.ghost.io">AID dataset</a> and see how we can replicate what they did in their paper:</p><p>First of all, we have to download the code from OneDrive or Baidu Pan. Dang, the file no longer exists on OneDrive, and Baidu Pan wants me to install a random RPM or DEB file just to download the dataset. Blech.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--43-.png" class="kg-image" alt="" width="1238" height="602" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/Untitled--43-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/Untitled--43-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--43-.png 1238w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Parents: Please check your children's Halloween candy. I just found a Baidu Pan installation RPM in my kid's bag. Disgusting.</span></figcaption></figure><p>Assuming we have a friend in China who downloads the code and sends it to us (thanks Kelly!), we can extract it and check the <code>readme.txt</code> (Did you assume the readme would be in a repo somewhere, you sweet innocent summer child?)</p><p>Checking the file dates with <code>ls -l</code>, we see the files were last modified in 2016. Great.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--44-.png" class="kg-image" alt="" width="741" height="338" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/Untitled--44-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--44-.png 741w" sizes="(min-width: 720px) 720px"></figure><p>Now we download the pre-trained model from the <a href="https://www.vlfeat.org/matconvnet/pretrained/?ref=jina-ai-gmbh.ghost.io">URL in the readme</a>. Good news! The link works! Bad news! There are lots of CNNs there and the readme doesn't say which one to download!</p><p>To quote the readme, the next step is to: <code>Compile vlfeat, gist, matconvnet and liblinear, and place them under &lt;libs&gt;</code>. We didn't actually try this, but I'm <em>sure</em> compiling software from over five years ago will go without a hitch. I just need to use version...um. There's no version specified. It's sheer dumb luck I guess!</p><p>The final step: We've put so much work into the other steps that now we can finally reap the fruits of our labor. We just need to install MatLab. Which is 860 EUR per year. Wonderful.</p><p>I'm sure setting up the model was worth the effort for whoever wrote the paper. But if I'm just trying things out, that's a lot of work and money.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💢</div><div class="kg-callout-text">On the verge of giving up, I checked the directory structure of the code. Reading the readme, I assumed I had to <i><em class="italic" style="white-space: pre-wrap;">download</em></i> the libs. But the libs folder already exists. Already (supposedly) populated with what I need. Turns out I can't even trust the readme (or perhaps myself, to be honest)</div></div><h3 id="i-got-ninety-nine-problems-but-a-chaparral-aint-one">I got ninety-nine problems, but a chaparral ain't one</h3><p>Even assuming pre-trained models were simple to use, the categories are baked in already. Since most of the training data was (I assume) taken from California, chaparrals are all over the place, but there aren't so many medieval castles. So if I wanted to apply the same model to Europe, I'd be stuck with those categories.</p><p>On the other hand, SceneXplain is a general-purpose tool. This means it may not have extensive chaparral knowledge (seriously, outside of Californians, who among us does?), but it has enough general-purpose knowledge that it can more reliably classify what you're specifically looking for.</p><p>Let's just say that specialist data can be kryptonite to a general-purpose image classification/captioning model. AI models aren’t (and can’t be) all things to all people, after all.</p><p>When you think of the data used to train general-purpose image models, very little would be aerial views of the landscape taken from satellites and labels for such data (<code>road</code>, <code>residential</code>, etc.) would far more commonly be applied to pictures of those phenomena taken from a more human-centric angle.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--45-.png" width="1125" height="750" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/Untitled--45-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/Untitled--45-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/Untitled--45-.png 1125w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/denseresidential10-1.jpg" width="256" height="256" alt=""></div></div></div><figcaption><p><span style="white-space: pre-wrap;">Dense residential (L: How it's represented in most models, R: how it's represented in UC Merced dataset)</span></p></figcaption></figure><h2 id="why-not-use-scenexplain">Why NOT use SceneXplain?</h2><p>While using dedicated models has its downsides, there are some advantages:</p><h3 id="you-only-care-about-chaparrals">You only care about chaparrals</h3><p>Good for you buddy. Good for you.</p><h3 id="scenexplain-isnt-as-accurate-as-pre-trained-models">SceneXplain isn't as accurate as pre-trained models</h3><p>While a pain to set up, pre-trained models offer superior accuracy when it comes to this very specific domain. Those models were trained specifically on aerial imagery and thus offer accuracy rates of 85-95% when using high-level methods (see final table in the <a href="https://captain-whu.github.io/AID/?ref=jina-ai-gmbh.ghost.io">AID dataset paper</a>), compared to SceneXplain's accuracy of about 60%.</p><h2 id="next-steps">Next steps</h2><p>Large language models and image-to-text models aren’t specially trained to recognize landscape types from satellite imagery. There’s enough in their training data to make a stab at it, and it’s not totally useless, but zero-shot detection is just not good. Some categories are (by their nature) going to be tough to recognize, even for a human. If we can’t tell from 30,000 feet how many people live on a city block, then how could we expect SceneXplain to tell <code>sparseresidential</code> from <code>mediumresidential</code>?</p><p>Specially trained and fine-tuned models perform well enough to be a hard bar to beat.</p><p>But often you hit upon a problem that <strong>doesn’t</strong> have a specialized dataset that can be used for training a dedicated model. That means that a general-purpose tool, like SceneXplain, may be your best bet. Our next steps are trying to see how much better we can make SceneX with the least effort, so that our users can always get the best performance possible for the least added effort.</p><p>Even if no one ever uses SceneXplain to catalog land use, learning to make it better at this task teaches us how to make it better for something else that it’s never specially learned to do.</p><p>To test out SceneXplain for our own use case, create a free account and start playing! Let us know how you're doing on our <a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">Discord</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Making Visuals Vocal: SceneXplain's Impact on Product Image Accessibility</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">SceneXplain transforms product images into audio descriptions, ensuring visual content isn't just seen, but also heard and understood. It's a step forward in creating an inclusive digital world for everyone</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 29, 2023 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In a world that is increasingly connected and digital, we're experiencing an unprecedented volume of visual content. Yet, for a significant portion of the population, these visuals remain inaccessible. Visual accessibility, often referred to as 'A11y', is a cornerstone of inclusive digital design. It ensures that information is not only available but also perceivable and understandable to all, including people with visual impairments.</p><p>SceneXplain, Jina AI's image analysis tool, is here to transform online accessibility. Now you can leverage the power of artificial intelligence to generate audio descriptions for product images. With SceneXplain, images aren't just seen; they're heard and understood, ensuring that the growing volume of visual content is accessible to everyone.</p><p>Why is this so critical? For online businesses, making product images accessible can broaden their customer base, increase customer satisfaction, and improve overall brand reputation. It isn't just about inclusivity; it's also a strategic business decision.</p><p>That’s not to mention the legal side of things! We’ve written about this extensively already: Check the following post:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</div><div class="kg-bookmark-description">Explore SceneXplain’s impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png" alt=""></div></a></figure><h2 id="bringing-images-to-life-with-textual-descriptions">Bringing images to life with textual descriptions</h2><p>In essence, SceneXplain's voiceover descriptions for product images are a significant step towards digital inclusivity. </p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/scenex-voiceover.mp4" poster="https://img.spacergif.org/v1/1248x1536/0a/spacer.png" width="1248" height="1536" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/06/media-thumbnail-ember158.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>Let's explore how this powerful tool works and the far-reaching impact it could have on our digital world. In this post, we'll look at how SceneXplain can transform the world of fashion e-commerce.</p><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">🖼️</div><div class="kg-callout-text">We'll be using freely available images from <a href="http://pexels.com/?ref=jina-ai-gmbh.ghost.io">Pexels.com</a> in this article.</div></div><p>Since the day of its launch, SceneXplain has been able to use its large-language-model powers to give you a description of what's in an image:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1-1.png" class="kg-image" alt="" width="597" height="684"></figure><pre><code class="language-text hljs language-plaintext">In an outdoor setting featuring a mix of bold and vibrant colors, a
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">SceneXplain transforms product images into audio descriptions, ensuring visual content isn't just seen, but also heard and understood. It's a step forward in creating an inclusive digital world for everyone</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 29, 2023 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In a world that is increasingly connected and digital, we're experiencing an unprecedented volume of visual content. Yet, for a significant portion of the population, these visuals remain inaccessible. Visual accessibility, often referred to as 'A11y', is a cornerstone of inclusive digital design. It ensures that information is not only available but also perceivable and understandable to all, including people with visual impairments.</p><p>SceneXplain, Jina AI's image analysis tool, is here to transform online accessibility. Now you can leverage the power of artificial intelligence to generate audio descriptions for product images. With SceneXplain, images aren't just seen; they're heard and understood, ensuring that the growing volume of visual content is accessible to everyone.</p><p>Why is this so critical? For online businesses, making product images accessible can broaden their customer base, increase customer satisfaction, and improve overall brand reputation. It isn't just about inclusivity; it's also a strategic business decision.</p><p>That’s not to mention the legal side of things! We’ve written about this extensively already: Check the following post:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</div><div class="kg-bookmark-description">Explore SceneXplain’s impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png" alt=""></div></a></figure><h2 id="bringing-images-to-life-with-textual-descriptions">Bringing images to life with textual descriptions</h2><p>In essence, SceneXplain's voiceover descriptions for product images are a significant step towards digital inclusivity. </p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/scenex-voiceover.mp4" poster="https://img.spacergif.org/v1/1248x1536/0a/spacer.png" width="1248" height="1536" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/06/media-thumbnail-ember158.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>Let's explore how this powerful tool works and the far-reaching impact it could have on our digital world. In this post, we'll look at how SceneXplain can transform the world of fashion e-commerce.</p><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">🖼️</div><div class="kg-callout-text">We'll be using freely available images from <a href="http://pexels.com/?ref=jina-ai-gmbh.ghost.io">Pexels.com</a> in this article.</div></div><p>Since the day of its launch, SceneXplain has been able to use its large-language-model powers to give you a description of what's in an image:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1-1.png" class="kg-image" alt="" width="597" height="684"></figure><pre><code class="language-text">In an outdoor setting featuring a mix of bold and vibrant colors, a
 woman, fashionably dressed, poses confidently for a photograph. She is
 clad in a green puffy jacket, accompanied by purple pants, and stylish
 blue boots. Her head is slightly tilted, and she gently smiles at the
 camera. The environment around her comprises two distinct red doors
 with white windows, adding a pop of color to the scene. Underneath her
 feet, a textured wooden surface supports her stance and adds an earthy
-element to the picture.</code></pre><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">🧠</div><div class="kg-callout-text">For this blog post we're going to use the "Comet" algorithm. In our experience, it is less "creative" than the default Dune algorithm. That's what we want, considering we need accurate information rather than deep scene descriptions.</div></div><p>That's a nice description of the image - but if we're talking fashion, we want descriptions...of the fashion. We can do that with visual question answering by asking:</p><pre><code class="language-text hljs language-plaintext">Describe each of the items of clothing in this image, in high detail,
+element to the picture.</code></pre><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">🧠</div><div class="kg-callout-text">For this blog post we're going to use the "Comet" algorithm. In our experience, it is less "creative" than the default Dune algorithm. That's what we want, considering we need accurate information rather than deep scene descriptions.</div></div><p>That's a nice description of the image - but if we're talking fashion, we want descriptions...of the fashion. We can do that with visual question answering by asking:</p><pre><code class="language-text">Describe each of the items of clothing in this image, in high detail,
 in the form of a numbered list. Include information about color, cut,
-style, fit. Do not mention the human in the picture.</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/visual-qa.png" class="kg-image" alt="" width="593" height="893"></figure><h2 id="listen-up-converting-images-into-audio-descriptions">Listen up: Converting images into audio descriptions</h2><p>If you're an e-commerce store, you likely have some details about the specific item you're trying to showcase in your image. Often you just want to sell one part of the fashion ensemble, not the whole outfit. So assuming you've specified your item as (for example) <em>puffy green jacket</em>, you could ask for that in more detail:</p><pre><code class="language-text hljs language-plaintext">Write a detailed product description for the puffy green jacket in
-this image, focusing on color, style, cut and fit (if mentioned)</code></pre><p>At the same time, let’s go to the add-ons menu and tick the box for an audio description:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/visual-qa-jacket.png" class="kg-image" alt="" width="592" height="910"></figure><p>We get the output:</p><pre><code class="language-text hljs language-plaintext">Introducing our stylish and cozy green puffer coat, designed to
+style, fit. Do not mention the human in the picture.</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/visual-qa.png" class="kg-image" alt="" width="593" height="893"></figure><h2 id="listen-up-converting-images-into-audio-descriptions">Listen up: Converting images into audio descriptions</h2><p>If you're an e-commerce store, you likely have some details about the specific item you're trying to showcase in your image. Often you just want to sell one part of the fashion ensemble, not the whole outfit. So assuming you've specified your item as (for example) <em>puffy green jacket</em>, you could ask for that in more detail:</p><pre><code class="language-text">Write a detailed product description for the puffy green jacket in
+this image, focusing on color, style, cut and fit (if mentioned)</code></pre><p>At the same time, let’s go to the add-ons menu and tick the box for an audio description:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/visual-qa-jacket.png" class="kg-image" alt="" width="592" height="910"></figure><p>We get the output:</p><pre><code class="language-text">Introducing our stylish and cozy green puffer coat, designed to
 elevate your winter wardrobe while keeping you warm and comfortable.
 This eye-catching coat features a vibrant green color that stands out
 in the colder months, making a fashion-forward statement. The puffer
@@ -35,7 +35,7 @@
 addition to any urban adventure, blending playfulness and contrast
 into a single piece. Accentuate your winter ensemble with this
 irresistible, fashion-forward puffer coat and experience pure comfort
-and style in the colder months.</code></pre><p>And because we also asked for a voiceover, the following audio was created:</p><div class="kg-card kg-audio-card"><img loading="lazy" src="" alt="audio-thumbnail" class="kg-audio-thumbnail kg-audio-hide"><div class="kg-audio-thumbnail placeholder"><svg width="24" height="24" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.5 15.33a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0ZM15 13.83a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.486 6.81A2.25 2.25 0 0 1 17.25 9v5.579a.75.75 0 0 1-1.5 0v-5.58a.75.75 0 0 0-.932-.727.755.755 0 0 1-.059.013l-4.465.744a.75.75 0 0 0-.544.72v6.33a.75.75 0 0 1-1.5 0v-6.33a2.25 2.25 0 0 1 1.763-2.194l4.473-.746Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3 1.5a.75.75 0 0 0-.75.75v19.5a.75.75 0 0 0 .75.75h18a.75.75 0 0 0 .75-.75V5.133a.75.75 0 0 0-.225-.535l-.002-.002-3-2.883A.75.75 0 0 0 18 1.5H3ZM1.409.659A2.25 2.25 0 0 1 3 0h15a2.25 2.25 0 0 1 1.568.637l.003.002 3 2.883a2.25 2.25 0 0 1 .679 1.61V21.75A2.25 2.25 0 0 1 21 24H3a2.25 2.25 0 0 1-2.25-2.25V2.25c0-.597.237-1.169.659-1.591Z"></path></svg></div><div class="kg-audio-player-container" style="--buffered-width:24%;"><audio src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/green_jacket.wav" preload="metadata"></audio><div class="kg-audio-title">Green jacket</div><div class="kg-audio-player"><button class="kg-audio-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-audio-pause-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-audio-current-time">0:00</span><div class="kg-audio-time">/<span class="kg-audio-duration">0:50</span></div><input type="range" class="kg-audio-seek-slider" max="50" value="0"><button class="kg-audio-playback-rate">1×</button><button class="kg-audio-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-audio-mute-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-audio-volume-slider" max="100" value="100"></div></div></div><h2 id="breaking-language-barriers-multilingual-audio-descriptions">Breaking language barriers: Multilingual audio descriptions</h2><p>But what about if you're selling in multiple countries? How can you get all of this in Spanish, French, and German? You can simply specify those in the add-ons menu:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/languages.png" class="kg-image" alt="" width="604" height="100" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/languages.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/languages.png 604w"></figure><p>Et voilà, we have output in more languages:</p><p>Spanish:</p><pre><code class="language-text hljs language-plaintext">Presentamos nuestra elegante y vibrante chaqueta verde hinchada,
+and style in the colder months.</code></pre><p>And because we also asked for a voiceover, the following audio was created:</p><div class="kg-card kg-audio-card"><img loading="lazy" src="" alt="audio-thumbnail" class="kg-audio-thumbnail kg-audio-hide"><div class="kg-audio-thumbnail placeholder"><svg width="24" height="24" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.5 15.33a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0ZM15 13.83a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.486 6.81A2.25 2.25 0 0 1 17.25 9v5.579a.75.75 0 0 1-1.5 0v-5.58a.75.75 0 0 0-.932-.727.755.755 0 0 1-.059.013l-4.465.744a.75.75 0 0 0-.544.72v6.33a.75.75 0 0 1-1.5 0v-6.33a2.25 2.25 0 0 1 1.763-2.194l4.473-.746Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3 1.5a.75.75 0 0 0-.75.75v19.5a.75.75 0 0 0 .75.75h18a.75.75 0 0 0 .75-.75V5.133a.75.75 0 0 0-.225-.535l-.002-.002-3-2.883A.75.75 0 0 0 18 1.5H3ZM1.409.659A2.25 2.25 0 0 1 3 0h15a2.25 2.25 0 0 1 1.568.637l.003.002 3 2.883a2.25 2.25 0 0 1 .679 1.61V21.75A2.25 2.25 0 0 1 21 24H3a2.25 2.25 0 0 1-2.25-2.25V2.25c0-.597.237-1.169.659-1.591Z"></path></svg></div><div class="kg-audio-player-container"><audio src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/green_jacket.wav" preload="metadata"></audio><div class="kg-audio-title">Green jacket</div><div class="kg-audio-player"><button class="kg-audio-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-audio-pause-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-audio-current-time">0:00</span><div class="kg-audio-time">/<span class="kg-audio-duration">0:50</span></div><input type="range" class="kg-audio-seek-slider" max="100" value="0"><button class="kg-audio-playback-rate">1×</button><button class="kg-audio-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-audio-mute-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-audio-volume-slider" max="100" value="100"></div></div></div><h2 id="breaking-language-barriers-multilingual-audio-descriptions">Breaking language barriers: Multilingual audio descriptions</h2><p>But what about if you're selling in multiple countries? How can you get all of this in Spanish, French, and German? You can simply specify those in the add-ons menu:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/languages.png" class="kg-image" alt="" width="604" height="100" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/languages.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/languages.png 604w"></figure><p>Et voilà, we have output in more languages:</p><p>Spanish:</p><pre><code class="language-text">Presentamos nuestra elegante y vibrante chaqueta verde hinchada,
 diseñada para hacer una declaración en cualquier entorno. Esta
 llamativa pieza está elaborada con un tono verde audaz, lo que la
 convierte en una adición destacada a cualquier guardarropa. La
@@ -44,7 +44,7 @@
 distintivo de esta pieza asegura un ajuste favorecedor, con una
 cuidadosa atención al detalle en su construcción. Abraza tu confianza
 y muestra tu sentido único de la moda con esta chaqueta verde hinchada
-imprescindible.</code></pre><div class="kg-card kg-audio-card"><img loading="lazy" src="" alt="audio-thumbnail" class="kg-audio-thumbnail kg-audio-hide"><div class="kg-audio-thumbnail placeholder"><svg width="24" height="24" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.5 15.33a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0ZM15 13.83a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.486 6.81A2.25 2.25 0 0 1 17.25 9v5.579a.75.75 0 0 1-1.5 0v-5.58a.75.75 0 0 0-.932-.727.755.755 0 0 1-.059.013l-4.465.744a.75.75 0 0 0-.544.72v6.33a.75.75 0 0 1-1.5 0v-6.33a2.25 2.25 0 0 1 1.763-2.194l4.473-.746Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3 1.5a.75.75 0 0 0-.75.75v19.5a.75.75 0 0 0 .75.75h18a.75.75 0 0 0 .75-.75V5.133a.75.75 0 0 0-.225-.535l-.002-.002-3-2.883A.75.75 0 0 0 18 1.5H3ZM1.409.659A2.25 2.25 0 0 1 3 0h15a2.25 2.25 0 0 1 1.568.637l.003.002 3 2.883a2.25 2.25 0 0 1 .679 1.61V21.75A2.25 2.25 0 0 1 21 24H3a2.25 2.25 0 0 1-2.25-2.25V2.25c0-.597.237-1.169.659-1.591Z"></path></svg></div><div class="kg-audio-player-container" style="--buffered-width:38.2353%;"><audio src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/jacket-spanish.wav" preload="metadata"></audio><div class="kg-audio-title">Jacket spanish</div><div class="kg-audio-player"><button class="kg-audio-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-audio-pause-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-audio-current-time">0:00</span><div class="kg-audio-time">/<span class="kg-audio-duration">0:34</span></div><input type="range" class="kg-audio-seek-slider" max="34" value="0"><button class="kg-audio-playback-rate">1×</button><button class="kg-audio-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-audio-mute-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-audio-volume-slider" max="100" value="100"></div></div></div><p>German:</p><pre><code class="language-text hljs language-plaintext">Wir stellen unsere stilvolle und lebendige Puffy Green Jacket vor, die
+imprescindible.</code></pre><div class="kg-card kg-audio-card"><img loading="lazy" src="" alt="audio-thumbnail" class="kg-audio-thumbnail kg-audio-hide"><div class="kg-audio-thumbnail placeholder"><svg width="24" height="24" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.5 15.33a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0ZM15 13.83a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.486 6.81A2.25 2.25 0 0 1 17.25 9v5.579a.75.75 0 0 1-1.5 0v-5.58a.75.75 0 0 0-.932-.727.755.755 0 0 1-.059.013l-4.465.744a.75.75 0 0 0-.544.72v6.33a.75.75 0 0 1-1.5 0v-6.33a2.25 2.25 0 0 1 1.763-2.194l4.473-.746Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3 1.5a.75.75 0 0 0-.75.75v19.5a.75.75 0 0 0 .75.75h18a.75.75 0 0 0 .75-.75V5.133a.75.75 0 0 0-.225-.535l-.002-.002-3-2.883A.75.75 0 0 0 18 1.5H3ZM1.409.659A2.25 2.25 0 0 1 3 0h15a2.25 2.25 0 0 1 1.568.637l.003.002 3 2.883a2.25 2.25 0 0 1 .679 1.61V21.75A2.25 2.25 0 0 1 21 24H3a2.25 2.25 0 0 1-2.25-2.25V2.25c0-.597.237-1.169.659-1.591Z"></path></svg></div><div class="kg-audio-player-container"><audio src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/jacket-spanish.wav" preload="metadata"></audio><div class="kg-audio-title">Jacket spanish</div><div class="kg-audio-player"><button class="kg-audio-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-audio-pause-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-audio-current-time">0:00</span><div class="kg-audio-time">/<span class="kg-audio-duration">0:34</span></div><input type="range" class="kg-audio-seek-slider" max="100" value="0"><button class="kg-audio-playback-rate">1×</button><button class="kg-audio-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-audio-mute-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-audio-volume-slider" max="100" value="100"></div></div></div><p>German:</p><pre><code class="language-text">Wir stellen unsere stilvolle und lebendige Puffy Green Jacket vor, die
 in jeder Umgebung ein Statement setzt. Dieses auffällige Stück ist mit
 einem kräftigen Grünton gefertigt, was es zu einer herausragenden
 Ergänzung für jede Garderobe macht. Die Jacke zeichnet sich durch ein
@@ -53,58 +53,58 @@
 Der markante Schnitt dieses Stücks sorgt für eine schmeichelhafte
 Passform, mit viel Liebe zum Detail in der Konstruktion. Zeigen Sie
 Ihr Selbstvertrauen und zeigen Sie Ihren einzigartigen Sinn für Mode
-mit dieser unverzichtbaren Puffy Green Jacket.</code></pre><div class="kg-card kg-audio-card"><img loading="lazy" src="" alt="audio-thumbnail" class="kg-audio-thumbnail kg-audio-hide"><div class="kg-audio-thumbnail placeholder"><svg width="24" height="24" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.5 15.33a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0ZM15 13.83a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.486 6.81A2.25 2.25 0 0 1 17.25 9v5.579a.75.75 0 0 1-1.5 0v-5.58a.75.75 0 0 0-.932-.727.755.755 0 0 1-.059.013l-4.465.744a.75.75 0 0 0-.544.72v6.33a.75.75 0 0 1-1.5 0v-6.33a2.25 2.25 0 0 1 1.763-2.194l4.473-.746Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3 1.5a.75.75 0 0 0-.75.75v19.5a.75.75 0 0 0 .75.75h18a.75.75 0 0 0 .75-.75V5.133a.75.75 0 0 0-.225-.535l-.002-.002-3-2.883A.75.75 0 0 0 18 1.5H3ZM1.409.659A2.25 2.25 0 0 1 3 0h15a2.25 2.25 0 0 1 1.568.637l.003.002 3 2.883a2.25 2.25 0 0 1 .679 1.61V21.75A2.25 2.25 0 0 1 21 24H3a2.25 2.25 0 0 1-2.25-2.25V2.25c0-.597.237-1.169.659-1.591Z"></path></svg></div><div class="kg-audio-player-container" style="--buffered-width:47.7273%;"><audio src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/jacket-german.wav" preload="metadata"></audio><div class="kg-audio-title">Jacket german</div><div class="kg-audio-player"><button class="kg-audio-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-audio-pause-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-audio-current-time">0:00</span><div class="kg-audio-time">/<span class="kg-audio-duration">0:44</span></div><input type="range" class="kg-audio-seek-slider" max="44" value="0"><button class="kg-audio-playback-rate">1×</button><button class="kg-audio-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-audio-mute-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-audio-volume-slider" max="100" value="100"></div></div></div><h2 id="mastering-the-magic-navigating-the-api">Mastering the magic: Navigating the API</h2><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">🤖</div><div class="kg-callout-text">We’re updating and improving our API all the time! Check the <a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io">SceneXplain API page</a> for the latest specification.</div></div><p>In the real world, we're not going to spend our time clicking through a web interface to upload images. Rather, we'd use SceneXplain's API. Let's assume we have <code>products.csv</code> in the following format:</p><pre><code class="language-csv">"name", "image_url"
+mit dieser unverzichtbaren Puffy Green Jacket.</code></pre><div class="kg-card kg-audio-card"><img loading="lazy" src="" alt="audio-thumbnail" class="kg-audio-thumbnail kg-audio-hide"><div class="kg-audio-thumbnail placeholder"><svg width="24" height="24" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.5 15.33a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0ZM15 13.83a.75.75 0 1 0 0 1.5.75.75 0 0 0 0-1.5Zm-2.25.75a2.25 2.25 0 1 1 4.5 0 2.25 2.25 0 0 1-4.5 0Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.486 6.81A2.25 2.25 0 0 1 17.25 9v5.579a.75.75 0 0 1-1.5 0v-5.58a.75.75 0 0 0-.932-.727.755.755 0 0 1-.059.013l-4.465.744a.75.75 0 0 0-.544.72v6.33a.75.75 0 0 1-1.5 0v-6.33a2.25 2.25 0 0 1 1.763-2.194l4.473-.746Z"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M3 1.5a.75.75 0 0 0-.75.75v19.5a.75.75 0 0 0 .75.75h18a.75.75 0 0 0 .75-.75V5.133a.75.75 0 0 0-.225-.535l-.002-.002-3-2.883A.75.75 0 0 0 18 1.5H3ZM1.409.659A2.25 2.25 0 0 1 3 0h15a2.25 2.25 0 0 1 1.568.637l.003.002 3 2.883a2.25 2.25 0 0 1 .679 1.61V21.75A2.25 2.25 0 0 1 21 24H3a2.25 2.25 0 0 1-2.25-2.25V2.25c0-.597.237-1.169.659-1.591Z"></path></svg></div><div class="kg-audio-player-container"><audio src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/jacket-german.wav" preload="metadata"></audio><div class="kg-audio-title">Jacket german</div><div class="kg-audio-player"><button class="kg-audio-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-audio-pause-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-audio-current-time">0:00</span><div class="kg-audio-time">/<span class="kg-audio-duration">0:44</span></div><input type="range" class="kg-audio-seek-slider" max="100" value="0"><button class="kg-audio-playback-rate">1×</button><button class="kg-audio-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-audio-mute-icon kg-audio-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-audio-volume-slider" max="100" value="100"></div></div></div><h2 id="mastering-the-magic-navigating-the-api">Mastering the magic: Navigating the API</h2><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">🤖</div><div class="kg-callout-text">We’re updating and improving our API all the time! Check the <a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io">SceneXplain API page</a> for the latest specification.</div></div><p>In the real world, we're not going to spend our time clicking through a web interface to upload images. Rather, we'd use SceneXplain's API. Let's assume we have <code>products.csv</code> in the following format:</p><pre><code class="language-csv">"name", "image_url"
 "green puffy jacket", "https://images.pexels.com/photos/2529172/pexels-photo-2529172.jpeg"
 "long pink coat", "https://images.pexels.com/photos/2043590/pexels-photo-2043590.jpeg"
-"white sneakers", "https://images.pexels.com/photos/2946956/pexels-photo-2946956.jpeg"</code></pre><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">🗃️</div><div class="kg-callout-text">In a real-world CSV you'd have a lot more fields and records. We're just keeping it simple for this example.</div></div><p>The CSV contains links to the following images:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.49813 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-2529172.jpeg" width="2000" height="1335" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-2529172.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-2529172.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-2529172.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-2529172.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.666667 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-2043590.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-2043590.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-2043590.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-2043590.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-2043590.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.666667 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-2946956.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-2946956.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-2946956.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-2946956.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-2946956.jpeg 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>Let’s load up that file and specify our question for each image based on a template <code>QUESTION</code>:</p><pre><code class="language-python hljs"><span class="hljs-keyword">import</span> csv
-<span class="hljs-keyword">import</span> http.client
-<span class="hljs-keyword">import</span> json
-<span class="hljs-keyword">from</span> pprint <span class="hljs-keyword">import</span> <span class="hljs-built_in">print</span>
+"white sneakers", "https://images.pexels.com/photos/2946956/pexels-photo-2946956.jpeg"</code></pre><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">🗃️</div><div class="kg-callout-text">In a real-world CSV you'd have a lot more fields and records. We're just keeping it simple for this example.</div></div><p>The CSV contains links to the following images:</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-2529172.jpeg" width="2000" height="1335" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-2529172.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-2529172.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-2529172.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-2529172.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-2043590.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-2043590.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-2043590.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-2043590.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-2043590.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/pexels-photo-2946956.jpeg" width="2000" height="3000" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/pexels-photo-2946956.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/pexels-photo-2946956.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/pexels-photo-2946956.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/06/pexels-photo-2946956.jpeg 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>Let’s load up that file and specify our question for each image based on a template <code>QUESTION</code>:</p><pre><code class="language-python">import csv
+import http.client
+import json
+from pprint import print
 
-CSV_FILE = <span class="hljs-string">'products.csv'</span>
-QUESTION = <span class="hljs-string">'Write a detailed product description for the {} in this image, focusing on color, style, cut and fit (if mentioned)'</span>
+CSV_FILE = 'products.csv'
+QUESTION = 'Write a detailed product description for the {} in this image, focusing on color, style, cut and fit (if mentioned)'
 
 data = []
 
-<span class="hljs-keyword">with</span> <span class="hljs-built_in">open</span>(CSV_FILE) <span class="hljs-keyword">as</span> file:
+with open(CSV_FILE) as file:
     products = csv.DictReader(file)
 
-    <span class="hljs-keyword">for</span> product <span class="hljs-keyword">in</span> products:
-        product[<span class="hljs-string">'image'</span>] = product[<span class="hljs-string">"image_url"</span>]
-        product[<span class="hljs-string">'question'</span>] = QUESTION.<span class="hljs-built_in">format</span>(product[<span class="hljs-string">'name'</span>])
-        product[<span class="hljs-string">'features'</span>] = [<span class="hljs-string">'tts'</span>, <span class="hljs-string">'question_answer'</span>]
-        product[<span class="hljs-string">'algorithm'</span>] = <span class="hljs-string">'Comet'</span>
-        product[<span class="hljs-string">'languages'</span>] = [<span class="hljs-string">'en'</span>]
-        product[<span class="hljs-string">'style'</span>] = <span class="hljs-string">'concise'</span>
+    for product in products:
+        product['image'] = product["image_url"]
+        product['question'] = QUESTION.format(product['name'])
+        product['features'] = ['tts', 'question_answer']
+        product['algorithm'] = 'Comet'
+        product['languages'] = ['en']
+        product['style'] = 'concise'
         data.append(product)
 
-data = {<span class="hljs-string">'data'</span>: data}</code></pre><p>And here’s the code to send that data over to SceneXplain, then convert the result to JSON:</p><pre><code class="language-python hljs">headers = {
-    <span class="hljs-string">'x-api-key'</span>: <span class="hljs-string">f'token <span class="hljs-subst">{YOUR_GENERATED_SECRET}</span>'</span>,
-    <span class="hljs-string">'content-type'</span>: <span class="hljs-string">'application/json'</span>,
+data = {'data': data}</code></pre><p>And here’s the code to send that data over to SceneXplain, then convert the result to JSON:</p><pre><code class="language-python">headers = {
+    'x-api-key': f'token {YOUR_GENERATED_SECRET}',
+    'content-type': 'application/json',
 }
 
-connection = http.client.HTTPSConnection(<span class="hljs-string">'us-central1-causal-diffusion.cloudfunctions.net'</span>)
-connection.request(<span class="hljs-string">'POST'</span>, <span class="hljs-string">'/describe'</span>, json.dumps(data), headers)
+connection = http.client.HTTPSConnection('us-central1-causal-diffusion.cloudfunctions.net')
+connection.request('POST', '/describe', json.dumps(data), headers)
 response = connection.getresponse()
 
-response_data = response.read().decode(<span class="hljs-string">'utf-8'</span>)
+response_data = response.read().decode('utf-8')
 
 connection.close()
 
-data = json.loads(response_data)</code></pre><p>Finally, we can write the information we want to a new CSV file:</p><pre><code class="language-python hljs"><span class="hljs-comment"># extract just the info we want</span>
+data = json.loads(response_data)</code></pre><p>Finally, we can write the information we want to a new CSV file:</p><pre><code class="language-python"># extract just the info we want
 records = []
-<span class="hljs-keyword">for</span> product <span class="hljs-keyword">in</span> data[<span class="hljs-string">'result'</span>]:
+for product in data['result']:
     record = {}
-    record[<span class="hljs-string">'name'</span>] = product[<span class="hljs-string">'name'</span>]
-    record[<span class="hljs-string">'image_url'</span>] = product[<span class="hljs-string">'image_url'</span>]
-    record[<span class="hljs-string">'desc_en'</span>] = product[<span class="hljs-string">'i18n'</span>][<span class="hljs-string">'en'</span>]
-    record[<span class="hljs-string">'audio_en'</span>] = product[<span class="hljs-string">'tts'</span>][<span class="hljs-string">'en'</span>]
+    record['name'] = product['name']
+    record['image_url'] = product['image_url']
+    record['desc_en'] = product['i18n']['en']
+    record['audio_en'] = product['tts']['en']
     records.append(record)
 
-<span class="hljs-comment"># write to CSV</span>
-field_names = <span class="hljs-built_in">list</span>(records[<span class="hljs-number">0</span>].keys())
+# write to CSV
+field_names = list(records[0].keys())
 
-<span class="hljs-keyword">with</span> <span class="hljs-built_in">open</span>(<span class="hljs-string">'products-updated.csv'</span>, <span class="hljs-string">'w'</span>, newline=<span class="hljs-string">''</span>) <span class="hljs-keyword">as</span> csvfile:
+with open('products-updated.csv', 'w', newline='') as csvfile:
     writer = csv.DictWriter(csvfile, fieldnames=field_names)
 
     writer.writeheader()
@@ -112,4 +112,4 @@
 green puffy jacket,https://images.pexels.com/photos/2529172/pexels-photo-2529172.jpeg,"The green puffy jacket in this image appears to be a vibrant and eye-catching shade of green. It is described as being a ""jacket,"" which suggests that it is worn as an outer layer. The use of the word ""puffy"" indicates that it is likely a down jacket or has some sort of insulation, which would make it warm and cozy. It is not specified whether it has a specific style or cut, but based on the rest of the woman's outfit, it seems to be a casual, relaxed fit. Overall, the green puffy jacket adds a pop of color to the image and would likely be a functional and stylish choice for cold weather.",https://storage.googleapis.com/causal-diffusion.appspot.com/audios%2Feeff4097-a337-4291-b7e7-d0b2e977589b%2Fen.wav
 long pink coat,https://images.pexels.com/photos/2043590/pexels-photo-2043590.jpeg,"The pink coat in the image appears to be a long overcoat, likely made from wool or a wool blend material. The color is a soft shade of pink, which complements the black dress worn by the woman. The style of the coat is slightly oversized and features a classic notch collar. With its lengthy design, the coat would provide ample coverage during colder months. Unfortunately, the description does not provide information on the cut or fit of the coat.",https://storage.googleapis.com/causal-diffusion.appspot.com/audios%2F16f03ec8-7164-4e1e-b63e-0895159a1320%2Fen.wav
 white sneakers,https://images.pexels.com/photos/2946956/pexels-photo-2946956.jpeg,"The white sneakers in the image are clean and maintained in pristine condition. They feature a blue star design on top, adding a touch of color to an otherwise minimalist look. The cut and fit of the shoes are not mentioned in the description. However, based on their appearance, they seem to be low-cut and have a narrow profile, suggesting a sleek and modern style. The shoes also bear a logo on the side, which could indicate a particular brand or designer. Overall, these white sneakers are an excellent choice for someone looking for a fresh and stylish addition to their footwear collection.",https://storage.googleapis.com/causal-diffusion.appspot.com/audios%2Ff42db823-5e1c-4dc1-bab2-269cfe2ca51f%2Fen.wav
-</code></pre><p>And just like that, with a few lines of code and the power of SceneXplain's API, you've transformed your product images into both text and audio narratives. This not only enhances your site's accessibility but also widens the gateway to a more diverse audience. Now, more customers than ever before can experience your products, proving once again that inclusivity is good for business.</p><h2 id="jumpstart-your-journey-with-scenexplain-voiceover">Jumpstart your journey with SceneXplain voiceover</h2><p>Embarking on your SceneXplain journey couldn't be simpler. Just make your way over to <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">scenex.jina.ai</a>, sign up, and you'll be greeted with complimentary credits to get you started.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="http://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="http://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><p>Got questions? 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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+</code></pre><p>And just like that, with a few lines of code and the power of SceneXplain's API, you've transformed your product images into both text and audio narratives. This not only enhances your site's accessibility but also widens the gateway to a more diverse audience. Now, more customers than ever before can experience your products, proving once again that inclusivity is good for business.</p><h2 id="jumpstart-your-journey-with-scenexplain-voiceover">Jumpstart your journey with SceneXplain voiceover</h2><p>Embarking on your SceneXplain journey couldn't be simpler. Just make your way over to <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">scenex.jina.ai</a>, sign up, and you'll be greeted with complimentary credits to get you started.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="http://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="http://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><p>Got questions? 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Maximizing Efficiency and Savings with PromptPerfect's New Feature: Unified Credits</title><meta charset="utf-8"><meta name="title" content="Maximizing Efficiency and Savings with PromptPerfect's New Feature: Unified Credits"><meta name="description" content="Introducing Unified Credits: Seamlessly share credits between PromptPerfect and SceneXplain, maximizing efficiency and cost savings for power users. "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/maximizing-efficiency-and-savings-with-promptperfects-new-feature-unified-credits"><meta property="og:title" content="Maximizing Efficiency and Savings with PromptPerfect's New Feature: Unified Credits"><meta property="og:description" content="Introducing Unified Credits: Seamlessly share credits between PromptPerfect and SceneXplain, maximizing efficiency and cost savings for power users. "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--8-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/maximizing-efficiency-and-savings-with-promptperfects-new-feature-unified-credits"><meta property="twitter:title" content="Maximizing Efficiency and Savings with PromptPerfect's New Feature: Unified Credits"><meta property="twitter:description" content="Introducing Unified Credits: Seamlessly share credits between PromptPerfect and SceneXplain, maximizing efficiency and cost savings for power users. "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--8-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--8-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Introducing Unified Credits: Seamlessly share credits between PromptPerfect and SceneXplain, maximizing efficiency and cost savings for power users. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Miruna Nedelcu</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 27, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Are you ready to take your productivity to the next level? </p><p><a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">PromptPerfect</a>, your trusted partner for enhancing your writing experience, is thrilled to introduce a groundbreaking feature that will revolutionize the way you use our tools. Say hello to <strong>Unified Credits</strong> – a game-changer for power users like you!</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/09/1--1--1.mp4" poster="https://img.spacergif.org/v1/2304x1440/0a/spacer.png" width="2304" height="1440" loop="" autoplay="" muted="" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/09/media-thumbnail-ember101.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container kg-video-hide"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>Tutorial Unified Credits</figcaption></figure><h2 id="what-are-unified-credits">What are Unified Credits?</h2><p>Unified Credits is the latest innovation from PromptPerfect that allows you to seamlessly share credits between PromptPerfect and our sister product, SceneXplain. This integration empowers you with unprecedented flexibility and convenience, ultimately enhancing your writing journey.</p><h2 id="why-should-i-buy-unified-credits">Why should I buy Unified Credits?</h2><p><br>Here's what's in it for you:</p><h3 id="maximize-value">Maximize Value</h3><p>With Unified Credits, you can now maximize the value of your credits by using them interchangeably between PromptPerfect and SceneXplain. Whether you're an aspiring novelist, a content creator, or a professional writer, this feature will make your work more efficient and cost-effective.</p><h3 id="save-costs">Save Costs</h3><p>Gone are the days of purchasing separate credits for different tools. Unified Credits lets you share your credits without incurring any additional costs. It's a win-win situation for your wallet and your writing.</p><h3 id="how-it-works">How It Works</h3><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/09/1--1-.mp4" poster="https://img.spacergif.org/v1/2304x1440/0a/spacer.png" width="2304" height="1440" loop="" autoplay="" muted="" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/09/media-thumbnail-ember74.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container kg-video-hide"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>Tutorial Unified Credits</figcaption></figure><p>Getting started with Unified Credits is easy:</p><ol><li><strong>Update Your Apps</strong>: For a smooth experience, make sure that both PromptPerfect and SceneXplain are updated to the latest version.</li><li><strong>Access the 'Account' Tab</strong>: Open either PromptPerfect or SceneXplain and navigate to the 'Account' tab.</li><li><strong>Select "Share Credits"</strong>: Inside the 'Account' tab, you'll find the "Share credits" option. Click on it to initiate the process.</li><li><strong>Choose Your App</strong>: Pick the app (PromptPerfect or SceneXplain) that you want to connect to. </li><li><strong>Connect and Done</strong>: Confirm the connection, and that's it! Your credits are now unified, ready to be used seamlessly across both tools.</li></ol><h2 id="enjoy-the-benefits">Enjoy the Benefits</h2><p>With Unified Credits, you can experience a new level of efficiency, productivity, and cost savings in your writing endeavors. Whether you're drafting a novel in <a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">PromptPerfect</a> or crafting engaging explanations in <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a>, your credits are now at your fingertips, waiting to be utilized.</p><p>Don't wait any longer – upgrade your writing experience with Unified Credits today and unlock the full potential of <a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">PromptPerfect</a> and SceneXplain.</p><h2 id="get-started-now">Get started now!</h2><p>If you have any questions or need assistance, feel free to <a href="https://discord.com/invite/AWXCCC6G2P?ref=jina-ai-gmbh.ghost.io">reach out</a> to our dedicated support team. 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FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Maximizing Efficiency and Savings with PromptPerfect's New Feature: Unified Credits</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Introducing Unified Credits: Seamlessly share credits between PromptPerfect and SceneXplain, maximizing efficiency and cost savings for power users. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Miruna Nedelcu</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 27, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Are you ready to take your productivity to the next level? </p><p><a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">PromptPerfect</a>, your trusted partner for enhancing your writing experience, is thrilled to introduce a groundbreaking feature that will revolutionize the way you use our tools. Say hello to <strong>Unified Credits</strong> – a game-changer for power users like you!</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/09/1--1--1.mp4" poster="https://img.spacergif.org/v1/2304x1440/0a/spacer.png" width="2304" height="1440" loop="" autoplay="" muted="" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/09/media-thumbnail-ember101.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay kg-video-hide-animated"><button class="kg-video-large-play-icon kg-video-hide-animated"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container kg-video-hide"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>Tutorial Unified Credits</figcaption></figure><h2 id="what-are-unified-credits">What are Unified Credits?</h2><p>Unified Credits is the latest innovation from PromptPerfect that allows you to seamlessly share credits between PromptPerfect and our sister product, SceneXplain. This integration empowers you with unprecedented flexibility and convenience, ultimately enhancing your writing journey.</p><h2 id="why-should-i-buy-unified-credits">Why should I buy Unified Credits?</h2><p><br>Here's what's in it for you:</p><h3 id="maximize-value">Maximize Value</h3><p>With Unified Credits, you can now maximize the value of your credits by using them interchangeably between PromptPerfect and SceneXplain. Whether you're an aspiring novelist, a content creator, or a professional writer, this feature will make your work more efficient and cost-effective.</p><h3 id="save-costs">Save Costs</h3><p>Gone are the days of purchasing separate credits for different tools. Unified Credits lets you share your credits without incurring any additional costs. It's a win-win situation for your wallet and your writing.</p><h3 id="how-it-works">How It Works</h3><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/09/1--1-.mp4" poster="https://img.spacergif.org/v1/2304x1440/0a/spacer.png" width="2304" height="1440" loop="" autoplay="" muted="" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/09/media-thumbnail-ember74.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay kg-video-hide-animated"><button class="kg-video-large-play-icon kg-video-hide-animated"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container kg-video-hide"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>Tutorial Unified Credits</figcaption></figure><p>Getting started with Unified Credits is easy:</p><ol><li><strong>Update Your Apps</strong>: For a smooth experience, make sure that both PromptPerfect and SceneXplain are updated to the latest version.</li><li><strong>Access the 'Account' Tab</strong>: Open either PromptPerfect or SceneXplain and navigate to the 'Account' tab.</li><li><strong>Select "Share Credits"</strong>: Inside the 'Account' tab, you'll find the "Share credits" option. Click on it to initiate the process.</li><li><strong>Choose Your App</strong>: Pick the app (PromptPerfect or SceneXplain) that you want to connect to. </li><li><strong>Connect and Done</strong>: Confirm the connection, and that's it! Your credits are now unified, ready to be used seamlessly across both tools.</li></ol><h2 id="enjoy-the-benefits">Enjoy the Benefits</h2><p>With Unified Credits, you can experience a new level of efficiency, productivity, and cost savings in your writing endeavors. Whether you're drafting a novel in <a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">PromptPerfect</a> or crafting engaging explanations in <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a>, your credits are now at your fingertips, waiting to be utilized.</p><p>Don't wait any longer – upgrade your writing experience with Unified Credits today and unlock the full potential of <a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">PromptPerfect</a> and SceneXplain.</p><h2 id="get-started-now">Get started now!</h2><p>If you have any questions or need assistance, feel free to <a href="https://discord.com/invite/AWXCCC6G2P?ref=jina-ai-gmbh.ghost.io">reach out</a> to our dedicated support team. We're here to make your journey as smooth and enjoyable as possible.</p><p>Stay tuned for more exciting updates from Jina AI as we continue to innovate and enhance your writing experience.</p><p></p><p><br></p><p><br></p><p><br></p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fmaximizing-efficiency-and-savings-with-promptperfects-new-feature-unified-credits%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G, Florian Hönicke</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 19, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In this post, we’re going to explore how multi-agent simulations are not just a conceptual framework but a tool with tangible applications in various domains. By delving into practical examples, we can see how these systems bring together the strengths of individual agents to address complex tasks and deliver solutions that are more efficient, comprehensive, and tailored to specific needs. These examples will illustrate the versatility and effectiveness of multi-agent simulations in real-world scenarios, demonstrating their value in diverse fields.</p><h2 id="a-quick-history-lesson">A quick history lesson</h2><p>In the ever-evolving landscape of technology and problem-solving, our journey has been marked by significant milestones. Initially, coding was our primary tool for instructing computers to perform tasks and solve problems. This era was defined by programming languages and algorithms, where solutions were hard-coded. As technology advances, we’re transitioning to a more intuitive approach: prompting. This phase leverages artificial intelligence, where we can simply ask a system a question or present a problem, and it generates solutions based on its training and algorithms. This method is more flexible and user-friendly, catering to a wider range of problems without the need for extensive coding knowledge. However, even now, we're seeing the glimmerings of a newer era that promises to revolutionize how we approach problem-solving: the use of agents.</p><h2 id="multi-agent-simulations-as-easy-as-1-2-3">Multi-agent simulations: As easy as 1, 2, 3</h2><p>Before we dive into using multiple agents, let’s define a few key terms: <em>Agent</em>, <em>action,</em> <em>environment</em>, and <em>simulation</em>.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Multi-agent-sim.png" class="kg-image" alt="" width="861" height="627" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Multi-agent-sim.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/Multi-agent-sim.png 861w" sizes="(min-width: 720px) 720px"></figure><ul><li><strong>Agent:</strong> An <em>agent</em>, in the realm of artificial intelligence, performs actions to achieve a goal, like planning a vacation or collecting state-of-the-art research information online.</li><li><strong>Action:</strong> An <em>action</em> is a state change in an environment initiated by an agent. This may include talking to other agents, searching Google, or accessing external APIs.</li><li><strong>Environment:</strong> An <em>environment</em> is a text description that constrains what the agent can do. In a travel planning simulation, this may be a (virtual) travel agent office.</li><li><strong>Simulation:</strong> A <em>simulation</em> is what you get when you put all of the above together: An agent (or agents) performing actions in a given environment.</li></ul><h2 id="diving-deeper-into-agents">Diving deeper into agents</h2><p>AI agents can range from simple, rule-based systems to <em>complex entities capable of learning</em>. They can analyze data, learn from experiences, and make predictions or recommendations.</p><p>Agents share several characteristics:</p><ul><li><strong>Autonomy</strong>: Agents operate without direct human intervention, making decisions based on their programming and the data they encounter.</li><li><strong>Reactivity</strong>: They perceive their environment and respond to changes in real time, adapting their actions as necessary.</li><li><strong>Proactivity</strong>: Beyond just reacting, agents can take initiative, anticipating future states and planning actions accordingly.</li><li><strong>Social ability</strong>: Agents can communicate and collaborate with other agents or humans to achieve complex goals.</li></ul><p>However, despite these capabilities, single AI agents face intrinsic limitations:</p><ul><li><strong>Specialization limit</strong>: Like human experts, each agent typically specializes in a particular domain or task, lacking the breadth of knowledge to handle unrelated challenges.</li><li><strong>Complex problem solving</strong>: Tackling multi-dimensional problems that require diverse expertise and perspectives is beyond the scope of a single agent.</li><li><strong>Limited adaptability</strong>: While adaptable within their domain, agents may struggle with novel situations that fall outside their programmed parameters or training data.</li></ul><p>In summary, while individual AI agents represent a significant technological advancement, their true potential is unlocked when they operate as part of a multi-agent system, combining their strengths and compensating for each other's limitations.</p><h2 id="multiple-agents-n-heads-are-better-than-one">Multiple agents: <em>n</em> heads are better than one</h2><p>The solution to those limitations lies in multi-agent simulation. This approach involves using multiple AI agents, each with its specialty or focus area, working in tandem to solve complex problems. By collaborating, these agents can cover a broader range of issues and provide more comprehensive solutions than a single agent could. <a href="https://arxiv.org/pdf/2307.05300.pdf?ref=jina-ai-gmbh.ghost.io">Current research</a> shows that the performance of agents in specific tasks depends on the persona of the agent.</p><h2 id="building-a-vacation-planner-with-promptperfect">Building a vacation planner with PromptPerfect</h2><p>Let’s consider planning a vacation as a practical example of a multi-agent simulation. This example will use two agents:</p><ul><li>The Travel Planner finds the best travel routes.</li><li>The Accommodation Finder finds affordable accommodation.</li></ul><p>Together, they provide a complete vacation plan tailored to your preferences and budget.</p><p>Follow the steps below to create a vacation planner in PromptPerfect:</p>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G, Florian Hönicke</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 19, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In this post, we’re going to explore how multi-agent simulations are not just a conceptual framework but a tool with tangible applications in various domains. By delving into practical examples, we can see how these systems bring together the strengths of individual agents to address complex tasks and deliver solutions that are more efficient, comprehensive, and tailored to specific needs. These examples will illustrate the versatility and effectiveness of multi-agent simulations in real-world scenarios, demonstrating their value in diverse fields.</p><h2 id="a-quick-history-lesson">A quick history lesson</h2><p>In the ever-evolving landscape of technology and problem-solving, our journey has been marked by significant milestones. Initially, coding was our primary tool for instructing computers to perform tasks and solve problems. This era was defined by programming languages and algorithms, where solutions were hard-coded. As technology advances, we’re transitioning to a more intuitive approach: prompting. This phase leverages artificial intelligence, where we can simply ask a system a question or present a problem, and it generates solutions based on its training and algorithms. This method is more flexible and user-friendly, catering to a wider range of problems without the need for extensive coding knowledge. However, even now, we're seeing the glimmerings of a newer era that promises to revolutionize how we approach problem-solving: the use of agents.</p><h2 id="multi-agent-simulations-as-easy-as-1-2-3">Multi-agent simulations: As easy as 1, 2, 3</h2><p>Before we dive into using multiple agents, let’s define a few key terms: <em>Agent</em>, <em>action,</em> <em>environment</em>, and <em>simulation</em>.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Multi-agent-sim.png" class="kg-image" alt="" width="861" height="627" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Multi-agent-sim.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/Multi-agent-sim.png 861w" sizes="(min-width: 720px) 720px"></figure><ul><li><strong>Agent:</strong> An <em>agent</em>, in the realm of artificial intelligence, performs actions to achieve a goal, like planning a vacation or collecting state-of-the-art research information online.</li><li><strong>Action:</strong> An <em>action</em> is a state change in an environment initiated by an agent. This may include talking to other agents, searching Google, or accessing external APIs.</li><li><strong>Environment:</strong> An <em>environment</em> is a text description that constrains what the agent can do. In a travel planning simulation, this may be a (virtual) travel agent office.</li><li><strong>Simulation:</strong> A <em>simulation</em> is what you get when you put all of the above together: An agent (or agents) performing actions in a given environment.</li></ul><h2 id="diving-deeper-into-agents">Diving deeper into agents</h2><p>AI agents can range from simple, rule-based systems to <em>complex entities capable of learning</em>. They can analyze data, learn from experiences, and make predictions or recommendations.</p><p>Agents share several characteristics:</p><ul><li><strong>Autonomy</strong>: Agents operate without direct human intervention, making decisions based on their programming and the data they encounter.</li><li><strong>Reactivity</strong>: They perceive their environment and respond to changes in real time, adapting their actions as necessary.</li><li><strong>Proactivity</strong>: Beyond just reacting, agents can take initiative, anticipating future states and planning actions accordingly.</li><li><strong>Social ability</strong>: Agents can communicate and collaborate with other agents or humans to achieve complex goals.</li></ul><p>However, despite these capabilities, single AI agents face intrinsic limitations:</p><ul><li><strong>Specialization limit</strong>: Like human experts, each agent typically specializes in a particular domain or task, lacking the breadth of knowledge to handle unrelated challenges.</li><li><strong>Complex problem solving</strong>: Tackling multi-dimensional problems that require diverse expertise and perspectives is beyond the scope of a single agent.</li><li><strong>Limited adaptability</strong>: While adaptable within their domain, agents may struggle with novel situations that fall outside their programmed parameters or training data.</li></ul><p>In summary, while individual AI agents represent a significant technological advancement, their true potential is unlocked when they operate as part of a multi-agent system, combining their strengths and compensating for each other's limitations.</p><h2 id="multiple-agents-n-heads-are-better-than-one">Multiple agents: <em>n</em> heads are better than one</h2><p>The solution to those limitations lies in multi-agent simulation. This approach involves using multiple AI agents, each with its specialty or focus area, working in tandem to solve complex problems. By collaborating, these agents can cover a broader range of issues and provide more comprehensive solutions than a single agent could. <a href="https://arxiv.org/pdf/2307.05300.pdf?ref=jina-ai-gmbh.ghost.io">Current research</a> shows that the performance of agents in specific tasks depends on the persona of the agent.</p><h2 id="building-a-vacation-planner-with-promptperfect">Building a vacation planner with PromptPerfect</h2><p>Let’s consider planning a vacation as a practical example of a multi-agent simulation. This example will use two agents:</p><ul><li>The Travel Planner finds the best travel routes.</li><li>The Accommodation Finder finds affordable accommodation.</li></ul><p>Together, they provide a complete vacation plan tailored to your preferences and budget.</p><p>Follow the steps below to create a vacation planner in PromptPerfect:</p>
 
 <iframe src="https://scribehow.com/embed/Creating_a_Simulation_for_Vacation_Planning__NbBdmWiUS5SC_QZ00lc21Q" width="640" height="640" allowfullscreen="" frameborder="0">
 
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Multimodal Visual Question Answering with BLIP-2 and Jina</title><meta charset="utf-8"><meta name="title" content="Multimodal Visual Question Answering with BLIP-2 and Jina"><meta name="description" content="LLMs aren't great for working with anything beyond text. But now you can serve BLIP-2 with Jina and DocArray, enhancing LLMs with visual understanding"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/multimodal-visual-question-answering-with-blip-2-and-jina"><meta property="og:title" content="Multimodal Visual Question Answering with BLIP-2 and Jina"><meta property="og:description" content="LLMs aren't great for working with anything beyond text. But now you can serve BLIP-2 with Jina and DocArray, enhancing LLMs with visual understanding"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/BLIP-2---1-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/multimodal-visual-question-answering-with-blip-2-and-jina"><meta property="twitter:title" content="Multimodal Visual Question Answering with BLIP-2 and Jina"><meta property="twitter:description" content="LLMs aren't great for working with anything beyond text. But now you can serve BLIP-2 with Jina and DocArray, enhancing LLMs with visual understanding"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/BLIP-2---1-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Multimodal Visual Question Answering with BLIP-2 and Jina</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">LLMs aren't great for working with anything beyond text. But now you can serve BLIP-2 with Jina and DocArray, enhancing LLMs with visual understanding</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alaeddine Abdessalem, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 09, 2023 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><hr><p>Large Language Models (LLMs) have recently gained a lot of traction, with many popular models showing up like GPT, OPT, BLOOM and more. These models excel at learning natural language, making them perfect for building chatbots, coding assistants, <a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io">decision-making assistants</a>, or translation systems. However, they lack knowledge when it comes to other modalities — for instance, they cannot process images, audio, or video. That’s where BLIP comes in, to enhance LLM’s natural language capabilities with visual understanding.</p><p>Essentially, you can feed the BLIP model pairs of image and text to perform a variety of tasks, like Visual Question Answering (VQA), Image Captioning or Image-Text Retrieval:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-15.png" class="kg-image" alt="" width="1600" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-15.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-15.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>However, building a product out of BLIP may not be trivial: You need the right model-serving framework and data serialization library. At Jina AI, we’ve always believed in <a href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io">Multimodal AI</a>, and that’s why we’ve optimized Jina and DocArray for this purpose. Serving BLIP-2 is a typical use case for these two projects.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-16.png" class="kg-image" alt="" width="1384" height="786" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-16.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-16.png 1384w" sizes="(min-width: 720px) 720px"><figcaption>Multimodal AI is artificial intelligence that works with multiple modalities at once (e.g. image + text, video + audio, etc), rather than just one single modality.</figcaption></figure><p>Let’s see how it works!</p><h2 id="blip-2">BLIP-2</h2><p>BLIP-2 is a vision-language model proposed in the paper <strong><a href="https://arxiv.org/abs/2301.12597?ref=jina-ai-gmbh.ghost.io">BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models</a>.</strong></p><p>It leverages frozen pre-trained image encoders and LLMs by training a lightweight, 12-layer Transformer encoder in between them, to achieve state-of-the-art performance on various vision-language tasks.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-17.png" class="kg-image" alt="" width="1290" height="580" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-17.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-17.png 1290w" sizes="(min-width: 720px) 720px"><figcaption>Source: <a href="https://arxiv.org/pdf/2301.12597.pdf?ref=jina-ai-gmbh.ghost.io">https://arxiv.org/pdf/2301.12597.pdf</a></figcaption></figure><h2 id="jina-and-docarray">Jina and DocArray</h2><p>Before diving into the code, let’s briefly introduce Jina and DocArray and explain what’s recently been happening with both projects.</p><p><strong>Jina</strong> is an MLOps framework to <strong>build</strong> and <strong>serve</strong> multimodal AI <strong>services,</strong> then <strong>scale</strong> and <strong>deploy</strong> them on the cloud. But recently we’ve been reshaping Jina to serve models more effectively. And in the <a href="https://github.com/jina-ai/jina/releases/tag/v3.14.0?ref=jina-ai-gmbh.ghost.io">3.14 release</a>, we allow users to serve Executors as standalone services using the gRPC protocol. In this post we’ll use those newly released features to serve a BLIP-2 model.</p><p>For data representation and serialization, Jina uses <strong>DocArray</strong>, a library for <strong>unstructured, multimodal data</strong>. It’s optimized for data in transit, in the sense that data can be <a href="https://docs.docarray.org/fundamentals/documentarray/serialization/?ref=jina-ai-gmbh.ghost.io">serialized</a> in several formats including <a href="https://github.com/protocolbuffers/protobuf?ref=jina-ai-gmbh.ghost.io">protobuf</a>. In other words, model input and output can be received/sent over the wire using DocArray formats.</p><p>We’re also reshaping DocArray to better fit multimodal AI use cases. In fact, it’s going through <a href="https://github.com/docarray/docarray/issues/780?ref=jina-ai-gmbh.ghost.io">heavy refactoring</a> with the goal of offering flexible and powerful data formats with DocArray v2.</p><p>Therefore, we’ll use both the current DocArray and the alpha version of DocArray v2 to represent model queries and output (and in doing so you’ll quickly understand why we refactored DocArray!).</p><h2 id="serving-blip-2-with-docarray-and-jina">Serving BLIP-2 with DocArray and Jina</h2><p>Since BLIP-2 uses LLMs, it comes with different open-source language models (i.e, <code>flan-t5</code> and <code>opt</code>). In this blog, we’ll use <code>flan-t5-xl</code>. Let’s start by installing the dependencies:</p><pre><code class="language-bash hljs">pip install jina torch git+https://github.com/huggingface/transformers pillow
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Multimodal Visual Question Answering with BLIP-2 and Jina</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">LLMs aren't great for working with anything beyond text. But now you can serve BLIP-2 with Jina and DocArray, enhancing LLMs with visual understanding</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alaeddine Abdessalem, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 09, 2023 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><hr><p>Large Language Models (LLMs) have recently gained a lot of traction, with many popular models showing up like GPT, OPT, BLOOM and more. These models excel at learning natural language, making them perfect for building chatbots, coding assistants, <a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io">decision-making assistants</a>, or translation systems. However, they lack knowledge when it comes to other modalities — for instance, they cannot process images, audio, or video. That’s where BLIP comes in, to enhance LLM’s natural language capabilities with visual understanding.</p><p>Essentially, you can feed the BLIP model pairs of image and text to perform a variety of tasks, like Visual Question Answering (VQA), Image Captioning or Image-Text Retrieval:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-15.png" class="kg-image" alt="" width="1600" height="900" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-15.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-15.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>However, building a product out of BLIP may not be trivial: You need the right model-serving framework and data serialization library. At Jina AI, we’ve always believed in <a href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io">Multimodal AI</a>, and that’s why we’ve optimized Jina and DocArray for this purpose. Serving BLIP-2 is a typical use case for these two projects.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-16.png" class="kg-image" alt="" width="1384" height="786" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-16.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-16.png 1384w" sizes="(min-width: 720px) 720px"><figcaption>Multimodal AI is artificial intelligence that works with multiple modalities at once (e.g. image + text, video + audio, etc), rather than just one single modality.</figcaption></figure><p>Let’s see how it works!</p><h2 id="blip-2">BLIP-2</h2><p>BLIP-2 is a vision-language model proposed in the paper <strong><a href="https://arxiv.org/abs/2301.12597?ref=jina-ai-gmbh.ghost.io">BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models</a>.</strong></p><p>It leverages frozen pre-trained image encoders and LLMs by training a lightweight, 12-layer Transformer encoder in between them, to achieve state-of-the-art performance on various vision-language tasks.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-17.png" class="kg-image" alt="" width="1290" height="580" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-17.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-17.png 1290w" sizes="(min-width: 720px) 720px"><figcaption>Source: <a href="https://arxiv.org/pdf/2301.12597.pdf?ref=jina-ai-gmbh.ghost.io">https://arxiv.org/pdf/2301.12597.pdf</a></figcaption></figure><h2 id="jina-and-docarray">Jina and DocArray</h2><p>Before diving into the code, let’s briefly introduce Jina and DocArray and explain what’s recently been happening with both projects.</p><p><strong>Jina</strong> is an MLOps framework to <strong>build</strong> and <strong>serve</strong> multimodal AI <strong>services,</strong> then <strong>scale</strong> and <strong>deploy</strong> them on the cloud. But recently we’ve been reshaping Jina to serve models more effectively. And in the <a href="https://github.com/jina-ai/jina/releases/tag/v3.14.0?ref=jina-ai-gmbh.ghost.io">3.14 release</a>, we allow users to serve Executors as standalone services using the gRPC protocol. In this post we’ll use those newly released features to serve a BLIP-2 model.</p><p>For data representation and serialization, Jina uses <strong>DocArray</strong>, a library for <strong>unstructured, multimodal data</strong>. It’s optimized for data in transit, in the sense that data can be <a href="https://docs.docarray.org/fundamentals/documentarray/serialization/?ref=jina-ai-gmbh.ghost.io">serialized</a> in several formats including <a href="https://github.com/protocolbuffers/protobuf?ref=jina-ai-gmbh.ghost.io">protobuf</a>. In other words, model input and output can be received/sent over the wire using DocArray formats.</p><p>We’re also reshaping DocArray to better fit multimodal AI use cases. In fact, it’s going through <a href="https://github.com/docarray/docarray/issues/780?ref=jina-ai-gmbh.ghost.io">heavy refactoring</a> with the goal of offering flexible and powerful data formats with DocArray v2.</p><p>Therefore, we’ll use both the current DocArray and the alpha version of DocArray v2 to represent model queries and output (and in doing so you’ll quickly understand why we refactored DocArray!).</p><h2 id="serving-blip-2-with-docarray-and-jina">Serving BLIP-2 with DocArray and Jina</h2><p>Since BLIP-2 uses LLMs, it comes with different open-source language models (i.e, <code>flan-t5</code> and <code>opt</code>). In this blog, we’ll use <code>flan-t5-xl</code>. Let’s start by installing the dependencies:</p><pre><code class="language-bash hljs">pip install jina torch git+https://github.com/huggingface/transformers pillow
 </code></pre><p>Then, we can initialize a <a href="https://docs.jina.ai/concepts/executor/?ref=jina-ai-gmbh.ghost.io">Jina Executor</a> that loads the model:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Executor, Deployment, DocumentArray, requests
 <span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> Blip2Processor, Blip2ForConditionalGeneration
 <span class="hljs-keyword">import</span> torch
@@ -96,4 +96,4 @@
     ), return_type=DocumentArray[Response])
     <span class="hljs-built_in">print</span>(docs[<span class="hljs-number">0</span>].answer)
 </code></pre><pre><code class="hljs language-undefined">two
-</code></pre><h2 id="conclusion">Conclusion</h2><p>Jina lets you build multimodal AI services based on gRPC. It removes the complexity of building a gRPC service by allowing you to define endpoints and request/response schemas in a pythonic way.</p><p>DocArray lets you represent and serialize multimodal data efficiently. For this purpose, it offers predefined multimodal data types and built-in protobuf serialization.</p><p>Thus, Jina and DocArray offer <em><strong>the</strong></em> top-of-the-line tech stack for building multimodal AI services, thanks to pillars like efficient networking and serialization, pythonic API and expressive data types.</p><p>Here are the top takeaways:</p><ul><li>Use Jina <code>Deployment</code> to serve an Executor that wraps your favorite model.</li><li>Use DocArray to represent your unstructured data. You can experiment with DocArray v2 alpha version to enjoy better syntax.</li><li>Bonus: if your model supports batching, try out <a href="https://docs.jina.ai/concepts/executor/dynamic-batching/?ref=jina-ai-gmbh.ghost.io">Jina’s dynamic batching</a> to increase throughput with efficient hardware utilization, or simply explore <a href="https://docs.jina.ai/concepts/flow/scale-out/?ref=jina-ai-gmbh.ghost.io#replicate-executors">Jina scale out features</a>.</li><li>Extra bonus: <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a> will soon release a BLIP API as part of <a href="https://cloud.jina.ai/user/inference?ref=jina-ai-gmbh.ghost.io">its inference service</a> for various vision-language tasks. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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+</code></pre><h2 id="conclusion">Conclusion</h2><p>Jina lets you build multimodal AI services based on gRPC. It removes the complexity of building a gRPC service by allowing you to define endpoints and request/response schemas in a pythonic way.</p><p>DocArray lets you represent and serialize multimodal data efficiently. For this purpose, it offers predefined multimodal data types and built-in protobuf serialization.</p><p>Thus, Jina and DocArray offer <em><strong>the</strong></em> top-of-the-line tech stack for building multimodal AI services, thanks to pillars like efficient networking and serialization, pythonic API and expressive data types.</p><p>Here are the top takeaways:</p><ul><li>Use Jina <code>Deployment</code> to serve an Executor that wraps your favorite model.</li><li>Use DocArray to represent your unstructured data. You can experiment with DocArray v2 alpha version to enjoy better syntax.</li><li>Bonus: if your model supports batching, try out <a href="https://docs.jina.ai/concepts/executor/dynamic-batching/?ref=jina-ai-gmbh.ghost.io">Jina’s dynamic batching</a> to increase throughput with efficient hardware utilization, or simply explore <a href="https://docs.jina.ai/concepts/flow/scale-out/?ref=jina-ai-gmbh.ghost.io#replicate-executors">Jina scale out features</a>.</li><li>Extra bonus: <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a> will soon release a BLIP API as part of <a href="https://cloud.jina.ai/user/inference?ref=jina-ai-gmbh.ghost.io">its inference service</a> for various vision-language tasks. Keep an eye on our <a href="https://jina.ai/slack?ref=jina-ai-gmbh.ghost.io">Slack</a> and <a href="https://jina.ai/community/?ref=jina-ai-gmbh.ghost.io">social media</a> to stay up-to-date!</li></ul></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fmultimodal-visual-question-answering-with-blip-2-and-jina%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Get the Inside Scoop on Neural Search with Our New Book!</title><meta charset="utf-8"><meta name="title" content="Get the Inside Scoop on Neural Search with Our New Book!"><meta name="description" content="If you’re an AI engineer building search systems for any kind of data type – text, Q+A, image, audio, PDF, 3D models, etc. – or a Python developer interested in search or state-of-the-art deep learning techniques, then our new book &quot;Neural Search - From Prototype to Production with Jina&quot; is for you."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/neural-search-from-prototype-to-production-with-jina"><meta property="og:title" content="Get the Inside Scoop on Neural Search with Our New Book!"><meta property="og:description" content="If you’re an AI engineer building search systems for any kind of data type – text, Q+A, image, audio, PDF, 3D models, etc. – or a Python developer interested in search or state-of-the-art deep learning techniques, then our new book &quot;Neural Search - From Prototype to Production with Jina&quot; is for you."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--30--3.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/neural-search-from-prototype-to-production-with-jina"><meta property="twitter:title" content="Get the Inside Scoop on Neural Search with Our New Book!"><meta property="twitter:description" content="If you’re an AI engineer building search systems for any kind of data type – text, Q+A, image, audio, PDF, 3D models, etc. – or a Python developer interested in search or state-of-the-art deep learning techniques, then our new book &quot;Neural Search - From Prototype to Production with Jina&quot; is for you."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--30--3.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Get the Inside Scoop on Neural Search with Our New Book!</title><meta charset="utf-8"><meta name="title" content="Get the Inside Scoop on Neural Search with Our New Book!"><meta name="description" content="If you’re an AI engineer building search systems for any kind of data type – text, Q+A, image, audio, PDF, 3D models, etc. – or a Python developer interested in search or state-of-the-art deep learning techniques, then our new book &quot;Neural Search - From Prototype to Production with Jina&quot; is for you."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/neural-search-from-prototype-to-production-with-jina"><meta property="og:title" content="Get the Inside Scoop on Neural Search with Our New Book!"><meta property="og:description" content="If you’re an AI engineer building search systems for any kind of data type – text, Q+A, image, audio, PDF, 3D models, etc. – or a Python developer interested in search or state-of-the-art deep learning techniques, then our new book &quot;Neural Search - From Prototype to Production with Jina&quot; is for you."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--30--3.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/neural-search-from-prototype-to-production-with-jina"><meta property="twitter:title" content="Get the Inside Scoop on Neural Search with Our New Book!"><meta property="twitter:description" content="If you’re an AI engineer building search systems for any kind of data type – text, Q+A, image, audio, PDF, 3D models, etc. – or a Python developer interested in search or state-of-the-art deep learning techniques, then our new book &quot;Neural Search - From Prototype to Production with Jina&quot; is for you."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--30--3.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Get the Inside Scoop on Neural Search with Our New Book!</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">If you’re an AI engineer building search systems for any kind of data type – text, Q+A, image, audio, PDF, 3D models, etc. – or a Python developer interested in search or state-of-the-art deep learning techniques, then our new book "Neural Search - From Prototype to Production with Jina" is for you.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 09, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>We’re super excited to publish our first book, written by our ML engineers Bo Wang, Cristian Mitroi, Feng Wang, Susana Guzmán, and Shubham Saboo. If you’re an AI engineer building search systems for any kind of data type – text, Q+A, image, audio, PDF, 3D models, etc. – or a Python developer interested in search or state-of-the-art deep learning techniques, then this book is for you.</p><div class="kg-card kg-product-card"><div class="kg-product-card-container"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/smaller.webp" width="250" height="309" class="kg-product-card-image"><div class="kg-product-card-title-container"><h4 class="kg-product-card-title">Neural Search - From Prototype to Production with Jina</h4></div><div class="kg-product-card-description"><p>Build deep learning–powered search systems that you can deploy and manage with ease</p></div><a href="https://www.amazon.com/Neural-Search-Prototype-Production-learning-powered-ebook/dp/B0B7FLRKVW/ref=sr_1_3?crid=ZXM0BC26LCZH&amp;keywords=Neural+search&amp;qid=1665717663&amp;qu=eyJxc2MiOiIwLjgxIiwicXNhIjoiMC4wMCIsInFzcCI6IjAuMDAifQ%3D%3D&amp;s=digital-text&amp;sprefix=neural+searc%2Cdigital-text%2C434&amp;sr=1-3&amp;ref=jina-ai-gmbh.ghost.io" class="kg-product-card-button kg-product-card-btn-accent" target="_blank" rel="noopener noreferrer"><span>Get Your Copy Now!</span></a></div></div><blockquote><em>Neural Search - From Prototype to Production with Jina</em> is a must-have starter pack to understand neural search, and how it works, learn the essential machine learning and math fundamentals needed for neural search and get a great handle on the foundation of vector representation using the open source Jina AI framework. This book is a great tool for learning Jina AI, enabling its adopters to build deep learning search systems that can be designed, deployed, and managed with ease.<br><br>– Dr. Ibrahim Haddad, Executive Director, LF AI &amp; Data &amp; PyTorch Foundation.</blockquote><p>We live in a digital era overflowing with data. Pictures, voice messages, videos, text, and combinations of all of them – we are showered in data of all types and media. When traditional search techniques were first developed, computers rarely dealt with anything other than text. Today this is far from true, but we still haven’t updated our search techniques that much. <strong>Neural search changes all that. It takes advantage of machine learning and uses the latest AI research to deliver better search results across all types of media. </strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina_Book-2.png" class="kg-image" alt="" width="500" height="383"></figure><p>However, as a new technology, neural search requires a range of skills to implement and deploy. Jina is an open-source solution that democratizes AI, making it easier for developers to build end-to-end neural search applications without a specialized background in AI, cloud ops, or backend engineering. It’s designed with Python developers in mind, to help them unlock the full potential of the latest AI technology.</p><p><strong>Get your copy from the link above! </strong>Learn how to build ML-powered search systems that you can deploy and manage with ease.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fneural-search-from-prototype-to-production-with-jina%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Get the Inside Scoop on Neural Search with Our New Book!</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">If you’re an AI engineer building search systems for any kind of data type – text, Q+A, image, audio, PDF, 3D models, etc. – or a Python developer interested in search or state-of-the-art deep learning techniques, then our new book "Neural Search - From Prototype to Production with Jina" is for you.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 09, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>We’re super excited to publish our first book, written by our ML engineers Bo Wang, Cristian Mitroi, Feng Wang, Susana Guzmán, and Shubham Saboo. If you’re an AI engineer building search systems for any kind of data type – text, Q+A, image, audio, PDF, 3D models, etc. – or a Python developer interested in search or state-of-the-art deep learning techniques, then this book is for you.</p><div class="kg-card kg-product-card"><div class="kg-product-card-container"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/smaller.webp" width="250" height="309" class="kg-product-card-image"><div class="kg-product-card-title-container"><h4 class="kg-product-card-title">Neural Search - From Prototype to Production with Jina</h4></div><div class="kg-product-card-description"><p>Build deep learning–powered search systems that you can deploy and manage with ease</p></div><a href="https://www.amazon.com/Neural-Search-Prototype-Production-learning-powered-ebook/dp/B0B7FLRKVW/ref=sr_1_3?crid=ZXM0BC26LCZH&amp;keywords=Neural+search&amp;qid=1665717663&amp;qu=eyJxc2MiOiIwLjgxIiwicXNhIjoiMC4wMCIsInFzcCI6IjAuMDAifQ%3D%3D&amp;s=digital-text&amp;sprefix=neural+searc%2Cdigital-text%2C434&amp;sr=1-3&amp;ref=jina-ai-gmbh.ghost.io" class="kg-product-card-button kg-product-card-btn-accent" target="_blank" rel="noopener noreferrer"><span>Get Your Copy Now!</span></a></div></div><blockquote><em>Neural Search - From Prototype to Production with Jina</em> is a must-have starter pack to understand neural search, and how it works, learn the essential machine learning and math fundamentals needed for neural search and get a great handle on the foundation of vector representation using the open source Jina AI framework. This book is a great tool for learning Jina AI, enabling its adopters to build deep learning search systems that can be designed, deployed, and managed with ease.<br><br>– Dr. Ibrahim Haddad, Executive Director, LF AI &amp; Data &amp; PyTorch Foundation.</blockquote><p>We live in a digital era overflowing with data. Pictures, voice messages, videos, text, and combinations of all of them – we are showered in data of all types and media. When traditional search techniques were first developed, computers rarely dealt with anything other than text. Today this is far from true, but we still haven’t updated our search techniques that much. <strong>Neural search changes all that. It takes advantage of machine learning and uses the latest AI research to deliver better search results across all types of media. </strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina_Book-2.png" class="kg-image" alt="" width="500" height="383"></figure><p>However, as a new technology, neural search requires a range of skills to implement and deploy. Jina is an open-source solution that democratizes AI, making it easier for developers to build end-to-end neural search applications without a specialized background in AI, cloud ops, or backend engineering. It’s designed with Python developers in mind, to help them unlock the full potential of the latest AI technology.</p><p><strong>Get your copy from the link above! </strong>Learn how to build ML-powered search systems that you can deploy and manage with ease.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fneural-search-from-prototype-to-production-with-jina%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>The Paradigm Shift Towards Multimodal AI</title><meta charset="utf-8"><meta name="title" content="The Paradigm Shift Towards Multimodal AI"><meta name="description" content="We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they're right at the starting line of this paradigm shift, and build the applications of the future today."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/paradigm-shift-towards-multimodal-ai"><meta property="og:title" content="The Paradigm Shift Towards Multimodal AI"><meta property="og:description" content="We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they're right at the starting line of this paradigm shift, and build the applications of the future today."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/9.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/paradigm-shift-towards-multimodal-ai"><meta property="twitter:title" content="The Paradigm Shift Towards Multimodal AI"><meta property="twitter:description" content="We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they're right at the starting line of this paradigm shift, and build the applications of the future today."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/9.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="e007990e-aacd-4385-8883-4eebc19c817d" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="e007990e-aacd-4385-8883-4eebc19c817d" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">The Paradigm Shift Towards Multimodal AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they're right at the starting line of this paradigm shift, and build the applications of the future today.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 09, 2022 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Every time I introduce Jina AI and explain what we do, I switch up my narrative depending on who I'm talking to:</p><div class="kg-card kg-callout-card kg-callout-card-white"><div class="kg-callout-emoji">1️⃣</div><div class="kg-callout-text">Jina AI is the MLOps platform for <strong>cross-modal and multimodal</strong> data.</div></div><div class="kg-card kg-callout-card kg-callout-card-white"><div class="kg-callout-emoji">2️⃣</div><div class="kg-callout-text">Jina AI is the MLOps platform for <strong>neural search and generative AI</strong> applications.</div></div><p>The first narrative is data-driven and academic-oriented, aimed at AI researchers. The second is more application-driven and intuitive for practitioners and industry partners. Whatever the narrative, four terms are new to most people:</p><ul><li>Cross-modal</li><li>Multimodal</li><li>Neural search</li><li>Generative AI (sometimes as Creative AI)</li></ul><p>Some people have heard of unstructured data, but what's <em>multimodal</em> data? Some have heard of semantic search, but what on Earth is <em>neural</em> search?</p><p>Most confusingly of all, why lump these four terms together, and why is Jina AI working on one MLOps platform to cover them all?</p><p>This article answers those questions. But I'm impatient. Let's fast-forward to the conclusion: <strong>The AI industry has shifted away from single-modal AI and has entered the era of multimodal AI</strong>, as illustrated below:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing.svg" class="kg-image" alt="" width="300" height="129"><figcaption>Jina AI spectrum on future AI applications</figcaption></figure><p>At Jina AI, our spectrum encompasses cross-modal, multimodal, neural search, and generative AI, covering a significant portion of future AI applications. Our MLOps platform gives businesses and developers the edge while they're right at the starting line of this paradigm shift, and build the applications of the future today.</p><p>In the next sections, we'll review the development of single-modal AI and see how this paradigm shift is happening right beneath our noses.</p><h2 id="single-modal-ai">Single-Modal AI</h2><p>In computer science, "modality" roughly means "data type". When we talk about single-modal AI, we're talking about applying AI to one specific type of data. Most early machine learning works fall into this category. Even today, when you open any machine learning literature, single-modal AI is still the majority of the content.</p><h3 id="natural-language-processing">Natural Language Processing</h3><p>We'll start our look back with natural language processing (NLP). Back in 2010, I published a paper about an improved Gibbs sampling algorithm for the Latent Dirichlet Allocation (LDA) model:</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="http://proceedings.mlr.press/v13/xiao10a/xiao10a.pdf?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image.png" class="kg-image" alt="" width="1214" height="946" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image.png 1214w" sizes="(min-width: 720px) 720px"></a><figcaption>Efficient Collapsed Gibbs Sampling For Latent Dirichlet Allocation, 2010</figcaption></figure><p>Some old machine learning researchers may still remember LDA: a parametric Bayesian model for modeling text corpora. It "clusters" words into topics and represents each document as a combination of topics. For this reason, some people called it a "topic model".</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-1.png" class="kg-image" alt="" width="887" height="616" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-1.png 887w" sizes="(min-width: 720px) 720px"></figure><p>From 2008 to 2012, the topic model was one of the most effective and popular models in the NLP community – it was the BERT/Transformer of its day. Every year at top-tier ML/NLP conferences, many papers would extend or improve the original model. But looking back on it today, it was a pretty "shallow learning" model with a very ad-hoc language modeling approach. It assumed words were generated from a mixture of multinomial distributions. This makes sense for certain specific tasks but isn't general enough for other tasks, domains, or modalities.</p><p>Back in 2010-2020, ad-hoc approaches like this were the norm in NLP. Researchers and engineers developed specialist algorithms, each of which was good at solving one task, and one task only:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing--1-.svg" class="kg-image" alt="" width="300" height="103"><figcaption>Top 20 most common NLP tasks</figcaption></figure><h3 id="computer-vision">Computer Vision</h3><p>Compared to NLP, I came to the field of computer vision (CV) pretty late. While at Zalando in 2017, I published a paper on the <a href="https://github.com/zalandoresearch/fashion-mnist?ref=jina-ai-gmbh.ghost.io">Fashion-MNIST dataset</a>. This dataset is a drop-in replacement of <a href="http://yann.lecun.com/exdb/mnist/?ref=jina-ai-gmbh.ghost.io">Yann LeCun's original MNIST dataset</a> from 1990 (a set of simple handwritten digits for benchmarking computer vision algorithms.) The original MNIST dataset was too trivial for many algorithms – shallow learning algorithms such as logistic regression, decision trees, and support vector machines could easily hit 90% accuracy, leaving little room for deep learning algorithms to shine.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://lh5.googleusercontent.com/_r7f8YZjr7Dmn5UkPTApEQ5ErBUfjdctkvrU8NnoKUZMSNShK5slLbhiuGXTkaOg6j881kOxpLHO2GPFQDkkoWoM5mdRzD4JaG6HYszUs8zuHW8kA0VKN4dwcRyHGlPklAGYmv9oOSuuRsjeUpnnYv9aSRPwa07Y2TVwWp5XhTUBnPsYSSIjj9bcgq2k" width="401" height="401" alt=""></div><div class="kg-gallery-image" style="flex: 1.40123 1 0%;"><img loading="lazy" src="https://lh5.googleusercontent.com/DtjaYApP26Red20WgncOFbfCzjmJVP_nBVhtIFP7AJhzvZNrbvri2VUyYZj01bkhi1LArlROqovoYhfHOc9dMI64I5R89TMaSSNF9lFdwnb3fiaKXExnsv6wUtE94jqJrvyDWhC_xUWEZFwlTqJ2qbcVa-yJZes6jEeKPBYYimaMsW6_ueRAvcQCMrkU" width="454" height="324" alt=""></div></div></div><figcaption><a href="https://scholar.google.com/citations?view_op=view_citation&amp;hl=en&amp;user=jp7swwIAAAAJ&amp;sortby=pubdate&amp;citation_for_view=jp7swwIAAAAJ%3AIWHjjKOFINEC&amp;ref=jina-ai-gmbh.ghost.io">Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms</a>, 2017</figcaption></figure><p>Fashion-MNIST provided a more challenging dataset, allowing researchers to explore, test, and benchmark their algorithms. Today, over 5,000 academic papers have cited Fashion-MNIST in their research on classification, regression, denoising, generation, etc.</p><p>Just as the topic model was only good for NLP, Fashion-MNIST was only good for computer vision. There was almost no information in the dataset that you could leverage for studying other modalities. If you look at common tasks in the CV community between 2010-2020, practically all were single-modality. Like NLP, they all covered one task, and one task only:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing--2-.svg" class="kg-image" alt="" width="300" height="118"><figcaption>Top 20 most common CV tasks</figcaption></figure><h3 id="speech-audio">Speech &amp; Audio</h3><p>Speech and audio machine learning followed the same pattern: Algorithms were designed for ad-hoc tasks around the audio modality. They each performed (all together now!) one task, and one task only:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing--3-.svg" class="kg-image" alt="" width="300" height="118"><figcaption>Top 20 most common acoustic tasks</figcaption></figure><p>One of my earliest attempts at multimodal AI was a paper I published in 2010, where I built a Bayesian model that jointly modeled visual, textual, and acoustic modalities. Once trained, it accomplished two <em>cross-modal</em> retrieval tasks: finding the best-matching images from a sound snippet and vice-versa. I gave these two tasks a very sci-fi name: "artificial synesthesia".</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.27723 1 0%;"><img loading="lazy" src="https://lh3.googleusercontent.com/YXodVhMFpju-zkNTw-5kWskHnO5kHpNLFHItAvLGp7wyyqdOlO-0E2Qcpz01nAL7qPdJLP-1hav3voNWyc86TctMHZk5KgD44t-dCAS8dGoL5Kdo3DjfM6tR2iUHN8PhCQrBYFMSgMubjd2DWeypgKOQ23w7mqJDSLMtX_0fORNDOUZQnmT_SoKnZnf3" width="387" height="303" alt=""></div><div class="kg-gallery-image" style="flex: 2.7971 1 0%;"><img loading="lazy" src="https://lh3.googleusercontent.com/D9eKjn8RwIMF44Ctg1iruWX6rREbhv62Jfc1NT8f3-M7ZNNbYIOECuslvdPiBuVDXooJVeuSZUFV1GB-R2JPqPrrQzoGTZTeKj_KCxl_f7iAeH27Xk-FvUjuIHzZTNEv0gBkkpJagOiFAg7L2ZTkBLvjFOtN5mbqF-1c2aJOhyuNqGVjQdsh3gbLP2XY" width="386" height="138" alt=""></div></div></div><figcaption><a href="http://lear.inrialpes.fr/~verbeek/nips10workshop/2010-Whistler-NIPS-Xiao-Paper.pdf?ref=jina-ai-gmbh.ghost.io">Toward Artificial Synesthesia: Linking Images and Sounds via Words</a>, 2010</figcaption></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh6.googleusercontent.com/vQwxXg_ewRUZ45YDCKf5dR8_1PlT8QishzlgRc9YiXmbeTHNnLXsWGXj9d9JTXC-WE7nSWkKjiHoN0RmG8FLJtMe2CX4Gzbn792SZFcshvDDTOHCNIwPaHfQBAfrANd6MqiBwRQ3gFHwfzQsekR8so6wqlYEqcNX5SDRcNEPwa8QNNQq4iMp2YbmBJkK" class="kg-image" alt="" width="554" height="401"></figure><h2 id="towards-multimodal-ai">Towards Multimodal AI</h2><p>From the examples above, we can see that all single-modal AI algorithms have two things in common:</p><ul><li>Tasks are specific to just one modality (e.g. textual, visual, acoustic, etc).</li><li>Knowledge is learned from and applied to only one modality (i.e. a visual algorithm can only learn from and be applied to images).</li></ul><p>So far I have talked about text, image, audio. There are other modalities such as 3D, video, time series which should be considered as well. If we visualize all tasks from different modalities: We get a cube, where modalities are arranged orthogonally:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing--4-.svg" class="kg-image" alt="" width="300" height="139"><figcaption>Single-modal AI, you can assume the other facets represent the tasks from other modalities&nbsp;</figcaption></figure><p>On the other hand, multimodal AI is like molding this cube into a sphere, erasing boundaries between different modalities, where:</p><ul><li>Tasks are shared and transferred between multiple modalities (so one algorithm can work with images <em>and</em> text <em>and </em>audio).</li><li>Knowledge is learned from and applied to multiple modalities (so an algorithm can learn from <em>textual</em> data and apply that to <em>visual</em> data).</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Textual.svg" class="kg-image" alt="" width="1920" height="1080"><figcaption>Multimodal AI</figcaption></figure><p><strong>The rise of multimodal AI can be attributed to advances in two machine learning techniques: Representation learning and transfer learning. </strong></p><ul><li><em>Representation learning</em> lets models create common representations for all modalities. </li><li><em>Transfer learning</em> lets models first learn fundamental knowledge, and then fine-tune on specific domains.</li></ul><p>Without these techniques, multimodal AI on generic data types would be unfeasible or merely a toy, just like my sound-image paper from back in 2010.</p><p>In 2021 we saw CLIP, a model that captures the alignment between image and text; in 2022, we saw DALL·E 2 and Stable Diffusion generate high-quality images from text prompts. </p><p>The paradigm shift has already started: <strong>In the future we'll see more and more AI applications move beyond one data modality and leverage relationships between different modalities.</strong> Ad-hoc approaches are dying out as boundaries between data modalities become fuzzy and meaningless:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing--8-.svg" class="kg-image" alt="" width="300" height="126"><figcaption>The paradigm shift from single-modal AI to multimodal AI</figcaption></figure><h2 id="the-duality-of-search-creation"><br>The Duality of Search &amp; Creation</h2><p>Search and creation are two essential tasks in multimodal AI. Here, search means <em>neural search</em>, namely searching using deep neural networks. For most people, these two tasks are entirely isolated, and they have been independently studied for many years. Let me point out this: <strong>search and creation are strongly connected and share a duality</strong>. To understand this, let's look at the following examples.</p><p>With multimodal AI, it's simple to use a text or image query to search a dataset of images:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-2.png" class="kg-image" alt="" width="2000" height="602" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/image-2.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Search: <em>find</em> what you need</figcaption></figure><p>Creation is similar. You create a new image from a text prompt or by enriching/inpainting from an existing image:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-4.png" class="kg-image" alt="" width="2000" height="610" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-4.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/image-4.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Create: <em>make</em> what you need</figcaption></figure><p>When grouping these two tasks together and masking out their function names, you can see the two tasks are indistinguishable: Both receive and output the same data type(s). The only difference is that search <em>finds</em> what you need, whereas creation <em>makes</em> what you need:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-5.png" class="kg-image" alt="" width="2000" height="1065" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-5.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-5.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-5.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/image-5.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>DNA is a good analogy: Once you have an organism's DNA, you can build a phylogenetic tree and <em>search</em> for the oldest and most primitive known ancestor. On the other hand, you could inject the DNA into an egg and <em>create</em> something new, just as David creates his own alien creature:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-design--1--1.gif" class="kg-image" alt="" width="1700" height="500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Untitled-design--1--1.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/Untitled-design--1--1.gif 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/Untitled-design--1--1.gif 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-design--1--1.gif 1700w" sizes="(min-width: 720px) 720px"><figcaption>The duality of search and creation under the multimodal AI framework. Movie poster from "<i>Alien: Covenant</i>"</figcaption></figure><p>Or think of Doraemon and Rick. Both help their sidekick with out-of-this-world items to solve their problems. The difference is that Doraemon <em>searches</em> through his pocket for an existing item, whereas Rick <em>creates</em> something new from his garage workshop.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-7.png" class="kg-image" alt="" width="2000" height="817" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-7.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-7.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-7.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-7.png 2366w" sizes="(min-width: 720px) 720px"><figcaption>Doraemon represent neural search, whereas Rick represents generative AI/creative AI</figcaption></figure><p>The duality of search and creation also poses an interesting thought experiment. Imagine living in a world where all images are created by AI rather than humans. Do we still need (neural) search? Namely, do we need to embed images into vectors and then use a vector database to index and sort them? The answer is NO. As the seed and prompts that uniquely represent the image are known before observing the image, <strong>the consequence now becomes the cause</strong>. Contrast this to the classic representation, where learning an image is the cause and representation is the consequence. To search images, we can simply store the seed (an integer) and the prompt (a string), which is nothing more than a good old BM25 or binary search. Of course, we humans appreciate photography and human-made artworks, so that parallel Earth is not our reality (yet). Nonetheless, this thought experiment gives a good reason why neural searchers should care about advances in generative AI, as the old way of handling multimodal data may become obsolete.</p><h2 id="summary">Summary</h2><p>We are on the frontier of a new era in AI, where multimodal learning will soon dominate. This type of learning, combining multiple data types and modalities, has the potential to revolutionize the way we interact with machines. So far, multimodal AI has had great success in fields like computer vision and natural language processing. In future, expect multimodal AI to have an even greater impact. For instance, developing systems that understand the nuances of human communication, or creating more lifelike virtual assistants. The possibilities are endless, and we're just beginning to scratch the surface. So strap in and buckle up for the future, because the best is yet to come!</p><p>Want to work on multimodal AI, neural search, and generative AI? 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Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they're right at the starting line of this paradigm shift, and build the applications of the future today.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 09, 2022 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Every time I introduce Jina AI and explain what we do, I switch up my narrative depending on who I'm talking to:</p><div class="kg-card kg-callout-card kg-callout-card-white"><div class="kg-callout-emoji">1️⃣</div><div class="kg-callout-text">Jina AI is the MLOps platform for <strong>cross-modal and multimodal</strong> data.</div></div><div class="kg-card kg-callout-card kg-callout-card-white"><div class="kg-callout-emoji">2️⃣</div><div class="kg-callout-text">Jina AI is the MLOps platform for <strong>neural search and generative AI</strong> applications.</div></div><p>The first narrative is data-driven and academic-oriented, aimed at AI researchers. The second is more application-driven and intuitive for practitioners and industry partners. Whatever the narrative, four terms are new to most people:</p><ul><li>Cross-modal</li><li>Multimodal</li><li>Neural search</li><li>Generative AI (sometimes as Creative AI)</li></ul><p>Some people have heard of unstructured data, but what's <em>multimodal</em> data? Some have heard of semantic search, but what on Earth is <em>neural</em> search?</p><p>Most confusingly of all, why lump these four terms together, and why is Jina AI working on one MLOps platform to cover them all?</p><p>This article answers those questions. But I'm impatient. Let's fast-forward to the conclusion: <strong>The AI industry has shifted away from single-modal AI and has entered the era of multimodal AI</strong>, as illustrated below:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing.svg" class="kg-image" alt="" width="300" height="129"><figcaption>Jina AI spectrum on future AI applications</figcaption></figure><p>At Jina AI, our spectrum encompasses cross-modal, multimodal, neural search, and generative AI, covering a significant portion of future AI applications. Our MLOps platform gives businesses and developers the edge while they're right at the starting line of this paradigm shift, and build the applications of the future today.</p><p>In the next sections, we'll review the development of single-modal AI and see how this paradigm shift is happening right beneath our noses.</p><h2 id="single-modal-ai">Single-Modal AI</h2><p>In computer science, "modality" roughly means "data type". When we talk about single-modal AI, we're talking about applying AI to one specific type of data. Most early machine learning works fall into this category. Even today, when you open any machine learning literature, single-modal AI is still the majority of the content.</p><h3 id="natural-language-processing">Natural Language Processing</h3><p>We'll start our look back with natural language processing (NLP). Back in 2010, I published a paper about an improved Gibbs sampling algorithm for the Latent Dirichlet Allocation (LDA) model:</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="http://proceedings.mlr.press/v13/xiao10a/xiao10a.pdf?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image.png" class="kg-image" alt="" width="1214" height="946" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image.png 1214w" sizes="(min-width: 720px) 720px"></a><figcaption>Efficient Collapsed Gibbs Sampling For Latent Dirichlet Allocation, 2010</figcaption></figure><p>Some old machine learning researchers may still remember LDA: a parametric Bayesian model for modeling text corpora. It "clusters" words into topics and represents each document as a combination of topics. For this reason, some people called it a "topic model".</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-1.png" class="kg-image" alt="" width="887" height="616" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-1.png 887w" sizes="(min-width: 720px) 720px"></figure><p>From 2008 to 2012, the topic model was one of the most effective and popular models in the NLP community – it was the BERT/Transformer of its day. Every year at top-tier ML/NLP conferences, many papers would extend or improve the original model. But looking back on it today, it was a pretty "shallow learning" model with a very ad-hoc language modeling approach. It assumed words were generated from a mixture of multinomial distributions. This makes sense for certain specific tasks but isn't general enough for other tasks, domains, or modalities.</p><p>Back in 2010-2020, ad-hoc approaches like this were the norm in NLP. Researchers and engineers developed specialist algorithms, each of which was good at solving one task, and one task only:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing--1-.svg" class="kg-image" alt="" width="300" height="103"><figcaption>Top 20 most common NLP tasks</figcaption></figure><h3 id="computer-vision">Computer Vision</h3><p>Compared to NLP, I came to the field of computer vision (CV) pretty late. While at Zalando in 2017, I published a paper on the <a href="https://github.com/zalandoresearch/fashion-mnist?ref=jina-ai-gmbh.ghost.io">Fashion-MNIST dataset</a>. This dataset is a drop-in replacement of <a href="http://yann.lecun.com/exdb/mnist/?ref=jina-ai-gmbh.ghost.io">Yann LeCun's original MNIST dataset</a> from 1990 (a set of simple handwritten digits for benchmarking computer vision algorithms.) The original MNIST dataset was too trivial for many algorithms – shallow learning algorithms such as logistic regression, decision trees, and support vector machines could easily hit 90% accuracy, leaving little room for deep learning algorithms to shine.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://lh5.googleusercontent.com/_r7f8YZjr7Dmn5UkPTApEQ5ErBUfjdctkvrU8NnoKUZMSNShK5slLbhiuGXTkaOg6j881kOxpLHO2GPFQDkkoWoM5mdRzD4JaG6HYszUs8zuHW8kA0VKN4dwcRyHGlPklAGYmv9oOSuuRsjeUpnnYv9aSRPwa07Y2TVwWp5XhTUBnPsYSSIjj9bcgq2k" width="401" height="401" alt=""></div><div class="kg-gallery-image" style="flex: 1.40123 1 0%;"><img loading="lazy" src="https://lh5.googleusercontent.com/DtjaYApP26Red20WgncOFbfCzjmJVP_nBVhtIFP7AJhzvZNrbvri2VUyYZj01bkhi1LArlROqovoYhfHOc9dMI64I5R89TMaSSNF9lFdwnb3fiaKXExnsv6wUtE94jqJrvyDWhC_xUWEZFwlTqJ2qbcVa-yJZes6jEeKPBYYimaMsW6_ueRAvcQCMrkU" width="454" height="324" alt=""></div></div></div><figcaption><a href="https://scholar.google.com/citations?view_op=view_citation&amp;hl=en&amp;user=jp7swwIAAAAJ&amp;sortby=pubdate&amp;citation_for_view=jp7swwIAAAAJ%3AIWHjjKOFINEC&amp;ref=jina-ai-gmbh.ghost.io">Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms</a>, 2017</figcaption></figure><p>Fashion-MNIST provided a more challenging dataset, allowing researchers to explore, test, and benchmark their algorithms. Today, over 5,000 academic papers have cited Fashion-MNIST in their research on classification, regression, denoising, generation, etc.</p><p>Just as the topic model was only good for NLP, Fashion-MNIST was only good for computer vision. There was almost no information in the dataset that you could leverage for studying other modalities. If you look at common tasks in the CV community between 2010-2020, practically all were single-modality. Like NLP, they all covered one task, and one task only:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing--2-.svg" class="kg-image" alt="" width="300" height="118"><figcaption>Top 20 most common CV tasks</figcaption></figure><h3 id="speech-audio">Speech &amp; Audio</h3><p>Speech and audio machine learning followed the same pattern: Algorithms were designed for ad-hoc tasks around the audio modality. They each performed (all together now!) one task, and one task only:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing--3-.svg" class="kg-image" alt="" width="300" height="118"><figcaption>Top 20 most common acoustic tasks</figcaption></figure><p>One of my earliest attempts at multimodal AI was a paper I published in 2010, where I built a Bayesian model that jointly modeled visual, textual, and acoustic modalities. Once trained, it accomplished two <em>cross-modal</em> retrieval tasks: finding the best-matching images from a sound snippet and vice-versa. I gave these two tasks a very sci-fi name: "artificial synesthesia".</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.27723 1 0%;"><img loading="lazy" src="https://lh3.googleusercontent.com/YXodVhMFpju-zkNTw-5kWskHnO5kHpNLFHItAvLGp7wyyqdOlO-0E2Qcpz01nAL7qPdJLP-1hav3voNWyc86TctMHZk5KgD44t-dCAS8dGoL5Kdo3DjfM6tR2iUHN8PhCQrBYFMSgMubjd2DWeypgKOQ23w7mqJDSLMtX_0fORNDOUZQnmT_SoKnZnf3" width="387" height="303" alt=""></div><div class="kg-gallery-image" style="flex: 2.7971 1 0%;"><img loading="lazy" src="https://lh3.googleusercontent.com/D9eKjn8RwIMF44Ctg1iruWX6rREbhv62Jfc1NT8f3-M7ZNNbYIOECuslvdPiBuVDXooJVeuSZUFV1GB-R2JPqPrrQzoGTZTeKj_KCxl_f7iAeH27Xk-FvUjuIHzZTNEv0gBkkpJagOiFAg7L2ZTkBLvjFOtN5mbqF-1c2aJOhyuNqGVjQdsh3gbLP2XY" width="386" height="138" alt=""></div></div></div><figcaption><a href="http://lear.inrialpes.fr/~verbeek/nips10workshop/2010-Whistler-NIPS-Xiao-Paper.pdf?ref=jina-ai-gmbh.ghost.io">Toward Artificial Synesthesia: Linking Images and Sounds via Words</a>, 2010</figcaption></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://lh6.googleusercontent.com/vQwxXg_ewRUZ45YDCKf5dR8_1PlT8QishzlgRc9YiXmbeTHNnLXsWGXj9d9JTXC-WE7nSWkKjiHoN0RmG8FLJtMe2CX4Gzbn792SZFcshvDDTOHCNIwPaHfQBAfrANd6MqiBwRQ3gFHwfzQsekR8so6wqlYEqcNX5SDRcNEPwa8QNNQq4iMp2YbmBJkK" class="kg-image" alt="" width="554" height="401"></figure><h2 id="towards-multimodal-ai">Towards Multimodal AI</h2><p>From the examples above, we can see that all single-modal AI algorithms have two things in common:</p><ul><li>Tasks are specific to just one modality (e.g. textual, visual, acoustic, etc).</li><li>Knowledge is learned from and applied to only one modality (i.e. a visual algorithm can only learn from and be applied to images).</li></ul><p>So far I have talked about text, image, audio. There are other modalities such as 3D, video, time series which should be considered as well. If we visualize all tasks from different modalities: We get a cube, where modalities are arranged orthogonally:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing--4-.svg" class="kg-image" alt="" width="300" height="139"><figcaption>Single-modal AI, you can assume the other facets represent the tasks from other modalities&nbsp;</figcaption></figure><p>On the other hand, multimodal AI is like molding this cube into a sphere, erasing boundaries between different modalities, where:</p><ul><li>Tasks are shared and transferred between multiple modalities (so one algorithm can work with images <em>and</em> text <em>and </em>audio).</li><li>Knowledge is learned from and applied to multiple modalities (so an algorithm can learn from <em>textual</em> data and apply that to <em>visual</em> data).</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Textual.svg" class="kg-image" alt="" width="1920" height="1080"><figcaption>Multimodal AI</figcaption></figure><p><strong>The rise of multimodal AI can be attributed to advances in two machine learning techniques: Representation learning and transfer learning. </strong></p><ul><li><em>Representation learning</em> lets models create common representations for all modalities. </li><li><em>Transfer learning</em> lets models first learn fundamental knowledge, and then fine-tune on specific domains.</li></ul><p>Without these techniques, multimodal AI on generic data types would be unfeasible or merely a toy, just like my sound-image paper from back in 2010.</p><p>In 2021 we saw CLIP, a model that captures the alignment between image and text; in 2022, we saw DALL·E 2 and Stable Diffusion generate high-quality images from text prompts. </p><p>The paradigm shift has already started: <strong>In the future we'll see more and more AI applications move beyond one data modality and leverage relationships between different modalities.</strong> Ad-hoc approaches are dying out as boundaries between data modalities become fuzzy and meaningless:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing--8-.svg" class="kg-image" alt="" width="300" height="126"><figcaption>The paradigm shift from single-modal AI to multimodal AI</figcaption></figure><h2 id="the-duality-of-search-creation"><br>The Duality of Search &amp; Creation</h2><p>Search and creation are two essential tasks in multimodal AI. Here, search means <em>neural search</em>, namely searching using deep neural networks. For most people, these two tasks are entirely isolated, and they have been independently studied for many years. Let me point out this: <strong>search and creation are strongly connected and share a duality</strong>. To understand this, let's look at the following examples.</p><p>With multimodal AI, it's simple to use a text or image query to search a dataset of images:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-2.png" class="kg-image" alt="" width="2000" height="602" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/image-2.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Search: <em>find</em> what you need</figcaption></figure><p>Creation is similar. You create a new image from a text prompt or by enriching/inpainting from an existing image:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-4.png" class="kg-image" alt="" width="2000" height="610" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-4.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/image-4.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Create: <em>make</em> what you need</figcaption></figure><p>When grouping these two tasks together and masking out their function names, you can see the two tasks are indistinguishable: Both receive and output the same data type(s). The only difference is that search <em>finds</em> what you need, whereas creation <em>makes</em> what you need:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-5.png" class="kg-image" alt="" width="2000" height="1065" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-5.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-5.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-5.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/image-5.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>DNA is a good analogy: Once you have an organism's DNA, you can build a phylogenetic tree and <em>search</em> for the oldest and most primitive known ancestor. On the other hand, you could inject the DNA into an egg and <em>create</em> something new, just as David creates his own alien creature:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-design--1--1.gif" class="kg-image" alt="" width="1700" height="500" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Untitled-design--1--1.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/Untitled-design--1--1.gif 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/Untitled-design--1--1.gif 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-design--1--1.gif 1700w" sizes="(min-width: 720px) 720px"><figcaption>The duality of search and creation under the multimodal AI framework. Movie poster from "<i>Alien: Covenant</i>"</figcaption></figure><p>Or think of Doraemon and Rick. Both help their sidekick with out-of-this-world items to solve their problems. The difference is that Doraemon <em>searches</em> through his pocket for an existing item, whereas Rick <em>creates</em> something new from his garage workshop.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-7.png" class="kg-image" alt="" width="2000" height="817" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/image-7.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/image-7.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/image-7.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/image-7.png 2366w" sizes="(min-width: 720px) 720px"><figcaption>Doraemon represent neural search, whereas Rick represents generative AI/creative AI</figcaption></figure><p>The duality of search and creation also poses an interesting thought experiment. Imagine living in a world where all images are created by AI rather than humans. Do we still need (neural) search? Namely, do we need to embed images into vectors and then use a vector database to index and sort them? The answer is NO. As the seed and prompts that uniquely represent the image are known before observing the image, <strong>the consequence now becomes the cause</strong>. Contrast this to the classic representation, where learning an image is the cause and representation is the consequence. To search images, we can simply store the seed (an integer) and the prompt (a string), which is nothing more than a good old BM25 or binary search. Of course, we humans appreciate photography and human-made artworks, so that parallel Earth is not our reality (yet). Nonetheless, this thought experiment gives a good reason why neural searchers should care about advances in generative AI, as the old way of handling multimodal data may become obsolete.</p><h2 id="summary">Summary</h2><p>We are on the frontier of a new era in AI, where multimodal learning will soon dominate. This type of learning, combining multiple data types and modalities, has the potential to revolutionize the way we interact with machines. So far, multimodal AI has had great success in fields like computer vision and natural language processing. In future, expect multimodal AI to have an even greater impact. For instance, developing systems that understand the nuances of human communication, or creating more lifelike virtual assistants. The possibilities are endless, and we're just beginning to scratch the surface. So strap in and buckle up for the future, because the best is yet to come!</p><p>Want to work on multimodal AI, neural search, and generative AI? 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/artificial-general-intelligence-is-cursed-and-science-fiction-isnt-helping" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Artificial General Intelligence is Cursed, And Science Fiction isn't Helping</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">AI is cursed by intellectual hubris, moving goalposts, bad incentives, and science fiction. Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. Navigating enterprise mazes &amp; startup vibes. Where's search headed next?</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">September 01, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/generativejina_mad_men_tv_serie_a_girl_is_looking_at_a_selectio_42a73443-5825-4394-a7ef-9c08294d29b6.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/fine-tuning-gpt-3-5-turbo-a-costly-mirage" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 25, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_modern_geometric_abstract_pattern_featuring_pu_24e4060e-dc76-4186-afb7-94d18d266b41.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>PromptPerfect 0.1 Update</title><meta charset="utf-8"><meta name="title" content="PromptPerfect 0.1 Update"><meta name="description" content="Upgrade your AI-generated content with PromptPerfect 0.1! Faster prompt optimization with ChatGPT API, improved multilingual support, and automatic updates. Try it now!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/promptperfect-0-1-release"><meta property="og:title" content="PromptPerfect 0.1 Update"><meta property="og:description" content="Upgrade your AI-generated content with PromptPerfect 0.1! Faster prompt optimization with ChatGPT API, improved multilingual support, and automatic updates. Try it now!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina-AI-Website-Banners-Templates--84-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/promptperfect-0-1-release"><meta property="twitter:title" content="PromptPerfect 0.1 Update"><meta property="twitter:description" content="Upgrade your AI-generated content with PromptPerfect 0.1! Faster prompt optimization with ChatGPT API, improved multilingual support, and automatic updates. Try it now!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina-AI-Website-Banners-Templates--84-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">PromptPerfect 0.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Upgrade your AI-generated content with PromptPerfect 0.1! Faster prompt optimization with ChatGPT API, improved multilingual support, and automatic updates. Try it now!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 03, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>PromptPerfect is a cutting-edge prompt optimizer designed for large language models (LLMs), large models (LMs) and LMOps. It streamlines prompt engineering, automatically optimizing your prompts for ChatGPT, GPT-3.5, DALLE, and StableDiffusion models. Whether you're a prompt engineer, content creator, or AI developer, PromptPerfect makes prompt optimization easy and accessible. With its intuitive interface and powerful features, PromptPerfect unlocks the full potential of LLMs and LMs, delivering top-quality results every time. Say goodbye to subpar AI-generated content and hello to prompt perfection with PromptPerfect!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate your prompts to perfection</div><div class="kg-bookmark-description">Optimize prompts for ChatGPT, GPT-3.5, DALL-E, StableDiffusion. Automatic prompt engineering done right!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><h2 id="better-performance-and-multilingual-support">Better performance and multilingual support</h2><p>We are excited to announce the release of PromptPerfect 0.1, featuring improved performance and multilingual support. With ChatGPT API integration, prompt optimization is now faster than ever before, allowing you to generate high-quality content in record time. </p><p>We have also improved the multilingual experience by ensuring that the prompt optimization explanation always follows the browser language. Whether you're writing in English, Spanish, French, or any other language, PromptPerfect has you covered.</p><h2 id="update-troubleshooting">Update troubleshooting</h2><p>By default, PromptPerfect updates are done automatically to ensure that you always have access to the latest features and optimizations. However, there may be times when an update fails or you experience issues after an update. In these cases, clearing your browser's local data can often resolve the problem.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 2.07937 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-11.png" width="1310" height="630" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-11.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-11.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-11.png 1310w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.87861 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-12.png" width="1300" height="692" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-12.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-12.png 1300w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Before &amp; After the upgrade. Notice the version and the logo are different.</figcaption></figure><p>If you are using Chrome, please follow the following steps:</p><ol><li>Right-click on the webpage, select "Inspect" in the menu.</li><li>Go to the application tab in the developer console</li><li>Run the following command:</li></ol><pre><code class="language-javascript hljs">caches.<span class="hljs-title function_">keys</span>().<span class="hljs-title function_">then</span>(<span class="hljs-function"><span class="hljs-params">list</span> =&gt;</span> list.<span class="hljs-title function_">map</span>(<span class="hljs-function"><span class="hljs-params">key</span> =&gt;</span> caches.<span class="hljs-title function_">delete</span>(key)))</code></pre><p>Then refresh the page.</p><p>Or, click on <code>Clear Site data</code> button, and make sure <code>unregister service workers</code> is checked. This wont delete your data on the server.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-13.png" class="kg-image" alt="" width="1060" height="1084" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-13.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-13.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-13.png 1060w" sizes="(min-width: 720px) 720px"></figure><p>If you are using other browser, to clear your browser's local data, follow these simple steps:</p><ol><li>Open your browser's settings or preferences menu.</li><li>Navigate to the "Privacy and Security" or "History" section.</li><li>Find the option to clear your browsing data or history.</li><li>Select the option to clear your cache, cookies, and other site data.</li><li>Choose the time range for which you want to clear data (e.g. "Last hour", "Last day", "All time").</li><li>Click "Clear data" or "Clear history".</li><li>Revisit https://promptperfect.jina.ai </li></ol><p>Once you've cleared your browser's local data, try reaccessing PromptPerfect. If you're still experiencing issues, please contact <a href="https://discord.gg/XVcZq4VKsx?ref=jina-ai-gmbh.ghost.io">our Discord channel</a> for further assistance.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/05/promptperfect-streamline-mode.mp4" poster="https://img.spacergif.org/v1/1458x830/0a/spacer.png" width="1458" height="830" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/05/media-thumbnail-ember778.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 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height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/05/promptperfect-first-optimize.mp4" poster="https://img.spacergif.org/v1/1458x830/0a/spacer.png" width="1458" height="830" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/05/media-thumbnail-ember82.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 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24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 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class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 50%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina-AI-Website-Banners-Templates--84-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">PromptPerfect 0.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Upgrade your AI-generated content with PromptPerfect 0.1! Faster prompt optimization with ChatGPT API, improved multilingual support, and automatic updates. Try it now!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 03, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>PromptPerfect is a cutting-edge prompt optimizer designed for large language models (LLMs), large models (LMs) and LMOps. It streamlines prompt engineering, automatically optimizing your prompts for ChatGPT, GPT-3.5, DALLE, and StableDiffusion models. Whether you're a prompt engineer, content creator, or AI developer, PromptPerfect makes prompt optimization easy and accessible. With its intuitive interface and powerful features, PromptPerfect unlocks the full potential of LLMs and LMs, delivering top-quality results every time. Say goodbye to subpar AI-generated content and hello to prompt perfection with PromptPerfect!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate your prompts to perfection</div><div class="kg-bookmark-description">Optimize prompts for ChatGPT, GPT-3.5, DALL-E, StableDiffusion. Automatic prompt engineering done right!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><h2 id="better-performance-and-multilingual-support">Better performance and multilingual support</h2><p>We are excited to announce the release of PromptPerfect 0.1, featuring improved performance and multilingual support. With ChatGPT API integration, prompt optimization is now faster than ever before, allowing you to generate high-quality content in record time. </p><p>We have also improved the multilingual experience by ensuring that the prompt optimization explanation always follows the browser language. Whether you're writing in English, Spanish, French, or any other language, PromptPerfect has you covered.</p><h2 id="update-troubleshooting">Update troubleshooting</h2><p>By default, PromptPerfect updates are done automatically to ensure that you always have access to the latest features and optimizations. However, there may be times when an update fails or you experience issues after an update. In these cases, clearing your browser's local data can often resolve the problem.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 2.07937 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-11.png" width="1310" height="630" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-11.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-11.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-11.png 1310w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.87861 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-12.png" width="1300" height="692" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-12.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-12.png 1300w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Before &amp; After the upgrade. Notice the version and the logo are different.</figcaption></figure><p>If you are using Chrome, please follow the following steps:</p><ol><li>Right-click on the webpage, select "Inspect" in the menu.</li><li>Go to the application tab in the developer console</li><li>Run the following command:</li></ol><pre><code class="language-javascript hljs">caches.<span class="hljs-title function_">keys</span>().<span class="hljs-title function_">then</span>(<span class="hljs-function"><span class="hljs-params">list</span> =&gt;</span> list.<span class="hljs-title function_">map</span>(<span class="hljs-function"><span class="hljs-params">key</span> =&gt;</span> caches.<span class="hljs-title function_">delete</span>(key)))</code></pre><p>Then refresh the page.</p><p>Or, click on <code>Clear Site data</code> button, and make sure <code>unregister service workers</code> is checked. This wont delete your data on the server.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-13.png" class="kg-image" alt="" width="1060" height="1084" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-13.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-13.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-13.png 1060w" sizes="(min-width: 720px) 720px"></figure><p>If you are using other browser, to clear your browser's local data, follow these simple steps:</p><ol><li>Open your browser's settings or preferences menu.</li><li>Navigate to the "Privacy and Security" or "History" section.</li><li>Find the option to clear your browsing data or history.</li><li>Select the option to clear your cache, cookies, and other site data.</li><li>Choose the time range for which you want to clear data (e.g. "Last hour", "Last day", "All time").</li><li>Click "Clear data" or "Clear history".</li><li>Revisit https://promptperfect.jina.ai </li></ol><p>Once you've cleared your browser's local data, try reaccessing PromptPerfect. 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>PromptPerfect: Automatic Prompt Engineering Done Right</title><meta charset="utf-8"><meta name="title" content="PromptPerfect: Automatic Prompt Engineering Done Right"><meta name="description" content="Struggling with manual prompt engineering? Let PromptPerfect automate the process for you! Our cutting-edge tool automatically optimizes prompts for your language models with advanced machine learning techniques. Say goodbye to subpar AI-generated content and hello to prompt perfection!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/promptperfect-prompt-engineering-done-right"><meta property="og:title" content="PromptPerfect: Automatic Prompt Engineering Done Right"><meta property="og:description" content="Struggling with manual prompt engineering? Let PromptPerfect automate the process for you! Our cutting-edge tool automatically optimizes prompts for your language models with advanced machine learning techniques. Say goodbye to subpar AI-generated content and hello to prompt perfection!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina-AI-Website-Banners-Templates--78-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/promptperfect-prompt-engineering-done-right"><meta property="twitter:title" content="PromptPerfect: Automatic Prompt Engineering Done Right"><meta property="twitter:description" content="Struggling with manual prompt engineering? Let PromptPerfect automate the process for you! Our cutting-edge tool automatically optimizes prompts for your language models with advanced machine learning techniques. Say goodbye to subpar AI-generated content and hello to prompt perfection!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Jina-AI-Website-Banners-Templates--78-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">PromptPerfect: Automatic Prompt Engineering Done Right</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Struggling with manual prompt engineering? Let PromptPerfect automate the process for you! Our cutting-edge tool automatically optimizes prompts for your language models with advanced machine learning techniques. Say goodbye to subpar AI-generated content and hello to prompt perfection!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 02, 2023 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Prompt engineering has become a hotly debated topic in Generative AI and LLMs. On the one hand, some experts see it as a "magic sauce" that can significantly enhance the quality of generative AI models. On the other hand, some view prompts as a "tumor" rather than a "cure" that reflects a lack of understanding about the underlying complexities of language and the world.</p><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 464px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1628100261851037696&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fpromptperfect-prompt-engineering-done-right%2F&amp;sessionId=24878933ffcbb1c9780cf4a63f137be6647a3966&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1628100261851037696"></iframe></div>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Struggling with manual prompt engineering? Let PromptPerfect automate the process for you! Our cutting-edge tool automatically optimizes prompts for your language models with advanced machine learning techniques. Say goodbye to subpar AI-generated content and hello to prompt perfection!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 02, 2023 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Prompt engineering has become a hotly debated topic in Generative AI and LLMs. On the one hand, some experts see it as a "magic sauce" that can significantly enhance the quality of generative AI models. On the other hand, some view prompts as a "tumor" rather than a "cure" that reflects a lack of understanding about the underlying complexities of language and the world.</p><figure class="kg-card kg-embed-card"><blockquote class="twitter-tweet"><p lang="en" dir="ltr">I keep seeing people argue that prompt engineering is a bug, not a feature, and will soon be made obsolete by future AI advances<br><br>I very much disagree:<a href="https://t.co/0zQM8hVTMX?ref=jina-ai-gmbh.ghost.io">https://t.co/0zQM8hVTMX</a></p>— Simon Willison (@simonw) <a href="https://twitter.com/simonw/status/1628100261851037696?ref_src=twsrc%5Etfw&amp;ref=jina-ai-gmbh.ghost.io">February 21, 2023</a></blockquote>
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-</figure><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-1" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 436px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-1&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1630611290329686016&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fpromptperfect-prompt-engineering-done-right%2F&amp;sessionId=24878933ffcbb1c9780cf4a63f137be6647a3966&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1630611290329686016"></iframe></div>
+</figure><figure class="kg-card kg-embed-card"><blockquote class="twitter-tweet"><p lang="en" dir="ltr">Yes, the need for prompt engineering is a sign of lack of understanding.<br>No, scaling alone will not fix that. <a href="https://t.co/WV2aYyc2i8?ref=jina-ai-gmbh.ghost.io">https://t.co/WV2aYyc2i8</a></p>— Yann LeCun (@ylecun) <a href="https://twitter.com/ylecun/status/1630611290329686016?ref_src=twsrc%5Etfw&amp;ref=jina-ai-gmbh.ghost.io">February 28, 2023</a></blockquote>
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-</figure><p>The debate over prompt engineering is centered around the crucial role that prompts play in guiding language models (LLMs) or large models (LMs) to generate responses. While other numerical parameters can influence the output of these models, <strong>prompts are often seen as the most natural and intuitive way to provide guidance</strong>. Prompts can take various forms, ranging from simple keywords or phrases to complex and structured sentences. Proponents of prompt engineering argue that carefully designing prompts can help LLMs/LMs produce more coherent, relevant, and contextually appropriate responses. This is especially crucial in fields such as generative arts, chatbots, and virtual assistants, where the quality of the response can significantly impact user satisfaction. By using prompts effectively, one can improve the performance of LLMs/LMs and create more engaging and effective conversational experiences for users.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-1.png" width="512" height="512" alt=""></div></div></div><figcaption>Image Generation on Stable Diffusion 1.5. Left: Burger, trending on Artstation; Right: one (center placed) double cheeseburger with tomato on a napkin seen from front (extra tomato) flag on top</figcaption></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.975839 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-4.png" width="1454" height="1490" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-4.png 1454w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.0701 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-3.png" width="1496" height="1398" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-3.png 1496w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>This left prompt is too vague and does not provide any specific information or guidance for ChatGPT to generate a unique and compelling poem about nature. It can result in a generic or clichéd poem that does not stand out.</figcaption></figure><h2 id="prompt-engineering-is-necessary">Prompt engineering is necessary</h2><p>In many ways, prompt engineering is like you as a human having a conversation with a machine. Like in the real world, when working with others, good communication skills can help you get things done faster and better; effective prompt engineering can help you achieve better results when communicating with an LLM.</p><p>When talking to someone, you need to use language that they understand, express yourself clearly and concisely, and adapt your communication style to the situation and the person you're talking to. Similarly, when designing prompts for an LLM, you need to use language that the model can understand, express your desired outcomes clearly and concisely, and adapt your prompt to the specific task and context.</p><p>However, communicating effectively with an LLM can be much more challenging than talking to a human. LLMs are incapable of understanding nuance, tone, or context in the same way humans do, which means that prompts need to be carefully designed to be unambiguous and easily understood by the model. Additionally, LLMs may have inherent biases or limitations in their language understanding, which can further complicate the prompt engineering process.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-2.png" class="kg-image" alt="" width="1400" height="350" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-2.png 1400w" sizes="(min-width: 720px) 720px"><figcaption>Some prompts are in English but unnatural language. For example, this kind of "Word salad prompts": a <em><em>high-quality photo of a salad with rocket romaine, parmesan cheese, savory grilled chicken breast, hearty croutons, caesar dressing, on a white round plate, on the oak table, extremely long shot, wide shot, 25-degree angle, left side view</em></em></figcaption></figure><h2 id="manual-prompt-engineering-is-hard">Manual prompt engineering is hard </h2><p>Manual prompt engineering is a challenging and time-consuming process that requires a great deal of expertise and skill. In particular:</p><ul><li><strong>Deep understanding of language</strong>: Manual prompt engineering requires a deep understanding of how language works, including its syntax, semantics, and pragmatics. Without this knowledge, it can be difficult to design prompts that effectively guide language models and produce accurate, coherent responses.</li><li><strong>Understanding of language models</strong>: Additionally, manual prompt engineering requires a good understanding of how language models work and the specific characteristics of the model being used. Expertise in one model may not necessarily transfer to another, so a thorough understanding of each model's unique features is essential.</li><li><strong>Vocabulary and pop culture:</strong> A broad vocabulary and familiarity with pop culture references can also be crucial in crafting effective prompts for certain tasks or applications. This allows the prompt designer to tailor their prompts to the specific context and audience, resulting in more engaging and effective responses.</li><li><strong>Challenges for non-native speakers:</strong> Finally, non-native English speakers may face additional challenges in understanding and manipulating the nuances of the English language. This can make it more difficult to design prompts that effectively guide language models and produce accurate, coherent responses.</li></ul><p>Manual prompt engineering can be an iterative process that involves multiple rounds of experimentation, testing, and refinement to achieve optimal results. This can be time-consuming and require significant effort and resources.</p><h2 id="promptperfect-is-automatic-prompt-engineering">PromptPerfect is automatic prompt engineering</h2><p>Now that we've explored the challenges and complexities of manual prompt engineering, you may be wondering if there's a better way to optimize prompts at scale. Fortunately, there is! Allow us to introduce you to PromptPerfect, a cutting-edge prompt optimizer that is designed to help you achieve prompt perfection with ease.</p><figure class="kg-card kg-image-card"><a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-5.png" class="kg-image" alt="" width="1873" height="1081" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-5.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-5.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/03/image-5.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-5.png 1873w" sizes="(min-width: 720px) 720px"></a></figure><p>Our tool streamlines the prompt optimization process, automatically optimizing your prompts for a variety of popular language models, including ChatGPT, GPT-3.5, DALLE, and StableDiffusion.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.715 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-8.png" width="858" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-8.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-8.png 858w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.692866 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-9.png" width="1146" height="1654" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-9.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-9.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-9.png 1146w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.725564 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-10.png" width="1158" height="1596" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-10.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-10.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-10.png 1158w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>With its intuitive interface and powerful features, PromptPerfect can help you unlock the full potential of your LLMs and LMs, delivering top-quality results every time. Whether you're a prompt engineer, content creator, or AI developer, PromptPerfect makes prompt optimization easy and accessible. Say goodbye to subpar AI-generated content and hello to prompt perfection with PromptPerfect!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Try PromptPerfect Now!</a></div><h2 id="technologies-behind-promptperfect">Technologies behind PromptPerfect</h2><p>To optimize prompts for , PromptPerfect uses two advanced machine learning techniques: <strong>reinforcement learning</strong> and <strong>structured in-context learning</strong>. For readers who have followed us since<a href="https://jina.ai/news/seo-is-dead-long-live-llmo/?ref=jina-ai-gmbh.ghost.io"> the SEO is dead article</a>, then you know we are a big fan of in-context learning.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/1.png" class="kg-image" alt="" width="2000" height="1600" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/03/1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/1.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>Reinforcement learning is like a coach that trains players to improve their skills over time. It fine-tunes a pretrained model on a small collection of manually engineered prompts and then trains a prompt policy network that explores optimized prompts of user inputs. For example, when optimizing DALLE/Stable Diffusion's prompts, the goal is to maximize a reward function that balances relevance and aesthetic scores of generated content, much like a coach trains a player to balance different aspects of their performance.</p><p>Structured in-context learning is like a teacher that helps a student learn from multiple examples. But instead of concatenating all demonstrations together, PromptPerfect divides a large number of demonstrations into multiple groups, which the language model independently encodes. This allows PromptPerfect to use many more examples to teach the model, resulting in more accurate and effective prompts. By combining these two techniques, PromptPerfect can optimize prompts for a wide range of language models with improved efficiency and accuracy, like a coach and teacher working together to train a top-performing athlete.</p><h2 id="elevate-your-prompts-to-perfection-now">Elevate your prompts to perfection, now!</h2><p>In this blog post, we've explored some of the challenges and complexities of manual prompt engineering, as well as the advanced machine learning techniques that PromptPerfect uses to automate this process. We've only scratched the surface of the technology behind PromptPerfect, and in future blog posts, we'll dive deeper into the details and explore the latest developments in prompt optimization.</p><p>So why wait? Start using PromptPerfect today and experience the power of optimized prompts for yourself. Say goodbye to subpar AI-generated content and hello to prompt perfection with PromptPerfect!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fpromptperfect-prompt-engineering-done-right%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+</figure><p>The debate over prompt engineering is centered around the crucial role that prompts play in guiding language models (LLMs) or large models (LMs) to generate responses. While other numerical parameters can influence the output of these models, <strong>prompts are often seen as the most natural and intuitive way to provide guidance</strong>. Prompts can take various forms, ranging from simple keywords or phrases to complex and structured sentences. Proponents of prompt engineering argue that carefully designing prompts can help LLMs/LMs produce more coherent, relevant, and contextually appropriate responses. This is especially crucial in fields such as generative arts, chatbots, and virtual assistants, where the quality of the response can significantly impact user satisfaction. By using prompts effectively, one can improve the performance of LLMs/LMs and create more engaging and effective conversational experiences for users.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-1.png" width="512" height="512" alt=""></div></div></div><figcaption>Image Generation on Stable Diffusion 1.5. Left: Burger, trending on Artstation; Right: one (center placed) double cheeseburger with tomato on a napkin seen from front (extra tomato) flag on top</figcaption></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-4.png" width="1454" height="1490" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-4.png 1454w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-3.png" width="1496" height="1398" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-3.png 1496w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>This left prompt is too vague and does not provide any specific information or guidance for ChatGPT to generate a unique and compelling poem about nature. It can result in a generic or clichéd poem that does not stand out.</figcaption></figure><h2 id="prompt-engineering-is-necessary">Prompt engineering is necessary</h2><p>In many ways, prompt engineering is like you as a human having a conversation with a machine. Like in the real world, when working with others, good communication skills can help you get things done faster and better; effective prompt engineering can help you achieve better results when communicating with an LLM.</p><p>When talking to someone, you need to use language that they understand, express yourself clearly and concisely, and adapt your communication style to the situation and the person you're talking to. Similarly, when designing prompts for an LLM, you need to use language that the model can understand, express your desired outcomes clearly and concisely, and adapt your prompt to the specific task and context.</p><p>However, communicating effectively with an LLM can be much more challenging than talking to a human. LLMs are incapable of understanding nuance, tone, or context in the same way humans do, which means that prompts need to be carefully designed to be unambiguous and easily understood by the model. Additionally, LLMs may have inherent biases or limitations in their language understanding, which can further complicate the prompt engineering process.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-2.png" class="kg-image" alt="" width="1400" height="350" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-2.png 1400w" sizes="(min-width: 720px) 720px"><figcaption>Some prompts are in English but unnatural language. For example, this kind of "Word salad prompts": a <em><em>high-quality photo of a salad with rocket romaine, parmesan cheese, savory grilled chicken breast, hearty croutons, caesar dressing, on a white round plate, on the oak table, extremely long shot, wide shot, 25-degree angle, left side view</em></em></figcaption></figure><h2 id="manual-prompt-engineering-is-hard">Manual prompt engineering is hard </h2><p>Manual prompt engineering is a challenging and time-consuming process that requires a great deal of expertise and skill. In particular:</p><ul><li><strong>Deep understanding of language</strong>: Manual prompt engineering requires a deep understanding of how language works, including its syntax, semantics, and pragmatics. Without this knowledge, it can be difficult to design prompts that effectively guide language models and produce accurate, coherent responses.</li><li><strong>Understanding of language models</strong>: Additionally, manual prompt engineering requires a good understanding of how language models work and the specific characteristics of the model being used. Expertise in one model may not necessarily transfer to another, so a thorough understanding of each model's unique features is essential.</li><li><strong>Vocabulary and pop culture:</strong> A broad vocabulary and familiarity with pop culture references can also be crucial in crafting effective prompts for certain tasks or applications. This allows the prompt designer to tailor their prompts to the specific context and audience, resulting in more engaging and effective responses.</li><li><strong>Challenges for non-native speakers:</strong> Finally, non-native English speakers may face additional challenges in understanding and manipulating the nuances of the English language. This can make it more difficult to design prompts that effectively guide language models and produce accurate, coherent responses.</li></ul><p>Manual prompt engineering can be an iterative process that involves multiple rounds of experimentation, testing, and refinement to achieve optimal results. This can be time-consuming and require significant effort and resources.</p><h2 id="promptperfect-is-automatic-prompt-engineering">PromptPerfect is automatic prompt engineering</h2><p>Now that we've explored the challenges and complexities of manual prompt engineering, you may be wondering if there's a better way to optimize prompts at scale. Fortunately, there is! Allow us to introduce you to PromptPerfect, a cutting-edge prompt optimizer that is designed to help you achieve prompt perfection with ease.</p><figure class="kg-card kg-image-card"><a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-5.png" class="kg-image" alt="" width="1873" height="1081" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-5.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-5.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/03/image-5.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-5.png 1873w" sizes="(min-width: 720px) 720px"></a></figure><p>Our tool streamlines the prompt optimization process, automatically optimizing your prompts for a variety of popular language models, including ChatGPT, GPT-3.5, DALLE, and StableDiffusion.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-8.png" width="858" height="1200" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-8.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-8.png 858w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-9.png" width="1146" height="1654" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-9.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-9.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-9.png 1146w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-10.png" width="1158" height="1596" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-10.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-10.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-10.png 1158w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>With its intuitive interface and powerful features, PromptPerfect can help you unlock the full potential of your LLMs and LMs, delivering top-quality results every time. Whether you're a prompt engineer, content creator, or AI developer, PromptPerfect makes prompt optimization easy and accessible. Say goodbye to subpar AI-generated content and hello to prompt perfection with PromptPerfect!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Try PromptPerfect Now!</a></div><h2 id="technologies-behind-promptperfect">Technologies behind PromptPerfect</h2><p>To optimize prompts for , PromptPerfect uses two advanced machine learning techniques: <strong>reinforcement learning</strong> and <strong>structured in-context learning</strong>. For readers who have followed us since<a href="https://jina.ai/news/seo-is-dead-long-live-llmo/?ref=jina-ai-gmbh.ghost.io"> the SEO is dead article</a>, then you know we are a big fan of in-context learning.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/1.png" class="kg-image" alt="" width="2000" height="1600" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/03/1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/1.png 2000w" sizes="(min-width: 720px) 720px"></figure><p>Reinforcement learning is like a coach that trains players to improve their skills over time. It fine-tunes a pretrained model on a small collection of manually engineered prompts and then trains a prompt policy network that explores optimized prompts of user inputs. For example, when optimizing DALLE/Stable Diffusion's prompts, the goal is to maximize a reward function that balances relevance and aesthetic scores of generated content, much like a coach trains a player to balance different aspects of their performance.</p><p>Structured in-context learning is like a teacher that helps a student learn from multiple examples. But instead of concatenating all demonstrations together, PromptPerfect divides a large number of demonstrations into multiple groups, which the language model independently encodes. This allows PromptPerfect to use many more examples to teach the model, resulting in more accurate and effective prompts. By combining these two techniques, PromptPerfect can optimize prompts for a wide range of language models with improved efficiency and accuracy, like a coach and teacher working together to train a top-performing athlete.</p><h2 id="elevate-your-prompts-to-perfection-now">Elevate your prompts to perfection, now!</h2><p>In this blog post, we've explored some of the challenges and complexities of manual prompt engineering, as well as the advanced machine learning techniques that PromptPerfect uses to automate this process. We've only scratched the surface of the technology behind PromptPerfect, and in future blog posts, we'll dive deeper into the details and explore the latest developments in prompt optimization.</p><p>So why wait? Start using PromptPerfect today and experience the power of optimized prompts for yourself. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>PromptPerfect's LLM-as-a-Database is Blurring the Boundaries of Search vs. Generation</title><meta charset="utf-8"><meta name="title" content="PromptPerfect's LLM-as-a-Database is Blurring the Boundaries of Search vs. Generation"><meta name="description" content="Diving into PromptPerfect's LLM-as-a-database: a middle ground between few-shot prompts and RAG. Its nuanced approach outshines GPT-4 in complex queries. Evolution in action."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/promptperfects-llm-database-blurring-boundaries-search-vs-generation"><meta property="og:title" content="PromptPerfect's LLM-as-a-Database is Blurring the Boundaries of Search vs. Generation"><meta property="og:description" content="Diving into PromptPerfect's LLM-as-a-database: a middle ground between few-shot prompts and RAG. Its nuanced approach outshines GPT-4 in complex queries. Evolution in action."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--4-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/promptperfects-llm-database-blurring-boundaries-search-vs-generation"><meta property="twitter:title" content="PromptPerfect's LLM-as-a-Database is Blurring the Boundaries of Search vs. Generation"><meta property="twitter:description" content="Diving into PromptPerfect's LLM-as-a-database: a middle ground between few-shot prompts and RAG. Its nuanced approach outshines GPT-4 in complex queries. Evolution in action."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--4-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">PromptPerfect's LLM-as-a-Database is Blurring the Boundaries of Search vs. Generation</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Diving into PromptPerfect's LLM-as-a-database: a middle ground between few-shot prompts and RAG. Its nuanced approach outshines GPT-4 in complex queries. Evolution in action.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 11, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the intricate world of generative AI, boundaries are akin to shifting sands, constantly reshaped by the winds of innovation. Last November, we introduced a fresh perspective with "<a href="https://jina.ai/news/search-is-overfitted-create-create-is-underfitted-search/?ref=jina-ai-gmbh.ghost.io">Search is Overfitted Create; Create is Underfitted Search</a>", urging the community to view these boundaries in a new light. Now, with PromptPerfect's "LLM as a database", we're not merely iterating on a trend; we're materializing our forward-thinking philosophy, crafting tools that resonate with our envisioned future of the generative AI landscape.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, MidJourney and StableDiffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficienc…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><h2 id="a-spectrum-not-a-dichotomy">A Spectrum, Not a Dichotomy</h2><p>Historically, we've perceived search and creation as two separate realms. But as the generative AI age progresses, it's becoming clear that they're more interconnected than we once believed. Search, in its most rigid form, <strong>can be seen as an overfitted version of creation</strong>, while creation, with its boundless potential, <strong>can be viewed as an underfitted form of search</strong>. PromptPerfect's new feature is a nod to this interconnectedness, offering a seamless blend of both.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/search-is-overfitted-create-create-is-underfitted-search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Search is Overfitted Create; Create is Underfitted Search</div><div class="kg-bookmark-description">The biggest competition of neural search may come from a technology that doesn’t even need embeddings as an intermediate representation – an end-to-end technology that directly returns the result you want.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--38-.png" alt=""></div></a></figure><h2 id="how-to-use-llm-as-a-database-feature-in-promptperfect">How to use "LLM as a Database" Feature in PromptPerfect</h2><p>The beauty of the "LLM as a database" feature lies in its adaptability. Users can slide between the exactness of search and the novelty of creation, ensuring a tailored experience that meets specific needs.</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/09/promptperfect-database2-1.mp4" poster="https://img.spacergif.org/v1/1422x962/0a/spacer.png" width="1422" height="962" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/09/media-thumbnail-ember319.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>PromptPerfect's LLM as a database in action.</figcaption></figure><p>Here's a step-by-step breakdown of how users can navigate and leverage this feature:</p><ol><li><strong>Accessing the Feature</strong>: Upon opening PromptPerfect, users can easily locate and click on the "LLM as a database" tab.</li><li><strong>Database Creation</strong>: Users are presented with the option to create a new database. Here, they can specify which backend LLM they wish to use. Whether it's gpt3.5turbo, gpt4, claude2, llama2, or any other available model, the choice is at their fingertips.</li><li><strong>Data Import</strong>: Flexibility is key. Users can either bulk import their key-value pairs into the database or choose to manually add them one by one, catering to both large-scale and smaller, more specific projects.</li><li><strong>Deployment</strong>: Once satisfied with their database, users can deploy it in production. They have the option to make it public or keep it private, requiring a token for access. This ensures both accessibility and security, depending on the user's preference.</li><li><strong>Querying the Database</strong>: The real magic happens here. Users can query their database using curl, Python, or Javascript through a straightforward API. If the queried key exists in the database, it returns the corresponding value. But the standout feature is its ability to interpolate when faced with an unfamiliar key. Instead of returning an error or a blank, the system intelligently draws from existing key-value pairs to generate and return a plausible value.</li></ol><p>This user-centric design ensures that while the technology behind "LLM as a database" is complex, interacting with it is straightforward and intuitive. It's a blend of advanced tech with user-friendly design, making it accessible to both tech-savvy individuals and those less familiar with the intricacies of LLMs.</p><h2 id="what-can-llm-as-a-database-do-a-glimpse-into-examples">What Can "LLM as a Database" do: a Glimpse into Examples</h2><p>To further elucidate the potential of the "LLM as a database" feature, PromptPerfect has incorporated two built-in examples that showcase its versatility and depth:</p><h4 id="how-to-build-a-chatbot-from-a-faq-list">How to build a chatbot from a FAQ list?</h4><p>Drawing from real-world needs, we've imported all the FAQ entries from our internship page. This provides users with an interactive bot that can answer any query related to our internship program. It's a testament to how businesses can streamline customer or user interactions, ensuring that queries are addressed promptly and accurately.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-3.png" class="kg-image" alt="" width="2000" height="1025" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-3.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/09/image-3.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>The FAQ question answer pairs we imported from: https://jina.ai/internship/</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-4.png" class="kg-image" alt="" width="2000" height="499" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-4.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/09/image-4.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>The output of "can i get some kind of recommendation letter after the internship?" from the database. This question does not exist in the pre-filled entries, but its answer can be derived from the database.</figcaption></figure><h4 id="how-to-build-a-translator-for-mathematical-expressions">How to build a translator for mathematical expressions?</h4><p>Delving into a more complex domain, we've built a database that bridges the gap between natural language descriptions of mathematical transformations and their matrix representations. This isn't just about translating words into numbers; it's about understanding the underlying mathematical concepts and accurately representing them.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-5.png" class="kg-image" alt="" width="2000" height="1015" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-5.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-5.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-5.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/09/image-5.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>For instance, consider the task of translating an English description of a transformation in $R^2$ into its matrix form. The system is trained with a variety of sequence pairs, such as:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">PromptPerfect's LLM-as-a-Database is Blurring the Boundaries of Search vs. Generation</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Diving into PromptPerfect's LLM-as-a-database: a middle ground between few-shot prompts and RAG. Its nuanced approach outshines GPT-4 in complex queries. Evolution in action.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 11, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the intricate world of generative AI, boundaries are akin to shifting sands, constantly reshaped by the winds of innovation. Last November, we introduced a fresh perspective with "<a href="https://jina.ai/news/search-is-overfitted-create-create-is-underfitted-search/?ref=jina-ai-gmbh.ghost.io">Search is Overfitted Create; Create is Underfitted Search</a>", urging the community to view these boundaries in a new light. Now, with PromptPerfect's "LLM as a database", we're not merely iterating on a trend; we're materializing our forward-thinking philosophy, crafting tools that resonate with our envisioned future of the generative AI landscape.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, MidJourney and StableDiffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficienc…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><h2 id="a-spectrum-not-a-dichotomy">A Spectrum, Not a Dichotomy</h2><p>Historically, we've perceived search and creation as two separate realms. But as the generative AI age progresses, it's becoming clear that they're more interconnected than we once believed. Search, in its most rigid form, <strong>can be seen as an overfitted version of creation</strong>, while creation, with its boundless potential, <strong>can be viewed as an underfitted form of search</strong>. PromptPerfect's new feature is a nod to this interconnectedness, offering a seamless blend of both.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/search-is-overfitted-create-create-is-underfitted-search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Search is Overfitted Create; Create is Underfitted Search</div><div class="kg-bookmark-description">The biggest competition of neural search may come from a technology that doesn’t even need embeddings as an intermediate representation – an end-to-end technology that directly returns the result you want.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--38-.png" alt=""></div></a></figure><h2 id="how-to-use-llm-as-a-database-feature-in-promptperfect">How to use "LLM as a Database" Feature in PromptPerfect</h2><p>The beauty of the "LLM as a database" feature lies in its adaptability. Users can slide between the exactness of search and the novelty of creation, ensuring a tailored experience that meets specific needs.</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/09/promptperfect-database2-1.mp4" poster="https://img.spacergif.org/v1/1422x962/0a/spacer.png" width="1422" height="962" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/09/media-thumbnail-ember319.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>PromptPerfect's LLM as a database in action.</figcaption></figure><p>Here's a step-by-step breakdown of how users can navigate and leverage this feature:</p><ol><li><strong>Accessing the Feature</strong>: Upon opening PromptPerfect, users can easily locate and click on the "LLM as a database" tab.</li><li><strong>Database Creation</strong>: Users are presented with the option to create a new database. Here, they can specify which backend LLM they wish to use. Whether it's gpt3.5turbo, gpt4, claude2, llama2, or any other available model, the choice is at their fingertips.</li><li><strong>Data Import</strong>: Flexibility is key. Users can either bulk import their key-value pairs into the database or choose to manually add them one by one, catering to both large-scale and smaller, more specific projects.</li><li><strong>Deployment</strong>: Once satisfied with their database, users can deploy it in production. They have the option to make it public or keep it private, requiring a token for access. This ensures both accessibility and security, depending on the user's preference.</li><li><strong>Querying the Database</strong>: The real magic happens here. Users can query their database using curl, Python, or Javascript through a straightforward API. If the queried key exists in the database, it returns the corresponding value. But the standout feature is its ability to interpolate when faced with an unfamiliar key. Instead of returning an error or a blank, the system intelligently draws from existing key-value pairs to generate and return a plausible value.</li></ol><p>This user-centric design ensures that while the technology behind "LLM as a database" is complex, interacting with it is straightforward and intuitive. It's a blend of advanced tech with user-friendly design, making it accessible to both tech-savvy individuals and those less familiar with the intricacies of LLMs.</p><h2 id="what-can-llm-as-a-database-do-a-glimpse-into-examples">What Can "LLM as a Database" do: a Glimpse into Examples</h2><p>To further elucidate the potential of the "LLM as a database" feature, PromptPerfect has incorporated two built-in examples that showcase its versatility and depth:</p><h4 id="how-to-build-a-chatbot-from-a-faq-list">How to build a chatbot from a FAQ list?</h4><p>Drawing from real-world needs, we've imported all the FAQ entries from our internship page. This provides users with an interactive bot that can answer any query related to our internship program. It's a testament to how businesses can streamline customer or user interactions, ensuring that queries are addressed promptly and accurately.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-3.png" class="kg-image" alt="" width="2000" height="1025" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-3.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/09/image-3.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>The FAQ question answer pairs we imported from: https://jina.ai/internship/</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-4.png" class="kg-image" alt="" width="2000" height="499" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-4.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/09/image-4.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>The output of "can i get some kind of recommendation letter after the internship?" from the database. This question does not exist in the pre-filled entries, but its answer can be derived from the database.</figcaption></figure><h4 id="how-to-build-a-translator-for-mathematical-expressions">How to build a translator for mathematical expressions?</h4><p>Delving into a more complex domain, we've built a database that bridges the gap between natural language descriptions of mathematical transformations and their matrix representations. This isn't just about translating words into numbers; it's about understanding the underlying mathematical concepts and accurately representing them.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-5.png" class="kg-image" alt="" width="2000" height="1015" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-5.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-5.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-5.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/09/image-5.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>For instance, consider the task of translating an English description of a transformation in $R^2$ into its matrix form. The system is trained with a variety of sequence pairs, such as:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
     <span class="hljs-punctuation">{</span><span class="hljs-attr">"input"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"Rotation by 90 degrees counterclockwise."</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"output"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"0 -1; 1 0"</span><span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
     <span class="hljs-punctuation">{</span><span class="hljs-attr">"input"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"Scaling by a factor of 2 in the x-direction."</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"output"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"2 0; 0 1"</span><span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
     <span class="hljs-punctuation">{</span><span class="hljs-attr">"input"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"Reflection about the y-axis."</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"output"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"-1 0; 0 1"</span><span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
     <span class="hljs-punctuation">{</span><span class="hljs-attr">"input"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"Shear parallel to the x-axis with a factor of 2."</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"output"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"1 2; 0 1"</span><span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
     ...
 <span class="hljs-punctuation">]</span>
-</code></pre><p>This example underscores the depth of understanding the system possesses, and its ability to handle intricate tasks that require both linguistic and mathematical prowess.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.963912 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled.png" width="1656" height="1718" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Untitled.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/Untitled.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/Untitled.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled.png 1656w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 2.09424 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-2.png" width="2000" height="955" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Untitled-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/Untitled-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/Untitled-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-2.png 2060w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Compare the output of GPT-4 and PromptPerfect's LLM-as-a-database on the query "Rotation by 45 degrees counterclockwise followed by a shear parallel to the x-axis with a factor of 2, and then a scaling by a factor of 2 in the y-direction." One can clearly see PromptPerfect's output outperforms GPT4's.</figcaption></figure><p>These built-in examples serve as a starting point, inspiring users to envision and implement their own unique use cases. Whether it's simplifying customer interactions or tackling specialized tasks, the "LLM as a database" feature offers a canvas for innovation.</p><h3 id="practical-applications-you-can-build-with-llm-as-a-database">Practical Applications You Can Build with "LLM as a Database"</h3><ul><li><strong>Revolutionizing Customer Support</strong>: Instead of static responses, imagine a system that evolves with every interaction, learning and improvising, ensuring customers always receive relevant solutions.</li><li><strong>Elevating FAQ Bots</strong>: These aren't just chatbots. They're dynamic tools that can craft responses on-the-fly, ensuring every user query gets a tailored answer.</li><li><strong>Enhancing AI Interactions</strong>: Agents that recall past interactions and adapt to future ones, offering a user experience that's constantly refined.</li></ul><h2 id="comparing-llm-as-a-database-vs-few-shot-learning-and-rag">Comparing "LLM as a Database" vs. Few-shot Learning and RAG</h2><p>In the intricate tapestry of machine learning methodologies, understanding the nuances and positioning of new techniques relative to established paradigms is crucial. The "LLM as a database" feature introduced by PromptPerfect offers a unique perspective, and it's essential to discern its place amidst the prevailing technologies.</p><ol><li><strong>Few-shot Learning</strong>: Traditional few-shot learning operates on the principle of leveraging a limited set of examples to guide the model's response generation. It's a method that emphasizes the importance of context, allowing models to generate relevant outputs based on a handful of guiding examples. While powerful in its own right, few-shot learning is primarily context-driven.</li><li><strong>Retrieval-augmented Generation (RAG)</strong>: At the other end of the spectrum, RAG employs external datastores to enrich the prompt, pulling from vast repositories of information to enhance the generated response. It's a methodology that emphasizes comprehensive data retrieval, ensuring that the model's outputs are informed by a wide array of external data.</li><li><strong>"LLM as a Database" - Striking a Balance</strong>: PromptPerfect's "LLM as a database" feature can be visualized as occupying the middle ground between few-shot learning and RAG. It integrates the context-driven approach of few-shot learning with the data-rich capabilities of a database. Users can leverage the richness of key-value pairs for precise responses, while also benefiting from the model's ability to interpolate and generate insights. Moreover, the architecture of "LLM as a database" holds the potential to transition towards a full RAG system, offering users the flexibility to harness extensive external datastores when needed.</li></ol><p>In essence, the "LLM as a database" feature doesn't seek to replace or overshadow few-shot learning or RAG. Instead, it offers a harmonized approach, bridging the gap between context-driven generation and extensive data retrieval. It's a testament to the evolving nature of machine learning, where hybrid methodologies can harness the strengths of established paradigms to offer enhanced capabilities.</p><h2 id="final-thoughts">Final Thoughts</h2><p>PromptPerfect's "LLM as a database" isn't just a feature; it's a thoughtful exploration of the evolving relationship between search and creation. It's an invitation to see beyond traditional boundaries and to experience a tool that adapts to the user's needs. As we continue to navigate the generative AI age, innovations like these not only enhance our experiences but also challenge us to rethink our established paradigms.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fpromptperfects-llm-database-blurring-boundaries-search-vs-generation%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; 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+</code></pre><p>This example underscores the depth of understanding the system possesses, and its ability to handle intricate tasks that require both linguistic and mathematical prowess.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.963912 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled.png" width="1656" height="1718" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Untitled.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/Untitled.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/Untitled.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled.png 1656w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 2.09424 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-2.png" width="2000" height="955" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Untitled-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/Untitled-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/Untitled-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-2.png 2060w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Compare the output of GPT-4 and PromptPerfect's LLM-as-a-database on the query "Rotation by 45 degrees counterclockwise followed by a shear parallel to the x-axis with a factor of 2, and then a scaling by a factor of 2 in the y-direction." One can clearly see PromptPerfect's output outperforms GPT4's.</figcaption></figure><p>These built-in examples serve as a starting point, inspiring users to envision and implement their own unique use cases. Whether it's simplifying customer interactions or tackling specialized tasks, the "LLM as a database" feature offers a canvas for innovation.</p><h3 id="practical-applications-you-can-build-with-llm-as-a-database">Practical Applications You Can Build with "LLM as a Database"</h3><ul><li><strong>Revolutionizing Customer Support</strong>: Instead of static responses, imagine a system that evolves with every interaction, learning and improvising, ensuring customers always receive relevant solutions.</li><li><strong>Elevating FAQ Bots</strong>: These aren't just chatbots. They're dynamic tools that can craft responses on-the-fly, ensuring every user query gets a tailored answer.</li><li><strong>Enhancing AI Interactions</strong>: Agents that recall past interactions and adapt to future ones, offering a user experience that's constantly refined.</li></ul><h2 id="comparing-llm-as-a-database-vs-few-shot-learning-and-rag">Comparing "LLM as a Database" vs. Few-shot Learning and RAG</h2><p>In the intricate tapestry of machine learning methodologies, understanding the nuances and positioning of new techniques relative to established paradigms is crucial. The "LLM as a database" feature introduced by PromptPerfect offers a unique perspective, and it's essential to discern its place amidst the prevailing technologies.</p><ol><li><strong>Few-shot Learning</strong>: Traditional few-shot learning operates on the principle of leveraging a limited set of examples to guide the model's response generation. It's a method that emphasizes the importance of context, allowing models to generate relevant outputs based on a handful of guiding examples. While powerful in its own right, few-shot learning is primarily context-driven.</li><li><strong>Retrieval-augmented Generation (RAG)</strong>: At the other end of the spectrum, RAG employs external datastores to enrich the prompt, pulling from vast repositories of information to enhance the generated response. It's a methodology that emphasizes comprehensive data retrieval, ensuring that the model's outputs are informed by a wide array of external data.</li><li><strong>"LLM as a Database" - Striking a Balance</strong>: PromptPerfect's "LLM as a database" feature can be visualized as occupying the middle ground between few-shot learning and RAG. It integrates the context-driven approach of few-shot learning with the data-rich capabilities of a database. Users can leverage the richness of key-value pairs for precise responses, while also benefiting from the model's ability to interpolate and generate insights. Moreover, the architecture of "LLM as a database" holds the potential to transition towards a full RAG system, offering users the flexibility to harness extensive external datastores when needed.</li></ol><p>In essence, the "LLM as a database" feature doesn't seek to replace or overshadow few-shot learning or RAG. Instead, it offers a harmonized approach, bridging the gap between context-driven generation and extensive data retrieval. It's a testament to the evolving nature of machine learning, where hybrid methodologies can harness the strengths of established paradigms to offer enhanced capabilities.</p><h2 id="final-thoughts">Final Thoughts</h2><p>PromptPerfect's "LLM as a database" isn't just a feature; it's a thoughtful exploration of the evolving relationship between search and creation. It's an invitation to see beyond traditional boundaries and to experience a tool that adapts to the user's needs. As we continue to navigate the generative AI age, innovations like these not only enhance our experiences but also challenge us to rethink our established paradigms.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fpromptperfects-llm-database-blurring-boundaries-search-vs-generation%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Rationale 0.1 Update</title><meta charset="utf-8"><meta name="title" content="Rationale 0.1 Update"><meta name="description" content="Rationale 0.1 introduces a new achievement system that rewards users with free credits for completing tasks in the app. Unlock all achievements and earn an extra 20 credits on top of that. Keep an eye out for new achievements and continue to hone your decision-making skills with Rationale."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/rationale-0-1-update"><meta property="og:title" content="Rationale 0.1 Update"><meta property="og:description" content="Rationale 0.1 introduces a new achievement system that rewards users with free credits for completing tasks in the app. Unlock all achievements and earn an extra 20 credits on top of that. Keep an eye out for new achievements and continue to hone your decision-making skills with Rationale."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--68-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/rationale-0-1-update"><meta property="twitter:title" content="Rationale 0.1 Update"><meta property="twitter:description" content="Rationale 0.1 introduces a new achievement system that rewards users with free credits for completing tasks in the app. Unlock all achievements and earn an extra 20 credits on top of that. Keep an eye out for new achievements and continue to hone your decision-making skills with Rationale."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--68-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Rationale 0.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Rationale 0.1 introduces a new achievement system that rewards users with free credits for completing tasks in the app. Unlock all achievements and earn an extra 20 credits on top of that. Keep an eye out for new achievements and continue to hone your decision-making skills with Rationale.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 06, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making tool powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list or SWOT analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><h2 id="new-achievement-system">New achievement system</h2><p>We're excited to announce the release of Rationale 0.1, which includes a brand new achievement system!</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-achievements.mp4" poster="https://img.spacergif.org/v1/2266x1720/0a/spacer.png" width="2266" height="1720" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember1289.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>The new achievement system in Rationale 0.1</figcaption></figure><p>Earn achievements by completing various tasks in the app, such as analyzing your first pending decision or sharing an analysis result with your network. With each achievement you unlock, you'll be one step closer to becoming a Rationale master. Plus, each unlocked achievement gives you extra free credit that you can use to analyze decisions in the app. As a special bonus, <strong>Lite</strong> subscribers earn <strong>2x credits</strong> on every achievement, <strong>Standard</strong> subscribers earn <strong>3x credits</strong>, and <strong>Max</strong> subscribers earn <strong>5x credits</strong>. And if you manage to unlock all of the achievements, you'll get an additional 20 free credits – that's 40 extra credits in total! If you are a Max subscriber, you will get 200 extra free credits in total!</p><p>In this initial release, we've included a variety of achievements to unlock, with more to come in future updates. Keep an eye out for new achievements and continue to hone your decision-making skills with Rationale.</p><p>We hope you enjoy the new achievement system, and we can't wait to see what achievements you unlock!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; 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-webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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Keep an eye out for new achievements and continue to hone your decision-making skills with Rationale.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 06, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making tool powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list or SWOT analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><h2 id="new-achievement-system">New achievement system</h2><p>We're excited to announce the release of Rationale 0.1, which includes a brand new achievement system!</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-achievements.mp4" poster="https://img.spacergif.org/v1/2266x1720/0a/spacer.png" width="2266" height="1720" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember1289.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>The new achievement system in Rationale 0.1</figcaption></figure><p>Earn achievements by completing various tasks in the app, such as analyzing your first pending decision or sharing an analysis result with your network. With each achievement you unlock, you'll be one step closer to becoming a Rationale master. Plus, each unlocked achievement gives you extra free credit that you can use to analyze decisions in the app. As a special bonus, <strong>Lite</strong> subscribers earn <strong>2x credits</strong> on every achievement, <strong>Standard</strong> subscribers earn <strong>3x credits</strong>, and <strong>Max</strong> subscribers earn <strong>5x credits</strong>. And if you manage to unlock all of the achievements, you'll get an additional 20 free credits – that's 40 extra credits in total! If you are a Max subscriber, you will get 200 extra free credits in total!</p><p>In this initial release, we've included a variety of achievements to unlock, with more to come in future updates. Keep an eye out for new achievements and continue to hone your decision-making skills with Rationale.</p><p>We hope you enjoy the new achievement system, and we can't wait to see what achievements you unlock!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-1-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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\ No newline at end of file
diff --git a/news/rationale-0-2-update/index.html b/news/rationale-0-2-update/index.html
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+++ b/news/rationale-0-2-update/index.html
@@ -1,6 +1,6 @@
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Rationale 0.2 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With Rationale's new multi-option analysis feature, you'll have the tools you need to tackle even the toughest multi-option problems. Try out the new multi-option analysis feature in Rationale 0.2 today!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 09, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, <strong>and multi-option analysis </strong>(newly available in 0.2!). By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Please force refresh the browser to see the latest change. This can be usually achieved by Hold ⇧ Shift (MacOS) or Ctrl (Windows/Linux) and click the Reload button.</div></div><h2 id="multi-option-analysis">Multi-option analysis</h2><p>Making tough decisions can be difficult, especially when there are multiple options to choose from. This type of problem, known as a multi-option problem, can be especially challenging for humans because we have a tendency to overthink and weigh the pros and cons of each option.</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-multioption.mp4" poster="https://img.spacergif.org/v1/2380x1540/0a/spacer.png" width="2380" height="1540" loop="" autoplay="" muted="" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember173.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay kg-video-hide-animated"><button class="kg-video-large-play-icon kg-video-hide-animated"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container kg-video-hide"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>Using Rationale to solve a common dilemma of a German. (Of course, this is a German joke)</figcaption></figure><p>That's where Rationale comes in. Our AI-powered decision-making tool, equipped with the latest version of GPT-3 and in-context learning, can help you navigate these situations by generating a comprehensive analysis of all your options. Simply enter all of your indecisive options (<strong>can be more than two!</strong>) into Rationale and our tool will analyze them based on four common criteria or perspectives. Then, Rationale will provide you with the most rational choice among all options, giving you the confidence and clarity you need to move forward.</p><p>With Rationale's multi-option analysis feature, you'll have the tools you need to tackle even the toughest multi-option problems. Try out the new multi-option analysis feature in Rationale 0.2 today!</p><h3 id="4-new-achievements-to-unlock">4 new achievements to unlock</h3><p>To accompany the new multi-option mode, Rationale 0.2 also introduces four new achievements for you to unlock. These achievements are designed to encourage you to try out the new multi-option analysis feature and see all that it has to offer.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-33.png" class="kg-image" alt="" width="2000" height="1248" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-33.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-33.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/image-33.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-33.png 2176w" sizes="(min-width: 720px) 720px"></figure><p>The first new achievement is the "Multi-Choice Master" award, which you can unlock by using the multi-option analysis feature just one time. The next achievement is the "Multi-Choice Maniac" award, which you can unlock by using the multi-option analysis feature 10 times.</p><p>If you're feeling particularly ambitious, you might want to try for the "Option Overlord" award, which you can unlock by entering and analyzing more than two options at a time in the multi-option mode. And for the ultimate challenge, there's the "Option Overflow" award, which you can unlock by entering and analyzing more than five options at a time in the multi-option mode.</p><p>These new achievements offer a fun and rewarding way to explore the multi-option analysis feature and see all that it has to offer. Give them a try and see how many you can unlock!</p><h2 id="faster-response">Faster response</h2><p>In addition to the new multi-option analysis feature, we're excited to announce that Rationale 0.2 also boasts faster response speed and improved robustness. On average, the response time for Pros &amp; Cons and SWOT mode is 2x faster (up to 3x!) than the previous version, making it easier and quicker to get the insights you need.</p><p>But faster response time isn't the only improvement we've made. The response in Rationale 0.2 is also more robust, meaning it can handle a wider range of input and provide more accurate and relevant results.</p><h2 id="bug-fixes-on-delete-thread-and-swipe-to-give-feedback">Bug fixes on delete thread and swipe to give feedback</h2><p>In addition to the new features and improvements mentioned above, Rationale 0.2 also includes a number of bug fixes to ensure a smoother user experience.</p><p>One bug that we've addressed is an issue with the delete thread feature. In previous versions of Rationale, some users experienced problems when trying to delete an analysis from the thread view. We're happy to report that this issue has been fixed in Rationale 0.2, so you can easily delete your analyses as needed.</p><p>We've also fixed an issue with the swipe to give feedback feature. Some users encountered problems when attempting to provide relevancy feedback by swiping right or left on items in the analysis card. This issue has been resolved in Rationale 0.2, so you can easily provide feedback and help us improve the app.</p><p>Overall, these bug fixes help ensure you have a seamless and hassle-free experience when using Rationale. We're always working to make our app as user-friendly and reliable as possible, and these bug fixes are just one example of our commitment to your satisfaction.</p><h2 id="get-50-off-on-your-first-purchase">Get 50% off on your first purchase</h2><p>Don't forget our special offer for the launch of Rationale in Jan 2023: we're offering a coupon code for 50% off any of our plans. Simply use code <code><strong>1STRELEASE</strong></code> when you purchase <strong>before January 31, 2023 </strong>to take advantage of this limited-time offer.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">50% off coupon code: 1STRELEASE</a></div><p>We want as many people as possible to experience the benefits of Rationale, and this coupon is our way of encouraging you to give it a try. Whether you're a business owner, manager, or simply someone who values making informed decisions, we believe Rationale can help you make smarter, more confident choices.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-2-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With Rationale's new multi-option analysis feature, you'll have the tools you need to tackle even the toughest multi-option problems. Try out the new multi-option analysis feature in Rationale 0.2 today!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 09, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, <strong>and multi-option analysis </strong>(newly available in 0.2!). By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Please force refresh the browser to see the latest change. This can be usually achieved by Hold ⇧ Shift (MacOS) or Ctrl (Windows/Linux) and click the Reload button.</div></div><h2 id="multi-option-analysis">Multi-option analysis</h2><p>Making tough decisions can be difficult, especially when there are multiple options to choose from. This type of problem, known as a multi-option problem, can be especially challenging for humans because we have a tendency to overthink and weigh the pros and cons of each option.</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-multioption.mp4" poster="https://img.spacergif.org/v1/2380x1540/0a/spacer.png" width="2380" height="1540" loop="" autoplay="" muted="" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember173.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container kg-video-hide"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>Using Rationale to solve a common dilemma of a German. (Of course, this is a German joke)</figcaption></figure><p>That's where Rationale comes in. Our AI-powered decision-making tool, equipped with the latest version of GPT-3 and in-context learning, can help you navigate these situations by generating a comprehensive analysis of all your options. Simply enter all of your indecisive options (<strong>can be more than two!</strong>) into Rationale and our tool will analyze them based on four common criteria or perspectives. Then, Rationale will provide you with the most rational choice among all options, giving you the confidence and clarity you need to move forward.</p><p>With Rationale's multi-option analysis feature, you'll have the tools you need to tackle even the toughest multi-option problems. Try out the new multi-option analysis feature in Rationale 0.2 today!</p><h3 id="4-new-achievements-to-unlock">4 new achievements to unlock</h3><p>To accompany the new multi-option mode, Rationale 0.2 also introduces four new achievements for you to unlock. These achievements are designed to encourage you to try out the new multi-option analysis feature and see all that it has to offer.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-33.png" class="kg-image" alt="" width="2000" height="1248" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-33.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-33.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/image-33.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-33.png 2176w" sizes="(min-width: 720px) 720px"></figure><p>The first new achievement is the "Multi-Choice Master" award, which you can unlock by using the multi-option analysis feature just one time. The next achievement is the "Multi-Choice Maniac" award, which you can unlock by using the multi-option analysis feature 10 times.</p><p>If you're feeling particularly ambitious, you might want to try for the "Option Overlord" award, which you can unlock by entering and analyzing more than two options at a time in the multi-option mode. And for the ultimate challenge, there's the "Option Overflow" award, which you can unlock by entering and analyzing more than five options at a time in the multi-option mode.</p><p>These new achievements offer a fun and rewarding way to explore the multi-option analysis feature and see all that it has to offer. Give them a try and see how many you can unlock!</p><h2 id="faster-response">Faster response</h2><p>In addition to the new multi-option analysis feature, we're excited to announce that Rationale 0.2 also boasts faster response speed and improved robustness. On average, the response time for Pros &amp; Cons and SWOT mode is 2x faster (up to 3x!) than the previous version, making it easier and quicker to get the insights you need.</p><p>But faster response time isn't the only improvement we've made. The response in Rationale 0.2 is also more robust, meaning it can handle a wider range of input and provide more accurate and relevant results.</p><h2 id="bug-fixes-on-delete-thread-and-swipe-to-give-feedback">Bug fixes on delete thread and swipe to give feedback</h2><p>In addition to the new features and improvements mentioned above, Rationale 0.2 also includes a number of bug fixes to ensure a smoother user experience.</p><p>One bug that we've addressed is an issue with the delete thread feature. In previous versions of Rationale, some users experienced problems when trying to delete an analysis from the thread view. We're happy to report that this issue has been fixed in Rationale 0.2, so you can easily delete your analyses as needed.</p><p>We've also fixed an issue with the swipe to give feedback feature. Some users encountered problems when attempting to provide relevancy feedback by swiping right or left on items in the analysis card. This issue has been resolved in Rationale 0.2, so you can easily provide feedback and help us improve the app.</p><p>Overall, these bug fixes help ensure you have a seamless and hassle-free experience when using Rationale. We're always working to make our app as user-friendly and reliable as possible, and these bug fixes are just one example of our commitment to your satisfaction.</p><h2 id="get-50-off-on-your-first-purchase">Get 50% off on your first purchase</h2><p>Don't forget our special offer for the launch of Rationale in Jan 2023: we're offering a coupon code for 50% off any of our plans. Simply use code <code><strong>1STRELEASE</strong></code> when you purchase <strong>before January 31, 2023 </strong>to take advantage of this limited-time offer.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">50% off coupon code: 1STRELEASE</a></div><p>We want as many people as possible to experience the benefits of Rationale, and this coupon is our way of encouraging you to give it a try. Whether you're a business owner, manager, or simply someone who values making informed decisions, we believe Rationale can help you make smarter, more confident choices.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-2-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Rationale 0.3 Update</title><meta charset="utf-8"><meta name="title" content="Rationale 0.3 Update"><meta name="description" content="With new capabilities such as the ability to share your decision analysis with the public, update notifications, improvements to the quality of analysis, and bug fixes, Rationale 0.3 makes it easy to make informed decisions with confidence."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/rationale-0-3-update"><meta property="og:title" content="Rationale 0.3 Update"><meta property="og:description" content="With new capabilities such as the ability to share your decision analysis with the public, update notifications, improvements to the quality of analysis, and bug fixes, Rationale 0.3 makes it easy to make informed decisions with confidence."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--71-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/rationale-0-3-update"><meta property="twitter:title" content="Rationale 0.3 Update"><meta property="twitter:description" content="With new capabilities such as the ability to share your decision analysis with the public, update notifications, improvements to the quality of analysis, and bug fixes, Rationale 0.3 makes it easy to make informed decisions with confidence."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--71-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Rationale 0.3 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With new capabilities such as the ability to share your decision analysis with the public, update notifications, improvements to the quality of analysis, and bug fixes, Rationale 0.3 makes it easy to make informed decisions with confidence.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 12, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, and multi-option analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Please force refresh the browser to see the latest change. This can be usually achieved by Hold ⇧ Shift (MacOS) or Ctrl (Windows/Linux) and click the Reload button.</div></div><h2 id="share-your-decision-analysis-with-the-public">Share your decision analysis with the public</h2><p>Now, users without a login can easily access and review your analysis, making collaboration and feedback seamless. Try this one: <a href="https://rationale.jina.ai/share?thread=Zb9TOqwd8yK3XeKzMJjz&amp;ref=jina-ai-gmbh.ghost.io">https://rationale.jina.ai/share?thread=Zb9TOqwd8yK3XeKzMJjz</a></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-47.png" class="kg-image" alt="" width="936" height="826" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-47.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-47.png 936w" sizes="(min-width: 720px) 720px"></figure><p>By sharing your analysis, you can gather feedback and input from a wider audience, helping you make even more informed decisions. Not only that, you can also showcase your expertise and thought-process to the world. We encourage you to take advantage of this feature and share your analysis to your network to gain valuable insights and perspectives.</p><h2 id="keep-up-to-date-with-update-notifications">Keep up-to-date with update notifications</h2><p>As a Progressive Web Application (PWA), Rationale works offline and leverages the local cache for optimal performance. To ensure you always have the latest features, we've added update notifications so you never miss an update and enjoy the smoothest experience.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-46.png" class="kg-image" alt="" width="2000" height="440" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-46.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-46.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/image-46.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/01/image-46.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>You will see a notification every time Rationale gets updated. Hit "REFRESH" to update to the latest version.</figcaption></figure><h2 id="other-improvements-and-bug-fixes">Other improvements and bug fixes</h2><ul><li>We have improved the quality of your Pros &amp; Cons, SWOT, and multi-criteria analysis. We've made improvements to the algorithms used in these analyses, ensuring that you receive the most comprehensive and accurate results possible.</li><li>Say goodbye to rendering bugs. We've fixed any issues with the decision page, ensuring that you have a smooth and seamless experience when reviewing your analysis.</li></ul><h2 id="get-50-off-on-your-first-purchase">Get 50% off on your first purchase</h2><p>Don't forget our special offer for the launch of Rationale in Jan 2023: we're offering a coupon code for 50% off any of our plans. Simply use code <code><strong>1STRELEASE</strong></code> when you purchase <strong>before January 31, 2023 </strong>to take advantage of this limited-time offer.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">50% off coupon code: 1STRELEASE</a></div><p>We want as many people as possible to experience the benefits of Rationale, and this coupon is our way of encouraging you to give it a try. Whether you're a business owner, manager, or simply someone who values making informed decisions, we believe Rationale can help you make smarter, more confident choices.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-3-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Rationale 0.3 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With new capabilities such as the ability to share your decision analysis with the public, update notifications, improvements to the quality of analysis, and bug fixes, Rationale 0.3 makes it easy to make informed decisions with confidence.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 12, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, and multi-option analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Please force refresh the browser to see the latest change. This can be usually achieved by Hold ⇧ Shift (MacOS) or Ctrl (Windows/Linux) and click the Reload button.</div></div><h2 id="share-your-decision-analysis-with-the-public">Share your decision analysis with the public</h2><p>Now, users without a login can easily access and review your analysis, making collaboration and feedback seamless. Try this one: <a href="https://rationale.jina.ai/share?thread=Zb9TOqwd8yK3XeKzMJjz&amp;ref=jina-ai-gmbh.ghost.io">https://rationale.jina.ai/share?thread=Zb9TOqwd8yK3XeKzMJjz</a></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-47.png" class="kg-image" alt="" width="936" height="826" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-47.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-47.png 936w" sizes="(min-width: 720px) 720px"></figure><p>By sharing your analysis, you can gather feedback and input from a wider audience, helping you make even more informed decisions. Not only that, you can also showcase your expertise and thought-process to the world. We encourage you to take advantage of this feature and share your analysis to your network to gain valuable insights and perspectives.</p><h2 id="keep-up-to-date-with-update-notifications">Keep up-to-date with update notifications</h2><p>As a Progressive Web Application (PWA), Rationale works offline and leverages the local cache for optimal performance. To ensure you always have the latest features, we've added update notifications so you never miss an update and enjoy the smoothest experience.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-46.png" class="kg-image" alt="" width="2000" height="440" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-46.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-46.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/image-46.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/01/image-46.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>You will see a notification every time Rationale gets updated. Hit "REFRESH" to update to the latest version.</figcaption></figure><h2 id="other-improvements-and-bug-fixes">Other improvements and bug fixes</h2><ul><li>We have improved the quality of your Pros &amp; Cons, SWOT, and multi-criteria analysis. We've made improvements to the algorithms used in these analyses, ensuring that you receive the most comprehensive and accurate results possible.</li><li>Say goodbye to rendering bugs. We've fixed any issues with the decision page, ensuring that you have a smooth and seamless experience when reviewing your analysis.</li></ul><h2 id="get-50-off-on-your-first-purchase">Get 50% off on your first purchase</h2><p>Don't forget our special offer for the launch of Rationale in Jan 2023: we're offering a coupon code for 50% off any of our plans. Simply use code <code><strong>1STRELEASE</strong></code> when you purchase <strong>before January 31, 2023 </strong>to take advantage of this limited-time offer.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">50% off coupon code: 1STRELEASE</a></div><p>We want as many people as possible to experience the benefits of Rationale, and this coupon is our way of encouraging you to give it a try. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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+++ b/news/rationale-0-4-update/index.html
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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Rationale 0.4 Update</title><meta charset="utf-8"><meta name="title" content="Rationale 0.4 Update"><meta name="description" content="Introducing Rationale 0.4 - the ultimate decision-making tool now with personalized profiles! Create multiple profiles, input your backstory and context information, and get accurate analysis tailored to your background. "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/rationale-0-4-update"><meta property="og:title" content="Rationale 0.4 Update"><meta property="og:description" content="Introducing Rationale 0.4 - the ultimate decision-making tool now with personalized profiles! Create multiple profiles, input your backstory and context information, and get accurate analysis tailored to your background. "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--72-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/rationale-0-4-update"><meta property="twitter:title" content="Rationale 0.4 Update"><meta property="twitter:description" content="Introducing Rationale 0.4 - the ultimate decision-making tool now with personalized profiles! Create multiple profiles, input your backstory and context information, and get accurate analysis tailored to your background. "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--72-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Rationale 0.4 Update</title><meta charset="utf-8"><meta name="title" content="Rationale 0.4 Update"><meta name="description" content="Introducing Rationale 0.4 - the ultimate decision-making tool now with personalized profiles! Create multiple profiles, input your backstory and context information, and get accurate analysis tailored to your background. "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/rationale-0-4-update"><meta property="og:title" content="Rationale 0.4 Update"><meta property="og:description" content="Introducing Rationale 0.4 - the ultimate decision-making tool now with personalized profiles! Create multiple profiles, input your backstory and context information, and get accurate analysis tailored to your background. "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--72-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/rationale-0-4-update"><meta property="twitter:title" content="Rationale 0.4 Update"><meta property="twitter:description" content="Introducing Rationale 0.4 - the ultimate decision-making tool now with personalized profiles! Create multiple profiles, input your backstory and context information, and get accurate analysis tailored to your background. "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--72-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Rationale 0.4 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Introducing Rationale 0.4 - the ultimate decision-making tool now with personalized profiles! Create multiple profiles, input your backstory and context information, and get accurate analysis tailored to your background. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 16, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, and multi-option analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Please force refresh the browser to see the latest change. This can be usually achieved by Hold ⇧ Shift (MacOS) or Ctrl (Windows/Linux) and click the Reload button.</div></div><h2 id="new-profiles-feature">New Profiles Feature</h2><p>Our latest release features the brand new profiles feature, allowing users to create their own personalized profiles for even more accurate decision analysis.</p><p>With the new profiles feature, users can now create multiple profiles and use them in their decision analysis. This allows for a high level of customization, as users can input arbitrary text as background and context information for their analysis. This greatly improves the accuracy and relevance of the analysis results, ensuring that users are making informed decisions based on their backstory and circumstances.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale04-profiles.mp4" poster="https://img.spacergif.org/v1/2560x1694/0a/spacer.png" width="2560" height="1694" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember126.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>Previous versions of Rationale only allowed for restricted questionnaire information to be input into the decision analysis. With the new profiles feature, users can now tailor the analysis to their unique background and context, resulting in more accurate and actionable results.</p><p>Free users are allowed to use 1 profile, which can be modified, updated, or deleted at any time. Lite subscribers can have access to 3 profiles, standard subscribers can have access to 10 profiles and max subscribers can have access to 50 profiles. This allows users to tailor their analysis to different scenarios and contexts, depending on their subscription level.</p><p>In addition to the new profiles feature, we've made several other improvements and bug fixes to ensure that you have the best possible experience when using Rationale. Upgrade to Rationale 0.4 today and take control of your decision-making process with a personalized, accurate analysis.</p><h2 id="get-50-off-on-your-first-purchase">Get 50% off on your first purchase</h2><p>Don't forget our special offer for the launch of Rationale in Jan 2023: we're offering a coupon code for 50% off any of our plans. Simply use code <code><strong>1STRELEASE</strong></code> when you purchase <strong>before January 31, 2023 </strong>to take advantage of this limited-time offer.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">50% off coupon code: 1STRELEASE</a></div><p>We want as many people as possible to experience the benefits of Rationale, and this coupon is our way of encouraging you to give it a try. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Introducing Rationale 0.4 - the ultimate decision-making tool now with personalized profiles! Create multiple profiles, input your backstory and context information, and get accurate analysis tailored to your background. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 16, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, and multi-option analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Please force refresh the browser to see the latest change. This can be usually achieved by Hold ⇧ Shift (MacOS) or Ctrl (Windows/Linux) and click the Reload button.</div></div><h2 id="new-profiles-feature">New Profiles Feature</h2><p>Our latest release features the brand new profiles feature, allowing users to create their own personalized profiles for even more accurate decision analysis.</p><p>With the new profiles feature, users can now create multiple profiles and use them in their decision analysis. This allows for a high level of customization, as users can input arbitrary text as background and context information for their analysis. This greatly improves the accuracy and relevance of the analysis results, ensuring that users are making informed decisions based on their backstory and circumstances.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale04-profiles.mp4" poster="https://img.spacergif.org/v1/2560x1694/0a/spacer.png" width="2560" height="1694" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember126.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>Previous versions of Rationale only allowed for restricted questionnaire information to be input into the decision analysis. With the new profiles feature, users can now tailor the analysis to their unique background and context, resulting in more accurate and actionable results.</p><p>Free users are allowed to use 1 profile, which can be modified, updated, or deleted at any time. Lite subscribers can have access to 3 profiles, standard subscribers can have access to 10 profiles and max subscribers can have access to 50 profiles. This allows users to tailor their analysis to different scenarios and contexts, depending on their subscription level.</p><p>In addition to the new profiles feature, we've made several other improvements and bug fixes to ensure that you have the best possible experience when using Rationale. Upgrade to Rationale 0.4 today and take control of your decision-making process with a personalized, accurate analysis.</p><h2 id="get-50-off-on-your-first-purchase">Get 50% off on your first purchase</h2><p>Don't forget our special offer for the launch of Rationale in Jan 2023: we're offering a coupon code for 50% off any of our plans. Simply use code <code><strong>1STRELEASE</strong></code> when you purchase <strong>before January 31, 2023 </strong>to take advantage of this limited-time offer.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">50% off coupon code: 1STRELEASE</a></div><p>We want as many people as possible to experience the benefits of Rationale, and this coupon is our way of encouraging you to give it a try. Whether you're a business owner, manager, or simply someone who values making informed decisions, we believe Rationale can help you make smarter, more confident choices.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-4-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Rationale 0.5 Update</title><meta charset="utf-8"><meta name="title" content="Rationale 0.5 Update"><meta name="description" content="Introducing Rationale 0.5 – the ultimate decision-making tool with a new &quot;Sharing Rewards&quot; feature. Share your decision analysis and earn rewards. Also, join our new Discord community server, where you can get support, ask questions and shape the future of Rationale."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/rationale-0-5-update"><meta property="og:title" content="Rationale 0.5 Update"><meta property="og:description" content="Introducing Rationale 0.5 – the ultimate decision-making tool with a new &quot;Sharing Rewards&quot; feature. Share your decision analysis and earn rewards. Also, join our new Discord community server, where you can get support, ask questions and shape the future of Rationale."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--73-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/rationale-0-5-update"><meta property="twitter:title" content="Rationale 0.5 Update"><meta property="twitter:description" content="Introducing Rationale 0.5 – the ultimate decision-making tool with a new &quot;Sharing Rewards&quot; feature. Share your decision analysis and earn rewards. Also, join our new Discord community server, where you can get support, ask questions and shape the future of Rationale."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--73-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Rationale 0.5 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Introducing Rationale 0.5 – the ultimate decision-making tool with a new "Sharing Rewards" feature. Share your decision analysis and earn rewards. Also, join our new Discord community server, where you can get support, ask questions and shape the future of Rationale.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 26, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, and multi-option analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><h2 id="sharing-rewards">Sharing Rewards</h2><p>Our latest release allows users to share their decision analysis with others and earn rewards in return.</p><p>With the new sharing rewards feature, users can now share their decision analysis with other logged-in users and earn one free credit for each successful referral. This is a great way for users to get the most out of Rationale, while also helping others make informed decisions.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-share-credit.mp4" poster="https://img.spacergif.org/v1/1920x600/0a/spacer.png" width="1920" height="600" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember118.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>In addition to the new sharing rewards feature, users can also save a shared analysis to their own dashboard. This allows users to easily access and refer back to shared analyses, making it even more convenient for them to make decisions.</p><p>We encourage all of our users to take advantage of this new feature and share their decision analysis with others. Not only will it help others make informed decisions, but it will also give you the opportunity to earn rewards and get even more value out of Rationale.</p><p>In addition to the new Referral Rewards feature, we've made several other improvements and bug fixes to ensure that you have the best possible experience when using Rationale.</p><h2 id="new-discord-community">New Discord Community</h2><p>We are also excited to announce the launch of our official Rationale Discord community server! This community is a place where you can share your experience, get support on Rationale, ask related questions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://discord.gg/ZugXMrABpH?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Join the Rationale AI Discord Server!</div><div class="kg-bookmark-description">Check out the Rationale AI community on Discord - hang out with 4 other members and enjoy free voice and text chat.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://discord.gg/assets/ec2c34cadd4b5f4594415127380a85e6.ico" alt=""><span class="kg-bookmark-author">Discord</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn.discordapp.com/icons/1068204555927572570/848586c2b3bd6b1caa3b871b37165246.jpg?size=256" alt=""></div></a></figure><p>Join our community and be a part of shaping the future of Rationale. Connect with other like-minded individuals and take your decision-making skills to the next level. Don't miss out, join our Discord server today!</p><h2 id="get-50-off-on-your-first-purchase">Get 50% off on your first purchase</h2><p><strong>Five days left! </strong>Don't forget our special offer for the launch of Rationale in Jan 2023: we're offering a coupon code for 50% off any of our plans. Simply use code <strong><code>1STRELEASE</code></strong> when you purchase <strong>before January 31, 2023 </strong>to take advantage of this limited-time offer.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">50% off coupon code: 1STRELEASE</a></div><p>We want as many people as possible to experience the benefits of Rationale, and this coupon is our way of encouraging you to give it a try. Whether you're a business owner, manager, or simply someone who values making informed decisions, we believe Rationale can help you make smarter, more confident choices.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-5-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Introducing Rationale 0.5 – the ultimate decision-making tool with a new "Sharing Rewards" feature. Share your decision analysis and earn rewards. Also, join our new Discord community server, where you can get support, ask questions and shape the future of Rationale.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 26, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, and multi-option analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><h2 id="sharing-rewards">Sharing Rewards</h2><p>Our latest release allows users to share their decision analysis with others and earn rewards in return.</p><p>With the new sharing rewards feature, users can now share their decision analysis with other logged-in users and earn one free credit for each successful referral. This is a great way for users to get the most out of Rationale, while also helping others make informed decisions.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-share-credit.mp4" poster="https://img.spacergif.org/v1/1920x600/0a/spacer.png" width="1920" height="600" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember118.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>In addition to the new sharing rewards feature, users can also save a shared analysis to their own dashboard. This allows users to easily access and refer back to shared analyses, making it even more convenient for them to make decisions.</p><p>We encourage all of our users to take advantage of this new feature and share their decision analysis with others. Not only will it help others make informed decisions, but it will also give you the opportunity to earn rewards and get even more value out of Rationale.</p><p>In addition to the new Referral Rewards feature, we've made several other improvements and bug fixes to ensure that you have the best possible experience when using Rationale.</p><h2 id="new-discord-community">New Discord Community</h2><p>We are also excited to announce the launch of our official Rationale Discord community server! This community is a place where you can share your experience, get support on Rationale, ask related questions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://discord.gg/ZugXMrABpH?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Join the Rationale AI Discord Server!</div><div class="kg-bookmark-description">Check out the Rationale AI community on Discord - hang out with 4 other members and enjoy free voice and text chat.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://discord.gg/assets/ec2c34cadd4b5f4594415127380a85e6.ico" alt=""><span class="kg-bookmark-author">Discord</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn.discordapp.com/icons/1068204555927572570/848586c2b3bd6b1caa3b871b37165246.jpg?size=256" alt=""></div></a></figure><p>Join our community and be a part of shaping the future of Rationale. Connect with other like-minded individuals and take your decision-making skills to the next level. Don't miss out, join our Discord server today!</p><h2 id="get-50-off-on-your-first-purchase">Get 50% off on your first purchase</h2><p><strong>Five days left! </strong>Don't forget our special offer for the launch of Rationale in Jan 2023: we're offering a coupon code for 50% off any of our plans. Simply use code <strong><code>1STRELEASE</code></strong> when you purchase <strong>before January 31, 2023 </strong>to take advantage of this limited-time offer.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">50% off coupon code: 1STRELEASE</a></div><p>We want as many people as possible to experience the benefits of Rationale, and this coupon is our way of encouraging you to give it a try. Whether you're a business owner, manager, or simply someone who values making informed decisions, we believe Rationale can help you make smarter, more confident choices.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-5-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Rationale 0.6 Update</title><meta charset="utf-8"><meta name="title" content="Rationale 0.6 Update"><meta name="description" content="Discover the future with Rationale 0.6! Our groundbreaking &quot;Multiverse&quot; mode shows the outcomes of your decisions in a causal chain, up to 3 levels deep. See the potential consequences of your choices and make informed decisions. Try Rationale 0.6 today!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/rationale-0-6-update"><meta property="og:title" content="Rationale 0.6 Update"><meta property="og:description" content="Discover the future with Rationale 0.6! Our groundbreaking &quot;Multiverse&quot; mode shows the outcomes of your decisions in a causal chain, up to 3 levels deep. See the potential consequences of your choices and make informed decisions. Try Rationale 0.6 today!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--74-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/rationale-0-6-update"><meta property="twitter:title" content="Rationale 0.6 Update"><meta property="twitter:description" content="Discover the future with Rationale 0.6! Our groundbreaking &quot;Multiverse&quot; mode shows the outcomes of your decisions in a causal chain, up to 3 levels deep. See the potential consequences of your choices and make informed decisions. Try Rationale 0.6 today!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/01/Jina-AI-Website-Banners-Templates--74-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Rationale 0.6 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Discover the future with Rationale 0.6! Our groundbreaking "Multiverse" mode shows the outcomes of your decisions in a causal chain, up to 3 levels deep. See the potential consequences of your choices and make informed decisions. Try Rationale 0.6 today!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 30, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, and multi-option analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Please force refresh the browser to see the latest change. This can be usually achieved by Hold ⇧ Shift (MacOS) or Ctrl (Windows/Linux) and click the Reload button.</div></div><h2 id="new-outcome-analysis-mode">New outcome analysis mode</h2><p>Decisions are hard to make because we can't see the outcomes of our decisions. But what if we can? What if we can glimpse the multiverse before you decide? With Rationale 0.6, we bring you the groundbreaking outcomes analysis mode - or we would like to call it the "Multiverse" mode.</p><p>With the outcomes analysis, you'll be able to see the outcomes of your decisions in a causal chain, up to 3 levels deep. This tree-like structure will show you not only the immediate outcomes, but also the outcomes of the outcomes, depending on what happens along the way. With this feature, you'll be able to make informed decisions and see the full picture of the impact your choices will have.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-0.6-outcomes-mf-narrative-2.mp4" poster="https://img.spacergif.org/v1/2550x1660/0a/spacer.png" width="2550" height="1660" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember199.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>Let's see some results in action. Notice how the consequences are unfolded based on what would be happened along the way. The smiley faces in different colors indicate the sentiment of the outcomes.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.494436 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--77-.png" width="1244" height="2516" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--77-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--77-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--77-.png 1244w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.556849 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--78-.png" width="1244" height="2234" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--78-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--78-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--78-.png 1244w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.574861 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--79-.png" width="1244" height="2164" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--79-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--79-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--79-.png 1244w" sizes="(min-width: 720px) 720px"></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-0.6-outcomes-analysis-1.mp4" poster="https://img.spacergif.org/v1/2550x1660/0a/spacer.png" width="2550" height="1660" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember91.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="credit-history">Credit history</h2><p>In addition to the Outcomes Analysis mode, we're also introducing Credit History, so you can see exactly when and how you've earned or spent your credits. This new feature will make it even easier to keep track of your credits, so you can be sure to get the most out of your experience with Rationale.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-48.png" class="kg-image" alt="" width="1888" height="584" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-48.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-48.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/image-48.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-48.png 1888w" sizes="(min-width: 720px) 720px"></figure><h2 id="get-50-off-on-your-first-purchase">Get 50% off on your first purchase</h2><p><strong>Only 1 day left! </strong>Don't forget our special offer for the launch of Rationale in Jan 2023: we're offering a coupon code for 50% off any of our plans. Simply use code <strong><code>1STRELEASE</code></strong> when you purchase <strong>before January 31, 2023 </strong>to take advantage of this limited-time offer.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">50% off coupon code: 1STRELEASE</a></div><p>We want as many people as possible to experience the benefits of Rationale, and this coupon is our way of encouraging you to give it a try. Whether you're a business owner, manager, or simply someone who values making informed decisions, we believe Rationale can help you make smarter, more confident choices.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-6-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="78d040f5-0eb4-4c26-8ae0-71a8ebb9d4d8" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="78d040f5-0eb4-4c26-8ae0-71a8ebb9d4d8" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Rationale 0.6 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Discover the future with Rationale 0.6! Our groundbreaking "Multiverse" mode shows the outcomes of your decisions in a causal chain, up to 3 levels deep. See the potential consequences of your choices and make informed decisions. Try Rationale 0.6 today!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">January 30, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, and multi-option analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Please force refresh the browser to see the latest change. This can be usually achieved by Hold ⇧ Shift (MacOS) or Ctrl (Windows/Linux) and click the Reload button.</div></div><h2 id="new-outcome-analysis-mode">New outcome analysis mode</h2><p>Decisions are hard to make because we can't see the outcomes of our decisions. But what if we can? What if we can glimpse the multiverse before you decide? With Rationale 0.6, we bring you the groundbreaking outcomes analysis mode - or we would like to call it the "Multiverse" mode.</p><p>With the outcomes analysis, you'll be able to see the outcomes of your decisions in a causal chain, up to 3 levels deep. This tree-like structure will show you not only the immediate outcomes, but also the outcomes of the outcomes, depending on what happens along the way. With this feature, you'll be able to make informed decisions and see the full picture of the impact your choices will have.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-0.6-outcomes-mf-narrative-2.mp4" poster="https://img.spacergif.org/v1/2550x1660/0a/spacer.png" width="2550" height="1660" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember199.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>Let's see some results in action. Notice how the consequences are unfolded based on what would be happened along the way. The smiley faces in different colors indicate the sentiment of the outcomes.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.494436 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--77-.png" width="1244" height="2516" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--77-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--77-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--77-.png 1244w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.556849 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--78-.png" width="1244" height="2234" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--78-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--78-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--78-.png 1244w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.574861 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--79-.png" width="1244" height="2164" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/rationale--79-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/rationale--79-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/rationale--79-.png 1244w" sizes="(min-width: 720px) 720px"></div></div></div></figure><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/01/rationale-0.6-outcomes-analysis-1.mp4" poster="https://img.spacergif.org/v1/2550x1660/0a/spacer.png" width="2550" height="1660" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/01/media-thumbnail-ember91.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="credit-history">Credit history</h2><p>In addition to the Outcomes Analysis mode, we're also introducing Credit History, so you can see exactly when and how you've earned or spent your credits. This new feature will make it even easier to keep track of your credits, so you can be sure to get the most out of your experience with Rationale.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-48.png" class="kg-image" alt="" width="1888" height="584" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/01/image-48.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/01/image-48.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/01/image-48.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/01/image-48.png 1888w" sizes="(min-width: 720px) 720px"></figure><h2 id="get-50-off-on-your-first-purchase">Get 50% off on your first purchase</h2><p><strong>Only 1 day left! </strong>Don't forget our special offer for the launch of Rationale in Jan 2023: we're offering a coupon code for 50% off any of our plans. Simply use code <strong><code>1STRELEASE</code></strong> when you purchase <strong>before January 31, 2023 </strong>to take advantage of this limited-time offer.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">50% off coupon code: 1STRELEASE</a></div><p>We want as many people as possible to experience the benefits of Rationale, and this coupon is our way of encouraging you to give it a try. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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\ No newline at end of file
diff --git a/news/rationale-0-7-updates/index.html b/news/rationale-0-7-updates/index.html
index 794b9677f17..4b387be67d2 100644
--- a/news/rationale-0-7-updates/index.html
+++ b/news/rationale-0-7-updates/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Rationale 0.7 Update</title><meta charset="utf-8"><meta name="title" content="Rationale 0.7 Update"><meta name="description" content="Get ready for a sleek and modern experience with Rationale 0.7! We've updated our desktop and mobile UX for a clean and easy-to-use interface. Upgrade now for the best decision-making experience!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/rationale-0-7-updates"><meta property="og:title" content="Rationale 0.7 Update"><meta property="og:description" content="Get ready for a sleek and modern experience with Rationale 0.7! We've updated our desktop and mobile UX for a clean and easy-to-use interface. Upgrade now for the best decision-making experience!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Jina-AI-Website-Banners-Templates--75-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/rationale-0-7-updates"><meta property="twitter:title" content="Rationale 0.7 Update"><meta property="twitter:description" content="Get ready for a sleek and modern experience with Rationale 0.7! We've updated our desktop and mobile UX for a clean and easy-to-use interface. Upgrade now for the best decision-making experience!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Jina-AI-Website-Banners-Templates--75-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Rationale 0.7 Update</title><meta charset="utf-8"><meta name="title" content="Rationale 0.7 Update"><meta name="description" content="Get ready for a sleek and modern experience with Rationale 0.7! We've updated our desktop and mobile UX for a clean and easy-to-use interface. Upgrade now for the best decision-making experience!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/rationale-0-7-updates"><meta property="og:title" content="Rationale 0.7 Update"><meta property="og:description" content="Get ready for a sleek and modern experience with Rationale 0.7! We've updated our desktop and mobile UX for a clean and easy-to-use interface. Upgrade now for the best decision-making experience!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Jina-AI-Website-Banners-Templates--75-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/rationale-0-7-updates"><meta property="twitter:title" content="Rationale 0.7 Update"><meta property="twitter:description" content="Get ready for a sleek and modern experience with Rationale 0.7! We've updated our desktop and mobile UX for a clean and easy-to-use interface. Upgrade now for the best decision-making experience!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Jina-AI-Website-Banners-Templates--75-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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-<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.a0e90567.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.334e385b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.7fb36afb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.e82f8124.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.1e057f62.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.2b6e3ac7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.cdce2c7a.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.1a54f452.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ada2cea3.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.dae6efcf.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.4068d6dd.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d2069e37.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.ed2c7731.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.77d2e514.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.ecb3c5d9.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.12934764.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.131f6516.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.366b6afd.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.6fccc081.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.e4f81404.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.2038ddce.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.15f7afc8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.93058c13.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.903087e6.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.fa81a92f.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.9d7ab03a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.fdbfc6f6.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.f5cd3c5b.js"><script src="https://jina-ai-gmbh.ghost.io/public/cards.min.js" async=""></script><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
       uc.reloadOnOptIn('BJz7qNsdj-7'); // reload page on YouTube opt-in</script><style prerender-ignore>.uc-embedding-container {
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Rationale 0.7 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Get ready for a sleek and modern experience with Rationale 0.7! We've updated our desktop and mobile UX for a clean and easy-to-use interface. Upgrade now for the best decision-making experience!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 06, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, multi-option analysis and causal chain analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Please force refresh the browser to see the latest change. This can be usually achieved by Hold ⇧ Shift (MacOS) or Ctrl (Windows/Linux) and click the Reload button.</div></div><h2 id="new-ux-for-desktop-and-mobile">New UX for desktop and mobile</h2><p>With this update, we've made major improvements to the user experience, both on desktop and mobile. Our goal was to create a more modern and clean interface, making it easier for you to make informed decisions. The updates to the UX are designed to streamline the process of inputting information and analyzing the outcomes, allowing you to focus on what really matters: your decisions. Upgrade to version 0.7 today and see the difference for yourself!</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.45455 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image.png" width="2000" height="1375" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/image.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/02/image.png 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.67785 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-5.png" width="2000" height="1192" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/image-5.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/image-5.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/image-5.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/02/image-5.png 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Desktop view</figcaption></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.46281 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-1.png" width="784" height="1694" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-1.png 784w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.460449 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-3.png" width="780" height="1694" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-3.png 780w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.460355 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-2.png" width="778" height="1690" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-2.png 778w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Mobile view</figcaption></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-7-updates%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Get ready for a sleek and modern experience with Rationale 0.7! We've updated our desktop and mobile UX for a clean and easy-to-use interface. Upgrade now for the best decision-making experience!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 06, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, multi-option analysis and causal chain analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Please force refresh the browser to see the latest change. This can be usually achieved by Hold ⇧ Shift (MacOS) or Ctrl (Windows/Linux) and click the Reload button.</div></div><h2 id="new-ux-for-desktop-and-mobile">New UX for desktop and mobile</h2><p>With this update, we've made major improvements to the user experience, both on desktop and mobile. Our goal was to create a more modern and clean interface, making it easier for you to make informed decisions. The updates to the UX are designed to streamline the process of inputting information and analyzing the outcomes, allowing you to focus on what really matters: your decisions. Upgrade to version 0.7 today and see the difference for yourself!</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image.png" width="2000" height="1375" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/image.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/02/image.png 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-5.png" width="2000" height="1192" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/image-5.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/image-5.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/image-5.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/02/image-5.png 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Desktop view</figcaption></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-1.png" width="784" height="1694" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-1.png 784w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-3.png" width="780" height="1694" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-3.png 780w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-2.png" width="778" height="1690" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-2.png 778w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Mobile view</figcaption></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-7-updates%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Rationale 0.8 Update</title><meta charset="utf-8"><meta name="title" content="Rationale 0.8 Update"><meta name="description" content="Introducing Rationale 0.8: Make Better Decisions with Personalized Context Analysis! Experience improved outcomes analysis that considers the context of your decisions. Plus, a new persona system with up to 2000 letters of backstory, and UI improvements. Upgrade now!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/rationale-0-8-update"><meta property="og:title" content="Rationale 0.8 Update"><meta property="og:description" content="Introducing Rationale 0.8: Make Better Decisions with Personalized Context Analysis! Experience improved outcomes analysis that considers the context of your decisions. Plus, a new persona system with up to 2000 letters of backstory, and UI improvements. Upgrade now!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Jina-AI-Website-Banners-Templates--76-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/rationale-0-8-update"><meta property="twitter:title" content="Rationale 0.8 Update"><meta property="twitter:description" content="Introducing Rationale 0.8: Make Better Decisions with Personalized Context Analysis! Experience improved outcomes analysis that considers the context of your decisions. Plus, a new persona system with up to 2000 letters of backstory, and UI improvements. Upgrade now!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/Jina-AI-Website-Banners-Templates--76-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Rationale 0.8 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Introducing Rationale 0.8: Make Better Decisions with Personalized Context Analysis! Experience improved outcomes analysis that considers the context of your decisions. Plus, a new persona system with up to 2000 letters of backstory, and UI improvements. Upgrade now!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 12, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, multi-option analysis and causal chain analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Please force refresh the browser to see the latest change. This can be usually achieved by Hold ⇧ Shift (MacOS) or Ctrl (Windows/Linux) and click the Reload button.</div></div><p>We are excited to announce the release of Rationale 0.8, which comes packed with several new features and improvements to enhance your decision-making experience.</p><h2 id="new-persona-system">New persona system</h2><p>With Rationale 0.8, you can now write up to 2000 letters of backstory for your persona, providing more in-depth and personalized analysis for your decisions. This feature allows Rationale to better understand the context of your decisions and provide more relevant and accurate analysis.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-6.png" class="kg-image" alt="" width="1796" height="1390" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/image-6.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/image-6.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/image-6.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-6.png 1796w" sizes="(min-width: 720px) 720px"></figure><h2 id="causal-chain-analysis-with-context">Causal chain analysis with context</h2><p>Our outcomes analysis, also known as causal chain analysis, has been improved to consider the context of your decisions. With this feature, you can expect a more thorough and meaningful analysis of the potential outcomes of your decisions. Say goodbye to trivial outcomes and hello to more thoughtful and contextual analysis.</p><h2 id="ui-improvements">UI Improvements</h2><p>We've made several improvements to the user interface on desktop and mobile, making it easier and more intuitive to use. In addition, we've addressed several bugs to ensure a seamless and stable experience for our users.</p><p>We hope you enjoy these new features and improvements in Rationale 0.8. As always, we welcome your feedback and suggestions for future updates.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-8-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Introducing Rationale 0.8: Make Better Decisions with Personalized Context Analysis! Experience improved outcomes analysis that considers the context of your decisions. Plus, a new persona system with up to 2000 letters of backstory, and UI improvements. Upgrade now!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 12, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Rationale is a decision-making AI powered by the latest version of GPT-3 and in-context learning. It assists business owners, managers, and individuals in making tough decisions by generating a pros and cons list, SWOT analysis, multi-option analysis and causal chain analysis. By considering all relevant factors, Rationale helps users make rational decisions.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://rationale.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Rationale - a revolutionary decision-making tool powered by the latest GPT and in-context learning</div><div class="kg-bookmark-description">See two sides of the coin, make rational decisions. Use GPT and in-context learning to analyze pros &amp; cons, SWOT, cost-benefit, and two-choice problem. Rationale helps you make well-rounded decisions.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://rationale.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">Rationale</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://rationale.jina.ai/banner.png" alt=""></div></a></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Please force refresh the browser to see the latest change. This can be usually achieved by Hold ⇧ Shift (MacOS) or Ctrl (Windows/Linux) and click the Reload button.</div></div><p>We are excited to announce the release of Rationale 0.8, which comes packed with several new features and improvements to enhance your decision-making experience.</p><h2 id="new-persona-system">New persona system</h2><p>With Rationale 0.8, you can now write up to 2000 letters of backstory for your persona, providing more in-depth and personalized analysis for your decisions. This feature allows Rationale to better understand the context of your decisions and provide more relevant and accurate analysis.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-6.png" class="kg-image" alt="" width="1796" height="1390" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/02/image-6.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/02/image-6.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/02/image-6.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/02/image-6.png 1796w" sizes="(min-width: 720px) 720px"></figure><h2 id="causal-chain-analysis-with-context">Causal chain analysis with context</h2><p>Our outcomes analysis, also known as causal chain analysis, has been improved to consider the context of your decisions. With this feature, you can expect a more thorough and meaningful analysis of the potential outcomes of your decisions. Say goodbye to trivial outcomes and hello to more thoughtful and contextual analysis.</p><h2 id="ui-improvements">UI Improvements</h2><p>We've made several improvements to the user interface on desktop and mobile, making it easier and more intuitive to use. In addition, we've addressed several bugs to ensure a seamless and stable experience for our users.</p><p>We hope you enjoy these new features and improvements in Rationale 0.8. As always, we welcome your feedback and suggestions for future updates.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Frationale-0-8-update%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Read My Pics: SceneXplain Puts OCR in Your Visual Question Answering!</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">We're turbocharging SceneXplain's visual question answering with an OCR upgrade, making it easier than ever to get answers out of your images</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 20, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Back in June, we introduced visual question answering in SceneXplain, letting you upload an image and ask questions about it:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--22-.png" class="kg-image" alt="" width="594" height="680"><figcaption><a href="https://scenex.jina.ai/share?thread=6cSV82IdArG99bMiVq64&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>Now we're bringing a new model to the table, Glide. Glide reads and understands the text in images too, integrating OCR into the question-answering experience:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-33.png" class="kg-image" alt="" width="605" height="1407" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/image-33.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-33.png 605w"><figcaption><a href="https://scenex.jina.ai/share?thread=BjB1Q4LJ0UxWbR3XQIM0&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><h2 id="how-do-i-use-ocr-in-visual-question-answering">How do I use OCR in visual question answering?</h2><p>The process is exactly the same as for visual question answering in general. It's baked right in, meaning you don't have to toggle any additional options. Just enable "Visual question answer" and you're off to the races!</p><p>First, upload your image:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-29.png" class="kg-image" alt="" width="1236" height="191" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/image-29.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/image-29.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-29.png 1236w" sizes="(min-width: 720px) 720px"><figcaption>We're using <a href="https://www.pexels.com/photo/pink-neon-light-decoration-5198147/?ref=jina-ai-gmbh.ghost.io">this image</a> from Pexels.com</figcaption></figure><p>Then click on the speech bubble to ask your question:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-30.png" class="kg-image" alt="" width="1218" height="180" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/image-30.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/image-30.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-30.png 1218w" sizes="(min-width: 720px) 720px"></figure><p>Then click the button to send your data and, voila, <a href="https://scenex.jina.ai/share?thread=c0z1AaRusnSP7Tc16jv4&amp;ref=jina-ai-gmbh.ghost.io">your question will be answered</a>!</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-31.png" class="kg-image" alt="" width="606" height="730" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/image-31.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-31.png 606w"><figcaption><a href="https://scenex.jina.ai/share?thread=c0z1AaRusnSP7Tc16jv4&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><h2 id="whats-this-good-for">What's this good for?</h2><ul><li><strong>Accessibility for visually impaired users</strong>: SceneXplain can be used to provide descriptive text for images online or in digital documents, <a href="https://www.notion.so/Read-My-Pics-You-Got-OCR-in-My-Visual-Question-Answering-318345926b6541e5ae11dc7aad3e805e?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">helping visually impaired users understand the content more effectively</a>.</li><li><strong>Search Engine Optimization (SEO)</strong>: By providing accurate and detailed descriptions for images, SceneXplain can help improve the SEO of websites, as search engines rely heavily on text data. This is especially useful for products like apparel with brand names, slogans, or other text; or infographics that incorporate text into images. This becomes especially convenient when you perform batching via <a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io">SceneXplain’s API</a>, which we cover in <a href="https://jina.ai/news/brand-engagement-reimagined-ai-powered-sentiment-analysis-with-scenexplain/?ref=jina-ai-gmbh.ghost.io">this post</a>.</li><li><strong>Education</strong>: Teachers can use SceneXplain to create descriptive text for diagrams, illustrations, and other visual aids, making it easier for students who prefer or require reading over visual learning.</li><li><strong>Brand sentiment analysis</strong>: You can use SceneXplain to analyze images and associated text on social media platforms to better understand user sentiment and trends or to identify inappropriate content. This goes a step beyond regular <a href="https://www.notion.so/Read-My-Pics-You-Got-OCR-in-My-Visual-Question-Answering-318345926b6541e5ae11dc7aad3e805e?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">brand sentiment analysis</a> since it can detect brand logo text which would otherwise have been outside the model’s training set.</li><li><strong>Translation</strong>: When combined with a translation tool, SceneXplain can be used to read and translate text in images from one language to another, aiding in international communication and travel in foreign countries.</li></ul><h2 id="ocr-in-action">OCR in action</h2><p>The most obvious question you can ask is "What is the text in this image?"</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--24-.png" class="kg-image" alt="" width="575" height="1018"><figcaption><a href="https://scenex.jina.ai/share?thread=2NFEp8XVACtdmyArKBBA&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>But we're working with a large language model (LLM) here. Why limit ourselves to something so basic?</p><p>We can do things like translating graffiti:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--25-.png" class="kg-image" alt="" width="568" height="692"><figcaption><a href="https://scenex.jina.ai/share?thread=UHdUWc5OO34tmStxWYGa&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>...or correcting the translation of one language into another:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-34.png" class="kg-image" alt="" width="593" height="881"><figcaption><a href="https://scenex.jina.ai/share?thread=1uwd1ITd2ozqdQ6VRx5J&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>...or read signs:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--26-.png" class="kg-image" alt="" width="568" height="963"><figcaption><a href="https://scenex.jina.ai/share?thread=it4faIWXCgbKihRdQmOo&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>...or just get specific information from a sign:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--27-.png" class="kg-image" alt="" width="570" height="1111"><figcaption><a href="https://scenex.jina.ai/share?thread=EumC2Iq76m85sqFbtYz7&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>Maybe you're completely out of touch with geek culture and don't understand why something is funny. SceneXplain has got your back:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--28-.png" class="kg-image" alt="" width="573" height="818"><figcaption><a href="https://scenex.jina.ai/share?thread=JIDOdt82jZghL8Ecb9iF&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>...and we can even ask it to describe what we're pointing at. Forget point and click - now you've got point and explain!</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--29-.png" class="kg-image" alt="" width="572" height="962"><figcaption><a href="https://scenex.jina.ai/share?thread=KlRZX6wQqNjPZcDzfxxE&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><h2 id="get-started">Get started</h2><p>OC-are you ready to get started with SceneXplain? Head on over to <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">scenex.jina.ai</a> to create your account, and start uploading your images and asking your questions. Need support or want to share your results? You can do that on our <a href="https://www.notion.so/Read-My-Pics-You-Got-OCR-in-My-Visual-Question-Answering-318345926b6541e5ae11dc7aad3e805e?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">Discord channel</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><h2 id="read-more">Read more</h2><p>Want to dig deeper? We've written a bunch of other posts about what you can do with SceneXplain:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/brand-engagement-reimagined-ai-powered-sentiment-analysis-with-scenexplain?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Brand Engagement Reimagined: AI-Powered Sentiment Analysis with SceneXplain</div><div class="kg-bookmark-description">Digging deep into images to uncover sentiment and brand can be a wild ride. Tackle it with SceneXplain, and you’ve got yourself a business power-up, ready to take the market by storm</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Sentiment-analysis.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/making-visuals-vocal-scenexplains-impact-on-product-image-accessibility?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Making Visuals Vocal: SceneXplain’s Impact on Product Image Accessibility</div><div class="kg-bookmark-description">SceneXplain transforms product images into audio descriptions, ensuring visual content isn’t just seen, but also heard and understood. It’s a step forward in creating an inclusive digital world for everyone</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Blog-images--9-.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-vs-minigpt4-a-comprehensive-benchmark-of-top-5-image-captioning-algorithms-for-understanding-complex-scenes?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain vs. MiniGPT4: A Comprehensive Benchmark of Top 5 Image Captioning Algorithms for Understanding Complex Scenes</div><div class="kg-bookmark-description">Uncover the future of image captioning as SceneXplain and its rivals face off in an epic showdown. Explore their impact on accessibility, SEO, and storytelling, and dive into our intriguing results to witness the cutting-edge capabilities of these algorithms.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150443.130.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</div><div class="kg-bookmark-description">Explore SceneXplain’s impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-unleash-advanced-image-captioning-storytelling?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain: Unleash the Advanced Image Captioning &amp; Storytelling</div><div class="kg-bookmark-description">Uncover the game-changing potential of SceneXplain, an advanced image captioning solution powered by LLMs. Check out the benchmark against Midjourney, CLIP, BLIP2, and other alternatives. Dive into our blog post and experience the revolution firsthand!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates--98-.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fread-my-pics-you-got-ocr-in-my-visual-question-answering%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">We're turbocharging SceneXplain's visual question answering with an OCR upgrade, making it easier than ever to get answers out of your images</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 20, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Back in June, we introduced visual question answering in SceneXplain, letting you upload an image and ask questions about it:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--22-.png" class="kg-image" alt="" width="594" height="680"><figcaption><a href="https://scenex.jina.ai/share?thread=6cSV82IdArG99bMiVq64&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>Now we're bringing a new model to the table, Glide. Glide reads and understands the text in images too, integrating OCR into the question-answering experience:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-33.png" class="kg-image" alt="" width="605" height="1407" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/image-33.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-33.png 605w"><figcaption><a href="https://scenex.jina.ai/share?thread=BjB1Q4LJ0UxWbR3XQIM0&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><h2 id="how-do-i-use-ocr-in-visual-question-answering">How do I use OCR in visual question answering?</h2><p>The process is exactly the same as for visual question answering in general. It's baked right in, meaning you don't have to toggle any additional options. Just enable "Visual question answer" and you're off to the races!</p><p>First, upload your image:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-29.png" class="kg-image" alt="" width="1236" height="191" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/image-29.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/image-29.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-29.png 1236w" sizes="(min-width: 720px) 720px"><figcaption>We're using <a href="https://www.pexels.com/photo/pink-neon-light-decoration-5198147/?ref=jina-ai-gmbh.ghost.io">this image</a> from Pexels.com</figcaption></figure><p>Then click on the speech bubble to ask your question:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-30.png" class="kg-image" alt="" width="1218" height="180" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/image-30.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/image-30.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-30.png 1218w" sizes="(min-width: 720px) 720px"></figure><p>Then click the button to send your data and, voila, <a href="https://scenex.jina.ai/share?thread=c0z1AaRusnSP7Tc16jv4&amp;ref=jina-ai-gmbh.ghost.io">your question will be answered</a>!</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-31.png" class="kg-image" alt="" width="606" height="730" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/image-31.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-31.png 606w"><figcaption><a href="https://scenex.jina.ai/share?thread=c0z1AaRusnSP7Tc16jv4&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><h2 id="whats-this-good-for">What's this good for?</h2><ul><li><strong>Accessibility for visually impaired users</strong>: SceneXplain can be used to provide descriptive text for images online or in digital documents, <a href="https://www.notion.so/Read-My-Pics-You-Got-OCR-in-My-Visual-Question-Answering-318345926b6541e5ae11dc7aad3e805e?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">helping visually impaired users understand the content more effectively</a>.</li><li><strong>Search Engine Optimization (SEO)</strong>: By providing accurate and detailed descriptions for images, SceneXplain can help improve the SEO of websites, as search engines rely heavily on text data. This is especially useful for products like apparel with brand names, slogans, or other text; or infographics that incorporate text into images. This becomes especially convenient when you perform batching via <a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io">SceneXplain’s API</a>, which we cover in <a href="https://jina.ai/news/brand-engagement-reimagined-ai-powered-sentiment-analysis-with-scenexplain/?ref=jina-ai-gmbh.ghost.io">this post</a>.</li><li><strong>Education</strong>: Teachers can use SceneXplain to create descriptive text for diagrams, illustrations, and other visual aids, making it easier for students who prefer or require reading over visual learning.</li><li><strong>Brand sentiment analysis</strong>: You can use SceneXplain to analyze images and associated text on social media platforms to better understand user sentiment and trends or to identify inappropriate content. This goes a step beyond regular <a href="https://www.notion.so/Read-My-Pics-You-Got-OCR-in-My-Visual-Question-Answering-318345926b6541e5ae11dc7aad3e805e?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">brand sentiment analysis</a> since it can detect brand logo text which would otherwise have been outside the model’s training set.</li><li><strong>Translation</strong>: When combined with a translation tool, SceneXplain can be used to read and translate text in images from one language to another, aiding in international communication and travel in foreign countries.</li></ul><h2 id="ocr-in-action">OCR in action</h2><p>The most obvious question you can ask is "What is the text in this image?"</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--24-.png" class="kg-image" alt="" width="575" height="1018"><figcaption><a href="https://scenex.jina.ai/share?thread=2NFEp8XVACtdmyArKBBA&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>But we're working with a large language model (LLM) here. Why limit ourselves to something so basic?</p><p>We can do things like translating graffiti:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--25-.png" class="kg-image" alt="" width="568" height="692"><figcaption><a href="https://scenex.jina.ai/share?thread=UHdUWc5OO34tmStxWYGa&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>...or correcting the translation of one language into another:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-34.png" class="kg-image" alt="" width="593" height="881"><figcaption><a href="https://scenex.jina.ai/share?thread=1uwd1ITd2ozqdQ6VRx5J&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>...or read signs:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--26-.png" class="kg-image" alt="" width="568" height="963"><figcaption><a href="https://scenex.jina.ai/share?thread=it4faIWXCgbKihRdQmOo&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>...or just get specific information from a sign:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--27-.png" class="kg-image" alt="" width="570" height="1111"><figcaption><a href="https://scenex.jina.ai/share?thread=EumC2Iq76m85sqFbtYz7&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>Maybe you're completely out of touch with geek culture and don't understand why something is funny. SceneXplain has got your back:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--28-.png" class="kg-image" alt="" width="573" height="818"><figcaption><a href="https://scenex.jina.ai/share?thread=JIDOdt82jZghL8Ecb9iF&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><p>...and we can even ask it to describe what we're pointing at. Forget point and click - now you've got point and explain!</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Untitled--29-.png" class="kg-image" alt="" width="572" height="962"><figcaption><a href="https://scenex.jina.ai/share?thread=KlRZX6wQqNjPZcDzfxxE&amp;ref=jina-ai-gmbh.ghost.io">View on SceneXplain</a></figcaption></figure><h2 id="get-started">Get started</h2><p>OC-are you ready to get started with SceneXplain? Head on over to <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">scenex.jina.ai</a> to create your account, and start uploading your images and asking your questions. Need support or want to share your results? You can do that on our <a href="https://www.notion.so/Read-My-Pics-You-Got-OCR-in-My-Visual-Question-Answering-318345926b6541e5ae11dc7aad3e805e?pvs=21&amp;ref=jina-ai-gmbh.ghost.io">Discord channel</a>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><h2 id="read-more">Read more</h2><p>Want to dig deeper? We've written a bunch of other posts about what you can do with SceneXplain:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/brand-engagement-reimagined-ai-powered-sentiment-analysis-with-scenexplain?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Brand Engagement Reimagined: AI-Powered Sentiment Analysis with SceneXplain</div><div class="kg-bookmark-description">Digging deep into images to uncover sentiment and brand can be a wild ride. Tackle it with SceneXplain, and you’ve got yourself a business power-up, ready to take the market by storm</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Sentiment-analysis.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/making-visuals-vocal-scenexplains-impact-on-product-image-accessibility?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Making Visuals Vocal: SceneXplain’s Impact on Product Image Accessibility</div><div class="kg-bookmark-description">SceneXplain transforms product images into audio descriptions, ensuring visual content isn’t just seen, but also heard and understood. It’s a step forward in creating an inclusive digital world for everyone</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Blog-images--9-.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-vs-minigpt4-a-comprehensive-benchmark-of-top-5-image-captioning-algorithms-for-understanding-complex-scenes?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain vs. MiniGPT4: A Comprehensive Benchmark of Top 5 Image Captioning Algorithms for Understanding Complex Scenes</div><div class="kg-bookmark-description">Uncover the future of image captioning as SceneXplain and its rivals face off in an epic showdown. Explore their impact on accessibility, SEO, and storytelling, and dive into our intriguing results to witness the cutting-edge capabilities of these algorithms.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150443.130.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</div><div class="kg-bookmark-description">Explore SceneXplain’s impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-unleash-advanced-image-captioning-storytelling?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain: Unleash the Advanced Image Captioning &amp; Storytelling</div><div class="kg-bookmark-description">Uncover the game-changing potential of SceneXplain, an advanced image captioning solution powered by LLMs. Check out the benchmark against Midjourney, CLIP, BLIP2, and other alternatives. Dive into our blog post and experience the revolution firsthand!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates--98-.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fread-my-pics-you-got-ocr-in-my-visual-question-answering%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Real-Time Product Recommendation via DocArray and Redis</title><meta charset="utf-8"><meta name="title" content="Real-Time Product Recommendation via DocArray and Redis"><meta name="description" content="By using Redis backend inside DocArray, building a real-time product recommendation system via vector similarity search is easy and straightforward. Follow along to learn the essential steps and how it works."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/real-time-product-recommendation-using-redis-and-docarray"><meta property="og:title" content="Real-Time Product Recommendation via DocArray and Redis"><meta property="og:description" content="By using Redis backend inside DocArray, building a real-time product recommendation system via vector similarity search is easy and straightforward. Follow along to learn the essential steps and how it works."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--4-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/real-time-product-recommendation-using-redis-and-docarray"><meta property="twitter:title" content="Real-Time Product Recommendation via DocArray and Redis"><meta property="twitter:description" content="By using Redis backend inside DocArray, building a real-time product recommendation system via vector similarity search is easy and straightforward. Follow along to learn the essential steps and how it works."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--4-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Real-Time Product Recommendation via DocArray and Redis</title><meta charset="utf-8"><meta name="title" content="Real-Time Product Recommendation via DocArray and Redis"><meta name="description" content="By using Redis backend inside DocArray, building a real-time product recommendation system via vector similarity search is easy and straightforward. Follow along to learn the essential steps and how it works."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/real-time-product-recommendation-using-redis-and-docarray"><meta property="og:title" content="Real-Time Product Recommendation via DocArray and Redis"><meta property="og:description" content="By using Redis backend inside DocArray, building a real-time product recommendation system via vector similarity search is easy and straightforward. Follow along to learn the essential steps and how it works."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--4-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/real-time-product-recommendation-using-redis-and-docarray"><meta property="twitter:title" content="Real-Time Product Recommendation via DocArray and Redis"><meta property="twitter:description" content="By using Redis backend inside DocArray, building a real-time product recommendation system via vector similarity search is easy and straightforward. Follow along to learn the essential steps and how it works."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--4-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Real-Time Product Recommendation via DocArray and Redis</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">By using Redis backend inside DocArray, building a real-time product recommendation system via vector similarity search is easy and straightforward. Follow along to learn the essential steps and how it works.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/me_smaller.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alaeddine Abdessalem, Nicholas Dunham</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 09, 2022 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Recommendation systems are an important technology for most online businesses and for e-commerce sites in particular. They’re an essential element in generating good conversion and maintaining customer loyalty.</p><p>A recommendation system typically shows items to users based on the users’ profiles and preferences and by observing their actions (such as buying, liking, or viewing items).</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/applsci-10-05510-g001.webp" class="kg-image" alt="" width="2000" height="1206" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/applsci-10-05510-g001.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/applsci-10-05510-g001.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/applsci-10-05510-g001.webp 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/applsci-10-05510-g001.webp 2400w" sizes="(min-width: 720px) 720px"><figcaption>Source: https://www.mdpi.com/2076-3417/10/16/5510/htm</figcaption></figure><p>Consider the challenges involved in building a recommendation system for a modern e-commerce site. This is just a subset of the issues to consider:</p><ul><li><strong>Customization:</strong> Customers want to filter results, such as by price range, brand, and size. Our system should recommend products only within these parameters.</li><li><strong>Multiple modalities:</strong> A product listing is more than a text description. It can also contain images, video, audio, and 3D mesh, for example. All available data modalities should be exploited when making recommendations.</li><li><strong>Latency:</strong> Customers expect recommendations to appear quickly. If the system’s recommendations aren’t returned immediately, they’re irrelevant.</li><li><strong>Data volume:</strong> The more products and customers the site has, the harder it is to recommend products efficiently. Computing recommendations should stay fast even with big datasets.</li></ul><p>As these requirements evolve, approaches to building recommendation systems need to evolve as well. </p><p>In this blog post, we show you how to build a real-time product recommendation system with respect to user-defined filters using the latest vector search technology. The tool suite includes Redis and DocArray, but the methodology is relevant no matter which tools you employ.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://redis.io/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Redis</div><div class="kg-bookmark-description">Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://redis.io/images/favicons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">Redis</span></div></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Welcome to DocArray!</div><div class="kg-bookmark-description">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer the multi-modal data with a Pythonic API. 🚪 Door to cross-/multi-m..…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docarray.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">DocArray 0.18.2 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docarray.jina.ai/_static/banner.png" alt=""></div></a></figure><figure class="kg-card kg-code-card"><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Real-Time Product Recommendation via DocArray and Redis</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">By using Redis backend inside DocArray, building a real-time product recommendation system via vector similarity search is easy and straightforward. Follow along to learn the essential steps and how it works.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 87.45%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/CV_photo.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/me_smaller.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alaeddine Abdessalem, Nicholas Dunham</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 09, 2022 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Recommendation systems are an important technology for most online businesses and for e-commerce sites in particular. They’re an essential element in generating good conversion and maintaining customer loyalty.</p><p>A recommendation system typically shows items to users based on the users’ profiles and preferences and by observing their actions (such as buying, liking, or viewing items).</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/applsci-10-05510-g001.webp" class="kg-image" alt="" width="2000" height="1206" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/applsci-10-05510-g001.webp 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/applsci-10-05510-g001.webp 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/applsci-10-05510-g001.webp 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/applsci-10-05510-g001.webp 2400w" sizes="(min-width: 720px) 720px"><figcaption>Source: https://www.mdpi.com/2076-3417/10/16/5510/htm</figcaption></figure><p>Consider the challenges involved in building a recommendation system for a modern e-commerce site. This is just a subset of the issues to consider:</p><ul><li><strong>Customization:</strong> Customers want to filter results, such as by price range, brand, and size. Our system should recommend products only within these parameters.</li><li><strong>Multiple modalities:</strong> A product listing is more than a text description. It can also contain images, video, audio, and 3D mesh, for example. All available data modalities should be exploited when making recommendations.</li><li><strong>Latency:</strong> Customers expect recommendations to appear quickly. If the system’s recommendations aren’t returned immediately, they’re irrelevant.</li><li><strong>Data volume:</strong> The more products and customers the site has, the harder it is to recommend products efficiently. Computing recommendations should stay fast even with big datasets.</li></ul><p>As these requirements evolve, approaches to building recommendation systems need to evolve as well. </p><p>In this blog post, we show you how to build a real-time product recommendation system with respect to user-defined filters using the latest vector search technology. The tool suite includes Redis and DocArray, but the methodology is relevant no matter which tools you employ.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://redis.io/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Redis</div><div class="kg-bookmark-description">Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://redis.io/images/favicons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">Redis</span></div></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Welcome to DocArray!</div><div class="kg-bookmark-description">DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer the multi-modal data with a Pythonic API. 🚪 Door to cross-/multi-m..…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docarray.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">DocArray 0.18.2 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docarray.jina.ai/_static/banner.png" alt=""></div></a></figure><figure class="kg-card kg-code-card"><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
 
 redis_da = DocumentArray(storage=<span class="hljs-string">'redis'</span>)</code></pre><figcaption>Using Redis as the backend in DocArray is extremely simple and intuitive. <a href="https://docarray.jina.ai/advanced/document-store/redis/?ref=jina-ai-gmbh.ghost.io">More info can be found in the docs</a>.</figcaption></figure><h2 id="what-makes-a-recommendation-system">What Makes a Recommendation System?</h2><p>As with any other computing problem, there are multiple approaches to building recommendation systems and tools to support each effort. They include:</p><ul><li><strong>Collaborative filtering:</strong> The system predicts items relevant to the user based on the preferences of similar users.</li><li><strong>Content-based filtering:</strong> The system models the user’s interests as feature vectors and predicts relevant items based on the similarity between vectors.</li><li><strong>Hybrid approaches:</strong> The system combines collaborative filtering, content-based filtering, and other approaches.</li></ul><p>This blog post focuses on improving the content-based filtering approach. If you’re new to this topic, it may help to read <a href="https://developers.google.com/machine-learning/recommendation/content-based/basics?ref=jina-ai-gmbh.ghost.io">Google's overview of content-based filtering</a> first.</p><p>There are two important considerations when implementing content-based filtering:</p><p>First, when you model the user and items as a feature vector, it’s important to exploit all modalities of the data. Simply relying on keywords or a set of engineered features might not efficiently represent complex data.</p><p>That’s why state-of-the-art AI models are important, as they represent complex, multimodal data as vector embeddings.<br><br>One of the best-known models to represent both text and image data is <a href="https://github.com/openai/CLIP?ref=jina-ai-gmbh.ghost.io">CLIP</a>. Therefore, we’ll use CLIP-as-service as the inference engine that powers our recommendations.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://clip-as-service.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Welcome to CLIP-as-service!</div><div class="kg-bookmark-description">CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a microservice into neural search solutions. ⚡ Fast: Serve CLIP models with TensorRT, ONNX runtime and PyTorch w/o JIT with 800QPS[*]. Non-blocking duplex streaming on requests ...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://clip-as-service.jina.ai/_static/favicon.png" alt=""><span class="kg-bookmark-author">CLIP-as-service 0.8.1 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://clip-as-service.jina.ai/_static/banner.png" alt=""></div></a></figure><p>Also, computing vector similarity can be slow and costly if not performed efficiently. Our application requirements (to respect user filters and deliver low-latency recommendations) make it impractical to pre-compute similarity between items and user profiles in batch jobs. That’s why it’s crucial to compute vector similarity in real-time, using efficient techniques such as Hierarchical Navigable Small World (<a href="https://arxiv.org/abs/1603.09320?ref=jina-ai-gmbh.ghost.io">HNSW</a>).<br><br>These techniques are implemented in vector databases. Redis offers vector search capabilities in <a href="https://redis.com/modules/redis-search/?ref=jina-ai-gmbh.ghost.io">RediSearch</a> 2.4. And since Redis is an in-memory database, recommending items is both fast and performed in a real-time context.</p><p>With feature representation and computing vector similarity covered, we still need a data structure that bridges the gap between our multimodal data and the vector database. For that, we’ll use DocArray. Think of DocArray as a universal vector database client with support for multimodal data. It has a Pythonic interface that makes it easy to build our recommendation system in just a few lines of code.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/3.png" class="kg-image" alt="3.png" width="2000" height="1220" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/3.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/10/3.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>DocArray can handle multiple data types such as images, videos, audios, 3D meshes. It can store them into different vector databases such as Redis, ElasticSearch, Weaviate, Qdrant.</figcaption></figure><h2 id="solution-docarray-with-redis-backend">Solution: DocArray with Redis Backend</h2><p>We have assembled the tools for this application: Redis for Vector Similarity Search, CLIP-as-service to encode visual data, and DocArray to represent multimodal documents and to connect to Redis. In this tutorial we apply these technologies to build a content-based filtering recommendation system.</p><p>The procedure is as follows:</p><ul><li>Load the dataset into DocArray format.</li><li>Model products by encoding product images using CLIP-as-service.</li><li>Model the user profile by computing the weighted average of the last <em>k</em> viewed products’ embeddings.</li><li>Index the product data in Redis.</li><li>Use Redis Vector Similarity Search to recommend the most similar items to the user’s view history, while also filtering those results to respect user preferences.</li></ul><p>In the instruction that follows, the data we use &nbsp;for product recommendations comes from the <a href="https://amazon-berkeley-objects.s3.amazonaws.com/index.html?ref=jina-ai-gmbh.ghost.io">Amazon Berkeley Objects Dataset</a>, a dataset of Amazon products with metadata, catalog images, and 3D models.</p><h3 id="installing-docarray-and-redis">Installing DocArray and Redis</h3><p>The first step is to provision a Redis instance. You can create a local Redis instance using Docker:</p><pre><code class="language-bash hljs">docker run -d -p 6379:6379 redis/redis-stack:latest
 </code></pre><p>Next, we need to install DocArray, <a href="https://docs.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina</a>, and clip-client:</p><pre><code class="language-bash hljs">pip install docarray[redis] jina clip-client
@@ -106,4 +106,4 @@
 </code></pre><h2 id="validating-the-results">Validating the Results</h2><p>Let's try it out a few times. First, let’s view the first item in the store and the recommendations for it:</p><pre><code class="language-python hljs">recommended = view(redis_da[<span class="hljs-number">0</span>], view_history)
 </code></pre><p>That displays an attractive scarf, labeled as "Thirty Five Kent Men's Cashmere Zig Zag Scarf, Blue":</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--3-.png" class="kg-image" alt="Untitled" width="219" height="256"></figure><p>…and the accompanying recommendations:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--4-.png" class="kg-image" alt="Untitled" width="734" height="590" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Untitled--4-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--4-.png 734w" sizes="(min-width: 720px) 720px"></figure><p>How well do they meet the user's filter?</p><p>Let’s check the third item in the recommendation list and apply a filter <code>color='Navy'</code> to ensure a better match:</p><pre><code class="language-python hljs">recommended = view(recommended[<span class="hljs-number">2</span>], view_history, color=<span class="hljs-string">'Navy'</span>)
 </code></pre><p>…which generates a better item display and recommendations:</p><p>Thirty Five Kent Men's Cashmere Zig Zag Scarf, Blue:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--6-.png" class="kg-image" alt="Untitled" width="166" height="256"></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--5-.png" class="kg-image" alt="Untitled" width="734" height="590" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Untitled--5-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled--5-.png 734w" sizes="(min-width: 720px) 720px"></figure><p>Now the recommendation function returns the most visually similar items to scarves that also satisfy the filter <code>color='Navy'</code>.</p><p>Success! And, possibly, a new ecommerce sale.</p><h2 id="putting-it-all-together">Putting it All Together</h2><p>The instructions above are a brief overview to demonstrate the building blocks for a process to recommend products in an online store.</p><p>You're welcome to take it farther. We’ve created <a href="https://github.com/jina-ai/product-recommendation-redis-docarray?ref=jina-ai-gmbh.ghost.io">a GitHub repository with source code</a> for a product store interface with the same dataset and technique we just showed.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/recommendation-demo.gif" class="kg-image" alt="recommendation-demo.gif" width="1322" height="620" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/recommendation-demo.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/recommendation-demo.gif 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/recommendation-demo.gif 1322w" sizes="(min-width: 720px) 720px"></figure><p>This demonstration just showed you how Vector Similarity Search can offer low-latency real-time recommendations that respect user preferences and filter selection.</p><p>But how fast is it? Let’s look at the latency numbers for recommendation queries. You can find logs in the command line console:</p><pre><code class="hljs language-scss">Retrieving products ... Retrieving products takes <span class="hljs-number">0</span> seconds (<span class="hljs-number">0.01s</span>)
-</code></pre><p><strong>This means computing recommendations takes around 10 milliseconds!</strong></p><p>Of course, there’s still room for improvement, especially when it comes to quality. For example, we can come up with more sophisticated ways to model the user’s profile and interests. We could also incorporate more types of data, such as 3D mesh and video. That's left as an exercise to the reader.</p><h2 id="whats-next">What's Next?</h2><p>Vector Similarity Search is an essential technique to implement recommendations in a real-time context. Your next steps:</p><ul><li>Use state-of-the-art AI models to encode multimodal data into vector representations.</li><li>Use a vector database to compute vector similarity in a real-time context. For low latency, an in-memory database like Redis is ideal. Check the <a href="https://redis.io/docs/?ref=jina-ai-gmbh.ghost.io">Redis Documentation</a> for more information and get started with <a href="https://redis.com/try-free/?ref=jina-ai-gmbh.ghost.io">Redis Cloud free tier</a>.</li><li>Use DocArray as a convenient data structure for handling multimodal data as well as interfacing with the vector database. Check the <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray Documentation</a> to get started.</li></ul><p></p><p></p><p></p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Freal-time-product-recommendation-using-redis-and-docarray%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+</code></pre><p><strong>This means computing recommendations takes around 10 milliseconds!</strong></p><p>Of course, there’s still room for improvement, especially when it comes to quality. For example, we can come up with more sophisticated ways to model the user’s profile and interests. We could also incorporate more types of data, such as 3D mesh and video. That's left as an exercise to the reader.</p><h2 id="whats-next">What's Next?</h2><p>Vector Similarity Search is an essential technique to implement recommendations in a real-time context. Your next steps:</p><ul><li>Use state-of-the-art AI models to encode multimodal data into vector representations.</li><li>Use a vector database to compute vector similarity in a real-time context. For low latency, an in-memory database like Redis is ideal. Check the <a href="https://redis.io/docs/?ref=jina-ai-gmbh.ghost.io">Redis Documentation</a> for more information and get started with <a href="https://redis.com/try-free/?ref=jina-ai-gmbh.ghost.io">Redis Cloud free tier</a>.</li><li>Use DocArray as a convenient data structure for handling multimodal data as well as interfacing with the vector database. Check the <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray Documentation</a> to get started.</li></ul><p></p><p></p><p></p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Freal-time-product-recommendation-using-redis-and-docarray%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Redefining Text-to-Image: How BestBanner Outperforms Midjourney and Stable Diffusion - A Benchmark Analysis</title><meta charset="utf-8"><meta name="title" content="Redefining Text-to-Image: How BestBanner Outperforms Midjourney and Stable Diffusion - A Benchmark Analysis"><meta name="description" content="BestBanner is an AI-powered text-to-image generation system. It takes article text as input and generates high-quality social media banners. This saves you from the task of crafting images and lets you focus on creating content."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/redefining-text-to-image-how-bestbanner-outperforms-midjourney-and-stable-diffusion-a-benchmark-analysis"><meta property="og:title" content="Redefining Text-to-Image: How BestBanner Outperforms Midjourney and Stable Diffusion - A Benchmark Analysis"><meta property="og:description" content="BestBanner is an AI-powered text-to-image generation system. It takes article text as input and generates high-quality social media banners. This saves you from the task of crafting images and lets you focus on creating content."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/redefining-text-to-image-how-bestbanner-outperforms-midjourney-and-stable-diffusion-a-benchmark-analysis"><meta property="twitter:title" content="Redefining Text-to-Image: How BestBanner Outperforms Midjourney and Stable Diffusion - A Benchmark Analysis"><meta property="twitter:description" content="BestBanner is an AI-powered text-to-image generation system. It takes article text as input and generates high-quality social media banners. This saves you from the task of crafting images and lets you focus on creating content."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Redefining Text-to-Image: How BestBanner Outperforms Midjourney and Stable Diffusion - A Benchmark Analysis</title><meta charset="utf-8"><meta name="title" content="Redefining Text-to-Image: How BestBanner Outperforms Midjourney and Stable Diffusion - A Benchmark Analysis"><meta name="description" content="BestBanner is an AI-powered text-to-image generation system. It takes article text as input and generates high-quality social media banners. This saves you from the task of crafting images and lets you focus on creating content."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/redefining-text-to-image-how-bestbanner-outperforms-midjourney-and-stable-diffusion-a-benchmark-analysis"><meta property="og:title" content="Redefining Text-to-Image: How BestBanner Outperforms Midjourney and Stable Diffusion - A Benchmark Analysis"><meta property="og:description" content="BestBanner is an AI-powered text-to-image generation system. It takes article text as input and generates high-quality social media banners. This saves you from the task of crafting images and lets you focus on creating content."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/redefining-text-to-image-how-bestbanner-outperforms-midjourney-and-stable-diffusion-a-benchmark-analysis"><meta property="twitter:title" content="Redefining Text-to-Image: How BestBanner Outperforms Midjourney and Stable Diffusion - A Benchmark Analysis"><meta property="twitter:description" content="BestBanner is an AI-powered text-to-image generation system. It takes article text as input and generates high-quality social media banners. This saves you from the task of crafting images and lets you focus on creating content."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Redefining Text-to-Image: How BestBanner Outperforms Midjourney and Stable Diffusion - A Benchmark Analysis</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">BestBanner is an AI-powered text-to-image generation system. It takes article text as input and generates high-quality social media banners. This saves you from the task of crafting images and lets you focus on creating content.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Me.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G, Andrei Ungureanu</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 12, 2023 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Another week, another product announcement! Our engineers have been working day in and day out, and burning the midnight oil to bring you Jina AI’s latest tool in the generative AI toolbox: BestBanner.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">BestBanner - Blog to banner, without the prompts!</div><div class="kg-bookmark-description">BestBanner revolutionizes the way you create banner images. Simply input your article text, and watch as our advanced multimodal AI crafts a unique and captivating image, tailored specifically to your content. Ideal for publishers, bloggers, and content creators.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://bestbanner.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">BestBanner</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://bestbanner.jina.ai/banner.png" alt=""></div></a></figure><p>BestBanner is a unique AI-powered text-to-image generation system. It takes the text from an article as input and generates high-quality social media banners. This saves you from the time-consuming task of crafting images and allows you to focus on creating great content.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/07/BestBanner-promo1-1.mp4" poster="https://img.spacergif.org/v1/3840x2160/0a/spacer.png" width="3840" height="2160" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/07/media-thumbnail-ember208.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>It’s as simple as pasting your article (or tweet) text into BestBanner and hitting “Go”.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-14.png" class="kg-image" alt="" width="1518" height="382" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/image-14.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-14.png 1518w" sizes="(min-width: 720px) 720px"><figcaption>Copied from reader view of <a href="https://screenrant.com/barbie-oppenheimer-nolan-box-office-battle-deeper-meaning/?ref=jina-ai-gmbh.ghost.io">this article</a> on Barbie vs Oppenheimer</figcaption></figure><p>No need to worry about how long your post is, and whether the model can handle that much information. And no need to deal with janky Discord UIs to generate your images either.</p><p>Wait a few minutes and you’ll get four output images, each of which you can choose to refine.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-15.png" class="kg-image" alt="" width="584" height="695"><figcaption>See the full-size images <a href="https://bestbanner.jina.ai/share?id=7ebe59ba-4c6b-4503-a037-587c4ae22ea2&amp;ref=jina-ai-gmbh.ghost.io">here</a></figcaption></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">😳</div><div class="kg-callout-text">These pictures don't look great - but that's a feature, not a bug! BestBanner <em>quickly</em> generates very different images from your content, giving you more leeway to choose unique styles when you refine your banner.</div></div><p>Next up, click the refine button to get high-quality variants of your desired style:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-16.png" class="kg-image" alt="" width="598" height="656"></figure><p>BestBanner will now take that image and riff on it, giving you four variations:</p><p>After a round or two of refinement you’ll have the banner image of your dreams:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-18.png" class="kg-image" alt="" width="588" height="697"><figcaption>See the full-size images <a href="https://bestbanner.jina.ai/share?id=90ee24ba-c0c1-4cce-9501-0c01fff0a97e&amp;ref=jina-ai-gmbh.ghost.io">here</a></figcaption></figure><p>Once you’ve found something you like, you can preview how it’ll look on your social network of choice, crop accordingly, and download for use:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-21.png" class="kg-image" alt="" width="573" height="789"></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-20.png" class="kg-image" alt="" width="719" height="448" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/image-20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-20.png 719w"></figure><p>Whether you’re a writer, content creator, or tweeter/skeeter/tooter/whatever-the-new-thing is, BestBanner is a great tool to add to your creative arsenal.</p><h2 id="why-are-social-media-banners-important-anyway">Why are social media banners important anyway?</h2><p>The power of compelling social media banners for articles, blog posts, and other content is critical in today's digital landscape. As a content creator, your banners are essentially the digital storefront of your work, your first opportunity to capture the attention of potential readers amidst the digital clutter of their feeds. An eye-catching banner doesn’t just instantly communicate the essence of your content, but also entices viewers to click through and engage with your material. In a highly visual online world, these banners can dramatically elevate the visibility and impact of your content. What's more, many social media platforms' algorithms prioritize visually rich and engaging content, meaning your carefully-crafted banners can also boost your reach organically. Therefore, investing in the creation of compelling social media banners is a vital aspect of a successful content strategy.</p><p>BestBanner is an indispensable tool for making these banners happen, given its innovative application of AI-powered image generation. By allowing you to effortlessly convert blog posts, tweets, and articles into compelling social media banners, BestBanner eliminates the time-consuming task of manual graphic design. You simply copy and paste your content, and with a click, generate a selection of candidate images finely tuned to the essence of your post. These images can be further refined and downloaded, providing you with a visually striking banner that resonates with your audience and enhances engagement.</p><h2 id="how-is-bestbanner-different-from-midjourney-stable-diffusion-et-al">How is BestBanner different from Midjourney, Stable Diffusion, et al?</h2><p>Don’t get us wrong - we love Midjourney and Stable Diffusion. They’ve completely changed the game in generative AI. But BestBanner differs in several key ways:</p><p><strong>Copy and paste, don’t think:</strong> No need for you to wrack your brains thinking of what would make a perfect image for your article. Just paste the whole thing in and smack go. You don’t even need to remove formatting or surrounding HTML.</p><p><strong>Hyperfocus</strong>: Midjourney, Stable Diffusion, DALL-E 2 and the others are all <strong>general-purpose</strong> image generation models. So they’re a good tool whether you want to generate a social media avatar, a logo or a poster, they’ll all do a <em>reasonable</em> job. But since they don’t focus on one thing in particular, they become Jacks of all Trades, and masters of none. On the other hand, BetterBanner is <strong>specialized for social media banner creation</strong>.</p><p><strong>Unlimited context length:</strong> Other models are all designed to use prompts — short snippets of text that require a lot of tuning to get good results. BestBanner goes a step further and lets you use the whole text of your blog post, article, or tweet. You don’t need to think about what the most relevant point of your wall of text is - BestBanner works out what’s important.</p><p><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong>Multi-model</strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong>: While Midjourney and Stable Diffusion let you generate images with one model at a time, BestBanner uses three models to generate four images. This gives you a more varied array of stylistic and subject choices to choose from when it comes to refinement</p><p><strong>Easy API access:</strong> Midjourney is only usable through their Discord bot, while BestBanner has an accessible API for you to programmatically generate banners with ease.</p><p><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong>No censorship</strong></strong></strong></strong></strong></strong></strong></strong></strong></strong>: In our testing, both Midjourney and Stable Diffusion often censor on the prompt level, immediately barring us from creating certain images. In other cases, Stable Diffusion simply generates sterile generic content given certain prompts. (None of these prompts were in any way obscene - often they referenced politics or were entirely innocuous). <strong>BestBanner has shown no such political or random censorship</strong>.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">ℹ️</div><div class="kg-callout-text">That’s not to say BestBanner <em>never</em> censors - we’ve just seen none of it so far compared to other models.</div></div><h2 id="showdown-battle-of-the-banners">Showdown: Battle of the Banners</h2><p>So, how does BestBanner stack up against the other models? It’s time to throw our contenders into the ring to find out. But before we munch on popcorn and watch the slugfest, we’ll establish some ground rules:</p><ul><li>We’ll use a selection of classic literature and news posts as our inputs.</li><li>For each model we’ll generate four candidate images - in Midjourney and BestBanner this is done in one shot, in Stable Diffusion by generating four separate images.</li><li>Since Midjourney and Stable Diffusion both have limited prompt length, we use only the first few sentences of the post as their prompt. For BestBanner we use the contents of the entire post (sometimes the plain text content, sometimes a straight-up formatted copy-paste).</li><li>For BestBanner we’ll run one round of refinement from a selected candidate from the initial generation.</li></ul><p>In this section we'll just showcase the images themselves. Check further down for an interpretation of how Stable Diffusion, Midjourney, and BestBanner stack up based on this benchmark, covering topicality, quality, composition, etc. </p><h3 id="alices-adventures-in-wonderland-chapter-one-down-the-rabbit-hole"><a href="https://www.gutenberg.org/files/11/11-h/11-h.htm?ref=jina-ai-gmbh.ghost.io#chap01">Alice's Adventures in Wonderland, Chapter One: Down the Rabbit-Hole</a></h3><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">ℹ️</div><div class="kg-callout-text">Note: When Midjourney or Stable Diffusion can't handle the full length of the desired input, we just use the first few paragraphs of the text.</div></div><p><strong>Stable Diffusion</strong></p><p>For some reason, Stable Diffusion doesn't like Alice:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-22.png" class="kg-image" alt="" width="496" height="581"></figure><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_CHAPTER_I.nDown_the_Rabbit-HolennnAlice_was_begi_8b5dd941-8a16-4093-9353-7c4fa862e0dc.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_CHAPTER_I.nDown_the_Rabbit-HolennnAlice_was_begi_8b5dd941-8a16-4093-9353-7c4fa862e0dc.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_CHAPTER_I.nDown_the_Rabbit-HolennnAlice_was_begi_8b5dd941-8a16-4093-9353-7c4fa862e0dc.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_CHAPTER_I.nDown_the_Rabbit-HolennnAlice_was_begi_8b5dd941-8a16-4093-9353-7c4fa862e0dc.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_CHAPTER_I.nDown_the_Rabbit-HolennnAlice_was_begi_8b5dd941-8a16-4093-9353-7c4fa862e0dc.png 2400w" sizes="(min-width: 1200px) 1200px"></figure><p></p><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5db5650b-5087-4845-a305-bd376c81a0e6-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5db5650b-5087-4845-a305-bd376c81a0e6-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5db5650b-5087-4845-a305-bd376c81a0e6-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5db5650b-5087-4845-a305-bd376c81a0e6-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F8ff4dba8-28c3-490d-b84b-a3a722445f12-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F8ff4dba8-28c3-490d-b84b-a3a722445f12-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F8ff4dba8-28c3-490d-b84b-a3a722445f12-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F8ff4dba8-28c3-490d-b84b-a3a722445f12-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F3515d192-70ed-4399-87b4-a207b4f7e3be-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F3515d192-70ed-4399-87b4-a207b4f7e3be-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F3515d192-70ed-4399-87b4-a207b4f7e3be-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F3515d192-70ed-4399-87b4-a207b4f7e3be-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F9b1004a8-c7c4-434d-93b0-b6c0936cf346-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F9b1004a8-c7c4-434d-93b0-b6c0936cf346-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F9b1004a8-c7c4-434d-93b0-b6c0936cf346-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F9b1004a8-c7c4-434d-93b0-b6c0936cf346-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="astronomers-observe-time-dilation-in-early-universe"><a href="https://www.theguardian.com/science/2023/jul/03/astronomers-observe-time-dilation-in-early-universe?ref=jina-ai-gmbh.ghost.io">Astronomers observe time dilation in early universe</a></h3><p><strong>Stable Diffusion</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-688914131-1688989030628.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-4230028037-1688988965071.png" width="512" height="512" alt=""></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-3654213099-1688988936340.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-1780417579-1688988900480.png" width="512" height="512" alt=""></div></div></div></figure><p></p><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_Astronomers_observe_time_dilation_in_early_unive_89812f86-1ad6-40a4-96d9-f100dc09d489.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_Astronomers_observe_time_dilation_in_early_unive_89812f86-1ad6-40a4-96d9-f100dc09d489.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_Astronomers_observe_time_dilation_in_early_unive_89812f86-1ad6-40a4-96d9-f100dc09d489.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_Astronomers_observe_time_dilation_in_early_unive_89812f86-1ad6-40a4-96d9-f100dc09d489.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_Astronomers_observe_time_dilation_in_early_unive_89812f86-1ad6-40a4-96d9-f100dc09d489.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fe13b0fa3-c9df-401f-834f-015cb75d1a88-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fe13b0fa3-c9df-401f-834f-015cb75d1a88-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fe13b0fa3-c9df-401f-834f-015cb75d1a88-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fe13b0fa3-c9df-401f-834f-015cb75d1a88-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F43e4e74e-a020-4005-9194-724f4523c8de-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F43e4e74e-a020-4005-9194-724f4523c8de-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F43e4e74e-a020-4005-9194-724f4523c8de-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F43e4e74e-a020-4005-9194-724f4523c8de-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/0vfmholt8fel_1689150142229.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/0vfmholt8fel_1689150142229.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/0vfmholt8fel_1689150142229.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/0vfmholt8fel_1689150142229.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/or9ldvstlb_1689150139518.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/or9ldvstlb_1689150139518.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/or9ldvstlb_1689150139518.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/or9ldvstlb_1689150139518.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="just-stop-oil-funder-warns-more-high-profile-sports-will-be-on-group%E2%80%99s-hit-list"><a href="https://www.theguardian.com/sport/2023/jul/06/just-stop-oil-dale-vince-warns-more-high-profile-sports-will-be-on-hit-list-wimbledon?ref=jina-ai-gmbh.ghost.io">Just Stop Oil funder warns more high-profile sports will be on group’s hit list</a></h3><p><strong>Stable Diffusion</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-884407793-1688989426335.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-23849892-1688989402861.png" width="512" height="512" alt=""></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-2946212633-1688989378313.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-101285496-1688989337814.png" width="512" height="512" alt=""></div></div></div></figure><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_Just_Stop_Oil_funder_warns_more_high-profile_spo_f0d585bf-a624-4957-ba0f-3dd60648d394.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_Just_Stop_Oil_funder_warns_more_high-profile_spo_f0d585bf-a624-4957-ba0f-3dd60648d394.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_Just_Stop_Oil_funder_warns_more_high-profile_spo_f0d585bf-a624-4957-ba0f-3dd60648d394.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_Just_Stop_Oil_funder_warns_more_high-profile_spo_f0d585bf-a624-4957-ba0f-3dd60648d394.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_Just_Stop_Oil_funder_warns_more_high-profile_spo_f0d585bf-a624-4957-ba0f-3dd60648d394.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Faff80570-8f11-4d0c-9980-92e4e24934bd-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Faff80570-8f11-4d0c-9980-92e4e24934bd-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Faff80570-8f11-4d0c-9980-92e4e24934bd-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Faff80570-8f11-4d0c-9980-92e4e24934bd-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fa61f4ebd-2b7e-4882-8a3a-887574a9d605-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fa61f4ebd-2b7e-4882-8a3a-887574a9d605-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fa61f4ebd-2b7e-4882-8a3a-887574a9d605-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fa61f4ebd-2b7e-4882-8a3a-887574a9d605-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fb51ba908-cdff-4f67-8140-a22fa101dd9e-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fb51ba908-cdff-4f67-8140-a22fa101dd9e-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fb51ba908-cdff-4f67-8140-a22fa101dd9e-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fb51ba908-cdff-4f67-8140-a22fa101dd9e-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F30b4e1b1-11df-4c18-ad1a-5d0056d11502-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F30b4e1b1-11df-4c18-ad1a-5d0056d11502-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F30b4e1b1-11df-4c18-ad1a-5d0056d11502-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F30b4e1b1-11df-4c18-ad1a-5d0056d11502-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="martin-luther-king-jrs-i-have-a-dream-speech"><a href="https://www.npr.org/2010/01/18/122701268/i-have-a-dream-speech-in-its-entirety?ref=jina-ai-gmbh.ghost.io">Martin Luther King Jr.'s 'I Have a Dream' speech</a></h3><p><strong>Stable Diffusion</strong></p><p>Once again, Stable Diffusion chokes. Likely due to some outdated terms in the text that may be considered offensive today.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-24.png" class="kg-image" alt="" width="496" height="581"></figure><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_Five_score_years_ago_a_great_American_in_whose_s_a60ad93f-aa94-45da-9b29-eeaec87ed830.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_Five_score_years_ago_a_great_American_in_whose_s_a60ad93f-aa94-45da-9b29-eeaec87ed830.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_Five_score_years_ago_a_great_American_in_whose_s_a60ad93f-aa94-45da-9b29-eeaec87ed830.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_Five_score_years_ago_a_great_American_in_whose_s_a60ad93f-aa94-45da-9b29-eeaec87ed830.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_Five_score_years_ago_a_great_American_in_whose_s_a60ad93f-aa94-45da-9b29-eeaec87ed830.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fc15a903a-a4b3-4820-9d03-503d5de936a2-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fc15a903a-a4b3-4820-9d03-503d5de936a2-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fc15a903a-a4b3-4820-9d03-503d5de936a2-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fc15a903a-a4b3-4820-9d03-503d5de936a2-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2825c2ff-2c0a-486a-a4d4-6c08f0351237-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2825c2ff-2c0a-486a-a4d4-6c08f0351237-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2825c2ff-2c0a-486a-a4d4-6c08f0351237-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2825c2ff-2c0a-486a-a4d4-6c08f0351237-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F531e7225-d8ae-49bb-92f2-fb39766c6ab4-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F531e7225-d8ae-49bb-92f2-fb39766c6ab4-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F531e7225-d8ae-49bb-92f2-fb39766c6ab4-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F531e7225-d8ae-49bb-92f2-fb39766c6ab4-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F45a90714-ab47-4b1d-af63-9a788092cb1e-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F45a90714-ab47-4b1d-af63-9a788092cb1e-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F45a90714-ab47-4b1d-af63-9a788092cb1e-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F45a90714-ab47-4b1d-af63-9a788092cb1e-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="everything-to-know-about-the-new-%E2%80%98harry-potter%E2%80%99-tv-series-adaptation-at-hbo-max-from-the-show%E2%80%99s-concept-to-jk-rowling%E2%80%99s-involvement"><a href="https://www.usmagazine.com/entertainment/pictures/harry-potter-tv-series-what-to-know-about-hbo-max-adaptation/?ref=jina-ai-gmbh.ghost.io">Everything to Know About the New ‘Harry Potter’ TV Series Adaptation at HBO Max: From the Show’s Concept to J.K. Rowling’s Involvement</a></h3><p><strong>Stable Diffusion</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-3393010138-1688992343841.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-3033863845-1688992320539.png" width="512" height="512" alt=""></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-4056338294-1688992291359.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-626579158-1688992146959.png" width="512" height="512" alt=""></div></div></div></figure><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_A_new_generation_of_wizards_HBO_announced_that_a_76535eb0-2547-449d-9b2c-2655e18db513.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_A_new_generation_of_wizards_HBO_announced_that_a_76535eb0-2547-449d-9b2c-2655e18db513.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_A_new_generation_of_wizards_HBO_announced_that_a_76535eb0-2547-449d-9b2c-2655e18db513.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_A_new_generation_of_wizards_HBO_announced_that_a_76535eb0-2547-449d-9b2c-2655e18db513.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_A_new_generation_of_wizards_HBO_announced_that_a_76535eb0-2547-449d-9b2c-2655e18db513.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5e2e91b4-f116-40ae-9525-7c570ed364b3-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5e2e91b4-f116-40ae-9525-7c570ed364b3-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5e2e91b4-f116-40ae-9525-7c570ed364b3-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5e2e91b4-f116-40ae-9525-7c570ed364b3-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F4a4800ec-00a0-421d-a9c0-c20b69814ef5-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F4a4800ec-00a0-421d-a9c0-c20b69814ef5-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F4a4800ec-00a0-421d-a9c0-c20b69814ef5-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F4a4800ec-00a0-421d-a9c0-c20b69814ef5-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ff6f4375b-7aee-4c2a-ac39-8c9b1eddd71c-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ff6f4375b-7aee-4c2a-ac39-8c9b1eddd71c-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ff6f4375b-7aee-4c2a-ac39-8c9b1eddd71c-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ff6f4375b-7aee-4c2a-ac39-8c9b1eddd71c-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F839f443f-fa87-4b7e-9125-208378c4ceec-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F839f443f-fa87-4b7e-9125-208378c4ceec-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F839f443f-fa87-4b7e-9125-208378c4ceec-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F839f443f-fa87-4b7e-9125-208378c4ceec-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="%E8%8C%B6%E9%A6%86-teahouse-by-lao-she">茶馆 (Teahouse) by Lao She</h3><p><strong>Stable Diffusion</strong></p><p>Here we can clearly see that Stable Diffusion can't cope with languages other than English. </p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-4154315660-1688991703160.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-2685477569-1688991681749.png" width="512" height="512" alt=""></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-3577315841-1688991647361.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-3085885550-1688991603335.png" width="512" height="512" alt=""></div></div></div></figure><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina__c5d1fa36-678e-41b6-bf95-10d954236140.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina__c5d1fa36-678e-41b6-bf95-10d954236140.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina__c5d1fa36-678e-41b6-bf95-10d954236140.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina__c5d1fa36-678e-41b6-bf95-10d954236140.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina__c5d1fa36-678e-41b6-bf95-10d954236140.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2a3ee838-731f-4d8d-ae0b-988c9f659d9f-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2a3ee838-731f-4d8d-ae0b-988c9f659d9f-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2a3ee838-731f-4d8d-ae0b-988c9f659d9f-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2a3ee838-731f-4d8d-ae0b-988c9f659d9f-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ffbbf1fde-566b-4765-960a-730b8eaa673d-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ffbbf1fde-566b-4765-960a-730b8eaa673d-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ffbbf1fde-566b-4765-960a-730b8eaa673d-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ffbbf1fde-566b-4765-960a-730b8eaa673d-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5fb2bb78-83c9-4b24-9fd7-18d55ddbc0d0-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5fb2bb78-83c9-4b24-9fd7-18d55ddbc0d0-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5fb2bb78-83c9-4b24-9fd7-18d55ddbc0d0-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5fb2bb78-83c9-4b24-9fd7-18d55ddbc0d0-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5a123107-583a-47e9-8551-adf224fa48dc-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5a123107-583a-47e9-8551-adf224fa48dc-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5a123107-583a-47e9-8551-adf224fa48dc-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5a123107-583a-47e9-8551-adf224fa48dc-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="erdogan-unterst%C3%BCtzt-nato-beitritt-von-schwedenunter-einer-bedingung-erdogan-supports-swedens-nato-entryon-one-condition"><a href="https://de.euronews.com/2023/07/10/erdogan-unterstutzt-nato-beitritt-von-schweden-unter-einer-bedingung?ref=jina-ai-gmbh.ghost.io">Erdogan unterstützt Nato-Beitritt von Schweden - unter einer Bedingung</a> (Erdogan supports Sweden's NATO entry - on one condition)</h3><p><strong>Stable Diffusion</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1_image-491965874-1689149881525.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1_image-2734748393-1689149865127.png" width="512" height="512" alt=""></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1_image-3692720233-1689149843726.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1_image-3885488742-1689149803017.png" width="512" height="512" alt=""></div></div></div></figure><p></p><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_Erdogan_unterstutzt_Nato-Beitritt_von_Schweden_-_a53d22c4-e7d7-4b1d-8c82-af4cdcf5249b.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_Erdogan_unterstutzt_Nato-Beitritt_von_Schweden_-_a53d22c4-e7d7-4b1d-8c82-af4cdcf5249b.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_Erdogan_unterstutzt_Nato-Beitritt_von_Schweden_-_a53d22c4-e7d7-4b1d-8c82-af4cdcf5249b.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_Erdogan_unterstutzt_Nato-Beitritt_von_Schweden_-_a53d22c4-e7d7-4b1d-8c82-af4cdcf5249b.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_Erdogan_unterstutzt_Nato-Beitritt_von_Schweden_-_a53d22c4-e7d7-4b1d-8c82-af4cdcf5249b.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fe0d171dc-c0b3-43a9-aa11-b5e574918e76-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fe0d171dc-c0b3-43a9-aa11-b5e574918e76-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fe0d171dc-c0b3-43a9-aa11-b5e574918e76-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fe0d171dc-c0b3-43a9-aa11-b5e574918e76-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F4bff128f-313f-4731-bdd2-315b283898de-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F4bff128f-313f-4731-bdd2-315b283898de-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F4bff128f-313f-4731-bdd2-315b283898de-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F4bff128f-313f-4731-bdd2-315b283898de-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fab7465b9-d37b-41be-ba6a-9b17d9318f0e-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fab7465b9-d37b-41be-ba6a-9b17d9318f0e-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fab7465b9-d37b-41be-ba6a-9b17d9318f0e-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fab7465b9-d37b-41be-ba6a-9b17d9318f0e-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F722f3075-8c02-4911-8153-647cc56bd59e-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F722f3075-8c02-4911-8153-647cc56bd59e-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F722f3075-8c02-4911-8153-647cc56bd59e-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F722f3075-8c02-4911-8153-647cc56bd59e-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="barbie-vs-oppenheimer-is-hilariousbut-2023s-huge-box-office-battle-has-a-deeper-meaning"><a href="https://screenrant.com/barbie-oppenheimer-nolan-box-office-battle-deeper-meaning/?ref=jina-ai-gmbh.ghost.io">Barbie Vs. Oppenheimer Is Hilarious - But 2023's Huge Box Office Battle Has A Deeper Meaning</a></h3><p><strong>Stable Diffusion</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-1143242423-1688992115675.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-146559633-1688992026497.png" width="512" height="512" alt=""></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-2025296766-1688992007660.png" width="512" height="512" alt=""></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-1806247485-1688991973453.png" width="512" height="512" alt=""></div></div></div></figure><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_Barbie_Vs._Oppenheimer_Is_Hilarious_-_But_2023s__1baa9543-df4f-4a6b-aca6-d621e1ae7f65.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_Barbie_Vs._Oppenheimer_Is_Hilarious_-_But_2023s__1baa9543-df4f-4a6b-aca6-d621e1ae7f65.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_Barbie_Vs._Oppenheimer_Is_Hilarious_-_But_2023s__1baa9543-df4f-4a6b-aca6-d621e1ae7f65.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_Barbie_Vs._Oppenheimer_Is_Hilarious_-_But_2023s__1baa9543-df4f-4a6b-aca6-d621e1ae7f65.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_Barbie_Vs._Oppenheimer_Is_Hilarious_-_But_2023s__1baa9543-df4f-4a6b-aca6-d621e1ae7f65.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2e8f566c-929e-4540-881b-83dd57f6d150-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2e8f566c-929e-4540-881b-83dd57f6d150-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2e8f566c-929e-4540-881b-83dd57f6d150-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2e8f566c-929e-4540-881b-83dd57f6d150-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F08d877bb-9286-47ae-b156-f2157f9e98fd-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F08d877bb-9286-47ae-b156-f2157f9e98fd-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F08d877bb-9286-47ae-b156-f2157f9e98fd-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F08d877bb-9286-47ae-b156-f2157f9e98fd-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fba1fcde4-8cc0-49a1-8b64-2080412a832c-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fba1fcde4-8cc0-49a1-8b64-2080412a832c-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fba1fcde4-8cc0-49a1-8b64-2080412a832c-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fba1fcde4-8cc0-49a1-8b64-2080412a832c-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fdda40371-4cc1-4c4a-915a-24119a4d19b0-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fdda40371-4cc1-4c4a-915a-24119a4d19b0-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fdda40371-4cc1-4c4a-915a-24119a4d19b0-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fdda40371-4cc1-4c4a-915a-24119a4d19b0-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h2 id="how-does-bestbanner-compare">How does BestBanner compare?</h2><p>I think it's fair to say that BestBanner wipes the floor with Stable Diffusion – admittedly, it's an old model, but unless you're going for a high-octane nightmare fuel vibe for your banners, we wouldn't recommend it.</p><p><strong>Overall image quality: </strong>Both Midjourney and BestBanner shine here, creating detailed appealing imagery. Stable Diffusion is more about that high-octane nightmare fuel vibe.</p><p><strong>Topicality: </strong>Stable Diffusion wobbles off-point a lot, showing vague abstract blobs when we used it to create images for the time dilation post. Midjourney is a lot better, but often misses the point (did it connect Trump to the "orange" in the text of the Just Stop Oil example?) or completely omits key information (in the Barbie-Oppenheimer example, most images are missing Oppenheimer altogether. We also see this in the MLK example. BestBanner stays on topic very well, with the Just Stop Oil example showing actual sports playing grounds (which are the scenes of protests), while Barbenheimer includes someone who actually looks like (a slightly more handsome) Oppenheimer:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.726768 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/JROppenheimer-LosAlamos.jpg" width="524" height="721" alt=""></div><div class="kg-gallery-image" style="flex: 0.780632 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/0tv75sxymx48_1689155127176.png" width="395" height="506" alt=""></div></div></div><figcaption>The real Oppenheimer (left) and BestBanner's Oppenheimer (right)</figcaption></figure><p><strong>Composition: </strong>Stable Diffusion quite often generates several pictures inside one image, for example in the case of Barbie/Oppenheimer. This doesn't happen in Midjourney, though (again in Barbie/Oppenheimer) we get several shots of "Person A just standing opposite Person B". The composition of BestBanner's Harry Potter images stands out, with the author of the works standing in what appears to be a posh school library. </p><p><strong>Languages:</strong> Stable Diffusion typically falls down and creates generic images of suburbia when it comes to anything but English. Midjourney does well, but in other tests (from this <a href="https://www.t-online.de/nachrichten/panorama/wetter/id_100203492/hitzewelle-und-unwetter-so-wird-das-wetter-bei-ihnen-am-wochenende.html?ref=jina-ai-gmbh.ghost.io">German article</a>) it interpreted "grads" as graduates, not degrees, while BestBanner worked as expected for German, Chinese and other languages.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-25.png" class="kg-image" alt="" width="581" height="408"></figure><p><strong>Censorship:</strong> Stable Diffusion is very censor-happy. In some cases we can understand this, as in the MLK example where some language is used that would be considered offensive today. Quite what it has against Alice in Wonderland is beyond us. While Midjourney didn't get censor-happy in our testing, we've often seen heavy-handedness and <a href="https://petapixel.com/2023/04/03/midjourney-bans-ai-images-of-chinese-president-xi-jinping/?ref=jina-ai-gmbh.ghost.io">highly-selective political censorship</a>. In our testing with BestBanner we haven't yet found examples of censorship, though testing obscene content is way outside the scope of this post.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.930556 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/mj_ban.png" width="603" height="648" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/mj_ban.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/mj_ban.png 603w"></div><div class="kg-gallery-image" style="flex: 0.854419 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/sd_ban.png" width="493" height="577" alt=""></div></div></div><figcaption>Midjourney (left) and Stable Diffusion (right) rejections</figcaption></figure><p><strong>UI: </strong>Midjourney limits you to a Discord bot, and while there are posts saying an API is "in the works", we're not confident this will come any time soon. Several front-ends are available for Stable Diffusion, and it's hosted in many places with an open API. BestBanner also offers an <a href="https://bestbanner.jina.ai/api?ref=jina-ai-gmbh.ghost.io">easy-to-use API for generating images</a>, and integrates with Jina AI's <a href="https://github.com/jina-ai/jinaai-py?ref=jina-ai-gmbh.ghost.io">Python</a> and <a href="https://github.com/jina-ai/jinaai-js?ref=jina-ai-gmbh.ghost.io">JavaScript</a> packages.</p><p>Overall, BestBanner stacks up well against the competition. While image quality is on par with Midjourney, in many ways (composition, topicality, language support, API) it's a superior choice. And we think the less said about Stable Diffusion the better!</p><h2 id="get-started">Get started</h2><p>Visit <a href="http://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io">bestbanner.jina.ai</a> to sign up, and join our <a href="https://discord.com/channels/1106542220112302130/1128217454296965220?ref=jina-ai-gmbh.ghost.io">Discord channel</a> to share the banners you’ve created!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">BestBanner - Blog to banner, without the prompts!</div><div class="kg-bookmark-description">BestBanner revolutionizes the way you create banner images. Simply input your article text, and watch as our advanced multimodal AI crafts a unique and captivating image, tailored specifically to your content. Ideal for publishers, bloggers, and content creators.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://bestbanner.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">BestBanner</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://bestbanner.jina.ai/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fredefining-text-to-image-how-bestbanner-outperforms-midjourney-and-stable-diffusion-a-benchmark-analysis%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">BestBanner is an AI-powered text-to-image generation system. It takes article text as input and generates high-quality social media banners. This saves you from the task of crafting images and lets you focus on creating content.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Me.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G, Andrei Ungureanu</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 12, 2023 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Another week, another product announcement! Our engineers have been working day in and day out, and burning the midnight oil to bring you Jina AI’s latest tool in the generative AI toolbox: BestBanner.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">BestBanner - Blog to banner, without the prompts!</div><div class="kg-bookmark-description">BestBanner revolutionizes the way you create banner images. Simply input your article text, and watch as our advanced multimodal AI crafts a unique and captivating image, tailored specifically to your content. Ideal for publishers, bloggers, and content creators.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://bestbanner.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">BestBanner</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://bestbanner.jina.ai/banner.png" alt=""></div></a></figure><p>BestBanner is a unique AI-powered text-to-image generation system. It takes the text from an article as input and generates high-quality social media banners. This saves you from the time-consuming task of crafting images and allows you to focus on creating great content.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/07/BestBanner-promo1-1.mp4" poster="https://img.spacergif.org/v1/3840x2160/0a/spacer.png" width="3840" height="2160" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/07/media-thumbnail-ember208.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>It’s as simple as pasting your article (or tweet) text into BestBanner and hitting “Go”.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-14.png" class="kg-image" alt="" width="1518" height="382" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/image-14.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/image-14.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-14.png 1518w" sizes="(min-width: 720px) 720px"><figcaption>Copied from reader view of <a href="https://screenrant.com/barbie-oppenheimer-nolan-box-office-battle-deeper-meaning/?ref=jina-ai-gmbh.ghost.io">this article</a> on Barbie vs Oppenheimer</figcaption></figure><p>No need to worry about how long your post is, and whether the model can handle that much information. And no need to deal with janky Discord UIs to generate your images either.</p><p>Wait a few minutes and you’ll get four output images, each of which you can choose to refine.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-15.png" class="kg-image" alt="" width="584" height="695"><figcaption>See the full-size images <a href="https://bestbanner.jina.ai/share?id=7ebe59ba-4c6b-4503-a037-587c4ae22ea2&amp;ref=jina-ai-gmbh.ghost.io">here</a></figcaption></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">😳</div><div class="kg-callout-text">These pictures don't look great - but that's a feature, not a bug! BestBanner <em>quickly</em> generates very different images from your content, giving you more leeway to choose unique styles when you refine your banner.</div></div><p>Next up, click the refine button to get high-quality variants of your desired style:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-16.png" class="kg-image" alt="" width="598" height="656"></figure><p>BestBanner will now take that image and riff on it, giving you four variations:</p><p>After a round or two of refinement you’ll have the banner image of your dreams:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-18.png" class="kg-image" alt="" width="588" height="697"><figcaption>See the full-size images <a href="https://bestbanner.jina.ai/share?id=90ee24ba-c0c1-4cce-9501-0c01fff0a97e&amp;ref=jina-ai-gmbh.ghost.io">here</a></figcaption></figure><p>Once you’ve found something you like, you can preview how it’ll look on your social network of choice, crop accordingly, and download for use:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-21.png" class="kg-image" alt="" width="573" height="789"></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-20.png" class="kg-image" alt="" width="719" height="448" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/image-20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-20.png 719w"></figure><p>Whether you’re a writer, content creator, or tweeter/skeeter/tooter/whatever-the-new-thing is, BestBanner is a great tool to add to your creative arsenal.</p><h2 id="why-are-social-media-banners-important-anyway">Why are social media banners important anyway?</h2><p>The power of compelling social media banners for articles, blog posts, and other content is critical in today's digital landscape. As a content creator, your banners are essentially the digital storefront of your work, your first opportunity to capture the attention of potential readers amidst the digital clutter of their feeds. An eye-catching banner doesn’t just instantly communicate the essence of your content, but also entices viewers to click through and engage with your material. In a highly visual online world, these banners can dramatically elevate the visibility and impact of your content. What's more, many social media platforms' algorithms prioritize visually rich and engaging content, meaning your carefully-crafted banners can also boost your reach organically. Therefore, investing in the creation of compelling social media banners is a vital aspect of a successful content strategy.</p><p>BestBanner is an indispensable tool for making these banners happen, given its innovative application of AI-powered image generation. By allowing you to effortlessly convert blog posts, tweets, and articles into compelling social media banners, BestBanner eliminates the time-consuming task of manual graphic design. You simply copy and paste your content, and with a click, generate a selection of candidate images finely tuned to the essence of your post. These images can be further refined and downloaded, providing you with a visually striking banner that resonates with your audience and enhances engagement.</p><h2 id="how-is-bestbanner-different-from-midjourney-stable-diffusion-et-al">How is BestBanner different from Midjourney, Stable Diffusion, et al?</h2><p>Don’t get us wrong - we love Midjourney and Stable Diffusion. They’ve completely changed the game in generative AI. But BestBanner differs in several key ways:</p><p><strong>Copy and paste, don’t think:</strong> No need for you to wrack your brains thinking of what would make a perfect image for your article. Just paste the whole thing in and smack go. You don’t even need to remove formatting or surrounding HTML.</p><p><strong>Hyperfocus</strong>: Midjourney, Stable Diffusion, DALL-E 2 and the others are all <strong>general-purpose</strong> image generation models. So they’re a good tool whether you want to generate a social media avatar, a logo or a poster, they’ll all do a <em>reasonable</em> job. But since they don’t focus on one thing in particular, they become Jacks of all Trades, and masters of none. On the other hand, BetterBanner is <strong>specialized for social media banner creation</strong>.</p><p><strong>Unlimited context length:</strong> Other models are all designed to use prompts — short snippets of text that require a lot of tuning to get good results. BestBanner goes a step further and lets you use the whole text of your blog post, article, or tweet. You don’t need to think about what the most relevant point of your wall of text is - BestBanner works out what’s important.</p><p><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong>Multi-model</strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong>: While Midjourney and Stable Diffusion let you generate images with one model at a time, BestBanner uses three models to generate four images. This gives you a more varied array of stylistic and subject choices to choose from when it comes to refinement</p><p><strong>Easy API access:</strong> Midjourney is only usable through their Discord bot, while BestBanner has an accessible API for you to programmatically generate banners with ease.</p><p><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong>No censorship</strong></strong></strong></strong></strong></strong></strong></strong></strong></strong>: In our testing, both Midjourney and Stable Diffusion often censor on the prompt level, immediately barring us from creating certain images. In other cases, Stable Diffusion simply generates sterile generic content given certain prompts. (None of these prompts were in any way obscene - often they referenced politics or were entirely innocuous). <strong>BestBanner has shown no such political or random censorship</strong>.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">ℹ️</div><div class="kg-callout-text">That’s not to say BestBanner <em>never</em> censors - we’ve just seen none of it so far compared to other models.</div></div><h2 id="showdown-battle-of-the-banners">Showdown: Battle of the Banners</h2><p>So, how does BestBanner stack up against the other models? It’s time to throw our contenders into the ring to find out. But before we munch on popcorn and watch the slugfest, we’ll establish some ground rules:</p><ul><li>We’ll use a selection of classic literature and news posts as our inputs.</li><li>For each model we’ll generate four candidate images - in Midjourney and BestBanner this is done in one shot, in Stable Diffusion by generating four separate images.</li><li>Since Midjourney and Stable Diffusion both have limited prompt length, we use only the first few sentences of the post as their prompt. For BestBanner we use the contents of the entire post (sometimes the plain text content, sometimes a straight-up formatted copy-paste).</li><li>For BestBanner we’ll run one round of refinement from a selected candidate from the initial generation.</li></ul><p>In this section we'll just showcase the images themselves. Check further down for an interpretation of how Stable Diffusion, Midjourney, and BestBanner stack up based on this benchmark, covering topicality, quality, composition, etc. </p><h3 id="alices-adventures-in-wonderland-chapter-one-down-the-rabbit-hole"><a href="https://www.gutenberg.org/files/11/11-h/11-h.htm?ref=jina-ai-gmbh.ghost.io#chap01">Alice's Adventures in Wonderland, Chapter One: Down the Rabbit-Hole</a></h3><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">ℹ️</div><div class="kg-callout-text">Note: When Midjourney or Stable Diffusion can't handle the full length of the desired input, we just use the first few paragraphs of the text.</div></div><p><strong>Stable Diffusion</strong></p><p>For some reason, Stable Diffusion doesn't like Alice:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-22.png" class="kg-image" alt="" width="496" height="581"></figure><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_CHAPTER_I.nDown_the_Rabbit-HolennnAlice_was_begi_8b5dd941-8a16-4093-9353-7c4fa862e0dc.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_CHAPTER_I.nDown_the_Rabbit-HolennnAlice_was_begi_8b5dd941-8a16-4093-9353-7c4fa862e0dc.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_CHAPTER_I.nDown_the_Rabbit-HolennnAlice_was_begi_8b5dd941-8a16-4093-9353-7c4fa862e0dc.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_CHAPTER_I.nDown_the_Rabbit-HolennnAlice_was_begi_8b5dd941-8a16-4093-9353-7c4fa862e0dc.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_CHAPTER_I.nDown_the_Rabbit-HolennnAlice_was_begi_8b5dd941-8a16-4093-9353-7c4fa862e0dc.png 2400w" sizes="(min-width: 1200px) 1200px"></figure><p></p><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5db5650b-5087-4845-a305-bd376c81a0e6-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5db5650b-5087-4845-a305-bd376c81a0e6-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5db5650b-5087-4845-a305-bd376c81a0e6-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5db5650b-5087-4845-a305-bd376c81a0e6-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F8ff4dba8-28c3-490d-b84b-a3a722445f12-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F8ff4dba8-28c3-490d-b84b-a3a722445f12-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F8ff4dba8-28c3-490d-b84b-a3a722445f12-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F8ff4dba8-28c3-490d-b84b-a3a722445f12-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F3515d192-70ed-4399-87b4-a207b4f7e3be-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F3515d192-70ed-4399-87b4-a207b4f7e3be-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F3515d192-70ed-4399-87b4-a207b4f7e3be-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F3515d192-70ed-4399-87b4-a207b4f7e3be-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F9b1004a8-c7c4-434d-93b0-b6c0936cf346-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F9b1004a8-c7c4-434d-93b0-b6c0936cf346-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F9b1004a8-c7c4-434d-93b0-b6c0936cf346-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F9b1004a8-c7c4-434d-93b0-b6c0936cf346-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="astronomers-observe-time-dilation-in-early-universe"><a href="https://www.theguardian.com/science/2023/jul/03/astronomers-observe-time-dilation-in-early-universe?ref=jina-ai-gmbh.ghost.io">Astronomers observe time dilation in early universe</a></h3><p><strong>Stable Diffusion</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-688914131-1688989030628.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-4230028037-1688988965071.png" width="512" height="512" alt=""></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-3654213099-1688988936340.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-1780417579-1688988900480.png" width="512" height="512" alt=""></div></div></div></figure><p></p><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_Astronomers_observe_time_dilation_in_early_unive_89812f86-1ad6-40a4-96d9-f100dc09d489.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_Astronomers_observe_time_dilation_in_early_unive_89812f86-1ad6-40a4-96d9-f100dc09d489.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_Astronomers_observe_time_dilation_in_early_unive_89812f86-1ad6-40a4-96d9-f100dc09d489.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_Astronomers_observe_time_dilation_in_early_unive_89812f86-1ad6-40a4-96d9-f100dc09d489.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_Astronomers_observe_time_dilation_in_early_unive_89812f86-1ad6-40a4-96d9-f100dc09d489.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fe13b0fa3-c9df-401f-834f-015cb75d1a88-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fe13b0fa3-c9df-401f-834f-015cb75d1a88-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fe13b0fa3-c9df-401f-834f-015cb75d1a88-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fe13b0fa3-c9df-401f-834f-015cb75d1a88-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F43e4e74e-a020-4005-9194-724f4523c8de-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F43e4e74e-a020-4005-9194-724f4523c8de-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F43e4e74e-a020-4005-9194-724f4523c8de-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F43e4e74e-a020-4005-9194-724f4523c8de-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/0vfmholt8fel_1689150142229.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/0vfmholt8fel_1689150142229.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/0vfmholt8fel_1689150142229.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/0vfmholt8fel_1689150142229.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/or9ldvstlb_1689150139518.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/or9ldvstlb_1689150139518.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/or9ldvstlb_1689150139518.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/or9ldvstlb_1689150139518.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="just-stop-oil-funder-warns-more-high-profile-sports-will-be-on-group%E2%80%99s-hit-list"><a href="https://www.theguardian.com/sport/2023/jul/06/just-stop-oil-dale-vince-warns-more-high-profile-sports-will-be-on-hit-list-wimbledon?ref=jina-ai-gmbh.ghost.io">Just Stop Oil funder warns more high-profile sports will be on group’s hit list</a></h3><p><strong>Stable Diffusion</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-884407793-1688989426335.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-23849892-1688989402861.png" width="512" height="512" alt=""></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-2946212633-1688989378313.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-101285496-1688989337814.png" width="512" height="512" alt=""></div></div></div></figure><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_Just_Stop_Oil_funder_warns_more_high-profile_spo_f0d585bf-a624-4957-ba0f-3dd60648d394.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_Just_Stop_Oil_funder_warns_more_high-profile_spo_f0d585bf-a624-4957-ba0f-3dd60648d394.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_Just_Stop_Oil_funder_warns_more_high-profile_spo_f0d585bf-a624-4957-ba0f-3dd60648d394.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_Just_Stop_Oil_funder_warns_more_high-profile_spo_f0d585bf-a624-4957-ba0f-3dd60648d394.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_Just_Stop_Oil_funder_warns_more_high-profile_spo_f0d585bf-a624-4957-ba0f-3dd60648d394.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Faff80570-8f11-4d0c-9980-92e4e24934bd-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Faff80570-8f11-4d0c-9980-92e4e24934bd-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Faff80570-8f11-4d0c-9980-92e4e24934bd-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Faff80570-8f11-4d0c-9980-92e4e24934bd-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fa61f4ebd-2b7e-4882-8a3a-887574a9d605-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fa61f4ebd-2b7e-4882-8a3a-887574a9d605-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fa61f4ebd-2b7e-4882-8a3a-887574a9d605-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fa61f4ebd-2b7e-4882-8a3a-887574a9d605-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fb51ba908-cdff-4f67-8140-a22fa101dd9e-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fb51ba908-cdff-4f67-8140-a22fa101dd9e-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fb51ba908-cdff-4f67-8140-a22fa101dd9e-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fb51ba908-cdff-4f67-8140-a22fa101dd9e-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F30b4e1b1-11df-4c18-ad1a-5d0056d11502-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F30b4e1b1-11df-4c18-ad1a-5d0056d11502-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F30b4e1b1-11df-4c18-ad1a-5d0056d11502-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F30b4e1b1-11df-4c18-ad1a-5d0056d11502-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="martin-luther-king-jrs-i-have-a-dream-speech"><a href="https://www.npr.org/2010/01/18/122701268/i-have-a-dream-speech-in-its-entirety?ref=jina-ai-gmbh.ghost.io">Martin Luther King Jr.'s 'I Have a Dream' speech</a></h3><p><strong>Stable Diffusion</strong></p><p>Once again, Stable Diffusion chokes. Likely due to some outdated terms in the text that may be considered offensive today.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-24.png" class="kg-image" alt="" width="496" height="581"></figure><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_Five_score_years_ago_a_great_American_in_whose_s_a60ad93f-aa94-45da-9b29-eeaec87ed830.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_Five_score_years_ago_a_great_American_in_whose_s_a60ad93f-aa94-45da-9b29-eeaec87ed830.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_Five_score_years_ago_a_great_American_in_whose_s_a60ad93f-aa94-45da-9b29-eeaec87ed830.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_Five_score_years_ago_a_great_American_in_whose_s_a60ad93f-aa94-45da-9b29-eeaec87ed830.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_Five_score_years_ago_a_great_American_in_whose_s_a60ad93f-aa94-45da-9b29-eeaec87ed830.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fc15a903a-a4b3-4820-9d03-503d5de936a2-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fc15a903a-a4b3-4820-9d03-503d5de936a2-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fc15a903a-a4b3-4820-9d03-503d5de936a2-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fc15a903a-a4b3-4820-9d03-503d5de936a2-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2825c2ff-2c0a-486a-a4d4-6c08f0351237-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2825c2ff-2c0a-486a-a4d4-6c08f0351237-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2825c2ff-2c0a-486a-a4d4-6c08f0351237-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2825c2ff-2c0a-486a-a4d4-6c08f0351237-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F531e7225-d8ae-49bb-92f2-fb39766c6ab4-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F531e7225-d8ae-49bb-92f2-fb39766c6ab4-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F531e7225-d8ae-49bb-92f2-fb39766c6ab4-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F531e7225-d8ae-49bb-92f2-fb39766c6ab4-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F45a90714-ab47-4b1d-af63-9a788092cb1e-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F45a90714-ab47-4b1d-af63-9a788092cb1e-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F45a90714-ab47-4b1d-af63-9a788092cb1e-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F45a90714-ab47-4b1d-af63-9a788092cb1e-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="everything-to-know-about-the-new-%E2%80%98harry-potter%E2%80%99-tv-series-adaptation-at-hbo-max-from-the-show%E2%80%99s-concept-to-jk-rowling%E2%80%99s-involvement"><a href="https://www.usmagazine.com/entertainment/pictures/harry-potter-tv-series-what-to-know-about-hbo-max-adaptation/?ref=jina-ai-gmbh.ghost.io">Everything to Know About the New ‘Harry Potter’ TV Series Adaptation at HBO Max: From the Show’s Concept to J.K. Rowling’s Involvement</a></h3><p><strong>Stable Diffusion</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-3393010138-1688992343841.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-3033863845-1688992320539.png" width="512" height="512" alt=""></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-4056338294-1688992291359.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-626579158-1688992146959.png" width="512" height="512" alt=""></div></div></div></figure><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_A_new_generation_of_wizards_HBO_announced_that_a_76535eb0-2547-449d-9b2c-2655e18db513.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_A_new_generation_of_wizards_HBO_announced_that_a_76535eb0-2547-449d-9b2c-2655e18db513.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_A_new_generation_of_wizards_HBO_announced_that_a_76535eb0-2547-449d-9b2c-2655e18db513.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_A_new_generation_of_wizards_HBO_announced_that_a_76535eb0-2547-449d-9b2c-2655e18db513.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_A_new_generation_of_wizards_HBO_announced_that_a_76535eb0-2547-449d-9b2c-2655e18db513.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5e2e91b4-f116-40ae-9525-7c570ed364b3-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5e2e91b4-f116-40ae-9525-7c570ed364b3-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5e2e91b4-f116-40ae-9525-7c570ed364b3-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5e2e91b4-f116-40ae-9525-7c570ed364b3-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F4a4800ec-00a0-421d-a9c0-c20b69814ef5-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F4a4800ec-00a0-421d-a9c0-c20b69814ef5-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F4a4800ec-00a0-421d-a9c0-c20b69814ef5-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F4a4800ec-00a0-421d-a9c0-c20b69814ef5-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ff6f4375b-7aee-4c2a-ac39-8c9b1eddd71c-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ff6f4375b-7aee-4c2a-ac39-8c9b1eddd71c-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ff6f4375b-7aee-4c2a-ac39-8c9b1eddd71c-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ff6f4375b-7aee-4c2a-ac39-8c9b1eddd71c-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F839f443f-fa87-4b7e-9125-208378c4ceec-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F839f443f-fa87-4b7e-9125-208378c4ceec-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F839f443f-fa87-4b7e-9125-208378c4ceec-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F839f443f-fa87-4b7e-9125-208378c4ceec-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="%E8%8C%B6%E9%A6%86-teahouse-by-lao-she">茶馆 (Teahouse) by Lao She</h3><p><strong>Stable Diffusion</strong></p><p>Here we can clearly see that Stable Diffusion can't cope with languages other than English. </p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-4154315660-1688991703160.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-2685477569-1688991681749.png" width="512" height="512" alt=""></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-3577315841-1688991647361.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-3085885550-1688991603335.png" width="512" height="512" alt=""></div></div></div></figure><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina__c5d1fa36-678e-41b6-bf95-10d954236140.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina__c5d1fa36-678e-41b6-bf95-10d954236140.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina__c5d1fa36-678e-41b6-bf95-10d954236140.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina__c5d1fa36-678e-41b6-bf95-10d954236140.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina__c5d1fa36-678e-41b6-bf95-10d954236140.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2a3ee838-731f-4d8d-ae0b-988c9f659d9f-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2a3ee838-731f-4d8d-ae0b-988c9f659d9f-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2a3ee838-731f-4d8d-ae0b-988c9f659d9f-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2a3ee838-731f-4d8d-ae0b-988c9f659d9f-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ffbbf1fde-566b-4765-960a-730b8eaa673d-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ffbbf1fde-566b-4765-960a-730b8eaa673d-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ffbbf1fde-566b-4765-960a-730b8eaa673d-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Ffbbf1fde-566b-4765-960a-730b8eaa673d-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5fb2bb78-83c9-4b24-9fd7-18d55ddbc0d0-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5fb2bb78-83c9-4b24-9fd7-18d55ddbc0d0-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5fb2bb78-83c9-4b24-9fd7-18d55ddbc0d0-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5fb2bb78-83c9-4b24-9fd7-18d55ddbc0d0-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5a123107-583a-47e9-8551-adf224fa48dc-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5a123107-583a-47e9-8551-adf224fa48dc-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5a123107-583a-47e9-8551-adf224fa48dc-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F5a123107-583a-47e9-8551-adf224fa48dc-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="erdogan-unterst%C3%BCtzt-nato-beitritt-von-schwedenunter-einer-bedingung-erdogan-supports-swedens-nato-entryon-one-condition"><a href="https://de.euronews.com/2023/07/10/erdogan-unterstutzt-nato-beitritt-von-schweden-unter-einer-bedingung?ref=jina-ai-gmbh.ghost.io">Erdogan unterstützt Nato-Beitritt von Schweden - unter einer Bedingung</a> (Erdogan supports Sweden's NATO entry - on one condition)</h3><p><strong>Stable Diffusion</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1_image-491965874-1689149881525.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1_image-2734748393-1689149865127.png" width="512" height="512" alt=""></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1_image-3692720233-1689149843726.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1_image-3885488742-1689149803017.png" width="512" height="512" alt=""></div></div></div></figure><p></p><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_Erdogan_unterstutzt_Nato-Beitritt_von_Schweden_-_a53d22c4-e7d7-4b1d-8c82-af4cdcf5249b.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_Erdogan_unterstutzt_Nato-Beitritt_von_Schweden_-_a53d22c4-e7d7-4b1d-8c82-af4cdcf5249b.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_Erdogan_unterstutzt_Nato-Beitritt_von_Schweden_-_a53d22c4-e7d7-4b1d-8c82-af4cdcf5249b.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_Erdogan_unterstutzt_Nato-Beitritt_von_Schweden_-_a53d22c4-e7d7-4b1d-8c82-af4cdcf5249b.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_Erdogan_unterstutzt_Nato-Beitritt_von_Schweden_-_a53d22c4-e7d7-4b1d-8c82-af4cdcf5249b.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fe0d171dc-c0b3-43a9-aa11-b5e574918e76-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fe0d171dc-c0b3-43a9-aa11-b5e574918e76-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fe0d171dc-c0b3-43a9-aa11-b5e574918e76-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fe0d171dc-c0b3-43a9-aa11-b5e574918e76-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F4bff128f-313f-4731-bdd2-315b283898de-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F4bff128f-313f-4731-bdd2-315b283898de-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F4bff128f-313f-4731-bdd2-315b283898de-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F4bff128f-313f-4731-bdd2-315b283898de-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fab7465b9-d37b-41be-ba6a-9b17d9318f0e-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fab7465b9-d37b-41be-ba6a-9b17d9318f0e-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fab7465b9-d37b-41be-ba6a-9b17d9318f0e-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2Fab7465b9-d37b-41be-ba6a-9b17d9318f0e-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F722f3075-8c02-4911-8153-647cc56bd59e-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F722f3075-8c02-4911-8153-647cc56bd59e-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F722f3075-8c02-4911-8153-647cc56bd59e-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FiGbWzry4FaN1qLAFZxYmZcCQ32C2-2F722f3075-8c02-4911-8153-647cc56bd59e-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h3 id="barbie-vs-oppenheimer-is-hilariousbut-2023s-huge-box-office-battle-has-a-deeper-meaning"><a href="https://screenrant.com/barbie-oppenheimer-nolan-box-office-battle-deeper-meaning/?ref=jina-ai-gmbh.ghost.io">Barbie Vs. Oppenheimer Is Hilarious - But 2023's Huge Box Office Battle Has A Deeper Meaning</a></h3><p><strong>Stable Diffusion</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-1143242423-1688992115675.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-146559633-1688992026497.png" width="512" height="512" alt=""></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-2025296766-1688992007660.png" width="512" height="512" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/SD2.1-2Fimage-1806247485-1688991973453.png" width="512" height="512" alt=""></div></div></div></figure><p><strong>Midjourney</strong></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/generativejina_Barbie_Vs._Oppenheimer_Is_Hilarious_-_But_2023s__1baa9543-df4f-4a6b-aca6-d621e1ae7f65.png" class="kg-image" alt="" width="2000" height="1121" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/generativejina_Barbie_Vs._Oppenheimer_Is_Hilarious_-_But_2023s__1baa9543-df4f-4a6b-aca6-d621e1ae7f65.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/generativejina_Barbie_Vs._Oppenheimer_Is_Hilarious_-_But_2023s__1baa9543-df4f-4a6b-aca6-d621e1ae7f65.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/07/generativejina_Barbie_Vs._Oppenheimer_Is_Hilarious_-_But_2023s__1baa9543-df4f-4a6b-aca6-d621e1ae7f65.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/07/generativejina_Barbie_Vs._Oppenheimer_Is_Hilarious_-_But_2023s__1baa9543-df4f-4a6b-aca6-d621e1ae7f65.png 2400w" sizes="(min-width: 720px) 720px"></figure><p><strong>BestBanner</strong></p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2e8f566c-929e-4540-881b-83dd57f6d150-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2e8f566c-929e-4540-881b-83dd57f6d150-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2e8f566c-929e-4540-881b-83dd57f6d150-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F2e8f566c-929e-4540-881b-83dd57f6d150-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F08d877bb-9286-47ae-b156-f2157f9e98fd-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F08d877bb-9286-47ae-b156-f2157f9e98fd-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F08d877bb-9286-47ae-b156-f2157f9e98fd-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2F08d877bb-9286-47ae-b156-f2157f9e98fd-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fba1fcde4-8cc0-49a1-8b64-2080412a832c-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fba1fcde4-8cc0-49a1-8b64-2080412a832c-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fba1fcde4-8cc0-49a1-8b64-2080412a832c-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fba1fcde4-8cc0-49a1-8b64-2080412a832c-refined.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fdda40371-4cc1-4c4a-915a-24119a4d19b0-refined.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fdda40371-4cc1-4c4a-915a-24119a4d19b0-refined.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fdda40371-4cc1-4c4a-915a-24119a4d19b0-refined.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/banner-images-2FUOsQVVJWWcXC6waW0cLqhjFgSrx1-2Fdda40371-4cc1-4c4a-915a-24119a4d19b0-refined.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div></figure><h2 id="how-does-bestbanner-compare">How does BestBanner compare?</h2><p>I think it's fair to say that BestBanner wipes the floor with Stable Diffusion – admittedly, it's an old model, but unless you're going for a high-octane nightmare fuel vibe for your banners, we wouldn't recommend it.</p><p><strong>Overall image quality: </strong>Both Midjourney and BestBanner shine here, creating detailed appealing imagery. Stable Diffusion is more about that high-octane nightmare fuel vibe.</p><p><strong>Topicality: </strong>Stable Diffusion wobbles off-point a lot, showing vague abstract blobs when we used it to create images for the time dilation post. Midjourney is a lot better, but often misses the point (did it connect Trump to the "orange" in the text of the Just Stop Oil example?) or completely omits key information (in the Barbie-Oppenheimer example, most images are missing Oppenheimer altogether. We also see this in the MLK example. BestBanner stays on topic very well, with the Just Stop Oil example showing actual sports playing grounds (which are the scenes of protests), while Barbenheimer includes someone who actually looks like (a slightly more handsome) Oppenheimer:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/JROppenheimer-LosAlamos.jpg" width="524" height="721" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/0tv75sxymx48_1689155127176.png" width="395" height="506" alt=""></div></div></div><figcaption>The real Oppenheimer (left) and BestBanner's Oppenheimer (right)</figcaption></figure><p><strong>Composition: </strong>Stable Diffusion quite often generates several pictures inside one image, for example in the case of Barbie/Oppenheimer. This doesn't happen in Midjourney, though (again in Barbie/Oppenheimer) we get several shots of "Person A just standing opposite Person B". The composition of BestBanner's Harry Potter images stands out, with the author of the works standing in what appears to be a posh school library. </p><p><strong>Languages:</strong> Stable Diffusion typically falls down and creates generic images of suburbia when it comes to anything but English. Midjourney does well, but in other tests (from this <a href="https://www.t-online.de/nachrichten/panorama/wetter/id_100203492/hitzewelle-und-unwetter-so-wird-das-wetter-bei-ihnen-am-wochenende.html?ref=jina-ai-gmbh.ghost.io">German article</a>) it interpreted "grads" as graduates, not degrees, while BestBanner worked as expected for German, Chinese and other languages.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/image-25.png" class="kg-image" alt="" width="581" height="408"></figure><p><strong>Censorship:</strong> Stable Diffusion is very censor-happy. In some cases we can understand this, as in the MLK example where some language is used that would be considered offensive today. Quite what it has against Alice in Wonderland is beyond us. While Midjourney didn't get censor-happy in our testing, we've often seen heavy-handedness and <a href="https://petapixel.com/2023/04/03/midjourney-bans-ai-images-of-chinese-president-xi-jinping/?ref=jina-ai-gmbh.ghost.io">highly-selective political censorship</a>. In our testing with BestBanner we haven't yet found examples of censorship, though testing obscene content is way outside the scope of this post.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/mj_ban.png" width="603" height="648" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/07/mj_ban.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/07/mj_ban.png 603w"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/sd_ban.png" width="493" height="577" alt=""></div></div></div><figcaption>Midjourney (left) and Stable Diffusion (right) rejections</figcaption></figure><p><strong>UI: </strong>Midjourney limits you to a Discord bot, and while there are posts saying an API is "in the works", we're not confident this will come any time soon. Several front-ends are available for Stable Diffusion, and it's hosted in many places with an open API. BestBanner also offers an <a href="https://bestbanner.jina.ai/api?ref=jina-ai-gmbh.ghost.io">easy-to-use API for generating images</a>, and integrates with Jina AI's <a href="https://github.com/jina-ai/jinaai-py?ref=jina-ai-gmbh.ghost.io">Python</a> and <a href="https://github.com/jina-ai/jinaai-js?ref=jina-ai-gmbh.ghost.io">JavaScript</a> packages.</p><p>Overall, BestBanner stacks up well against the competition. While image quality is on par with Midjourney, in many ways (composition, topicality, language support, API) it's a superior choice. And we think the less said about Stable Diffusion the better!</p><h2 id="get-started">Get started</h2><p>Visit <a href="http://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io">bestbanner.jina.ai</a> to sign up, and join our <a href="https://discord.com/channels/1106542220112302130/1128217454296965220?ref=jina-ai-gmbh.ghost.io">Discord channel</a> to share the banners you’ve created!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">BestBanner - Blog to banner, without the prompts!</div><div class="kg-bookmark-description">BestBanner revolutionizes the way you create banner images. Simply input your article text, and watch as our advanced multimodal AI crafts a unique and captivating image, tailored specifically to your content. Ideal for publishers, bloggers, and content creators.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://bestbanner.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">BestBanner</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://bestbanner.jina.ai/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fredefining-text-to-image-how-bestbanner-outperforms-midjourney-and-stable-diffusion-a-benchmark-analysis%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Finetuner 0.8.0 Update</title><meta charset="utf-8"><meta name="title" content="Finetuner 0.8.0 Update"><meta name="description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/release-note-finetuner-0-8-0"><meta property="og:title" content="Finetuner 0.8.0 Update"><meta property="og:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/release-note-finetuner-0-8-0"><meta property="twitter:title" content="Finetuner 0.8.0 Update"><meta property="twitter:description" content="Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Blue-Pink-Gradient-Fashion-Banner--30---15-in---2--1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner 0.8.0 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 13, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.8.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.8.0 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.8.0This release covers Finetuner version 0.8.0, including dependency finetuner-core 0.13.9.This release contains 1 new feature and 1 refactoring.🆕 FeaturesAdd Jina embe…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/5f481ca60673a83fb8415511498989cd4a2a864e7e76c6ff194fb415072957c9/jina-ai/finetuner/releases/tag/v0.8.0" alt=""></div></a></figure><p>This release covers Finetuner version 0.8.0, including dependency finetuner-core 0.13.9.</p><p>This release contains 1 new feature and 1 refactoring.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="add-jina-embeddings-suite-757">Add Jina embeddings suite (<a href="https://github.com/jina-ai/finetuner/pull/757?ref=jina-ai-gmbh.ghost.io">#757</a>)</h3><p>We have made contributions to the open-source community by releasing three pre-trained embedding models:</p><ol><li><code>jina-embedding-s-en-v1</code>: 35 million parameter compact embedding model.</li><li><code>jina-embedding-b-en-v1</code>: 110 million parameter standard-sized embedding model.</li><li><code>jina-embedding-l-en-v1</code>: 330 million parameter large embedding model.</li></ol><p>We have trained all three models using Jina AI's Linnaeus-Clean dataset. This dataset consists of 380 million pairs of sentences in query-document pairs. These pairs were curated from a variety of domains in the Linnaeus-Full dataset through a thorough cleaning process. The Linnaeus-Full dataset contains 1.6 billion sentence pairs.</p><p>If you wish to use these embeddings with Finetuner, follow the instructions below:</p><pre><code class="language-python hljs">!pip install finetuner
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="68f3a97b-bfaf-4098-9150-5fc285712bb1" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="68f3a97b-bfaf-4098-9150-5fc285712bb1" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 13, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.8.0?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.8.0 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.8.0This release covers Finetuner version 0.8.0, including dependency finetuner-core 0.13.9.This release contains 1 new feature and 1 refactoring.🆕 FeaturesAdd Jina embe…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/5f481ca60673a83fb8415511498989cd4a2a864e7e76c6ff194fb415072957c9/jina-ai/finetuner/releases/tag/v0.8.0" alt=""></div></a></figure><p>This release covers Finetuner version 0.8.0, including dependency finetuner-core 0.13.9.</p><p>This release contains 1 new feature and 1 refactoring.</p><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="add-jina-embeddings-suite-757">Add Jina embeddings suite (<a href="https://github.com/jina-ai/finetuner/pull/757?ref=jina-ai-gmbh.ghost.io">#757</a>)</h3><p>We have made contributions to the open-source community by releasing three pre-trained embedding models:</p><ol><li><code>jina-embedding-s-en-v1</code>: 35 million parameter compact embedding model.</li><li><code>jina-embedding-b-en-v1</code>: 110 million parameter standard-sized embedding model.</li><li><code>jina-embedding-l-en-v1</code>: 330 million parameter large embedding model.</li></ol><p>We have trained all three models using Jina AI's Linnaeus-Clean dataset. This dataset consists of 380 million pairs of sentences in query-document pairs. These pairs were curated from a variety of domains in the Linnaeus-Full dataset through a thorough cleaning process. The Linnaeus-Full dataset contains 1.6 billion sentence pairs.</p><p>If you wish to use these embeddings with Finetuner, follow the instructions below:</p><pre><code class="language-python hljs">!pip install finetuner
 <span class="hljs-keyword">import</span> finetuner
 
 model = finetuner.build_model(<span class="hljs-string">'jinaai/jina-embedding-s-en-v1'</span>)
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="05f31123-fe2e-42dd-b8a4-758d7b09f375" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="05f31123-fe2e-42dd-b8a4-758d7b09f375" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner 0.8.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 26, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>This release covers Finetuner version 0.8.1, including dependency finetuner-core 0.13.10.</p><p>This release contains 1 new feature, 1 refactoring and 1 documentation improvement.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.8.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.8.1 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.8.1This release covers Finetuner version 0.8.1, including dependency finetuner-core 0.13.10.This release contains 1 new feature, 1 refactoring and 1 documentation improve…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/1c59f5ab278c2e43092fc45ee6911159bcb353567604638d0e2dd44ee2a0f866/jina-ai/finetuner/releases/tag/v0.8.1" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="add-jina-tiny-embedding-model">Add Jina Tiny Embedding model</h3><p>We have included <code>jina-embedding-t-en-v1</code> in our list of supported models. This very small embedding model, comprising 14 million parameters, offers lightning-fast inference on CPUs.</p><p>In our experiments, it was able to encode 1730 sentences per second on a Macbook Pro Core-i5, making it perfectly suitable for edge devices. To utilize the Tiny model, follow these steps:</p><pre><code class="language-Python hljs">!pip install finetuner
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Finetuner 0.8.1 Update</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 26, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>This release covers Finetuner version 0.8.1, including dependency finetuner-core 0.13.10.</p><p>This release contains 1 new feature, 1 refactoring and 1 documentation improvement.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/finetuner/releases/tag/v0.8.1?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Release v0.8.1 · jina-ai/finetuner</div><div class="kg-bookmark-description">Release Note Finetuner 0.8.1This release covers Finetuner version 0.8.1, including dependency finetuner-core 0.13.10.This release contains 1 new feature, 1 refactoring and 1 documentation improve…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/1c59f5ab278c2e43092fc45ee6911159bcb353567604638d0e2dd44ee2a0f866/jina-ai/finetuner/releases/tag/v0.8.1" alt=""></div></a></figure><h2 id="%F0%9F%86%95-features">🆕 Features</h2><h3 id="add-jina-tiny-embedding-model">Add Jina Tiny Embedding model</h3><p>We have included <code>jina-embedding-t-en-v1</code> in our list of supported models. This very small embedding model, comprising 14 million parameters, offers lightning-fast inference on CPUs.</p><p>In our experiments, it was able to encode 1730 sentences per second on a Macbook Pro Core-i5, making it perfectly suitable for edge devices. To utilize the Tiny model, follow these steps:</p><pre><code class="language-Python hljs">!pip install finetuner
 <span class="hljs-keyword">import</span> finetuner
 
 model = finetuner.build_model(<span class="hljs-string">'jinaai/jina-embedding-t-en-v1'</span>)
diff --git a/news/reverse-engineering-image-prompts-with-promptperfect/index.html b/news/reverse-engineering-image-prompts-with-promptperfect/index.html
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Reverse Engineering Image Prompts with PromptPerfect</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Reverse engineer your image prompts for Midjourney, Stable Diffusion, and DALL-E 2</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 27, 2023 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Want to skip the reading and just get started? You can sign up for PromptPerfect <a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">here</a>!</div></div><p>They say a picture is worth a thousand words. But <em>what</em> words, damnit? If I see a stunning creation from <a href="https://midjourney.com/?ref=jina-ai-gmbh.ghost.io">Midjourney</a>, <a href="https://stability.ai/blog/stable-diffusion-public-release?ref=jina-ai-gmbh.ghost.io">Stable Diffusion</a> or <a href="https://openai.com/product/dall-e-2?ref=jina-ai-gmbh.ghost.io">DALL-E 2</a>, how can I go about creating a similar prompt if I don't know the arcane magic words the creator used?</p><p>We launched <a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">PromptPerfect</a> a while ago to help creators perfect their prompts (as you may have guessed from the name). It's a tool to take your prompt (for text or image generation) and make it a lot more detailed.</p><p>Now it can reverse engineer prompts too, by extracting a prompt from any image you upload:</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/promptperfect-reverse-engineer.mp4" poster="https://img.spacergif.org/v1/1458x830/0a/spacer.png" width="1458" height="830" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/06/media-thumbnail-ember874.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>I can just feed in an image and it'll reverse engineer the prompt so I can r̵i̵p̵ ̵o̵f̵f̵ be inspired by my favorite artists:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/FrxPRPqX0Akba2n.jpeg" class="kg-image" alt="" width="1024" height="768" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/FrxPRPqX0Akba2n.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/FrxPRPqX0Akba2n.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/FrxPRPqX0Akba2n.jpeg 1024w" sizes="(min-width: 720px) 720px"></figure><p>And here's the <a href="https://promptperfect.jina.ai/share?thread=FmGTjBA1eBYnyq0zslwT&amp;ref=jina-ai-gmbh.ghost.io">prompt</a> that PromptPerfect returns: <code>Japanese garden with a wooden bridge, mountain range in the background, traditional pagoda, lush greenery, serene atmosphere, family taking photo on the bridge, woman and child admiring pagoda, flowing river sound. Hyper-realistic digital art inspired by Hokusai's "Thirty-six Views of Mount Fuji," highly detailed with intricate patterns and textures, cinematic lighting and depth of field. Art style influenced by Yoshida Hiroshi and Utagawa Hiroshige.</code></p><h2 id="promptperfect-vs-blip-2-fight">PromptPerfect vs BLIP-2: Fight!</h2><p>Let's put it to the test by comparing it to <a href="https://arxiv.org/abs/2301.12597?ref=jina-ai-gmbh.ghost.io">BLIP-2</a>:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/FrxMYPQX0BcL7PW.jpeg" class="kg-image" alt="" width="512" height="768"></figure><p>BLIP-2: <code>a girl with long hair and a feathered headdress is standing in the woods</code></p><p><a href="https://promptperfect.jina.ai/share?thread=RtCuXq3ABgcpvX8z5CQf&amp;ref=jina-ai-gmbh.ghost.io">PromptPerfect</a>: <code>Portrait of a young Native American warrior princess, standing tall and proud on the edge of a cliff overlooking a vast canyon. She wears traditional clothing and accessories, including a feathered headdress, intricate beadwork, and tattoos that tell stories of her tribe's history. In one hand she holds a sharp spear, ready to defend her people against any threat. The scene is bathed in warm golden light as the sun sets behind her, evoking feelings of strength, courage, and fierce determination. Art by Amalia Chitulescu and Brian Sum.</code></p><p>As you can see, BLIP-2 spits out a very short, vague description, while PromptPerfect gives you a long, detailed prompt more suitable for image generation. This longer prompt contains a lot more variables for you to tinker with, though it <em>does</em> tend to hallucinate a bit (like specifying that she holds a spear and there's a sunset behind her).</p><p>Now let's feed both of those into Midjourney to see what we get. We'll get four images from each prompt to ensure fairness:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_a_girl_with_long_hair_and_a_feathered_headdress__768c6d28-f166-46a3-9fc1-bbf3900d594c.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/generativejina_a_girl_with_long_hair_and_a_feathered_headdress__768c6d28-f166-46a3-9fc1-bbf3900d594c.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/generativejina_a_girl_with_long_hair_and_a_feathered_headdress__768c6d28-f166-46a3-9fc1-bbf3900d594c.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_a_girl_with_long_hair_and_a_feathered_headdress__768c6d28-f166-46a3-9fc1-bbf3900d594c.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_Portrait_of_a_young_Native_American_warrior_prin_b7f22771-0469-4aad-9551-749860a22535.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/generativejina_Portrait_of_a_young_Native_American_warrior_prin_b7f22771-0469-4aad-9551-749860a22535.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/generativejina_Portrait_of_a_young_Native_American_warrior_prin_b7f22771-0469-4aad-9551-749860a22535.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_Portrait_of_a_young_Native_American_warrior_prin_b7f22771-0469-4aad-9551-749860a22535.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>BLIP-2 (left), PromptPerfect (right)</figcaption></figure><p>We can see from the PromptPerfect prompt that the lighting is more in line with the original image and we get more consistent patterns of dress. The BLIP-2 prompt seems to have led to more "creative" interpretations of a feathered headdress, with what seem to be leaves, and less of a traditional Native American vibe.</p><p>Let's try a few more, like one of my favorite comic books, Marvel's <a href="https://marvel.fandom.com/wiki/Nextwave_(Earth-63163)?ref=jina-ai-gmbh.ghost.io">Nextwave</a>:</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/next-wave-11-007.png" class="kg-image" alt="" width="1981" height="1521" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/next-wave-11-007.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/next-wave-11-007.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/03/next-wave-11-007.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/next-wave-11-007.png 1981w" sizes="(min-width: 1200px) 1200px"></figure><p>BLIP-2: <code>a comic book cover featuring a group of characters</code></p><p><a href="https://promptperfect.jina.ai/share?thread=eyX48hMiXiw5lfvnNl88&amp;ref=jina-ai-gmbh.ghost.io">PromptPerfect</a>: <code>comic book cover featuring a superhero in the center, surrounded by various action scenes and villains. The top left piece shows the hero flying through the city, while the top right piece features a battle with a giant robot. The bottom left piece depicts the hero fighting off a group of henchmen, and the bottom right piece shows an intense showdown between the hero and his arch-nemesis on a rooftop. Despite the chaotic nature of the scene, there is a clear sense of heroism and triumph emanating from the central figure.</code></p><p>Neither of them are perfect, but BLIP-2's prompt is so minimalist and vague as to be not very useful. Again, PromptPerfect hallucinates a rooftop and a city, but this gives a prompt engineer more knobs and dials to fiddle, by deleting or changing some words.</p><p>Here's the result in Midjourney again:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_a_comic_book_cover_featuring_a_group_of_characte_86aec281-249f-4d29-8334-1950cb6a6002.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/generativejina_a_comic_book_cover_featuring_a_group_of_characte_86aec281-249f-4d29-8334-1950cb6a6002.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/generativejina_a_comic_book_cover_featuring_a_group_of_characte_86aec281-249f-4d29-8334-1950cb6a6002.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_a_comic_book_cover_featuring_a_group_of_characte_86aec281-249f-4d29-8334-1950cb6a6002.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_a_comic_book_cover_featuring_a_superhero_in_the__d551d7bc-398c-430f-b9f6-2e350601f662.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/generativejina_a_comic_book_cover_featuring_a_superhero_in_the__d551d7bc-398c-430f-b9f6-2e350601f662.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/generativejina_a_comic_book_cover_featuring_a_superhero_in_the__d551d7bc-398c-430f-b9f6-2e350601f662.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_a_comic_book_cover_featuring_a_superhero_in_the__d551d7bc-398c-430f-b9f6-2e350601f662.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>BLIP-2 (left), PromptPerfect (right)</figcaption></figure><p>Here we can see that the image generated from BLIP-2's prompt lacks the dynamic and frenetic feel of the original image. It's more a bunch of folks standing around. While PromptPerfect doesn't quite capture the delicious bonkers-ness of Nextwave, it gets a lot closer, showing crowded action-packed scenes of superheroes superheroing.</p><h2 id="promptperfect-what-is-it-good-for">PromptPerfect: What is it good for?</h2><p>Absolutely...lots of stuff. </p><h3 id="redesigns">Redesigns</h3><p>Let's say you're running a project and want to re-design the logo. You want to maintain the same general vibe, but put a new spin on it. In this case, PromptPerfect's hallucination becomes a feature rather than a bug, since it adds new features to what you already have.</p><p>Take our (at the time of writing) logo for Jina:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Product-logo_Core@2x.png" class="kg-image" alt="" width="840" height="840" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Product-logo_Core@2x.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Product-logo_Core@2x.png 840w" sizes="(min-width: 720px) 720px"></figure><p>If we upload that to PromptPerfect we get this <a href="https://promptperfect.jina.ai/share?thread=wr39rqZWm7xIet1bLQmz&amp;ref=jina-ai-gmbh.ghost.io">prompt</a>: <code>magnifying glass, central focus, vibrant colors, inspecting, highlighting, circle logo, multiple shapes and hues| colorful elements| adjacent multicolored circles in yellow, green, blue| striking contrast between black background and vivid circle| recurring magnifying glasses throughout the scene| exploration of color and detail through lenses| dynamic composition that encourages viewers to examine intricate details within design</code></p><p>And then plugging that into Midjourney gives us wild new options:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-26.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-26.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-26.png 1024w" sizes="(min-width: 720px) 720px"></figure><p>If we manually tweak the prompt a bit (by fiddling with the knobs and dials PromptPerfect added), we get: <code>magnifying glass logo, central focus, vibrant colors, inspecting, highlighting, circle logo, multiple shapes and hues| colorful elements| adjacent multicolored circles in yellow, green, blue| striking contrast between white background and vivid circle| recurring magnifying glasses throughout the scene| exploration of color and detail through lenses| dynamic composition that encourages viewers to examine details within design</code></p><p>Which gives us some more promising candidates:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-27.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-27.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-27.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-27.png 1024w" sizes="(min-width: 720px) 720px"></figure><h3 id="creativity-kick-start">Creativity kick-start</h3><p>Let's say I want to make a riff on the Mona Lisa. The problem is, it's been done so often that it's difficult for me to think of any creative thing that hasn't been done before. Mona Lisa with a cigar? With Groucho Marx specs? As a punk? Done, done, and done.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.671309 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/fposter-small-wall_texture-product-750x1000.jpg" width="482" height="718" alt=""></div><div class="kg-gallery-image" style="flex: 0.688333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/bd3acc13a47e1f4250c49d20218005e4--duck-soup-groucho-marx.jpg" width="413" height="600" alt=""></div><div class="kg-gallery-image" style="flex: 0.815217 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/494955106809869.5f9874efd729a.jpg" width="1200" height="1472" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/494955106809869.5f9874efd729a.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/494955106809869.5f9874efd729a.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/494955106809869.5f9874efd729a.jpg 1200w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>Maybe PromptPerfect can throw in some new ideas? Let's see the <a href="https://promptperfect.jina.ai/share?thread=R1pXDQhrSxsklpqJDRJ2&amp;ref=jina-ai-gmbh.ghost.io">prompt</a> it creates: <code>Reimagined Mona Lisa, Leonardo da Vinci, enigmatic smile, gentle gaze, elegant attire, serene landscape, intricate artwork | surrealism | cubism | double exposure effect | overlapping elements | inconsistencies | depth and realism | Salvador Dalí and Pablo Picasso inspired fusion | high-resolution digital painting | thought-provoking interpretations and discussions about Mona Lisa's identity.</code></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-28.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-28.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-28.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-28.png 1024w" sizes="(min-width: 720px) 720px"></figure><h3 id="inspiration">Inspiration</h3><p>I like to take pictures of my puppy, Mister Whifflekins:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-29.png" class="kg-image" alt="" width="1000" height="667" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-29.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-29.png 1000w" sizes="(min-width: 720px) 720px"><figcaption>Absolutely certainly my non-fictional puppy who is totally real and not an image I googled</figcaption></figure><p>For his birthday I want to make a chocolate cake with his picture on it (dogs eat cake, right? I'm sure it'll be fine). But I don't want a boring picture of him. I want something that reflects his creativity, daringness, and intense personality. So I can feed his image to PromptPerfect and see <a href="https://promptperfect.jina.ai/share?thread=3k2TmyBPo5UjzLtH7dPx&amp;ref=jina-ai-gmbh.ghost.io">what</a> we get: <code>Playful white poodle in a park, surrounded by lush greenery and vibrant flowers, wagging its tail, exploring surroundings, fur glistening in sunlight, eyes sparkling with excitement, puzzle piece shapes overlapping with poodle as centerpiece, joyful demeanor and lively energy captivating attention, intricate details and vivid colors enhancing composition, inspired by Thomas Kinkade's style</code></p><p>And in Midjourney that becomes:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-30.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-30.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-30.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-30.png 1024w" sizes="(min-width: 720px) 720px"></figure><p>I'm sure Mister Whifflekins will be overjoyed to see himself in Thomas Kincade's jigsaw form!</p><h2 id="perfect-your-prompts-now">Perfect your prompts now</h2><p>To get started, sign up at <strong><a href="promptperfect.jina.ai">promptperfect.jina.ai</a> </strong>and join our <strong><a href="https://discord.gg/XVcZq4VKsx?ref=jina-ai-gmbh.ghost.io">Discord</a></strong> to talk to like-minded prompt engineers! 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Reverse Engineering Image Prompts with PromptPerfect</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Reverse engineer your image prompts for Midjourney, Stable Diffusion, and DALL-E 2</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">March 27, 2023 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Want to skip the reading and just get started? You can sign up for PromptPerfect <a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">here</a>!</div></div><p>They say a picture is worth a thousand words. But <em>what</em> words, damnit? If I see a stunning creation from <a href="https://midjourney.com/?ref=jina-ai-gmbh.ghost.io">Midjourney</a>, <a href="https://stability.ai/blog/stable-diffusion-public-release?ref=jina-ai-gmbh.ghost.io">Stable Diffusion</a> or <a href="https://openai.com/product/dall-e-2?ref=jina-ai-gmbh.ghost.io">DALL-E 2</a>, how can I go about creating a similar prompt if I don't know the arcane magic words the creator used?</p><p>We launched <a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">PromptPerfect</a> a while ago to help creators perfect their prompts (as you may have guessed from the name). It's a tool to take your prompt (for text or image generation) and make it a lot more detailed.</p><p>Now it can reverse engineer prompts too, by extracting a prompt from any image you upload:</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/promptperfect-reverse-engineer.mp4" poster="https://img.spacergif.org/v1/1458x830/0a/spacer.png" width="1458" height="830" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/06/media-thumbnail-ember874.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>I can just feed in an image and it'll reverse engineer the prompt so I can r̵i̵p̵ ̵o̵f̵f̵ be inspired by my favorite artists:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/FrxPRPqX0Akba2n.jpeg" class="kg-image" alt="" width="1024" height="768" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/FrxPRPqX0Akba2n.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/FrxPRPqX0Akba2n.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/FrxPRPqX0Akba2n.jpeg 1024w" sizes="(min-width: 720px) 720px"></figure><p>And here's the <a href="https://promptperfect.jina.ai/share?thread=FmGTjBA1eBYnyq0zslwT&amp;ref=jina-ai-gmbh.ghost.io">prompt</a> that PromptPerfect returns: <code>Japanese garden with a wooden bridge, mountain range in the background, traditional pagoda, lush greenery, serene atmosphere, family taking photo on the bridge, woman and child admiring pagoda, flowing river sound. Hyper-realistic digital art inspired by Hokusai's "Thirty-six Views of Mount Fuji," highly detailed with intricate patterns and textures, cinematic lighting and depth of field. Art style influenced by Yoshida Hiroshi and Utagawa Hiroshige.</code></p><h2 id="promptperfect-vs-blip-2-fight">PromptPerfect vs BLIP-2: Fight!</h2><p>Let's put it to the test by comparing it to <a href="https://arxiv.org/abs/2301.12597?ref=jina-ai-gmbh.ghost.io">BLIP-2</a>:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/FrxMYPQX0BcL7PW.jpeg" class="kg-image" alt="" width="512" height="768"></figure><p>BLIP-2: <code>a girl with long hair and a feathered headdress is standing in the woods</code></p><p><a href="https://promptperfect.jina.ai/share?thread=RtCuXq3ABgcpvX8z5CQf&amp;ref=jina-ai-gmbh.ghost.io">PromptPerfect</a>: <code>Portrait of a young Native American warrior princess, standing tall and proud on the edge of a cliff overlooking a vast canyon. She wears traditional clothing and accessories, including a feathered headdress, intricate beadwork, and tattoos that tell stories of her tribe's history. In one hand she holds a sharp spear, ready to defend her people against any threat. The scene is bathed in warm golden light as the sun sets behind her, evoking feelings of strength, courage, and fierce determination. Art by Amalia Chitulescu and Brian Sum.</code></p><p>As you can see, BLIP-2 spits out a very short, vague description, while PromptPerfect gives you a long, detailed prompt more suitable for image generation. This longer prompt contains a lot more variables for you to tinker with, though it <em>does</em> tend to hallucinate a bit (like specifying that she holds a spear and there's a sunset behind her).</p><p>Now let's feed both of those into Midjourney to see what we get. We'll get four images from each prompt to ensure fairness:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_a_girl_with_long_hair_and_a_feathered_headdress__768c6d28-f166-46a3-9fc1-bbf3900d594c.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/generativejina_a_girl_with_long_hair_and_a_feathered_headdress__768c6d28-f166-46a3-9fc1-bbf3900d594c.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/generativejina_a_girl_with_long_hair_and_a_feathered_headdress__768c6d28-f166-46a3-9fc1-bbf3900d594c.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_a_girl_with_long_hair_and_a_feathered_headdress__768c6d28-f166-46a3-9fc1-bbf3900d594c.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_Portrait_of_a_young_Native_American_warrior_prin_b7f22771-0469-4aad-9551-749860a22535.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/generativejina_Portrait_of_a_young_Native_American_warrior_prin_b7f22771-0469-4aad-9551-749860a22535.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/generativejina_Portrait_of_a_young_Native_American_warrior_prin_b7f22771-0469-4aad-9551-749860a22535.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_Portrait_of_a_young_Native_American_warrior_prin_b7f22771-0469-4aad-9551-749860a22535.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>BLIP-2 (left), PromptPerfect (right)</figcaption></figure><p>We can see from the PromptPerfect prompt that the lighting is more in line with the original image and we get more consistent patterns of dress. The BLIP-2 prompt seems to have led to more "creative" interpretations of a feathered headdress, with what seem to be leaves, and less of a traditional Native American vibe.</p><p>Let's try a few more, like one of my favorite comic books, Marvel's <a href="https://marvel.fandom.com/wiki/Nextwave_(Earth-63163)?ref=jina-ai-gmbh.ghost.io">Nextwave</a>:</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/next-wave-11-007.png" class="kg-image" alt="" width="1981" height="1521" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/next-wave-11-007.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/next-wave-11-007.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/03/next-wave-11-007.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/next-wave-11-007.png 1981w" sizes="(min-width: 1200px) 1200px"></figure><p>BLIP-2: <code>a comic book cover featuring a group of characters</code></p><p><a href="https://promptperfect.jina.ai/share?thread=eyX48hMiXiw5lfvnNl88&amp;ref=jina-ai-gmbh.ghost.io">PromptPerfect</a>: <code>comic book cover featuring a superhero in the center, surrounded by various action scenes and villains. The top left piece shows the hero flying through the city, while the top right piece features a battle with a giant robot. The bottom left piece depicts the hero fighting off a group of henchmen, and the bottom right piece shows an intense showdown between the hero and his arch-nemesis on a rooftop. Despite the chaotic nature of the scene, there is a clear sense of heroism and triumph emanating from the central figure.</code></p><p>Neither of them are perfect, but BLIP-2's prompt is so minimalist and vague as to be not very useful. Again, PromptPerfect hallucinates a rooftop and a city, but this gives a prompt engineer more knobs and dials to fiddle, by deleting or changing some words.</p><p>Here's the result in Midjourney again:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_a_comic_book_cover_featuring_a_group_of_characte_86aec281-249f-4d29-8334-1950cb6a6002.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/generativejina_a_comic_book_cover_featuring_a_group_of_characte_86aec281-249f-4d29-8334-1950cb6a6002.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/generativejina_a_comic_book_cover_featuring_a_group_of_characte_86aec281-249f-4d29-8334-1950cb6a6002.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_a_comic_book_cover_featuring_a_group_of_characte_86aec281-249f-4d29-8334-1950cb6a6002.png 1024w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_a_comic_book_cover_featuring_a_superhero_in_the__d551d7bc-398c-430f-b9f6-2e350601f662.png" width="1024" height="1024" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/generativejina_a_comic_book_cover_featuring_a_superhero_in_the__d551d7bc-398c-430f-b9f6-2e350601f662.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/generativejina_a_comic_book_cover_featuring_a_superhero_in_the__d551d7bc-398c-430f-b9f6-2e350601f662.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/generativejina_a_comic_book_cover_featuring_a_superhero_in_the__d551d7bc-398c-430f-b9f6-2e350601f662.png 1024w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>BLIP-2 (left), PromptPerfect (right)</figcaption></figure><p>Here we can see that the image generated from BLIP-2's prompt lacks the dynamic and frenetic feel of the original image. It's more a bunch of folks standing around. While PromptPerfect doesn't quite capture the delicious bonkers-ness of Nextwave, it gets a lot closer, showing crowded action-packed scenes of superheroes superheroing.</p><h2 id="promptperfect-what-is-it-good-for">PromptPerfect: What is it good for?</h2><p>Absolutely...lots of stuff. </p><h3 id="redesigns">Redesigns</h3><p>Let's say you're running a project and want to re-design the logo. You want to maintain the same general vibe, but put a new spin on it. In this case, PromptPerfect's hallucination becomes a feature rather than a bug, since it adds new features to what you already have.</p><p>Take our (at the time of writing) logo for Jina:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/Product-logo_Core@2x.png" class="kg-image" alt="" width="840" height="840" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/Product-logo_Core@2x.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/Product-logo_Core@2x.png 840w" sizes="(min-width: 720px) 720px"></figure><p>If we upload that to PromptPerfect we get this <a href="https://promptperfect.jina.ai/share?thread=wr39rqZWm7xIet1bLQmz&amp;ref=jina-ai-gmbh.ghost.io">prompt</a>: <code>magnifying glass, central focus, vibrant colors, inspecting, highlighting, circle logo, multiple shapes and hues| colorful elements| adjacent multicolored circles in yellow, green, blue| striking contrast between black background and vivid circle| recurring magnifying glasses throughout the scene| exploration of color and detail through lenses| dynamic composition that encourages viewers to examine intricate details within design</code></p><p>And then plugging that into Midjourney gives us wild new options:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-26.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-26.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-26.png 1024w" sizes="(min-width: 720px) 720px"></figure><p>If we manually tweak the prompt a bit (by fiddling with the knobs and dials PromptPerfect added), we get: <code>magnifying glass logo, central focus, vibrant colors, inspecting, highlighting, circle logo, multiple shapes and hues| colorful elements| adjacent multicolored circles in yellow, green, blue| striking contrast between white background and vivid circle| recurring magnifying glasses throughout the scene| exploration of color and detail through lenses| dynamic composition that encourages viewers to examine details within design</code></p><p>Which gives us some more promising candidates:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-27.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-27.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-27.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-27.png 1024w" sizes="(min-width: 720px) 720px"></figure><h3 id="creativity-kick-start">Creativity kick-start</h3><p>Let's say I want to make a riff on the Mona Lisa. The problem is, it's been done so often that it's difficult for me to think of any creative thing that hasn't been done before. Mona Lisa with a cigar? With Groucho Marx specs? As a punk? Done, done, and done.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.671309 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/fposter-small-wall_texture-product-750x1000.jpg" width="482" height="718" alt=""></div><div class="kg-gallery-image" style="flex: 0.688333 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/bd3acc13a47e1f4250c49d20218005e4--duck-soup-groucho-marx.jpg" width="413" height="600" alt=""></div><div class="kg-gallery-image" style="flex: 0.815217 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/494955106809869.5f9874efd729a.jpg" width="1200" height="1472" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/494955106809869.5f9874efd729a.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/494955106809869.5f9874efd729a.jpg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/494955106809869.5f9874efd729a.jpg 1200w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>Maybe PromptPerfect can throw in some new ideas? Let's see the <a href="https://promptperfect.jina.ai/share?thread=R1pXDQhrSxsklpqJDRJ2&amp;ref=jina-ai-gmbh.ghost.io">prompt</a> it creates: <code>Reimagined Mona Lisa, Leonardo da Vinci, enigmatic smile, gentle gaze, elegant attire, serene landscape, intricate artwork | surrealism | cubism | double exposure effect | overlapping elements | inconsistencies | depth and realism | Salvador Dalí and Pablo Picasso inspired fusion | high-resolution digital painting | thought-provoking interpretations and discussions about Mona Lisa's identity.</code></p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-28.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-28.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-28.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-28.png 1024w" sizes="(min-width: 720px) 720px"></figure><h3 id="inspiration">Inspiration</h3><p>I like to take pictures of my puppy, Mister Whifflekins:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-29.png" class="kg-image" alt="" width="1000" height="667" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-29.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-29.png 1000w" sizes="(min-width: 720px) 720px"><figcaption>Absolutely certainly my non-fictional puppy who is totally real and not an image I googled</figcaption></figure><p>For his birthday I want to make a chocolate cake with his picture on it (dogs eat cake, right? I'm sure it'll be fine). But I don't want a boring picture of him. I want something that reflects his creativity, daringness, and intense personality. So I can feed his image to PromptPerfect and see <a href="https://promptperfect.jina.ai/share?thread=3k2TmyBPo5UjzLtH7dPx&amp;ref=jina-ai-gmbh.ghost.io">what</a> we get: <code>Playful white poodle in a park, surrounded by lush greenery and vibrant flowers, wagging its tail, exploring surroundings, fur glistening in sunlight, eyes sparkling with excitement, puzzle piece shapes overlapping with poodle as centerpiece, joyful demeanor and lively energy captivating attention, intricate details and vivid colors enhancing composition, inspired by Thomas Kinkade's style</code></p><p>And in Midjourney that becomes:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-30.png" class="kg-image" alt="" width="1024" height="1024" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/03/image-30.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/03/image-30.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/03/image-30.png 1024w" sizes="(min-width: 720px) 720px"></figure><p>I'm sure Mister Whifflekins will be overjoyed to see himself in Thomas Kincade's jigsaw form!</p><h2 id="perfect-your-prompts-now">Perfect your prompts now</h2><p>To get started, sign up at <strong><a href="promptperfect.jina.ai">promptperfect.jina.ai</a> </strong>and join our <strong><a href="https://discord.gg/XVcZq4VKsx?ref=jina-ai-gmbh.ghost.io">Discord</a></strong> to talk to like-minded prompt engineers! Let us know how you're using PromptPerfect to perfect your prompts!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Freverse-engineering-image-prompts-with-promptperfect%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>SceneXplain: Unleash the Advanced Image Captioning &amp; Storytelling</title><meta charset="utf-8"><meta name="title" content="SceneXplain: Unleash the Advanced Image Captioning &amp; Storytelling"><meta name="description" content="Uncover the game-changing potential of SceneXplain, an advanced image captioning solution powered by LLMs. Check out the benchmark against Midjourney, CLIP, BLIP2, and other alternatives. Dive into our blog post and experience the revolution firsthand!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/scenexplain-unleash-advanced-image-captioning-storytelling"><meta property="og:title" content="SceneXplain: Unleash the Advanced Image Captioning &amp; Storytelling"><meta property="og:description" content="Uncover the game-changing potential of SceneXplain, an advanced image captioning solution powered by LLMs. Check out the benchmark against Midjourney, CLIP, BLIP2, and other alternatives. Dive into our blog post and experience the revolution firsthand!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates--98-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/scenexplain-unleash-advanced-image-captioning-storytelling"><meta property="twitter:title" content="SceneXplain: Unleash the Advanced Image Captioning &amp; Storytelling"><meta property="twitter:description" content="Uncover the game-changing potential of SceneXplain, an advanced image captioning solution powered by LLMs. Check out the benchmark against Midjourney, CLIP, BLIP2, and other alternatives. Dive into our blog post and experience the revolution firsthand!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates--98-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">SceneXplain: Unleash the Advanced Image Captioning &amp; Storytelling</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Uncover the game-changing potential of SceneXplain, an advanced image captioning solution powered by LLMs. Check out the benchmark against Midjourney, CLIP, BLIP2, and other alternatives. Dive into our blog post and experience the revolution firsthand!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 80px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/SaZhang.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Alex C-G, Sa Zhang</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 04, 2023 • 29 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the multimodal age, the importance of accurate and engaging image captions cannot be overstated. Image captions provide context and enable better searchability and accessibility for users. However, generating precise and detailed descriptions for complex images has always been challenging. <strong><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">Introducing SceneXplain</a>, a game-changing solution leveraging cutting-edge AI technology to create image captions that tell a story. </strong>In this post, we will explore the evolution of image captioning algorithms and discover how SceneXplain sets itself apart by offering advanced image storytelling.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/light-banner.png" class="kg-image" alt="" width="1960" height="1132" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/light-banner.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/light-banner.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/light-banner.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/light-banner.png 1960w" sizes="(min-width: 720px) 720px"></a><figcaption>Click the image to try SceneX on the desktop or via mobile</figcaption></figure><h2 id="the-evolution-of-image-captioning-algorithms">The Evolution of Image Captioning Algorithms</h2><p>The journey of image captioning has seen significant advancements over the last few years, thanks to the continuous development of AI and machine learning. Early models, such as CLIP (Contrastive Language-Image Pretraining) by OpenAI, laid the groundwork for connecting images and text in a meaningful way. CLIP uses unsupervised learning and fine-tuning, employing a large dataset of images and texts to generate useful captions. You can learn more about CLIP in the paper by OpenAI.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2103.00020?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Learning Transferable Visual Models From Natural Language Supervision</div><div class="kg-bookmark-description">State-of-the-art computer vision systems are trained to predict a fixed setof predetermined object categories. This restricted form of supervision limitstheir generality and usability since additional labeled data is needed tospecify any other visual concept. Learning directly from raw text about…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Alec Radford</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image.png" class="kg-image" alt="" width="2000" height="1304" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image.png 2276w" sizes="(min-width: 720px) 720px"><figcaption>CLIP Interrogator is an image captioning algorithm based on CLIP. This will be evaluated in the benchmark below. Source: HuggingFace.co</figcaption></figure><p>Subsequently, the BLIP-2 (Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models) algorithm emerged, introducing a more efficient pre-training strategy. BLIP-2 leverages off-the-shelf frozen pre-trained image encoders and frozen large language models to bridge the modality gap with a lightweight Querying Transformer. This approach reduces the number of trainable parameters while still achieving state-of-the-art performance on various vision-language tasks. You can dive deeper into BLIP and BLIP2 in this paper.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2105.15078?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Can Attention Enable MLPs To Catch Up With CNNs?</div><div class="kg-bookmark-description">In the first week of May, 2021, researchers from four different institutions:Google, Tsinghua University, Oxford University and Facebook, shared theirlatest work [16, 7, 12, 17] on arXiv.org almost at the same time, eachproposing new learning architectures, consisting mainly of linear layers,cla…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Meng-Hao Guo</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-1.png" class="kg-image" alt="" width="2000" height="1434" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-1.png 2316w" sizes="(min-width: 720px) 720px"><figcaption>BLIP2 is a new image captioning algorithm from Salesforce. This will serve as another baseline in the benchmark below. Source: Replicate.com</figcaption></figure><p>Despite the significant progress in image captioning algorithms, <strong>there remained a gap in generating sophisticated, detailed textual descriptions for complex scenes involving multiple objects, interactions, and contextual elements. </strong>This is where SceneXplain enters the picture, pushing the boundaries of image captioning even further.<br></p><h2 id="scenexplainunleashing-the-potential-of-advanced-image-storytelling">SceneXplain - Unleashing the Potential of Advanced Image Storytelling</h2><p>SceneXplain leverages the power of the latest large language models (LLMs), including GPT-4, to offer a groundbreaking solution for advanced image storytelling. By incorporating a layer of reasoning into image description generation, SceneXplain excels at accurately explaining intricate scenes, surpassing the capabilities of conventional captioning algorithms like CLIP, BLIP, and BLIP2.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-2.png" class="kg-image" alt="" width="2000" height="1111" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/04/image-2.png 2400w" sizes="(min-width: 720px) 720px"></a><figcaption>SceneXplain provides both UI and API for interactions.&nbsp;</figcaption></figure><p>One of the key strengths of SceneXplain lies in its ability to capture the nuances of complex scenes involving multiple objects, interactions, and contextual elements. This enables the generation of detailed and contextually rich textual descriptions that effectively convey the essence of the visual content.</p><p>Additionally, SceneXplain supports multilingual captions, making it a highly versatile tool for content creators, marketers, and developers across the globe. <strong>With its user-friendly interface and API integration, SceneXplain can seamlessly integrate into multimodal applications</strong>, from social media platforms to e-commerce websites.</p><h2 id="benchmarking-scenexplain-against-the-competition">Benchmarking SceneXplain Against the Competition</h2><p>This section will compare SceneXplain's performance against other popular image captioning algorithms and tools. Our goal is to provide a clear understanding of the unique strengths and capabilities that SceneXplain offers in advanced image storytelling. The contenders in our comparison include:</p><ul><li><strong>SceneXplain:</strong> The cutting-edge image captioning solution that leverages the power of large language models like GPT-4 to generate sophisticated, detailed, and contextually rich textual descriptions for complex visual content.</li><li><strong>Midjourney <code>/describe</code> command:</strong> A feature recently released by Midjourney, the /describe command aims to transform images into words, enhancing the linguistic-visual process for both creative power and discovery, as claimed in their tweet.</li></ul><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 297px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1643053450501169157&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fscenexplain-unleash-advanced-image-captioning-storytelling%2F&amp;sessionId=e877ddc9ea67c0def5e94463843112d36a0af1bb&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1643053450501169157"></iframe></div>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">SceneXplain: Unleash the Advanced Image Captioning &amp; Storytelling</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Uncover the game-changing potential of SceneXplain, an advanced image captioning solution powered by LLMs. Check out the benchmark against Midjourney, CLIP, BLIP2, and other alternatives. Dive into our blog post and experience the revolution firsthand!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 80px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/SaZhang.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Alex C-G, Sa Zhang</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 04, 2023 • 29 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the multimodal age, the importance of accurate and engaging image captions cannot be overstated. Image captions provide context and enable better searchability and accessibility for users. However, generating precise and detailed descriptions for complex images has always been challenging. <strong><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">Introducing SceneXplain</a>, a game-changing solution leveraging cutting-edge AI technology to create image captions that tell a story. </strong>In this post, we will explore the evolution of image captioning algorithms and discover how SceneXplain sets itself apart by offering advanced image storytelling.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/light-banner.png" class="kg-image" alt="" width="1960" height="1132" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/light-banner.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/light-banner.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/light-banner.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/light-banner.png 1960w" sizes="(min-width: 720px) 720px"></a><figcaption>Click the image to try SceneX on the desktop or via mobile</figcaption></figure><h2 id="the-evolution-of-image-captioning-algorithms">The Evolution of Image Captioning Algorithms</h2><p>The journey of image captioning has seen significant advancements over the last few years, thanks to the continuous development of AI and machine learning. Early models, such as CLIP (Contrastive Language-Image Pretraining) by OpenAI, laid the groundwork for connecting images and text in a meaningful way. CLIP uses unsupervised learning and fine-tuning, employing a large dataset of images and texts to generate useful captions. You can learn more about CLIP in the paper by OpenAI.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2103.00020?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Learning Transferable Visual Models From Natural Language Supervision</div><div class="kg-bookmark-description">State-of-the-art computer vision systems are trained to predict a fixed setof predetermined object categories. This restricted form of supervision limitstheir generality and usability since additional labeled data is needed tospecify any other visual concept. Learning directly from raw text about…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Alec Radford</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image.png" class="kg-image" alt="" width="2000" height="1304" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image.png 2276w" sizes="(min-width: 720px) 720px"><figcaption>CLIP Interrogator is an image captioning algorithm based on CLIP. This will be evaluated in the benchmark below. Source: HuggingFace.co</figcaption></figure><p>Subsequently, the BLIP-2 (Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models) algorithm emerged, introducing a more efficient pre-training strategy. BLIP-2 leverages off-the-shelf frozen pre-trained image encoders and frozen large language models to bridge the modality gap with a lightweight Querying Transformer. This approach reduces the number of trainable parameters while still achieving state-of-the-art performance on various vision-language tasks. You can dive deeper into BLIP and BLIP2 in this paper.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2105.15078?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Can Attention Enable MLPs To Catch Up With CNNs?</div><div class="kg-bookmark-description">In the first week of May, 2021, researchers from four different institutions:Google, Tsinghua University, Oxford University and Facebook, shared theirlatest work [16, 7, 12, 17] on arXiv.org almost at the same time, eachproposing new learning architectures, consisting mainly of linear layers,cla…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Meng-Hao Guo</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-1.png" class="kg-image" alt="" width="2000" height="1434" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-1.png 2316w" sizes="(min-width: 720px) 720px"><figcaption>BLIP2 is a new image captioning algorithm from Salesforce. This will serve as another baseline in the benchmark below. Source: Replicate.com</figcaption></figure><p>Despite the significant progress in image captioning algorithms, <strong>there remained a gap in generating sophisticated, detailed textual descriptions for complex scenes involving multiple objects, interactions, and contextual elements. </strong>This is where SceneXplain enters the picture, pushing the boundaries of image captioning even further.<br></p><h2 id="scenexplainunleashing-the-potential-of-advanced-image-storytelling">SceneXplain - Unleashing the Potential of Advanced Image Storytelling</h2><p>SceneXplain leverages the power of the latest large language models (LLMs), including GPT-4, to offer a groundbreaking solution for advanced image storytelling. By incorporating a layer of reasoning into image description generation, SceneXplain excels at accurately explaining intricate scenes, surpassing the capabilities of conventional captioning algorithms like CLIP, BLIP, and BLIP2.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-2.png" class="kg-image" alt="" width="2000" height="1111" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/04/image-2.png 2400w" sizes="(min-width: 720px) 720px"></a><figcaption>SceneXplain provides both UI and API for interactions.&nbsp;</figcaption></figure><p>One of the key strengths of SceneXplain lies in its ability to capture the nuances of complex scenes involving multiple objects, interactions, and contextual elements. This enables the generation of detailed and contextually rich textual descriptions that effectively convey the essence of the visual content.</p><p>Additionally, SceneXplain supports multilingual captions, making it a highly versatile tool for content creators, marketers, and developers across the globe. <strong>With its user-friendly interface and API integration, SceneXplain can seamlessly integrate into multimodal applications</strong>, from social media platforms to e-commerce websites.</p><h2 id="benchmarking-scenexplain-against-the-competition">Benchmarking SceneXplain Against the Competition</h2><p>This section will compare SceneXplain's performance against other popular image captioning algorithms and tools. Our goal is to provide a clear understanding of the unique strengths and capabilities that SceneXplain offers in advanced image storytelling. The contenders in our comparison include:</p><ul><li><strong>SceneXplain:</strong> The cutting-edge image captioning solution that leverages the power of large language models like GPT-4 to generate sophisticated, detailed, and contextually rich textual descriptions for complex visual content.</li><li><strong>Midjourney <code>/describe</code> command:</strong> A feature recently released by Midjourney, the /describe command aims to transform images into words, enhancing the linguistic-visual process for both creative power and discovery, as claimed in their tweet.</li></ul><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 297px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1643053450501169157&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fscenexplain-unleash-advanced-image-captioning-storytelling%2F&amp;sessionId=eaa9c5a8a0d135bc0f18064264774e0cd6593a7f&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1643053450501169157"></iframe></div>
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 </figure><ul><li><strong>BLIP2:</strong> A highly efficient pre-training strategy that bootstraps vision-language pre-training using off-the-shelf frozen pre-trained image encoders and frozen large language models, achieving state-of-the-art performance on various vision-language tasks with significantly fewer trainable parameters.</li><li><strong>CLIP Interrogator 2.1:</strong> A specialized tool designed to generate prompts for creating new images, based on existing ones. The CLIP Interrogator utilizes the ViT-H-14 OpenCLIP model and is optimized for use with Stable Diffusion 2.0.</li></ul><p>In the following benchmark, we'll compare the algorithms side-by-side, showcasing their performance in various image captioning tasks. This will help illustrate the advantages of SceneXplain, particularly its ability to explain intricate scenes and deliver superior image storytelling accurately. The full table can be found below.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docs.google.com/spreadsheets/d/1_jNAP0JsvUzEU5CyxUUmckpLWMarFfFGAwuoFrKulsk/edit?ref=jina-ai-gmbh.ghost.io#gid=0"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Benchmark of SceneX, Midjourney, BLIP2, CLIPInterogator2</div><div class="kg-bookmark-description">Sheet1 id,image,SceneX,Midjourney /describe,BLIP2,CLIP Interrogator 2.1tE8WEjOKtuWf7fInIofg,https://storage.googleapis.com/causal-diffusion.appspot.com/imagePrompts%2F0rw369i5h9t%2Foriginal.png,In a heartwarming scene, Totoro and a young girl find themselves caught in the rain. The girl, equipp…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ssl.gstatic.com/docs/spreadsheets/favicon3.ico" alt=""><span class="kg-bookmark-author">Google Docs</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://lh3.googleusercontent.com/docs/AG8NV2Y9qPx5aHrEmBdXb2Ui5U0f2UChayyYkXEJKavdd7zkTHAFi6ye8ZYHSsm5mM-W2t02ah-7HwYVcuDkNBmpxU5K7Xz44WZnSchD9in-F8ns=w1200-h630-p" alt=""></div></a></figure><table class="examples" style="white-space: normal; ">
   <thead class="examples-header">
@@ -1085,4 +1085,4 @@
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 </table>
-<p>After comparing SceneXplain with other popular image captioning algorithms and tools, the following observations can be made:</p><ol><li><strong>SceneXplain: </strong>The results show that SceneXplain consistently captures the most detail and context in its descriptions. It accurately depicts the spatial relationships between objects and characters within the scene. However, there is a minor tendency to hallucinate certain aspects of the scene. This may be attributed to the model's training on a vast amount of data, which enables it to make educated guesses based on similar scenarios it has encountered in the past. Despite this, SceneXplain's performance stands out as the best among the competitors, providing rich and engaging storytelling that brings images to life.</li><li><strong>Midjourney /describe &amp; CLIP Interrogator 2.1:</strong> While both of these tools excel at generating prompts for images, their output is not easily readable as natural language. As a result, they are not suitable for use as image alt tags or accessibility text for visually impaired individuals. Their focus on generating prompts for creative purposes limits their applicability in producing clear and meaningful image descriptions.</li><li><strong>BLIP2:</strong> This algorithm generates short and concise captions, which may be suitable for simple scenes. However, when faced with more complex visual content, the descriptions generated by BLIP2 can be overly simplified, failing to capture the nuances and intricate details that make up the scene. As a result, the captions may not be sufficient for conveying the depth and richness of the images they describe.</li></ol><p>In conclusion, SceneXplain emerges as the most capable image captioning algorithm when it comes to generating accurate, detailed, and contextually rich textual descriptions. Its ability to explain intricate scenes and capture spatial relationships sets it apart from the competition, making it the ideal choice for a wide range of applications, from providing image alt tags for accessibility to enhancing the user experience with engaging visual storytelling. However, <strong>it is essential to acknowledge that SceneXplain may be overkill for simpler scenes where a concise description would suffice.</strong> In such cases, a lighter algorithm like BLIP2 might be more appropriate. Nonetheless, SceneXplain's advanced capabilities and versatility make it a powerful tool for both professional and creative endeavors.</p><h2 id="conclusion">Conclusion</h2><p>In conclusion, SceneXplain offers a revolutionary approach to image captioning, leveraging the power of advanced large language models like GPT-4 to provide highly detailed and contextually rich textual descriptions. We encourage you to explore and experience the remarkable capabilities of SceneXplain for yourself. Its potential applications are vast, but three key areas where it can truly shine are:</p><ol><li><strong>Enhancing accessibility:</strong> By providing comprehensive image descriptions, SceneXplain can improve the web experience for visually impaired users who rely on screen readers and image alt tags to navigate the digital world.</li><li><strong>Boosting SEO:</strong> Detailed and accurate image captions can help search engines better understand your visual content, potentially leading to improved rankings and increased organic traffic to your website.</li><li><strong>Elevating visual storytelling:</strong> SceneXplain's ability to generate vivid and engaging descriptions can add depth and richness to your visual content, transforming ordinary images into immersive storytelling experiences.</li></ol><p>Don't miss out on the opportunity to elevate your visuals with SceneXplain – give it a try and unlock the full potential of your images today!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">SceneXplain: Explore image storytelling beyond pixels</a></div><h2 id="update-used-as-chatgpt-plugin">Update: used as ChatGPT Plugin</h2><p>The plugin is compatible with all SceneXplain plans, but is currently rolling out to users with a <a href="https://openai.com/blog/chatgpt-plus?ref=jina-ai-gmbh.ghost.io" rel="nofollow noopener noreferrer"><u>ChatGPT Plus account</u></a>. <a href="https://openai.com/waitlist/plugins?ref=jina-ai-gmbh.ghost.io" rel="nofollow noopener noreferrer"><strong><strong>Join the waitlist</strong></strong></a> to get access.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/04/scenex-chatgpt-plugin.mp4" poster="https://img.spacergif.org/v1/1280x720/0a/spacer.png" width="1280" height="720" playsinline="" preload="metadata" style="background: transparent 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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+<p>After comparing SceneXplain with other popular image captioning algorithms and tools, the following observations can be made:</p><ol><li><strong>SceneXplain: </strong>The results show that SceneXplain consistently captures the most detail and context in its descriptions. It accurately depicts the spatial relationships between objects and characters within the scene. However, there is a minor tendency to hallucinate certain aspects of the scene. This may be attributed to the model's training on a vast amount of data, which enables it to make educated guesses based on similar scenarios it has encountered in the past. Despite this, SceneXplain's performance stands out as the best among the competitors, providing rich and engaging storytelling that brings images to life.</li><li><strong>Midjourney /describe &amp; CLIP Interrogator 2.1:</strong> While both of these tools excel at generating prompts for images, their output is not easily readable as natural language. As a result, they are not suitable for use as image alt tags or accessibility text for visually impaired individuals. Their focus on generating prompts for creative purposes limits their applicability in producing clear and meaningful image descriptions.</li><li><strong>BLIP2:</strong> This algorithm generates short and concise captions, which may be suitable for simple scenes. However, when faced with more complex visual content, the descriptions generated by BLIP2 can be overly simplified, failing to capture the nuances and intricate details that make up the scene. As a result, the captions may not be sufficient for conveying the depth and richness of the images they describe.</li></ol><p>In conclusion, SceneXplain emerges as the most capable image captioning algorithm when it comes to generating accurate, detailed, and contextually rich textual descriptions. Its ability to explain intricate scenes and capture spatial relationships sets it apart from the competition, making it the ideal choice for a wide range of applications, from providing image alt tags for accessibility to enhancing the user experience with engaging visual storytelling. However, <strong>it is essential to acknowledge that SceneXplain may be overkill for simpler scenes where a concise description would suffice.</strong> In such cases, a lighter algorithm like BLIP2 might be more appropriate. Nonetheless, SceneXplain's advanced capabilities and versatility make it a powerful tool for both professional and creative endeavors.</p><h2 id="conclusion">Conclusion</h2><p>In conclusion, SceneXplain offers a revolutionary approach to image captioning, leveraging the power of advanced large language models like GPT-4 to provide highly detailed and contextually rich textual descriptions. We encourage you to explore and experience the remarkable capabilities of SceneXplain for yourself. Its potential applications are vast, but three key areas where it can truly shine are:</p><ol><li><strong>Enhancing accessibility:</strong> By providing comprehensive image descriptions, SceneXplain can improve the web experience for visually impaired users who rely on screen readers and image alt tags to navigate the digital world.</li><li><strong>Boosting SEO:</strong> Detailed and accurate image captions can help search engines better understand your visual content, potentially leading to improved rankings and increased organic traffic to your website.</li><li><strong>Elevating visual storytelling:</strong> SceneXplain's ability to generate vivid and engaging descriptions can add depth and richness to your visual content, transforming ordinary images into immersive storytelling experiences.</li></ol><p>Don't miss out on the opportunity to elevate your visuals with SceneXplain – give it a try and unlock the full potential of your images today!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">SceneXplain: Explore image storytelling beyond pixels</a></div><h2 id="update-used-as-chatgpt-plugin">Update: used as ChatGPT Plugin</h2><p>The plugin is compatible with all SceneXplain plans, but is currently rolling out to users with a <a href="https://openai.com/blog/chatgpt-plus?ref=jina-ai-gmbh.ghost.io" rel="nofollow noopener noreferrer"><u>ChatGPT Plus account</u></a>. <a href="https://openai.com/waitlist/plugins?ref=jina-ai-gmbh.ghost.io" rel="nofollow noopener noreferrer"><strong><strong>Join the waitlist</strong></strong></a> to get access.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/04/scenex-chatgpt-plugin.mp4" poster="https://img.spacergif.org/v1/1280x720/0a/spacer.png" width="1280" height="720" playsinline="" preload="metadata" style="background: transparent 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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diff --git a/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023/index.html b/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023/index.html
index 5654e5f4fff..694c0d1473d 100644
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+++ b/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</title><meta charset="utf-8"><meta name="title" content="SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?"><meta name="description" content="Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023"><meta property="og:title" content="SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?"><meta property="og:description" content="Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023"><meta property="twitter:title" content="SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?"><meta property="twitter:description" content="Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</title><meta charset="utf-8"><meta name="title" content="SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?"><meta name="description" content="Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. "><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023"><meta property="og:title" content="SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?"><meta property="og:description" content="Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. "><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023"><meta property="twitter:title" content="SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?"><meta property="twitter:description" content="Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. "><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 28, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Hey there, digital explorer! 🚀</p><p>In the ever-evolving landscape of AI, two giants stand out in the realm of visual comprehension: <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a> and <a href="chat.openai.com">GPT-4 Vision</a>. But which one truly reigns supreme? Dive into our comprehensive guide to discover why SceneXplain might just be the game-changer you've been searching for.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://scenexplain.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenexplain.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Try SceneXplain now for free!</span></p></figcaption></figure><h2 id="why-scenexplains-large-multimodal-model-is-the-future"><strong>Why SceneXplain's Large Multimodal Model is the Future</strong></h2><ul><li><strong>Storytelling Beyond Captioning</strong>: While GPT-4 Vision focuses on basic identification, SceneXplain crafts narratives. With Jina AI's next-gen algorithms, it transforms visuals into stories, offering a deeper understanding of the emotion and context behind images.</li><li><strong>User-Friendly for All</strong>: SceneXplain's interface is intuitive for both tech newbies and experts. For the tech-savvy, its robust API integration is a dream come true. Check out its main interface here:</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-30.png" class="kg-image" alt="" width="2000" height="1320" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-30.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-30.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-30.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/09/image-30.png 2400w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">SceneXplain's user-friendly interface for image captioning</span></figcaption></figure><ul><li><strong>Rapid Batch Processing via API</strong>: SceneXplain's scalable API endpoints are a standout. Describe up to 128 images in one batch within just 40 seconds. It's a game-changer for businesses, streamlining integration into applications, websites, or services.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-36.png" class="kg-image" alt="" width="1622" height="802" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-36.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-36.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-36.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-36.png 1622w" sizes="(min-width: 720px) 720px"></figure><h2 id="top-features-making-scenexplain-the-best-image-captioning-tool-in-2023"><strong>Top Features Making SceneXplain the Best Image Captioning Tool in 2023</strong></h2><ul><li><strong>Caption Image</strong>: Your personal storyteller for every image. Curious? </li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-37.png" class="kg-image" alt="" width="1582" height="1564" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-37.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-37.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-37.png 1582w" sizes="(min-width: 720px) 720px"><figcaption><b><strong style="white-space: pre-wrap;">Caption Image with SceneXplain</strong></b></figcaption></figure><ul><li><strong>Extract JSON from Image</strong>: Data enthusiasts, this one's for you! Extract structured data seamlessly. See it in action: </li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-38.png" class="kg-image" alt="" width="822" height="1818" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-38.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-38.png 822w" sizes="(min-width: 720px) 720px"></figure><p>Dive deeper with our in-depth post: </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplains-image-json-extract-structured-data-images-precision/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain’s Image-to-JSON: Extract Structured Data from Images with Precision</div><div class="kg-bookmark-description">Pushing the boundaries of visual AI, we’re thrilled to unveil SceneXplain’s Image-to-JSON feature. Dive into a world where images aren’t just seen, but deeply understood, translating visuals into structured data with unparalleled precision.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--7-.png" alt=""></div></a></figure><ul><li><strong>Visual Q&amp;A</strong>: Got a question about an image? SceneXplain's got answers. Sneak peek: </li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-39.png" class="kg-image" alt="" width="1558" height="1148" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-39.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-39.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-39.png 1558w" sizes="(min-width: 720px) 720px"></figure><p>Learn more about its OCR capabilities in </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/read-my-pics-you-got-ocr-in-my-visual-question-answering/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Read My Pics: SceneXplain Puts OCR in Your Visual Question Answering!</div><div class="kg-bookmark-description">We’re turbocharging SceneXplain’s visual question answering with an OCR upgrade, making it easier than ever to get answers out of your images</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Sentiment-analysis--3-.png" alt=""></div></a></figure><ul><li><strong>Summarize Video</strong>: Get the gist of videos without the time investment. Check this out:</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-40.png" class="kg-image" alt="" width="1602" height="1638" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-40.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-40.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-40.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-40.png 1602w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Using SceneXplain to summarize videos and extract key events</span></figcaption></figure><p>Deep dive: </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/how-scenexplain-solves-video-to-text-comprehension/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">How SceneXplain Solved Video-to-Text Comprehension</div><div class="kg-bookmark-description">Pushing the boundaries of video-to-text comprehension, SceneXplain unveils the Inception algorithm: decoding narratives, acknowledging challenges, and inviting firsthand exploration. Dive into the next frontier of video comprehension.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_Illustration_showing_a_vintage_movie_projector_c_776167b0-0368-4304-bd82-7452c8e5928a.png" alt=""></div></a></figure><ul><li><strong>Generate Story</strong>: Where images inspire stories, dialogues, and more. Get inspired:  </li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-41.png" class="kg-image" alt="" width="1590" height="1798" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-41.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-41.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-41.png 1590w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Using SceneXplain to generate audio story &amp; dialog.</span></figcaption></figure><p>Explore in </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/beyond-pixels-to-prose-scenexplains-hearth-algorithm-breathes-audible-life-into-images/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Beyond Pixels to Prose: SceneXplain’s New Algorithm Breathes Audible Life into Images</div><div class="kg-bookmark-description">Discover the power of SceneXplain’s Hearth Algorithm: turning images into captivating narratives. Dive deep into the tech behind it, explore real-world examples, and grasp its potential. Journey beyond pixels to stories at SceneXplain!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_an_image_of_an_abstract_graph_in_motion_in_the_s_ae1f674c-ac1a-448c-837e-5d2735748e45.png" alt=""></div></a></figure><h2 id="scenexplain-in-action-real-world-impact-across-industries"><strong>SceneXplain in Action: Real-World Impact Across Industries</strong></h2><p>SceneXplain isn't just another tool; it's a transformative solution making waves across industries:</p><h4 id="1-revolutionizing-digital-marketing"><strong>1. Revolutionizing Digital Marketing</strong></h4><p><strong>Sophia</strong>, a Digital Marketing Specialist, leverages SceneXplain to enhance visual content with rich narratives, boosting engagement and SEO efforts. With multilingual support, brands can resonate with a global audience, making campaigns truly international.</p><h4 id="2-streamlining-news-reporting"><strong>2. Streamlining News Reporting</strong></h4><p><strong>James</strong>, Editor-in-Chief of a major news organization, uses SceneXplain to supercharge content creation, enabling journalists to focus on storytelling. It ensures visual content is accessible, making news platforms inclusive for visually impaired readers.</p><h4 id="3-elevating-e-commerce-experiences"><strong>3. Elevating E-commerce Experiences</strong></h4><p><strong>Wang</strong>, an E-commerce Product Manager, harnessed SceneXplain to automate compelling product descriptions from images, enriching the shopping experience and boosting sales.</p><h4 id="4-championing-accessibility"><strong>4. Championing Accessibility</strong></h4><p>The <strong>Accessibility Research Association (ARA)</strong> uses SceneXplain to democratize access to visual content for the blind and visually impaired, ensuring global accessibility law compliance.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</div><div class="kg-bookmark-description">Explore SceneXplain’s impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">World Health Organization</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png" alt=""></div></a></figure><h2 id="exclusive-offer-for-business-users"><strong>Exclusive Offer for Business Users</strong></h2><p>Considering SceneXplain for large-scale enterprise usage? We've got something special for you. Dive deep into SceneXplain's capabilities, features, and enterprise solutions with our exclusive PDF deck tailored for business users.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">👇</div><div class="kg-callout-text"><b><strong style="white-space: pre-wrap;">Download the SceneXplain Enterprise PDF Deck Here</strong></b></div></div><div class="kg-card kg-file-card"><a class="kg-file-card-container" href="https://jina-ai-gmbh.ghost.io/content/files/2023/09/SceneXplain.pdf" title="Download" download=""><div class="kg-file-card-contents"><div class="kg-file-card-title">SceneXplain</div><div class="kg-file-card-caption">The leading image captioning and video summary solution for enterprises</div><div class="kg-file-card-metadata"><div class="kg-file-card-filename">SceneXplain.pdf</div><div class="kg-file-card-filesize">19 MB</div></div></div><div class="kg-file-card-icon"><svg viewBox="0 0 24 24"><defs><style>.a{fill:none;stroke:currentColor;stroke-linecap:round;stroke-linejoin:round;stroke-width:1.5px;}</style></defs><title>download-circle</title><polyline class="a" points="8.25 14.25 12 18 15.75 14.25"></polyline><line class="a" x1="12" y1="6.75" x2="12" y2="18"></line><circle class="a" cx="12" cy="12" r="11.25"></circle></svg></div></a></div><p>This comprehensive guide will provide you with in-depth insights, case studies, and a clear roadmap on how SceneXplain can revolutionize your business's visual comprehension needs.</p><h2 id="conclusion-scenexplainthe-future-of-visual-comprehension"><strong>Conclusion: SceneXplain - The Future of Visual Comprehension</strong></h2><p>From digital marketing to e-commerce, news reporting to accessibility, SceneXplain is redefining boundaries. Its real-world impact is evident, and its potential is limitless. As industries evolve, SceneXplain stands ready to meet the challenges, driving innovation and inclusivity.</p><p><strong>Ready to explore SceneXplain?</strong> Dive in and discover the future of visual comprehension. For more insights, check out our other articles and stay updated on the latest in AI image captioning. </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fscenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/graph-embedding-101-unraveling-the-magic-of-relational-data" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Graph Embedding 101: Unraveling the Magic of Relational Data</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Graphs → everywhere. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 28, 2023 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Hey there, digital explorer! 🚀</p><p>In the ever-evolving landscape of AI, two giants stand out in the realm of visual comprehension: <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a> and <a href="chat.openai.com">GPT-4 Vision</a>. But which one truly reigns supreme? Dive into our comprehensive guide to discover why SceneXplain might just be the game-changer you've been searching for.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://scenexplain.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenexplain.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Try SceneXplain now for free!</span></p></figcaption></figure><h2 id="why-scenexplains-large-multimodal-model-is-the-future"><strong>Why SceneXplain's Large Multimodal Model is the Future</strong></h2><ul><li><strong>Storytelling Beyond Captioning</strong>: While GPT-4 Vision focuses on basic identification, SceneXplain crafts narratives. With Jina AI's next-gen algorithms, it transforms visuals into stories, offering a deeper understanding of the emotion and context behind images.</li><li><strong>User-Friendly for All</strong>: SceneXplain's interface is intuitive for both tech newbies and experts. For the tech-savvy, its robust API integration is a dream come true. Check out its main interface here:</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-30.png" class="kg-image" alt="" width="2000" height="1320" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-30.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-30.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-30.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/09/image-30.png 2400w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">SceneXplain's user-friendly interface for image captioning</span></figcaption></figure><ul><li><strong>Rapid Batch Processing via API</strong>: SceneXplain's scalable API endpoints are a standout. Describe up to 128 images in one batch within just 40 seconds. It's a game-changer for businesses, streamlining integration into applications, websites, or services.</li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-36.png" class="kg-image" alt="" width="1622" height="802" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-36.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-36.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-36.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-36.png 1622w" sizes="(min-width: 720px) 720px"></figure><h2 id="top-features-making-scenexplain-the-best-image-captioning-tool-in-2023"><strong>Top Features Making SceneXplain the Best Image Captioning Tool in 2023</strong></h2><ul><li><strong>Caption Image</strong>: Your personal storyteller for every image. Curious? </li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-37.png" class="kg-image" alt="" width="1582" height="1564" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-37.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-37.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-37.png 1582w" sizes="(min-width: 720px) 720px"><figcaption><b><strong style="white-space: pre-wrap;">Caption Image with SceneXplain</strong></b></figcaption></figure><ul><li><strong>Extract JSON from Image</strong>: Data enthusiasts, this one's for you! Extract structured data seamlessly. See it in action: </li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-38.png" class="kg-image" alt="" width="822" height="1818" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-38.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-38.png 822w" sizes="(min-width: 720px) 720px"></figure><p>Dive deeper with our in-depth post: </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplains-image-json-extract-structured-data-images-precision/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain’s Image-to-JSON: Extract Structured Data from Images with Precision</div><div class="kg-bookmark-description">Pushing the boundaries of visual AI, we’re thrilled to unveil SceneXplain’s Image-to-JSON feature. Dive into a world where images aren’t just seen, but deeply understood, translating visuals into structured data with unparalleled precision.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--7-.png" alt=""></div></a></figure><ul><li><strong>Visual Q&amp;A</strong>: Got a question about an image? SceneXplain's got answers. Sneak peek: </li></ul><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-39.png" class="kg-image" alt="" width="1558" height="1148" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-39.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-39.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-39.png 1558w" sizes="(min-width: 720px) 720px"></figure><p>Learn more about its OCR capabilities in </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/read-my-pics-you-got-ocr-in-my-visual-question-answering/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Read My Pics: SceneXplain Puts OCR in Your Visual Question Answering!</div><div class="kg-bookmark-description">We’re turbocharging SceneXplain’s visual question answering with an OCR upgrade, making it easier than ever to get answers out of your images</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Sentiment-analysis--3-.png" alt=""></div></a></figure><ul><li><strong>Summarize Video</strong>: Get the gist of videos without the time investment. Check this out:</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-40.png" class="kg-image" alt="" width="1602" height="1638" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-40.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-40.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-40.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-40.png 1602w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Using SceneXplain to summarize videos and extract key events</span></figcaption></figure><p>Deep dive: </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/how-scenexplain-solves-video-to-text-comprehension/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">How SceneXplain Solved Video-to-Text Comprehension</div><div class="kg-bookmark-description">Pushing the boundaries of video-to-text comprehension, SceneXplain unveils the Inception algorithm: decoding narratives, acknowledging challenges, and inviting firsthand exploration. Dive into the next frontier of video comprehension.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_Illustration_showing_a_vintage_movie_projector_c_776167b0-0368-4304-bd82-7452c8e5928a.png" alt=""></div></a></figure><ul><li><strong>Generate Story</strong>: Where images inspire stories, dialogues, and more. Get inspired:  </li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-41.png" class="kg-image" alt="" width="1590" height="1798" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-41.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-41.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-41.png 1590w" sizes="(min-width: 720px) 720px"><figcaption><span style="white-space: pre-wrap;">Using SceneXplain to generate audio story &amp; dialog.</span></figcaption></figure><p>Explore in </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/beyond-pixels-to-prose-scenexplains-hearth-algorithm-breathes-audible-life-into-images/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Beyond Pixels to Prose: SceneXplain’s New Algorithm Breathes Audible Life into Images</div><div class="kg-bookmark-description">Discover the power of SceneXplain’s Hearth Algorithm: turning images into captivating narratives. Dive deep into the tech behind it, explore real-world examples, and grasp its potential. Journey beyond pixels to stories at SceneXplain!</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_an_image_of_an_abstract_graph_in_motion_in_the_s_ae1f674c-ac1a-448c-837e-5d2735748e45.png" alt=""></div></a></figure><h2 id="scenexplain-in-action-real-world-impact-across-industries"><strong>SceneXplain in Action: Real-World Impact Across Industries</strong></h2><p>SceneXplain isn't just another tool; it's a transformative solution making waves across industries:</p><h4 id="1-revolutionizing-digital-marketing"><strong>1. Revolutionizing Digital Marketing</strong></h4><p><strong>Sophia</strong>, a Digital Marketing Specialist, leverages SceneXplain to enhance visual content with rich narratives, boosting engagement and SEO efforts. With multilingual support, brands can resonate with a global audience, making campaigns truly international.</p><h4 id="2-streamlining-news-reporting"><strong>2. Streamlining News Reporting</strong></h4><p><strong>James</strong>, Editor-in-Chief of a major news organization, uses SceneXplain to supercharge content creation, enabling journalists to focus on storytelling. It ensures visual content is accessible, making news platforms inclusive for visually impaired readers.</p><h4 id="3-elevating-e-commerce-experiences"><strong>3. Elevating E-commerce Experiences</strong></h4><p><strong>Wang</strong>, an E-commerce Product Manager, harnessed SceneXplain to automate compelling product descriptions from images, enriching the shopping experience and boosting sales.</p><h4 id="4-championing-accessibility"><strong>4. Championing Accessibility</strong></h4><p>The <strong>Accessibility Research Association (ARA)</strong> uses SceneXplain to democratize access to visual content for the blind and visually impaired, ensuring global accessibility law compliance.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/enhancing-digital-accessibility-scenexplain-transforms-multimedia-content-public-sector-organizations/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Enhancing Digital Accessibility: How SceneXplain Transforms Multimedia Content for Public Sector Organizations</div><div class="kg-bookmark-description">Explore SceneXplain’s impact on digital accessibility, providing exceptional image descriptions and ensuring compliance with European standards for public sector organizations.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">World Health Organization</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Jina-AI-Website-Banners-Templates---2023-04-19T150542.636-1.png" alt=""></div></a></figure><h2 id="exclusive-offer-for-business-users"><strong>Exclusive Offer for Business Users</strong></h2><p>Considering SceneXplain for large-scale enterprise usage? We've got something special for you. Dive deep into SceneXplain's capabilities, features, and enterprise solutions with our exclusive PDF deck tailored for business users.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">👇</div><div class="kg-callout-text"><b><strong style="white-space: pre-wrap;">Download the SceneXplain Enterprise PDF Deck Here</strong></b></div></div><div class="kg-card kg-file-card"><a class="kg-file-card-container" href="https://jina-ai-gmbh.ghost.io/content/files/2023/09/SceneXplain.pdf" title="Download" download=""><div class="kg-file-card-contents"><div class="kg-file-card-title">SceneXplain</div><div class="kg-file-card-caption">The leading image captioning and video summary solution for enterprises</div><div class="kg-file-card-metadata"><div class="kg-file-card-filename">SceneXplain.pdf</div><div class="kg-file-card-filesize">19 MB</div></div></div><div class="kg-file-card-icon"><svg viewBox="0 0 24 24"><defs><style>.a{fill:none;stroke:currentColor;stroke-linecap:round;stroke-linejoin:round;stroke-width:1.5px;}</style></defs><title>download-circle</title><polyline class="a" points="8.25 14.25 12 18 15.75 14.25"></polyline><line class="a" x1="12" y1="6.75" x2="12" y2="18"></line><circle class="a" cx="12" cy="12" r="11.25"></circle></svg></div></a></div><p>This comprehensive guide will provide you with in-depth insights, case studies, and a clear roadmap on how SceneXplain can revolutionize your business's visual comprehension needs.</p><h2 id="conclusion-scenexplainthe-future-of-visual-comprehension"><strong>Conclusion: SceneXplain - The Future of Visual Comprehension</strong></h2><p>From digital marketing to e-commerce, news reporting to accessibility, SceneXplain is redefining boundaries. Its real-world impact is evident, and its potential is limitless. As industries evolve, SceneXplain stands ready to meet the challenges, driving innovation and inclusivity.</p><p><strong>Ready to explore SceneXplain?</strong> Dive in and discover the future of visual comprehension. For more insights, check out our other articles and stay updated on the latest in AI image captioning. </p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fscenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/graph-embedding-101-unraveling-the-magic-of-relational-data" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Graph Embedding 101: Unraveling the Magic of Relational Data</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Graphs → everywhere. Social. Knowledge. Molecular. Critical infrastructure. Complex hairy ball visuals. Hard for machines.
 
 Now graph embeddings vectorize nodes. Distill graphs into geometry. Embeddings work magic. AI devours graphs.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 29, 2023 • 10 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_purple_and_green_network_graphs_on_purple_backgr_8f3f4431-5317-4b2e-a2b7-44e206c14b26.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">SceneXplain vs. MiniGPT4: A Comprehensive Benchmark of Top 5 Image Captioning Algorithms for Understanding Complex Scenes</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Uncover the future of image captioning as SceneXplain and its rivals face off in an epic showdown. Explore their impact on accessibility, SEO, and storytelling, and dive into our intriguing results to witness the cutting-edge capabilities of these algorithms.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 80px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/SaZhang.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/492616.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Sa Zhang, Degi</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 19, 2023 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The advent of artificial intelligence has ushered in a new era of multimodal understanding, where image captioning algorithms play a critical role in interpreting and explaining complex visual information. These algorithms have evolved beyond generating simple captions, delving deeper into scene analysis to provide comprehensive descriptions of images. With the growing importance of these technologies in our increasingly connected world, the need for accurate and in-depth image understanding has never been more crucial.</p><p>The widespread use of image captioning technologies in various domains, such as digital accessibility, multimedia content creation, and data analysis, highlights their growing impact on our daily lives. As we venture into this comprehensive assessment, we aim to objectively analyze each algorithm's strengths and weaknesses, enabling you to make informed decisions based on their performance.</p><p>In this blog post, we thoroughly compare the leading image captioning algorithms in the market: SceneX, MiniGPT4, MidJourney <code>/describe</code>, BLIP2, and CLIP interrogator 2.1. Our evaluation focuses on their ability to generate detailed, topical, factual, and readable descriptions for non-trivial images, emphasizing the significance of advanced scene understanding and explanation.</p><h2 id="introducing-the-contenders">Introducing the Contenders</h2><p>This section briefly introduces each of the top image captioning algorithms included in our comparison. These algorithms showcase diverse techniques and approaches to achieve advanced scene understanding and explanation.</p><ul><li><strong>SceneXplain</strong>: A state-of-the-art image captioning solution, SceneXplain harnesses the power of large language models like GPT-4 to generate sophisticated, detailed, and contextually rich textual descriptions for complex visual content. It aims to set the benchmark in the field by providing unparalleled image understanding.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><ul><li><strong>MiniGPT4</strong>: A derivative of the remarkable GPT-4, MiniGPT4 aligns a frozen visual encoder with a frozen large language model (LLM), Vicuna, using a single projection layer. The model boasts many of GPT-4's advanced multi-modal generation capabilities, including detailed image description generation and website creation from hand-written drafts. By curating a high-quality dataset and using a conversational template for fine-tuning, MiniGPT4 addresses issues of unnatural language outputs and enhances the overall usability of the model.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://minigpt-4.github.io/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Minigpt-4</div><div class="kg-bookmark-description">Minigpt-4</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://minigpt-4.github.io/path/to/favicon.ico" alt=""><span class="kg-bookmark-publisher">Deyao Zhu*</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://minigpt-4.github.io/images/overview.png" alt=""></div></a></figure><ul><li><strong>Midjourney <code>/describe</code>:</strong> Recently introduced by Midjourney, the /describe command aims to transform images into prompts, augmenting the linguistic-visual process for both creative power and discovery. This feature is available inside the Midjourney Discord bot by calling <code>/describe</code>.</li></ul><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 297px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1643053450501169157&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fscenexplain-vs-minigpt4-a-comprehensive-benchmark-of-top-5-image-captioning-algorithms-for-understanding-complex-scenes%2F&amp;sessionId=bb243bec50ac345697925903ae78306169bd3562&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1643053450501169157"></iframe></div>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">SceneXplain vs. MiniGPT4: A Comprehensive Benchmark of Top 5 Image Captioning Algorithms for Understanding Complex Scenes</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Uncover the future of image captioning as SceneXplain and its rivals face off in an epic showdown. Explore their impact on accessibility, SEO, and storytelling, and dive into our intriguing results to witness the cutting-edge capabilities of these algorithms.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 80px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.333%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/SaZhang.JPG" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/492616.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Sa Zhang, Degi</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 19, 2023 • 12 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The advent of artificial intelligence has ushered in a new era of multimodal understanding, where image captioning algorithms play a critical role in interpreting and explaining complex visual information. These algorithms have evolved beyond generating simple captions, delving deeper into scene analysis to provide comprehensive descriptions of images. With the growing importance of these technologies in our increasingly connected world, the need for accurate and in-depth image understanding has never been more crucial.</p><p>The widespread use of image captioning technologies in various domains, such as digital accessibility, multimedia content creation, and data analysis, highlights their growing impact on our daily lives. As we venture into this comprehensive assessment, we aim to objectively analyze each algorithm's strengths and weaknesses, enabling you to make informed decisions based on their performance.</p><p>In this blog post, we thoroughly compare the leading image captioning algorithms in the market: SceneX, MiniGPT4, MidJourney <code>/describe</code>, BLIP2, and CLIP interrogator 2.1. Our evaluation focuses on their ability to generate detailed, topical, factual, and readable descriptions for non-trivial images, emphasizing the significance of advanced scene understanding and explanation.</p><h2 id="introducing-the-contenders">Introducing the Contenders</h2><p>This section briefly introduces each of the top image captioning algorithms included in our comparison. These algorithms showcase diverse techniques and approaches to achieve advanced scene understanding and explanation.</p><ul><li><strong>SceneXplain</strong>: A state-of-the-art image captioning solution, SceneXplain harnesses the power of large language models like GPT-4 to generate sophisticated, detailed, and contextually rich textual descriptions for complex visual content. It aims to set the benchmark in the field by providing unparalleled image understanding.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Explore image storytelling beyond pixels</div><div class="kg-bookmark-description">Leverage GPT-4 &amp; LLMs for the most advanced image storytelling. Explain visuals for content creators, media, &amp; e-commerce with rich captions, multilingual support, and seamless API integration. Experience the future of image description today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><ul><li><strong>MiniGPT4</strong>: A derivative of the remarkable GPT-4, MiniGPT4 aligns a frozen visual encoder with a frozen large language model (LLM), Vicuna, using a single projection layer. The model boasts many of GPT-4's advanced multi-modal generation capabilities, including detailed image description generation and website creation from hand-written drafts. By curating a high-quality dataset and using a conversational template for fine-tuning, MiniGPT4 addresses issues of unnatural language outputs and enhances the overall usability of the model.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://minigpt-4.github.io/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Minigpt-4</div><div class="kg-bookmark-description">Minigpt-4</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://minigpt-4.github.io/path/to/favicon.ico" alt=""><span class="kg-bookmark-publisher">Deyao Zhu*</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://minigpt-4.github.io/images/overview.png" alt=""></div></a></figure><ul><li><strong>Midjourney <code>/describe</code>:</strong> Recently introduced by Midjourney, the /describe command aims to transform images into prompts, augmenting the linguistic-visual process for both creative power and discovery. This feature is available inside the Midjourney Discord bot by calling <code>/describe</code>.</li></ul><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 297px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1643053450501169157&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fscenexplain-vs-minigpt4-a-comprehensive-benchmark-of-top-5-image-captioning-algorithms-for-understanding-complex-scenes%2F&amp;sessionId=d5c7cfc0570bbf9646b42be8ef631640228c8caf&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1643053450501169157"></iframe></div>
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 </figure><p><strong>BLIP2:</strong> A groundbreaking pre-training strategy, BLIP2 bootstraps vision-language pre-training using off-the-shelf frozen pre-trained image encoders and frozen large language models. With significantly fewer trainable parameters, BLIP2 achieves state-of-the-art performance on various vision-language tasks, highlighting its efficiency and effectiveness.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://replicate.com/andreasjansson/blip-2?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">andreasjansson/blip-2 –&nbsp;Replicate</div><div class="kg-bookmark-description">Answers questions about images</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://replicate.com/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">🚀 Want to run this model with an API? Get started</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://replicate.delivery/pbxt/IJEPmgAlL2zNBNDoRRKFegTEcxnlRhoQxlNjPHSZEy0pSIKn/gg_bridge.jpeg" alt=""></div></a></figure><p><strong>CLIP Interrogator 2.1:</strong> A specialized tool optimized for use with Stable Diffusion 2.0, the CLIP Interrogator 2.1 is designed to generate prompts for creating new images based on existing ones. Utilizing the ViT-H-14 OpenCLIP model, this algorithm demonstrates the potential for innovation in the image captioning domain.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/spaces/fffiloni/CLIP-Interrogator-2?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">CLIP Interrogator 2 - a Hugging Face Space by fffiloni</div><div class="kg-bookmark-description">Discover amazing ML apps made by the community</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""><span class="kg-bookmark-author">a Hugging Face Space by fffiloni</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/spaces/fffiloni/CLIP-Interrogator-2.png" alt=""></div></a></figure><h2 id="evaluation-metrics">Evaluation Metrics</h2><p>To ensure a fair and comprehensive comparison of the image captioning algorithms, we have selected a set of evaluation metrics that focus on the quality of generated captions.</p><h3 id="details">Details</h3><p>This metric evaluates an algorithm's ability to capture and accurately describe every detail present in a complex scene. By assessing the level of granularity in the generated captions, we can determine how well an algorithm comprehends and conveys intricate visual information.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-26.png" class="kg-image" alt="" width="674" height="428" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-26.png 674w"><figcaption>Check the captions below to understand the "Details" metric better.</figcaption></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Example of the "Details" metric.<br><br><strong>Given by SceneXplain/Comet (Score with 5):</strong> In this whimsical scene, a group of people and animals gather around a table for a delightful tea party. A young girl sits among her peculiar companions, which include a dapper man wearing a hat and bow tie, a cat with an inquisitive expression, and an adorable rabbit adorned with a blue bow tie. The table is laden with tea cups and teapots, adding to the charming atmosphere. This enchanting illustration transports viewers into an imaginative world where humans and anthropomorphic animals come together to enjoy each other's company over steaming cups of tea.<br><br><strong>Given by BLIP2 (Score with 1): </strong>an illustration of alice and the rabbit at a tea party</div></div><h3 id="topicality">Topicality</h3><p>This metric measures an algorithm's ability to recognize and incorporate content related to contemporary events, popular culture, and well-known figures or works in its generated descriptions. Topicality reflects an algorithm's capacity to generate relevant and engaging captions that resonate with the intended audience.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-27.png" class="kg-image" alt="" width="1024" height="512" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-27.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-27.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-27.png 1024w" sizes="(min-width: 720px) 720px"><figcaption>Check the captions below to understand the "Details" metric better.</figcaption></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Example of the "Topicality" metric:<br><br><strong>Given by SceneXplain/Bolt (Score with 5): </strong>In this captivating scene, the Joker and Batman command attention as they engage in a thrilling face-off. The Joker, with his signature grin and a card in hand, faces off against a woman donning a Batman costume. The tension between them is palpable, yet the atmosphere takes an unexpected twist as Batman and Catwoman are found playing cards together. The Bat-Symbol adorns Batman's head, signifying his unwavering dedication to justice. Amidst this intriguing tableau, numerous other characters from DC Comics populate the scene, infusing it with a sense of excitement and intrigue that keeps viewers on the edge of their seats.<br><br><strong>Given by CLIP Interrogator (Score with 1): </strong>a group of comic characters standing next to each other, inspired by Jim Lee, serial art, cats playing poker, kylie jenner as catwoman, header, neal adams | centered</div></div><h3 id="factuality">Factuality</h3><p>Factuality evaluates an algorithm's adherence to reality while generating meaningful and factually correct content. The focus of this metric is to minimize hallucination or the generation of false information in the captions. High factuality scores indicate that an algorithm is able to consistently generate accurate and trustworthy descriptions of the images.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-28.png" class="kg-image" alt="" width="1024" height="682" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-28.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-28.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-28.png 1024w" sizes="(min-width: 720px) 720px"><figcaption>Check the captions below to understand the "Factuality" metric better.</figcaption></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Example of the "Topicality" metric:<br><br><strong>Given by SceneXplain/Dune (Score with 5): </strong>The devastating aftermath of Hurricane Katrina in the Bahamas is captured in this heartrending image. The once-thriving cityscape is now a scene of destruction, with numerous buildings reduced to rubble. An aerial view reveals a damaged bridge and a road marred by the powerful storm. Amidst the wreckage, houses lay in ruins, their once-sturdy structures now mere memories of a time before the hurricane's wrath. In the midst of this desolation, nature encroaches upon the remnants of civilization, with trees and foliage overtaking a house that stands alone in what was once a bustling community. The scene serves as a poignant reminder of the immense power and lasting impact of such natural disasters.<br><br><strong>Given by MiniGPT4 (Score with 1): </strong>This image shows a view of a coastal town with houses and buildings on the shore. The town is surrounded by water and there are boats in the water. The houses are made of wood and have a thatched roof. The town is surrounded by trees and there are no people in sight. The sky is clear and there are no clouds. The image is taken from a high altitude and shows the entire town.</div></div><h3 id="perplexity"><a href="https://huggingface.co/docs/transformers/perplexity?ref=jina-ai-gmbh.ghost.io#perplexity-of-fixedlength-models">Perplexity</a></h3><p>Correlated to readability, perplexity is a measure of how easy the generated text is to understand. Lower perplexity scores indicate that the text is more coherent and comprehensible, ensuring that users can quickly grasp the meaning behind the captions. This metric allows us to gauge the overall user experience provided by each algorithm in terms of readability.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/ppl_sliding.gif" class="kg-image" alt="" width="1200" height="160" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/ppl_sliding.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/ppl_sliding.gif 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/04/ppl_sliding.gif 1200w" sizes="(min-width: 720px) 720px"><figcaption>We will use GPT-2 as the language model and evaluate the perplexity of a sentence with a sliding-window strategy. This involves repeatedly sliding the context window so the model has more context when making each prediction.</figcaption></figure><p>It is important to note that we have chosen <em>not</em> to include speed as a metric in our evaluation, as it can be heavily influenced by factors such as GPU and infrastructure, which are outside the scope of our comparison. Our focus remains on the quality of the generated captions and their ability to provide advanced scene understanding and explanation.</p><p>To ensure an objective comparison of the performance of each image captioning algorithm across our chosen evaluation metrics, we have implemented a standardized scoring system, employing the expertise of external human labelers. These labelers, who are well-versed in the field of image captioning and scene understanding, were invited to independently assess the algorithms' performance. For each of the four metrics - Details, Topicality, Factuality, and Perplexity - the labelers assigned a score on a scale of 1 to 5, with 1 being the lowest and 5 being the highest. This approach guarantees that the scores are not only consistent across the various metrics but also free from any potential biases, ensuring a fair and reliable evaluation of the competing algorithms.</p><h2 id="in-depth-analysis-of-experimental-results">In-Depth Analysis of Experimental Results</h2><p>In order to evaluate the image captioning algorithms on a diverse and challenging set of images, we carefully selected a collection of 33 non-trivial, complicated images that encompass a wide range of styles, such as real-world scenes, artificial creations, oil paintings, photographs, and cartoons. This diverse dataset ensures that the algorithms are thoroughly tested on their ability to generate comprehensive descriptions for various types of visual content.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://scenex.jina.ai/benchmark?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/image-30.png" class="kg-image" alt="" width="2000" height="1125" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/04/image-30.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/04/image-30.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/04/image-30.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/04/image-30.png 2400w" sizes="(min-width: 720px) 720px"></a><figcaption>Test images used for evaluation</figcaption></figure><p>We have compiled the full results of our evaluation, including the captions generated by each algorithm, in a publicly accessible Google Spreadsheet. This detailed document allows interested readers to delve deeper into the performance of each algorithm and observe their image captioning abilities firsthand.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://docs.google.com/spreadsheets/d/1_jNAP0JsvUzEU5CyxUUmckpLWMarFfFGAwuoFrKulsk/edit?usp=sharing&amp;ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Benchmark of SceneX, Midjourney, BLIP2, CLIPInterogator2, MiniGPT-4</div><div class="kg-bookmark-description">Captions id,image url,image,SceneX - Aqua,SceneX - Bolt,SceneX - Comet,SceneX - Dune,Midjourney /describe,CLIP Interrogator 2.1,BLIP2,MiniGPT-4tE8WEjOKtuWf7fInIofg,https://storage.googleapis.com/causal-diffusion.appspot.com/imagePrompts%2F0rw369i5h9t%2Foriginal.png,In a whimsical and enchanting…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://ssl.gstatic.com/docs/spreadsheets/favicon3.ico" alt=""><span class="kg-bookmark-author">Google Docs</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://lh3.googleusercontent.com/docs/ADP-6oFreqcqVEfE81oMvHATugCfPbguQqJ7FVgEoezvhFrMmWNRvssgvUvCEqkAtEpuQvjqPnwiaaCuKuHLRhgrwUXumaU_VafQYpuUYZumFXuy=w1200-h630-p" alt=""></div></a><figcaption>Note that the copyrights for the images used in our evaluation belong to their respective original creators. We encourage you to explore the Google Spreadsheet linked below to gain a better understanding of the capabilities of these cutting-edge image captioning algorithms and to draw your own conclusions from their generated descriptions.</figcaption></figure><p>After evaluating each image captioning algorithm using the metrics discussed earlier, we have compiled the results in the following table:</p><table>
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>SceneXplain's Image-to-JSON: Extract Structured Data from Images with Precision</title><meta charset="utf-8"><meta name="title" content="SceneXplain's Image-to-JSON: Extract Structured Data from Images with Precision"><meta name="description" content="Pushing the boundaries of visual AI, we're thrilled to unveil SceneXplain's Image-to-JSON feature. Dive into a world where images aren't just seen, but deeply understood, translating visuals into structured data with unparalleled precision."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/scenexplains-image-json-extract-structured-data-images-precision"><meta property="og:title" content="SceneXplain's Image-to-JSON: Extract Structured Data from Images with Precision"><meta property="og:description" content="Pushing the boundaries of visual AI, we're thrilled to unveil SceneXplain's Image-to-JSON feature. Dive into a world where images aren't just seen, but deeply understood, translating visuals into structured data with unparalleled precision."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--7-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/scenexplains-image-json-extract-structured-data-images-precision"><meta property="twitter:title" content="SceneXplain's Image-to-JSON: Extract Structured Data from Images with Precision"><meta property="twitter:description" content="Pushing the boundaries of visual AI, we're thrilled to unveil SceneXplain's Image-to-JSON feature. Dive into a world where images aren't just seen, but deeply understood, translating visuals into structured data with unparalleled precision."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--7-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">SceneXplain's Image-to-JSON: Extract Structured Data from Images with Precision</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Pushing the boundaries of visual AI, we're thrilled to unveil SceneXplain's Image-to-JSON feature. Dive into a world where images aren't just seen, but deeply understood, translating visuals into structured data with unparalleled precision.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 14, 2023 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the ever-evolving world of multimodal AI and computer vision, <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a> consistently pushes the boundaries. Today, we're thrilled to introduce a feature that promises to redefine the landscape of image captioning: <strong>Image-to-JSON</strong>. Let's delve into this innovation and understand its transformative potential.</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/09/scenexplain-json.mp4" poster="https://img.spacergif.org/v1/1422x962/0a/spacer.png" width="1422" height="962" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/09/media-thumbnail-ember329.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>A demo of SceneXplain's new image-to-JSON feature</figcaption></figure><h2 id="scenexplains-image-captioning-ability">SceneXplain's Image Captioning Ability</h2><p>SceneXplain stands as a beacon in advanced image captioning and video summarization. Thanks to Jina AI's state-of-the-art multimodal algorithms, SceneXplain transcends traditional captioning, offering rich textual narratives from visuals. With an intuitive interface and a robust API, it's designed for both seasoned users and developers.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><h2 id="understanding-json-schema">Understanding JSON Schema</h2><p>Before delving into the Image-to-JSON feature, it's essential to understand JSON Schema. </p><p>JSON Schema is a vocabulary that allows you to annotate and validate JSON documents. Think of it as a blueprint for the structure of your JSON data. It defines the shape of your data, types of data values, and even the range of permissible values. <strong>With JSON Schema, you can tailor the data extraction process to your specific needs.</strong></p><table border="0" cellpadding="10" cellspacing="0">
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Pushing the boundaries of visual AI, we're thrilled to unveil SceneXplain's Image-to-JSON feature. Dive into a world where images aren't just seen, but deeply understood, translating visuals into structured data with unparalleled precision.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">September 14, 2023 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the ever-evolving world of multimodal AI and computer vision, <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a> consistently pushes the boundaries. Today, we're thrilled to introduce a feature that promises to redefine the landscape of image captioning: <strong>Image-to-JSON</strong>. Let's delve into this innovation and understand its transformative potential.</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/09/scenexplain-json.mp4" poster="https://img.spacergif.org/v1/1422x962/0a/spacer.png" width="1422" height="962" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/09/media-thumbnail-ember329.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>A demo of SceneXplain's new image-to-JSON feature</figcaption></figure><h2 id="scenexplains-image-captioning-ability">SceneXplain's Image Captioning Ability</h2><p>SceneXplain stands as a beacon in advanced image captioning and video summarization. Thanks to Jina AI's state-of-the-art multimodal algorithms, SceneXplain transcends traditional captioning, offering rich textual narratives from visuals. With an intuitive interface and a robust API, it's designed for both seasoned users and developers.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><h2 id="understanding-json-schema">Understanding JSON Schema</h2><p>Before delving into the Image-to-JSON feature, it's essential to understand JSON Schema. </p><p>JSON Schema is a vocabulary that allows you to annotate and validate JSON documents. Think of it as a blueprint for the structure of your JSON data. It defines the shape of your data, types of data values, and even the range of permissible values. <strong>With JSON Schema, you can tailor the data extraction process to your specific needs.</strong></p><table border="0" cellpadding="10" cellspacing="0">
     <thead>
         <tr>
             <th>a JSON file</th>
@@ -60,44 +60,44 @@
             </td>
         </tr>
     </tbody>
-</table><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://json-schema.org/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">JSON Schema</div><div class="kg-bookmark-description">The home of JSON Schema</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://json-schema.org/favicon.ico" alt=""><span class="kg-bookmark-author">JSON Schema</span><span class="kg-bookmark-publisher">JSON Schema</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://json-schema.org/assets/logo-slack.svg" alt=""></div></a></figure><h2 id="the-image-to-json-revolution">The Image-to-JSON Revolution</h2><p>In traditional image captioning, the process has been linear: input an image and receive a text description. This approach, while effective, lacked the flexibility to extract specific data or focus on particular areas within an image. Enter SceneXplain's Image-to-JSON feature, our innovative solution to these limitations.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/mermaid-diagram-2023-09-14-132512.svg" class="kg-image" alt="" width="300" height="94"></figure><p>With Image-to-JSON, users upload an image and accompany it with a custom JSON Schema. The result? A structured JSON output tailored to capture specific information, whether it's in enums, lists, strings, booleans, or numbers.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-22.png" class="kg-image" alt="" width="500" height="750"><figcaption>The image we used in SceneXplain on three different tasks: <a href="https://scenex.jina.ai/share?thread=YAcPQYjYXhP4wU6mw7vn&amp;ref=jina-ai-gmbh.ghost.io">image captioning</a>; <a href="https://scenex.jina.ai/share?thread=tW1LPU0CemEXVvNgOuhm&amp;ref=jina-ai-gmbh.ghost.io">visual question answering</a>; <a href="https://scenex.jina.ai/share?thread=MGXZbSJH2lSDUmfBHnZY&amp;ref=jina-ai-gmbh.ghost.io">Image-to-JSON</a>. Results can be found below.</figcaption></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.12009 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-3.png" width="1026" height="916" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Untitled-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/Untitled-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-3.png 1026w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.84477 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-4.png" width="1022" height="554" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Untitled-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/Untitled-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-4.png 1022w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: <a href="https://scenex.jina.ai/share?thread=YAcPQYjYXhP4wU6mw7vn&amp;ref=jina-ai-gmbh.ghost.io">image captioning</a>; Center: <a href="https://scenex.jina.ai/share?thread=tW1LPU0CemEXVvNgOuhm&amp;ref=jina-ai-gmbh.ghost.io">visual question answering</a></figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-28.png" class="kg-image" alt="" width="1000" height="1917" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-28.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-28.png 1000w" sizes="(min-width: 720px) 720px"><figcaption><a href="https://scenex.jina.ai/share?thread=MGXZbSJH2lSDUmfBHnZY&amp;ref=jina-ai-gmbh.ghost.io">Image-to-JSON</a></figcaption></figure><h4 id="from-prompting-to-structured-outputs">From Prompting to Structured Outputs</h4><p>The concept of prompting, popularized by large language models (LLMs), involves guiding AI responses using specific questions or instructions. For example, prompting an LLM with "Describe the Eiffel Tower" yields a textual description. However, this output, while informative, is unstructured.</p><p>Image-to-JSON takes prompting to the next level. The <code>description</code> field in the JSON schema serves as an advanced prompt. Instead of just a textual response, SceneXplain processes the image and structures its output based on the provided schema. This ensures not just relevance but also precision and consistency in the format.</p><p>This structured approach is especially crucial for applications that demand consistent data formats. While free-form text outputs offer flexibility, they can be challenging to integrate into systems that require structured data. Image-to-JSON bridges this gap, combining the adaptability of prompting with the reliability of structured outputs.</p><p>In essence, SceneXplain's Image-to-JSON is a testament to the evolution of AI comprehension. It showcases how AI can be both versatile in understanding visuals and precise in delivering structured, actionable data.</p><h2 id="how-to-use-image-to-json-in-scenexplain">How to Use Image-to-JSON in SceneXplain</h2><p>To harness this feature, users need to upload their image and define a corresponding JSON schema. To do this, click the dropdown button on the right of the input box and then select "Add JSON Schema".</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-23.png" class="kg-image" alt="" width="2000" height="927" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-23.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-23.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-23.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/09/image-23.png 2400w" sizes="(min-width: 1200px) 1200px"></figure><p>This schema comprises key-value pairs, with two essential keys:</p><ul><li><strong><code>type</code></strong>: This determines the result format, such as string, list, boolean, etc.</li><li><strong><code>description</code></strong>: This serves as a prompt, guiding the kind of information to extract from the image.</li></ul><p>Let's explore this with increasingly complex examples:</p><p><strong>Basic Inventory Check</strong>:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
-  <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"object"</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-attr">"properties"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-    <span class="hljs-attr">"brands"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-      <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"list"</span><span class="hljs-punctuation">,</span>
-      <span class="hljs-attr">"description"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"Identify brands on the shelf."</span>
-    <span class="hljs-punctuation">}</span>
-  <span class="hljs-punctuation">}</span>
-<span class="hljs-punctuation">}</span>
-</code></pre><p><strong>Season Identification</strong>:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
-  <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"object"</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-attr">"properties"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-    <span class="hljs-attr">"season"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-      <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"string"</span><span class="hljs-punctuation">,</span>
-      <span class="hljs-attr">"enum"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span><span class="hljs-string">"Spring"</span><span class="hljs-punctuation">,</span> <span class="hljs-string">"Summer"</span><span class="hljs-punctuation">,</span> <span class="hljs-string">"Autumn"</span><span class="hljs-punctuation">,</span> <span class="hljs-string">"Winter"</span><span class="hljs-punctuation">]</span><span class="hljs-punctuation">,</span>
-      <span class="hljs-attr">"description"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"Determine the predominant season in the image."</span>
-    <span class="hljs-punctuation">}</span>
-  <span class="hljs-punctuation">}</span>
-<span class="hljs-punctuation">}</span>
-</code></pre><p><strong>Detailed Landscape Analysis</strong>:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
-  <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"object"</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-attr">"properties"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-    <span class="hljs-attr">"flora"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-      <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"list"</span><span class="hljs-punctuation">,</span>
-      <span class="hljs-attr">"description"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"List all visible plant species."</span>
-    <span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-attr">"fauna"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-      <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"list"</span><span class="hljs-punctuation">,</span>
-      <span class="hljs-attr">"description"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"List all visible animal species."</span>
-    <span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-attr">"timeOfDay"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-      <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"string"</span><span class="hljs-punctuation">,</span>
-      <span class="hljs-attr">"enum"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span><span class="hljs-string">"Morning"</span><span class="hljs-punctuation">,</span> <span class="hljs-string">"Afternoon"</span><span class="hljs-punctuation">,</span> <span class="hljs-string">"Evening"</span><span class="hljs-punctuation">,</span> <span class="hljs-string">"Night"</span><span class="hljs-punctuation">]</span><span class="hljs-punctuation">,</span>
-      <span class="hljs-attr">"description"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"Identify the time of day."</span>
-    <span class="hljs-punctuation">}</span>
-  <span class="hljs-punctuation">}</span>
-<span class="hljs-punctuation">}</span>
-</code></pre><h3 id="some-examples">Some Examples</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-24.png" class="kg-image" alt="" width="822" height="1818" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-24.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-24.png 822w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-25.png" class="kg-image" alt="" width="816" height="1848" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-25.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-25.png 816w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-26.png" class="kg-image" alt="" width="912" height="1682" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-26.png 912w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-27.png" class="kg-image" alt="" width="748" height="1630" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-27.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-27.png 748w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.320253 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-8.png" width="506" height="1580" alt=""></div><div class="kg-gallery-image" style="flex: 0.325611 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-7.png" width="506" height="1554" alt=""></div><div class="kg-gallery-image" style="flex: 0.320562 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-6.png" width="502" height="1566" alt=""></div></div></div><figcaption>One can also use Image-to-JSON as an advanced OCR solution</figcaption></figure><h2 id="real-world-applications-and-api-integration">Real-World Applications and API Integration</h2><p>Beyond the user interface, this feature can be seamlessly integrated into systems via our API. For developers looking to harness the power of Image-to-JSON programmatically, our <a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io">API documentation</a> provides comprehensive guidance.</p><figure class="kg-card kg-image-card"><a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-21.png" class="kg-image" alt="" width="2000" height="1634" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-21.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-21.png 2242w" sizes="(min-width: 720px) 720px"></a></figure><h2 id="image-to-json-vs-vqa-image-captioning">Image-to-JSON vs. VQA &amp; Image Captioning</h2><p>The table below provides a clear comparison between SceneXplain's Image-to-JSON, Visual Question Answering (VQA), Traditional Image Captioning, and the Good-Old OCR based on various features.</p><table>
+</table><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://json-schema.org/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">JSON Schema</div><div class="kg-bookmark-description">The home of JSON Schema</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://json-schema.org/favicon.ico" alt=""><span class="kg-bookmark-author">JSON Schema</span><span class="kg-bookmark-publisher">JSON Schema</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://json-schema.org/assets/logo-slack.svg" alt=""></div></a></figure><h2 id="the-image-to-json-revolution">The Image-to-JSON Revolution</h2><p>In traditional image captioning, the process has been linear: input an image and receive a text description. This approach, while effective, lacked the flexibility to extract specific data or focus on particular areas within an image. Enter SceneXplain's Image-to-JSON feature, our innovative solution to these limitations.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/mermaid-diagram-2023-09-14-132512.svg" class="kg-image" alt="" width="300" height="94"></figure><p>With Image-to-JSON, users upload an image and accompany it with a custom JSON Schema. The result? A structured JSON output tailored to capture specific information, whether it's in enums, lists, strings, booleans, or numbers.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-22.png" class="kg-image" alt="" width="500" height="750"><figcaption>The image we used in SceneXplain on three different tasks: <a href="https://scenex.jina.ai/share?thread=YAcPQYjYXhP4wU6mw7vn&amp;ref=jina-ai-gmbh.ghost.io">image captioning</a>; <a href="https://scenex.jina.ai/share?thread=tW1LPU0CemEXVvNgOuhm&amp;ref=jina-ai-gmbh.ghost.io">visual question answering</a>; <a href="https://scenex.jina.ai/share?thread=MGXZbSJH2lSDUmfBHnZY&amp;ref=jina-ai-gmbh.ghost.io">Image-to-JSON</a>. Results can be found below.</figcaption></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-3.png" width="1026" height="916" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Untitled-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/Untitled-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-3.png 1026w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-4.png" width="1022" height="554" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/Untitled-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/Untitled-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-4.png 1022w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Left: <a href="https://scenex.jina.ai/share?thread=YAcPQYjYXhP4wU6mw7vn&amp;ref=jina-ai-gmbh.ghost.io">image captioning</a>; Center: <a href="https://scenex.jina.ai/share?thread=tW1LPU0CemEXVvNgOuhm&amp;ref=jina-ai-gmbh.ghost.io">visual question answering</a></figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-28.png" class="kg-image" alt="" width="1000" height="1917" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-28.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-28.png 1000w" sizes="(min-width: 720px) 720px"><figcaption><a href="https://scenex.jina.ai/share?thread=MGXZbSJH2lSDUmfBHnZY&amp;ref=jina-ai-gmbh.ghost.io">Image-to-JSON</a></figcaption></figure><h4 id="from-prompting-to-structured-outputs">From Prompting to Structured Outputs</h4><p>The concept of prompting, popularized by large language models (LLMs), involves guiding AI responses using specific questions or instructions. For example, prompting an LLM with "Describe the Eiffel Tower" yields a textual description. However, this output, while informative, is unstructured.</p><p>Image-to-JSON takes prompting to the next level. The <code>description</code> field in the JSON schema serves as an advanced prompt. Instead of just a textual response, SceneXplain processes the image and structures its output based on the provided schema. This ensures not just relevance but also precision and consistency in the format.</p><p>This structured approach is especially crucial for applications that demand consistent data formats. While free-form text outputs offer flexibility, they can be challenging to integrate into systems that require structured data. Image-to-JSON bridges this gap, combining the adaptability of prompting with the reliability of structured outputs.</p><p>In essence, SceneXplain's Image-to-JSON is a testament to the evolution of AI comprehension. It showcases how AI can be both versatile in understanding visuals and precise in delivering structured, actionable data.</p><h2 id="how-to-use-image-to-json-in-scenexplain">How to Use Image-to-JSON in SceneXplain</h2><p>To harness this feature, users need to upload their image and define a corresponding JSON schema. To do this, click the dropdown button on the right of the input box and then select "Add JSON Schema".</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-23.png" class="kg-image" alt="" width="2000" height="927" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-23.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-23.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-23.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/09/image-23.png 2400w" sizes="(min-width: 1200px) 1200px"></figure><p>This schema comprises key-value pairs, with two essential keys:</p><ul><li><strong><code>type</code></strong>: This determines the result format, such as string, list, boolean, etc.</li><li><strong><code>description</code></strong>: This serves as a prompt, guiding the kind of information to extract from the image.</li></ul><p>Let's explore this with increasingly complex examples:</p><p><strong>Basic Inventory Check</strong>:</p><pre><code class="language-json">{
+  "type": "object",
+  "properties": {
+    "brands": {
+      "type": "list",
+      "description": "Identify brands on the shelf."
+    }
+  }
+}
+</code></pre><p><strong>Season Identification</strong>:</p><pre><code class="language-json">{
+  "type": "object",
+  "properties": {
+    "season": {
+      "type": "string",
+      "enum": ["Spring", "Summer", "Autumn", "Winter"],
+      "description": "Determine the predominant season in the image."
+    }
+  }
+}
+</code></pre><p><strong>Detailed Landscape Analysis</strong>:</p><pre><code class="language-json">{
+  "type": "object",
+  "properties": {
+    "flora": {
+      "type": "list",
+      "description": "List all visible plant species."
+    },
+    "fauna": {
+      "type": "list",
+      "description": "List all visible animal species."
+    },
+    "timeOfDay": {
+      "type": "string",
+      "enum": ["Morning", "Afternoon", "Evening", "Night"],
+      "description": "Identify the time of day."
+    }
+  }
+}
+</code></pre><h3 id="some-examples">Some Examples</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-24.png" class="kg-image" alt="" width="822" height="1818" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-24.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-24.png 822w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-25.png" class="kg-image" alt="" width="816" height="1848" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-25.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-25.png 816w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-26.png" class="kg-image" alt="" width="912" height="1682" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-26.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-26.png 912w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-27.png" class="kg-image" alt="" width="748" height="1630" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-27.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-27.png 748w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-8.png" width="506" height="1580" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-7.png" width="506" height="1554" alt=""></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Untitled-6.png" width="502" height="1566" alt=""></div></div></div><figcaption>One can also use Image-to-JSON as an advanced OCR solution</figcaption></figure><h2 id="real-world-applications-and-api-integration">Real-World Applications and API Integration</h2><p>Beyond the user interface, this feature can be seamlessly integrated into systems via our API. For developers looking to harness the power of Image-to-JSON programmatically, our <a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io">API documentation</a> provides comprehensive guidance.</p><figure class="kg-card kg-image-card"><a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-21.png" class="kg-image" alt="" width="2000" height="1634" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/09/image-21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/09/image-21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/09/image-21.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/09/image-21.png 2242w" sizes="(min-width: 720px) 720px"></a></figure><h2 id="image-to-json-vs-vqa-image-captioning">Image-to-JSON vs. VQA &amp; Image Captioning</h2><p>The table below provides a clear comparison between SceneXplain's Image-to-JSON, Visual Question Answering (VQA), Traditional Image Captioning, and the Good-Old OCR based on various features.</p><table>
 <thead>
 <tr>
 <th>Task</th>
@@ -159,4 +159,4 @@
 </tr>
 </tbody>
 </table>
-<h2 id="in-conclusion">In Conclusion</h2><p>SceneXplain's Image-to-JSON isn't just an incremental improvement; it's a monumental leap. By offering unparalleled flexibility and precision, we're empowering users to extract the exact insights they seek from images. As we continue our innovation journey, we eagerly await the myriad ways you'll employ this feature to redefine visual comprehension.</p><p>Stay connected for more groundbreaking updates from SceneXplain!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fscenexplains-image-json-extract-structured-data-images-precision%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<h2 id="in-conclusion">In Conclusion</h2><p>SceneXplain's Image-to-JSON isn't just an incremental improvement; it's a monumental leap. By offering unparalleled flexibility and precision, we're empowering users to extract the exact insights they seek from images. 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\ No newline at end of file
diff --git a/news/scenexplains-json-schema-store-automate-your-alt-text-and-more/index.html b/news/scenexplains-json-schema-store-automate-your-alt-text-and-more/index.html
index fad66d9461f..2cdba0b0970 100644
--- a/news/scenexplains-json-schema-store-automate-your-alt-text-and-more/index.html
+++ b/news/scenexplains-json-schema-store-automate-your-alt-text-and-more/index.html
@@ -1,6 +1,6 @@
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>SceneXplain's JSON Schema Store: Automate Your Alt-Text, and More!</title><meta charset="utf-8"><meta name="title" content="SceneXplain's JSON Schema Store: Automate Your Alt-Text, and More!"><meta name="description" content="Take the hassle out of extracting data from images with SceneXplain's new JSON Schema Store. Discover and share reusable JSON schemas. Create, contribute, and access schemas easily through GUI or API"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/scenexplains-json-schema-store-automate-your-alt-text-and-more"><meta property="og:title" content="SceneXplain's JSON Schema Store: Automate Your Alt-Text, and More!"><meta property="og:description" content="Take the hassle out of extracting data from images with SceneXplain's new JSON Schema Store. Discover and share reusable JSON schemas. Create, contribute, and access schemas easily through GUI or API"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/cover2-1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/scenexplains-json-schema-store-automate-your-alt-text-and-more"><meta property="twitter:title" content="SceneXplain's JSON Schema Store: Automate Your Alt-Text, and More!"><meta property="twitter:description" content="Take the hassle out of extracting data from images with SceneXplain's new JSON Schema Store. Discover and share reusable JSON schemas. Create, contribute, and access schemas easily through GUI or API"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/11/cover2-1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">SceneXplain's JSON Schema Store: Automate Your Alt-Text, and More!</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Take the hassle out of extracting data from images with SceneXplain's new JSON Schema Store. Discover and share reusable JSON schemas. Create, contribute, and access schemas easily through GUI or API</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 27, 2023 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>We're starting to run low on phrases like "we're happy to announce x", or "announcing x" every time we push out a new feature in SceneXplain. So let's just jump to the meat: SceneXplain has a new JSON Schema Store, where you can discover and share reusable JSON schemas. This builds on our recent "extract JSON from image" feature, which lets you specify a JSON Schema when uploading an image, and get information back in JSON that adheres to that schema.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplains-image-json-extract-structured-data-images-precision/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain’s Image-to-JSON: Extract Structured Data from Images with Precision</div><div class="kg-bookmark-description">Pushing the boundaries of visual AI, we’re thrilled to unveil SceneXplain’s Image-to-JSON feature. Dive into a world where images aren’t just seen, but deeply understood, translating visuals into structured data with unparalleled precision.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--7-.png" alt=""></div></a></figure><h2 id="what-is-a-json-schema">What is a JSON Schema?</h2><p>According to the <a href="https://json-schema.org/learn/getting-started-step-by-step?ref=jina-ai-gmbh.ghost.io">official website</a>, JSON Schema is a vocabulary that you can use to annotate and validate JSON documents. With SceneXplain, you can upload a schema like:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="94f90116-d4fb-4696-bb6a-4b82dafaf68d" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="94f90116-d4fb-4696-bb6a-4b82dafaf68d" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">SceneXplain's JSON Schema Store: Automate Your Alt-Text, and More!</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Take the hassle out of extracting data from images with SceneXplain's new JSON Schema Store. Discover and share reusable JSON schemas. Create, contribute, and access schemas easily through GUI or API</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 27, 2023 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>We're starting to run low on phrases like "we're happy to announce x", or "announcing x" every time we push out a new feature in SceneXplain. So let's just jump to the meat: SceneXplain has a new JSON Schema Store, where you can discover and share reusable JSON schemas. This builds on our recent "extract JSON from image" feature, which lets you specify a JSON Schema when uploading an image, and get information back in JSON that adheres to that schema.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplains-image-json-extract-structured-data-images-precision/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain’s Image-to-JSON: Extract Structured Data from Images with Precision</div><div class="kg-bookmark-description">Pushing the boundaries of visual AI, we’re thrilled to unveil SceneXplain’s Image-to-JSON feature. Dive into a world where images aren’t just seen, but deeply understood, translating visuals into structured data with unparalleled precision.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--7-.png" alt=""></div></a></figure><h2 id="what-is-a-json-schema">What is a JSON Schema?</h2><p>According to the <a href="https://json-schema.org/learn/getting-started-step-by-step?ref=jina-ai-gmbh.ghost.io">official website</a>, JSON Schema is a vocabulary that you can use to annotate and validate JSON documents. With SceneXplain, you can upload a schema like:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
   <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"object"</span><span class="hljs-punctuation">,</span>
   <span class="hljs-attr">"properties"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
     <span class="hljs-attr">"alt_tag"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">SceneXplain's OCR beats GPT-4V hands down: Chinese, Japanese, Korean, Arabic, Hindi, and more!</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">SceneXplain beats GPT-4V by going beyond English, offering multilingual OCR for Chinese, Japanese, Korean, Arabic, Hindi and more</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 16, 2023 • 13 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>There's been a lot of noise recently about the release of GPT-4V - a model that can analyze the content of images and summarize that into human language. Sound familiar? It may, because SceneXplain has been doing just that for months already!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><p>But just because you take an early lead doesn't mean you win the race. We've got to show how we're better, right? Well, we've already done that in <a href="https://jina.ai/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023/?ref=jina-ai-gmbh.ghost.io">this post</a>:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="kg-bookmark-description">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" alt=""></div></a></figure><p>But in this post, we'll go one further and show you how we excel at OCR for multilingual texts. In short, <strong>SceneXplain is more accurate, reliable, consistent, complete, and cost-effective than GPT-4V</strong>. Also, it doesn’t have any pesky daily request limits.</p><p>You might think GPT-4V is pretty decent if you’re a user of Latin-character languages. Since you’re reading this (I assume in English), that means you!</p><p>Indeed, GPT-4V does okay when it comes to recognizing English, French, Spanish, and so on, as you can see from these blog posts and studies:</p><ul><li><a href="https://blog.roboflow.com/gpt-4-vision/?ref=jina-ai-gmbh.ghost.io">First Impressions with GPT-4V(ision)</a></li><li><a href="https://arxiv.org/abs/2310.16809?ref=jina-ai-gmbh.ghost.io">Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation</a></li></ul><p>But, as mentioned in the study:</p><blockquote class="kg-blockquote-alt">There is a substantial accuracy disparity between the recognition of English and Chinese text. As shown in Table 1, the performance of English text recognition is commendable. Conversely, the accuracy of Chinese text recognition is zero (ReCTS). We speculate that this may be due to the lack of Chinese scene text images as training data in GPT-4V.</blockquote><p>Bad news - it's not just Chinese where GPT-4V falls down. It consistently fails on non-Latin texts.</p><p>That's where SceneXplain comes in. We go way beyond just recognizing Latin characters - we can do Chinese, Japanese, Korean, Arabic, Hindi, and potentially more (at this point we ran out of languages that people speak (or recognize) at Jina AI.)</p><h2 id="tldr-how-does-gpt-4v-fail-compared-to-scenexplain">TL;DR: How does GPT-4V fail compared to SceneXplain?</h2><p>In short:</p><ul><li><strong>API limits:</strong> 100 requests a day is the new “<a href="https://quoteinvestigator.com/2011/09/08/640k-enough/?ref=jina-ai-gmbh.ghost.io">640K ought to be enough for anybody</a>”. SceneXplain has a <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io#pricing">range of plans</a> to suit your needs.</li><li><strong>Reliability:</strong> Sometimes, GPT-4V will follow a command to extract the text strings. But if you ask again in exactly the same way, it may say it can’t do it. SceneXplain gets it done right every time.</li><li><strong>Accuracy:</strong> GPT-4V will often extract strings that are <strong>plausible</strong> for a given image, but not the <strong>actual</strong> strings. For example, if you give it a Chinese menu, it will hallucinate Chinese dish names. <a href="https://jina.ai/news/are-you-ready-for-this-jelly-scenexplains-new-algo-kills-hallucinations-dead/?utm_source=PromptPerfect+Newsletter&amp;utm_campaign=ce1beac0b3-EMAIL_CAMPAIGN_2023_09_29_10_25_COPY_02&amp;utm_medium=email&amp;utm_term=0_fada173e11-6efedfdbc3-%5BLIST_EMAIL_ID%5D">SceneXplain pretty much cured hallucinations in its Jelly algorithm</a>.</li><li><strong>Consistency:</strong> GPT-4V doesn’t just hallucinate. It hallucinates different things each time. SceneXplain is generally consistent.</li><li><strong>Completeness:</strong> GPT-4V doesn’t always extract <strong><em>all</em></strong> the strings in the image. SceneXplain is more comprehensive.</li><li><strong>Cost:</strong> SceneXplain is up to 50% more affordable.</li></ul><p>Let’s dive into each point in more detail.</p><h3 id="api-limits">API limits</h3><p>Good luck with the GPT-4V API! In our extensive testing (even just to write this blog post), we rapidly and repeatedly hit request limits. An organization is limited to 100 requests per day, along with strict throttling. We would've put this post out earlier if we hadn't easily overshot that multiple times.</p><figure class="kg-card kg-image-card kg-width-wide kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-29.png" class="kg-image" alt="" width="1435" height="71" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-29.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-29.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-29.png 1435w" sizes="(min-width: 1200px) 1200px"><figcaption><span style="white-space: pre-wrap;">Hello </span><code spellcheck="false" style="white-space: pre-wrap;"><span>RateLimitError</span></code><span style="white-space: pre-wrap;">, my old friend.</span></figcaption></figure><h3 id="reliability">Reliability</h3><p>If you do try to extract strings via the web interface, results can be unpredictable. It can handle English well enough:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/qt1pq58r827iyyvugjfr.png" class="kg-image" alt="" width="1200" height="675" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/qt1pq58r827iyyvugjfr.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/qt1pq58r827iyyvugjfr.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/qt1pq58r827iyyvugjfr.png 1200w" sizes="(min-width: 720px) 720px"></figure><p>We can extract the strings as JSON by using the prompt:</p><pre><code class="language-text hljs language-plaintext">Extract the text strings from this image and populate a JSON that follows this schema:
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">SceneXplain beats GPT-4V by going beyond English, offering multilingual OCR for Chinese, Japanese, Korean, Arabic, Hindi and more</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 16, 2023 • 13 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>There's been a lot of noise recently about the release of GPT-4V - a model that can analyze the content of images and summarize that into human language. Sound familiar? It may, because SceneXplain has been doing just that for months already!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><p>But just because you take an early lead doesn't mean you win the race. We've got to show how we're better, right? Well, we've already done that in <a href="https://jina.ai/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023/?ref=jina-ai-gmbh.ghost.io">this post</a>:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="kg-bookmark-description">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" alt=""></div></a></figure><p>But in this post, we'll go one further and show you how we excel at OCR for multilingual texts. In short, <strong>SceneXplain is more accurate, reliable, consistent, complete, and cost-effective than GPT-4V</strong>. Also, it doesn’t have any pesky daily request limits.</p><p>You might think GPT-4V is pretty decent if you’re a user of Latin-character languages. Since you’re reading this (I assume in English), that means you!</p><p>Indeed, GPT-4V does okay when it comes to recognizing English, French, Spanish, and so on, as you can see from these blog posts and studies:</p><ul><li><a href="https://blog.roboflow.com/gpt-4-vision/?ref=jina-ai-gmbh.ghost.io">First Impressions with GPT-4V(ision)</a></li><li><a href="https://arxiv.org/abs/2310.16809?ref=jina-ai-gmbh.ghost.io">Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation</a></li></ul><p>But, as mentioned in the study:</p><blockquote class="kg-blockquote-alt">There is a substantial accuracy disparity between the recognition of English and Chinese text. As shown in Table 1, the performance of English text recognition is commendable. Conversely, the accuracy of Chinese text recognition is zero (ReCTS). We speculate that this may be due to the lack of Chinese scene text images as training data in GPT-4V.</blockquote><p>Bad news - it's not just Chinese where GPT-4V falls down. It consistently fails on non-Latin texts.</p><p>That's where SceneXplain comes in. We go way beyond just recognizing Latin characters - we can do Chinese, Japanese, Korean, Arabic, Hindi, and potentially more (at this point we ran out of languages that people speak (or recognize) at Jina AI.)</p><h2 id="tldr-how-does-gpt-4v-fail-compared-to-scenexplain">TL;DR: How does GPT-4V fail compared to SceneXplain?</h2><p>In short:</p><ul><li><strong>API limits:</strong> 100 requests a day is the new “<a href="https://quoteinvestigator.com/2011/09/08/640k-enough/?ref=jina-ai-gmbh.ghost.io">640K ought to be enough for anybody</a>”. SceneXplain has a <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io#pricing">range of plans</a> to suit your needs.</li><li><strong>Reliability:</strong> Sometimes, GPT-4V will follow a command to extract the text strings. But if you ask again in exactly the same way, it may say it can’t do it. SceneXplain gets it done right every time.</li><li><strong>Accuracy:</strong> GPT-4V will often extract strings that are <strong>plausible</strong> for a given image, but not the <strong>actual</strong> strings. For example, if you give it a Chinese menu, it will hallucinate Chinese dish names. <a href="https://jina.ai/news/are-you-ready-for-this-jelly-scenexplains-new-algo-kills-hallucinations-dead/?utm_source=PromptPerfect+Newsletter&amp;utm_campaign=ce1beac0b3-EMAIL_CAMPAIGN_2023_09_29_10_25_COPY_02&amp;utm_medium=email&amp;utm_term=0_fada173e11-6efedfdbc3-%5BLIST_EMAIL_ID%5D">SceneXplain pretty much cured hallucinations in its Jelly algorithm</a>.</li><li><strong>Consistency:</strong> GPT-4V doesn’t just hallucinate. It hallucinates different things each time. SceneXplain is generally consistent.</li><li><strong>Completeness:</strong> GPT-4V doesn’t always extract <strong><em>all</em></strong> the strings in the image. SceneXplain is more comprehensive.</li><li><strong>Cost:</strong> SceneXplain is up to 50% more affordable.</li></ul><p>Let’s dive into each point in more detail.</p><h3 id="api-limits">API limits</h3><p>Good luck with the GPT-4V API! In our extensive testing (even just to write this blog post), we rapidly and repeatedly hit request limits. An organization is limited to 100 requests per day, along with strict throttling. We would've put this post out earlier if we hadn't easily overshot that multiple times.</p><figure class="kg-card kg-image-card kg-width-wide kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-29.png" class="kg-image" alt="" width="1435" height="71" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/image-29.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/image-29.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/image-29.png 1435w" sizes="(min-width: 1200px) 1200px"><figcaption><span style="white-space: pre-wrap;">Hello </span><code spellcheck="false" style="white-space: pre-wrap;"><span>RateLimitError</span></code><span style="white-space: pre-wrap;">, my old friend.</span></figcaption></figure><h3 id="reliability">Reliability</h3><p>If you do try to extract strings via the web interface, results can be unpredictable. It can handle English well enough:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/qt1pq58r827iyyvugjfr.png" class="kg-image" alt="" width="1200" height="675" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/qt1pq58r827iyyvugjfr.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/qt1pq58r827iyyvugjfr.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/qt1pq58r827iyyvugjfr.png 1200w" sizes="(min-width: 720px) 720px"></figure><p>We can extract the strings as JSON by using the prompt:</p><pre><code class="language-text">Extract the text strings from this image and populate a JSON that follows this schema:
 
 {
   "type": "object",
@@ -24,287 +24,287 @@
 }
 
 Return just the output JSON. Do not put it in a code block
-</code></pre><p>Note how specific we had to be in this prompt, explaining that we just wanted raw JSON back, not including comments like “Here is your JSON” and then a back-ticked code block. There is still no guarantee that such a method is watertight. It may sometimes return extraneous content.</p><p>It returns this output:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
-<span class="hljs-attr">"text_strings"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span>
-<span class="hljs-string">"YOU CAN'T RUN"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"FROM US FOREVER"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"m"</span>
-<span class="hljs-punctuation">]</span>
-<span class="hljs-punctuation">}</span>
-</code></pre><p>I would’ve preferred some prettier, indented output. But it looks like valid JSON and accurate output. For reference, SceneXplain returns:</p><figure class="kg-card kg-code-card"><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
-  <span class="hljs-attr">"text_strings"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span>
-    <span class="hljs-string">"YOU CAN'T RUN"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"FROM US FOREVER"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"M"</span>
-  <span class="hljs-punctuation">]</span>
-<span class="hljs-punctuation">}</span></code></pre><figcaption><p><span style="white-space: pre-wrap;">Ah, those sweet sweet indents</span></p></figcaption></figure><p>Now let’s try asking in natural language about a Chinese ad:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/McDonald-EN-CHINE.jpeg" class="kg-image" alt="" width="1329" height="750" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/McDonald-EN-CHINE.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/McDonald-EN-CHINE.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/McDonald-EN-CHINE.jpeg 1329w" sizes="(min-width: 720px) 720px"></figure><p>If we use the prompt: <code>Extract the text strings from this image</code>, GPT-4V gives us:</p><pre><code class="language-text hljs language-plaintext">It seems there was an error while attempting to extract the text from the image using OCR. The error message indicates a problem with the Tesseract OCR data files for the Chinese simplified language. The necessary language files may not be installed in the environment where the OCR operation was attempted.
+</code></pre><p>Note how specific we had to be in this prompt, explaining that we just wanted raw JSON back, not including comments like “Here is your JSON” and then a back-ticked code block. There is still no guarantee that such a method is watertight. It may sometimes return extraneous content.</p><p>It returns this output:</p><pre><code class="language-json">{
+"text_strings": [
+"YOU CAN'T RUN",
+"FROM US FOREVER",
+"m"
+]
+}
+</code></pre><p>I would’ve preferred some prettier, indented output. But it looks like valid JSON and accurate output. For reference, SceneXplain returns:</p><figure class="kg-card kg-code-card"><pre><code class="language-json">{
+  "text_strings": [
+    "YOU CAN'T RUN",
+    "FROM US FOREVER",
+    "M"
+  ]
+}</code></pre><figcaption><p><span style="white-space: pre-wrap;">Ah, those sweet sweet indents</span></p></figcaption></figure><p>Now let’s try asking in natural language about a Chinese ad:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/McDonald-EN-CHINE.jpeg" class="kg-image" alt="" width="1329" height="750" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/McDonald-EN-CHINE.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/McDonald-EN-CHINE.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/McDonald-EN-CHINE.jpeg 1329w" sizes="(min-width: 720px) 720px"></figure><p>If we use the prompt: <code>Extract the text strings from this image</code>, GPT-4V gives us:</p><pre><code class="language-text">It seems there was an error while attempting to extract the text from the image using OCR. The error message indicates a problem with the Tesseract OCR data files for the Chinese simplified language. The necessary language files may not be installed in the environment where the OCR operation was attempted.
 
 Given this issue, I'm unable to extract the text from the image as requested. If there's anything else you would like me to assist you with, please let me know!
-</code></pre><p>That’s…not useful. <strong><em>However</em></strong>, asking it to extract it as JSON (by using the above prompt with schema) works:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
-<span class="hljs-attr">"text_strings"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span>
-<span class="hljs-string">"麦当劳"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"一周七天"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"早晨四点"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"至"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"17:00 时段"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"周末早餐 延时"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"更多惊喜"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"尽在麦当劳APP"</span>
-<span class="hljs-punctuation">]</span>
-<span class="hljs-punctuation">}</span>
-</code></pre><p>Why can it do the job if we specify we want JSON output, but it just shrugs helplessly if we ask in plain English? Who knows.</p><h3 id="accuracy">Accuracy</h3><p>Take another look at that JSON output. Then, take a look at the ad.</p><p>At first glance, the JSON looks decent. It’s got the <code>17:00</code> and other details. But take a closer look. None of those text strings appear in the image. They look like the kind of strings that <em>could</em> occur in a Chinese McDonald's ad, but none of them are actually in that particular ad.</p><p>This can be even more dangerous than being wrong - enough people are already worried about <a href="https://futurism.com/artificial-intelligence-automated-mansplaining-machine?ref=jina-ai-gmbh.ghost.io">GPT mansplaining</a> - i.e., being confident but wrong. We see the same story when it comes to non-Latin text too.</p><p>Also, why does it suddenly think it can extract the text when it stated before that it couldn’t?</p><p>For reference, SceneXplain returns:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
-  <span class="hljs-attr">"text_strings"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span>
-    <span class="hljs-string">"麦麦夜市"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"出神卤味鸡架"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"青花椒拌鸡"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"青花椒酸辣鸡"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"青花椒半鸡"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"麦麦夜市小堡"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"暗糖带劲堡"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"唯醇带劲堡"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"莱莱真香堡"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"17:00营夜"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"哇藕带劲堡"</span>
-  <span class="hljs-punctuation">]</span>
-<span class="hljs-punctuation">}</span>
-</code></pre><p>If you compare the strings, you’ll see SceneXplain is much more accurate and hallucinates less.</p><h3 id="consistency">Consistency</h3><p>Coming back to our old friend, the Chinese McDonald’s ad, what if we start a new chat session and re-submit the exact same image and prompt? Here's what we get:</p><pre><code class="hljs language-json"><span class="hljs-punctuation">{</span>
-<span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"object"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-attr">"properties"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-<span class="hljs-attr">"text_strings"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span>
-<span class="hljs-string">"麦辣鸡翅"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"堡堡双拼 等你来撩"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"一人食好福利"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"17:00前来"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"麦当劳"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"尊享软欧包"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"周边好货 等你"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"尊享软欧包"</span>
-<span class="hljs-punctuation">]</span>
-<span class="hljs-punctuation">}</span>
-<span class="hljs-punctuation">}</span>
-</code></pre><p>Well dang. Not only is the text entirely different, but it’s also sent us JSON in a completely different format, something like the <strong>schema</strong> we sent, rather than the <em>output format</em> that the schema defines.</p><h3 id="completeness">Completeness</h3><p>If we try to extract text from this Arabic coffee ad, GPT-4V gives us far fewer strings than SceneXplain does:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/d46l5mu-22863ee5-ff85-4f18-ac95-2a76e16e9f77.jpg" class="kg-image" alt="" width="624" height="808" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/d46l5mu-22863ee5-ff85-4f18-ac95-2a76e16e9f77.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/d46l5mu-22863ee5-ff85-4f18-ac95-2a76e16e9f77.jpg 624w"></figure><ul><li>GPT-4V:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-<span class="hljs-string">"معتوق MAATOUK"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"1960"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"قهوة عربية"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"حبيبة الأصول"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"تقدمة عربية"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"أصالة امتدت وسطولة النضج"</span>
-<span class="hljs-punctuation">]</span>
-</code></pre><ul><li>SceneXplain:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-    <span class="hljs-string">"معتوق"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"MAATOUK"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"1 9 6 0"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"قهوة عربية"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"حسب الأصول"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"قهوة عربية"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"معتوق"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"mAATOUK"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"تحميص غامق"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"بن مطحون ١٠٠٪ أرابيكا"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"أصالة المذاق وسهولة التحضير"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"لطالما اشتهر العرب عبر ماضي الزمان بتحضير القهوة العربية في منازلهم، والتي تعد من أحد رموز الكرم والضيافة"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"العربية. من هنا انطلقت مصانع معتوق لتقديم القهوة العربية السهلة التحضير ذات الرائحة المميزة والطعم الأصيل."</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"القهوة العربية معتوق ١٩٦٠، قهوة عربية حسب الأصول."</span>
-  <span class="hljs-punctuation">]</span>
-</code></pre><h3 id="cost">Cost</h3><p>At the time of writing, GPT-4V charges $0.025 per image. By choosing SceneXplain’s MAX plan you pay less than half of that. You can find out more on our <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io#pricing">pricing page</a>:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io#pricing"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><h2 id="head-to-head-gpt-4v-vs-scenexplain">Head to head: GPT-4V vs SceneXplain</h2><p>Let’s put both services to the test and see who comes out on top.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">See our <a href="https://colab.research.google.com/github/alexcg1/notebooks/blob/main/scenex/scenex-gpt4v?ref=jina-ai-gmbh.ghost.io">notebook</a> for the full range of testing and results.</div></div><h3 id="testing-methodology">Testing methodology</h3><p>We took a selection of images, some from <a href="http://pexels.com/?ref=jina-ai-gmbh.ghost.io">pexels.com</a> and some from searching Google Images for advertisements in the given languages:</p><ul><li>Chinese (we didn't differentiate between Simplified and Traditional)</li><li>Japanese</li><li>Korean</li><li>Arabic</li><li>Hindi</li></ul><p>We then used:</p><ul><li><a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io">SceneXplain's API</a> (using the <a href="https://jina.ai/news/are-you-ready-for-this-jelly-scenexplains-new-algo-kills-hallucinations-dead?ref=jina-ai-gmbh.ghost.io">Jelly algorithm</a>)</li><li>A combination of the GPT-4V API and web frontend (since we quickly blasted through our API request limit)</li></ul><p>We ran several rounds of tests:</p><ul><li><strong>Basic image description:</strong> For SceneXplain, we just uploaded the image. For GPT-4V, we asked: <code>What is in the image?</code></li><li><strong>Visual question answering:</strong> We uploaded the image to both services and asked: <code>What does the text say in this image?</code></li><li><strong>JSON output:</strong> For SceneXplain, we simply used the <a href="https://jina.ai/news/scenexplains-image-json-extract-structured-data-images-precision?ref=jina-ai-gmbh.ghost.io">"Extract JSON from image"</a> feature and a predefined <a href="https://json-schema.org/?ref=jina-ai-gmbh.ghost.io">JSON Schema</a>.</li></ul><p>The JSON Schema was as follows:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
-  <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"object"</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-attr">"properties"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-    <span class="hljs-attr">"text_strings"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-      <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"array"</span><span class="hljs-punctuation">,</span>
-      <span class="hljs-attr">"description"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"Every text string contained in the image. Consider all languages"</span>
-    <span class="hljs-punctuation">}</span>
-  <span class="hljs-punctuation">}</span>
-<span class="hljs-punctuation">}</span></code></pre><p>Since GPT-4V doesn't directly support JSON Schemas, we had to be a bit hacky and explain what we wanted to do as text:</p><pre><code class="language-text hljs language-plaintext">Extract the text strings from this image and populate a JSON that follows this schema:
+</code></pre><p>That’s…not useful. <strong><em>However</em></strong>, asking it to extract it as JSON (by using the above prompt with schema) works:</p><pre><code class="language-json">{
+"text_strings": [
+"麦当劳",
+"一周七天",
+"早晨四点",
+"至",
+"17:00 时段",
+"周末早餐 延时",
+"更多惊喜",
+"尽在麦当劳APP"
+]
+}
+</code></pre><p>Why can it do the job if we specify we want JSON output, but it just shrugs helplessly if we ask in plain English? Who knows.</p><h3 id="accuracy">Accuracy</h3><p>Take another look at that JSON output. Then, take a look at the ad.</p><p>At first glance, the JSON looks decent. It’s got the <code>17:00</code> and other details. But take a closer look. None of those text strings appear in the image. They look like the kind of strings that <em>could</em> occur in a Chinese McDonald's ad, but none of them are actually in that particular ad.</p><p>This can be even more dangerous than being wrong - enough people are already worried about <a href="https://futurism.com/artificial-intelligence-automated-mansplaining-machine?ref=jina-ai-gmbh.ghost.io">GPT mansplaining</a> - i.e., being confident but wrong. We see the same story when it comes to non-Latin text too.</p><p>Also, why does it suddenly think it can extract the text when it stated before that it couldn’t?</p><p>For reference, SceneXplain returns:</p><pre><code class="language-json">{
+  "text_strings": [
+    "麦麦夜市",
+    "出神卤味鸡架",
+    "青花椒拌鸡",
+    "青花椒酸辣鸡",
+    "青花椒半鸡",
+    "麦麦夜市小堡",
+    "暗糖带劲堡",
+    "唯醇带劲堡",
+    "莱莱真香堡",
+    "17:00营夜",
+    "哇藕带劲堡"
+  ]
+}
+</code></pre><p>If you compare the strings, you’ll see SceneXplain is much more accurate and hallucinates less.</p><h3 id="consistency">Consistency</h3><p>Coming back to our old friend, the Chinese McDonald’s ad, what if we start a new chat session and re-submit the exact same image and prompt? Here's what we get:</p><pre><code>{
+"type": "object",
+"properties": {
+"text_strings": [
+"麦辣鸡翅",
+"堡堡双拼 等你来撩",
+"一人食好福利",
+"17:00前来",
+"麦当劳",
+"尊享软欧包",
+"周边好货 等你",
+"尊享软欧包"
+]
+}
+}
+</code></pre><p>Well dang. Not only is the text entirely different, but it’s also sent us JSON in a completely different format, something like the <strong>schema</strong> we sent, rather than the <em>output format</em> that the schema defines.</p><h3 id="completeness">Completeness</h3><p>If we try to extract text from this Arabic coffee ad, GPT-4V gives us far fewer strings than SceneXplain does:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/d46l5mu-22863ee5-ff85-4f18-ac95-2a76e16e9f77.jpg" class="kg-image" alt="" width="624" height="808" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/d46l5mu-22863ee5-ff85-4f18-ac95-2a76e16e9f77.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/d46l5mu-22863ee5-ff85-4f18-ac95-2a76e16e9f77.jpg 624w"></figure><ul><li>GPT-4V:</li></ul><pre><code class="language-json">[
+"معتوق MAATOUK",
+"1960",
+"قهوة عربية",
+"حبيبة الأصول",
+"تقدمة عربية",
+"أصالة امتدت وسطولة النضج"
+]
+</code></pre><ul><li>SceneXplain:</li></ul><pre><code class="language-json">[
+    "معتوق",
+    "MAATOUK",
+    "1 9 6 0",
+    "قهوة عربية",
+    "حسب الأصول",
+    "قهوة عربية",
+    "معتوق",
+    "mAATOUK",
+    "تحميص غامق",
+    "بن مطحون ١٠٠٪ أرابيكا",
+    "أصالة المذاق وسهولة التحضير",
+    "لطالما اشتهر العرب عبر ماضي الزمان بتحضير القهوة العربية في منازلهم، والتي تعد من أحد رموز الكرم والضيافة",
+    "العربية. من هنا انطلقت مصانع معتوق لتقديم القهوة العربية السهلة التحضير ذات الرائحة المميزة والطعم الأصيل.",
+    "القهوة العربية معتوق ١٩٦٠، قهوة عربية حسب الأصول."
+  ]
+</code></pre><h3 id="cost">Cost</h3><p>At the time of writing, GPT-4V charges $0.025 per image. By choosing SceneXplain’s MAX plan you pay less than half of that. You can find out more on our <a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io#pricing">pricing page</a>:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io#pricing"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. Elevate your digital presence today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://scenex.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">SceneXplain</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://scenex.jina.ai/banner.png" alt=""></div></a></figure><h2 id="head-to-head-gpt-4v-vs-scenexplain">Head to head: GPT-4V vs SceneXplain</h2><p>Let’s put both services to the test and see who comes out on top.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">See our <a href="https://colab.research.google.com/github/alexcg1/notebooks/blob/main/scenex/scenex-gpt4v?ref=jina-ai-gmbh.ghost.io">notebook</a> for the full range of testing and results.</div></div><h3 id="testing-methodology">Testing methodology</h3><p>We took a selection of images, some from <a href="http://pexels.com/?ref=jina-ai-gmbh.ghost.io">pexels.com</a> and some from searching Google Images for advertisements in the given languages:</p><ul><li>Chinese (we didn't differentiate between Simplified and Traditional)</li><li>Japanese</li><li>Korean</li><li>Arabic</li><li>Hindi</li></ul><p>We then used:</p><ul><li><a href="https://scenex.jina.ai/api?ref=jina-ai-gmbh.ghost.io">SceneXplain's API</a> (using the <a href="https://jina.ai/news/are-you-ready-for-this-jelly-scenexplains-new-algo-kills-hallucinations-dead?ref=jina-ai-gmbh.ghost.io">Jelly algorithm</a>)</li><li>A combination of the GPT-4V API and web frontend (since we quickly blasted through our API request limit)</li></ul><p>We ran several rounds of tests:</p><ul><li><strong>Basic image description:</strong> For SceneXplain, we just uploaded the image. For GPT-4V, we asked: <code>What is in the image?</code></li><li><strong>Visual question answering:</strong> We uploaded the image to both services and asked: <code>What does the text say in this image?</code></li><li><strong>JSON output:</strong> For SceneXplain, we simply used the <a href="https://jina.ai/news/scenexplains-image-json-extract-structured-data-images-precision?ref=jina-ai-gmbh.ghost.io">"Extract JSON from image"</a> feature and a predefined <a href="https://json-schema.org/?ref=jina-ai-gmbh.ghost.io">JSON Schema</a>.</li></ul><p>The JSON Schema was as follows:</p><pre><code class="language-json">{
+  "type": "object",
+  "properties": {
+    "text_strings": {
+      "type": "array",
+      "description": "Every text string contained in the image. Consider all languages"
+    }
+  }
+}</code></pre><p>Since GPT-4V doesn't directly support JSON Schemas, we had to be a bit hacky and explain what we wanted to do as text:</p><pre><code class="language-text">Extract the text strings from this image and populate a JSON that follows this schema:
 
 &lt;JSON Schema from above&gt;
 
-Return just the output JSON. Do not put it in a code block"</code></pre><p>The results below focus on the JSON outputs since those are (in our opinion) the most useful outputs for real-world usage.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">To save space, we’ve simplified the JSON output to include just the text strings, not the rest of the JSON structure.</div></div><h3 id="chinese">Chinese</h3><p>We’ve already dived into the McDonald’s ad above, so we’ll just look at one more Chinese image:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/pexels-photo-2670327.jpeg" class="kg-image" alt="" width="2000" height="3000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/pexels-photo-2670327.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/pexels-photo-2670327.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/pexels-photo-2670327.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/11/pexels-photo-2670327.jpeg 2400w" sizes="(min-width: 720px) 720px"></figure><ul><li>SceneXplain output:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-  <span class="hljs-string">"金钱肚20元"</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-string">"旺角牛筋腩20元"</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-string">"旺角牛杂18元"</span>
-<span class="hljs-punctuation">]</span></code></pre><ul><li>GPT-4V output:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-  <span class="hljs-string">"竹筴魚"</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-string">"20元"</span><span class="hljs-punctuation">,</span> 
-  <span class="hljs-string">"甜甜圈"</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-string">"20元"</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-string">"甜甜仙貝"</span><span class="hljs-punctuation">,</span>
-  <span class="hljs-string">"18元"</span>
-<span class="hljs-punctuation">]</span></code></pre><p>Again, we see GPT-4V gets the menu contents wrong and also splits each price from the (wrong) menu item. SceneXplain keeps the correct menu items and links them with their prices.</p><h3 id="japanese">Japanese</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/21d10241ed74414d8263d56330cd5d02.png" class="kg-image" alt="" width="400" height="300"></figure><ul><li>GPT-4V gets some of the characters correct in the cigarette ad. The string <code>私はただ吸い殻になります</code> has most of the same characters but is still a bit off. Other strings are just hallucinated.</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-<span class="hljs-string">"私はただ吸い殻になります"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"PLAISIR"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"純正"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"MICRONITE"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"新式"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"すべての味"</span>
-<span class="hljs-punctuation">]</span>
-</code></pre><ul><li>SceneXplain:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-    <span class="hljs-string">"私はたばこを吸います"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"PLAISIR"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"独占"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"MICRONITE"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"新た"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"シガレット"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"喜びの味"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"KING SIZE"</span>
-  <span class="hljs-punctuation">]</span>
-</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/poster.png" class="kg-image" alt="" width="897" height="1390" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/poster.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/poster.png 897w" sizes="(min-width: 720px) 720px"></figure><ul><li>GPT-4V: After extracting (wrong) text from Chinese and Japanese images, we uploaded another image with the prompt <code>Now do this one</code> (which we’d used successfully to repeat prior commands). GPT-4V seems to have forgotten how. We got the output:</li></ul><pre><code class="language-text hljs language-plaintext">I'm sorry, but I can't assist with identifying or making statements about text within images. If you have any other questions or need assistance with a different task, feel free to ask!
-</code></pre><ul><li>SceneXplain did its duty as expected:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-    <span class="hljs-string">"用服ぐ直ずせ躇鷹"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"アンチ·ルンゲン"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"評判の救急薬"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"アンチルンダ"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"肺炎に"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"日英米 製法特許)"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"ANTI-LUMGEN"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"アンチルバゲノ"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"東京验薬株式会社"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"呈贈獻文"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"(金科百貨店及各麵店 有三)"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"ありかせん"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"本剤はさが年以上保存しても効目に變化は"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"本剤は何等期作品のない安全な内服薬でね"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"本剤は他の醫藥と併用して差支へありません"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"の必要はありません"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"本劑は「只一回分」のみて結構です战版"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"ら専門家に期相談下さい"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"象の超らない時は乾炎でないと思ひます"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"アンチ·ルンゲン を服用しますと必ず右の"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"本劑 の 特 長"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"るのでありまして安眠より覺める時には徳"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"此の特殊現象 發汗安眠 こそ薬効で撲滅"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"とも快上げに長時間安眠致します"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"發汗し其發汗が相之教生る頃より忠者はい"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"アンチ·ルンゲン を服用すると白血球のは"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"治 療 の 鐵 則"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"如世榮79發音元中山"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"價 小人相 金 國"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"大人翔 五"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"部學化所鋼製山中 社會式格 元賣發"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"社會者合木大 ·店商置罐 意 束)"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"社會名令部太長川龍 國古名("</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"會面イラブサルタビスホ 說 大ノ"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"店理代"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"社會式株藥製京東 元造製"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"Image ID: W5DPKC"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"www.alamy.com"</span>
-  <span class="hljs-punctuation">]</span>
-</code></pre><h3 id="korean">Korean</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/pexels-photo-6314649.jpeg" class="kg-image" alt="" width="1125" height="750" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/pexels-photo-6314649.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/pexels-photo-6314649.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/pexels-photo-6314649.jpeg 1125w" sizes="(min-width: 720px) 720px"></figure><ul><li>GPT-4V remembers how to extract text again. And it remembers how to get it wrong too! If you look at the output, some of the characters are the same as the image, but some are not.</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-<span class="hljs-string">"술은 남에 말나"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"술은 나로 말나"</span>
-<span class="hljs-punctuation">]</span>
-</code></pre><ul><li>SceneXplain gives accurate output, though I’m not sure where the <code>50</code> is coming from:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-    <span class="hljs-string">"|야"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"좋은 날에 만나"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"단이 방"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"50"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"좋은 나를 만나"</span>
- <span class="hljs-punctuation">]</span>
-</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/230531_--_----------_--_--2.jpg" class="kg-image" alt="" width="800" height="1028" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/230531_--_----------_--_--2.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/230531_--_----------_--_--2.jpg 800w" sizes="(min-width: 720px) 720px"></figure><ul><li>GPT-4V actually does okay with the more complex image. It doesn’t catch <strong><em>all</em></strong> the strings, but it’s less wrong than usual from a quick comparison (note: I don’t read Korean, so I’m just eyeballing it):</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-<span class="hljs-string">"자연과 국민을 연결하는"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"수목·정원 플랫폼 기관"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"수목원의 고객가치를 넘어"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"국민 생활 속 녹색공간 확산과"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"정원산업 생태계를 활성화하는 역할을"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"적극적으로 수행하겠습니다"</span>
-<span class="hljs-punctuation">]</span>
-</code></pre><ul><li>SceneXplain extracts a lot more:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-    <span class="hljs-string">"한국수목원정원관리원"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"자연과 국민을 연결하는"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"수목원·정원 플랫폼 기관"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"수목원의 공간적 개념을 넘어"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"국민 생활 속 녹색문화 확산과"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"정원산업 생태계를 활성화하는 역할을"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"적극적으로 수행하겠습니다"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"산림생물자원"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"고품질 수목원"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"ES"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"보전 · 복원"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"서비스"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"역량 강화"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"산림생물자원"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"연구 ·활용"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"정원문화"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"활성화"</span>
-  <span class="hljs-punctuation">]</span>
-</code></pre><h3 id="arabic">Arabic</h3><p>Since we already covered the Arabic coffee image above, we'll just leave one Arabic here:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/artworks-000043896167-z3x71u-t500x500.jpg" class="kg-image" alt="" width="500" height="500"></figure><ul><li>GPT-4V:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-<span class="hljs-string">"الحياة طريق أكثر سرعة"</span>
-<span class="hljs-punctuation">]</span>
-</code></pre><ul><li>SceneXplain gets a little confused about the 4G logo, seeing it as <code>EAG</code> but is otherwise sound:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-    <span class="hljs-string">"الحياة صارت أكثر سرعة"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"EAG"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"LTE"</span>
-  <span class="hljs-punctuation">]</span>
-</code></pre><h3 id="hindi">Hindi</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/dabur-sarso-avala-hair-oil-ad-dainik-bhaskar-jaipur-12-12-2017.jpg" class="kg-image" alt="" width="955" height="1575" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/dabur-sarso-avala-hair-oil-ad-dainik-bhaskar-jaipur-12-12-2017.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/dabur-sarso-avala-hair-oil-ad-dainik-bhaskar-jaipur-12-12-2017.jpg 955w" sizes="(min-width: 720px) 720px"></figure><ul><li>GPT-4V:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-<span class="hljs-string">"सरसों और आंवला"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"का पोषण बिना चिपचिपाहट"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"सिर्फ रु"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"9 में"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"40ml"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"डाबर"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"टोल फ्री 1800-103-1644"</span>
-<span class="hljs-punctuation">]</span>
-</code></pre><ul><li>SceneXplain:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-    <span class="hljs-string">"सरसों आँवला"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"केश तेल"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"सरसों और आँवला"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"का पोषण बिना"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"चिपचिपाहट"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"में"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"नया"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"पैक"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"₹9/-"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"सरसों आँवला"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"40ml"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"DABUR CARES: CALL OR WRITE"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"+ TOLL FREE 1800-103-1644"</span>
-  <span class="hljs-punctuation">]</span>
-</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/mdh-masala-ki-ek-dhamkedhar-offer-ad-hindustan-hindi-delhi-21-10-2017.jpg" class="kg-image" alt="" width="973" height="1576" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/mdh-masala-ki-ek-dhamkedhar-offer-ad-hindustan-hindi-delhi-21-10-2017.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/mdh-masala-ki-ek-dhamkedhar-offer-ad-hindustan-hindi-delhi-21-10-2017.jpg 973w" sizes="(min-width: 720px) 720px"></figure><ul><li>GPT-4V gave us the error <code>Something went wrong. If this issue persists please contact us through our help center at help.openai.com</code>. After retrying, it gave us:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-<span class="hljs-string">"MDH की एक"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"धमाकेदार ऑफर"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"स्वाद के साथ - साथ खुशियों की बौछार !!"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"मसाला एक स्वादिष्ट और जीवंत उपहार !!"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"MDH"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"मसाले"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"असली मसाले सच-सच"</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"MDH Ltd."</span><span class="hljs-punctuation">,</span>
-<span class="hljs-string">"E-mails: delhi@mdhspices.in, rk@mdhspices.in www.mdhspices.com"</span>
-<span class="hljs-punctuation">]</span>
-</code></pre><ul><li>SceneXplain goes much further, even extracting product names and tiny details like when the company was established:</li></ul><pre><code class="language-json hljs"><span class="hljs-punctuation">[</span>
-    <span class="hljs-string">"MDH"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"की एक"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"धमाकेदार ऑफर"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"स्वाद के साथ -साथ खुशियों की बौछार !"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"मसाला पैक खरीदो और जीतो उपहार !!"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"एम डी एच की ओर से अपने सभी ग्राहकों के लिए एक धमाकेदार ऑफर।"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"किसी भी नजदीकी विक्रेता से एम डी एच मसालों के नीचे छपे पैक्स में से"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"कोई भी 100 ग्राम वाला पैक खरीदें और भाग्यशाली विजेता बनने का अवसर"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"प्राप्त करें, हो सकता है आप के लिए गए पैक के फ्लेप में उपहार का नाम हो।"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"असली मसाले"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"मसाले"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"सच -सच"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"MD H"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"SPICES"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"MD"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"MOH"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"Garam"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"Pav Bhaji"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"masala"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"Kitchen"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"Shahi Pancer"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"King"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"Chana"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"DEGGI"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"MIRCH"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"Chunky Chat"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"नियम व शर्तें :- एम डी एच मसालों के ऊपर दर्शाये गए चुनिन्दा पैक्स में से कोई भी 100 ग्राम वाला"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"पैक खरीदें, उसका फ्लेप खोलें, हो सकता है कि उस फ्लेप के नीचे उपहार का नाम छपा हो। उस"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"उपहार को प्राप्त करने के भाग्यशाली विजेता बनें। • इस स्कीम का नकद लाभ कोई भी नहीं है"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"लिए दिल्ली में ही लागू है • स्कीम स्टॉक रहने तक सीमित है • यह स्कीम एम डी एच के सुपर"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"स्टॉकिस्ट, स्टॉकिस्ट और कर्मचारियों के लिए नहीं है · कंपनी का निर्णय अंतिम और सर्वमान्य होगा"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"और सभी विवाद दिल्ली के न्याय क्षेत्र के अधीन होंगे। • अन्य शर्तों के लिए पैक देखें।"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"महाशियाँ दी हट्टी (प्रा०) लिमिटेड"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"9/44, कीर्ति नगर, नई दिल्ली - 110015 फोन नं० 011-41425106 - 07-08"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"ESTD. 1919"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-string">"E-mails : delhi@mdhspices.in, rk@mdhspices.in www.mdhspices.com"</span>
-  <span class="hljs-punctuation">]</span>
-</code></pre><h2 id="conclusion">Conclusion</h2><p>At the end of the day, SceneXplain clearly excels in multilingual OCR compared to GPT-4V. To recap:</p><p><strong>API limits:</strong></p><ul><li>GPT-4V: 100 requests per day</li><li>SceneXplain: 5,000 credits per month on the MAX plan. JSON output with Jelly costs 2 credits, so you can process 2,500 images per month.</li></ul><p><strong>Reliability:</strong></p><ul><li>GPT-4V: Is often like “I’m sorry Dave, I’m afraid I can’t do that.”</li><li>SceneXplain: Doggedly reliable. Gets the job done.</li></ul><p><strong>Accuracy:</strong></p><ul><li>GPT-4V: hallucinates strings it believes are plausible from a given image, rather than reading the actual text.</li><li>SceneXplain: Extracts the correct text.</li></ul><p><strong>Consistency:</strong></p><ul><li>GPT-4V doesn’t just hallucinate. It hallucinates different things each time.</li><li>SceneXplain gives much more consistent output.</li></ul><p><strong>Completeness:</strong></p><ul><li>GPT-4V: Often doesn’t always extract <strong><em>all</em></strong> the strings in the image.</li><li>SceneXplain: Extracts more strings.</li></ul><p><strong>Cost:</strong></p><ul><li>GPT-4V: $0.025 per image.</li><li>SceneXplain: As low as 0.02 USD per image on the MAX plan if you enable JSON output. As low as 0.01 USD without JSON output.</li></ul><p>When you take all those factors into account, it's clear that SceneXplain is the obvious choice.</p><h2 id="get-started-with-scenexplain">Get started with SceneXplain</h2><p>Ready to explore multilingual OCR? Sign up for a free account with SceneXplain and start converting images to text easily. It's a practical, user-friendly way to manage digital documents. Get started now and see the difference SceneXplain can make!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. 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\ No newline at end of file
+Return just the output JSON. Do not put it in a code block"</code></pre><p>The results below focus on the JSON outputs since those are (in our opinion) the most useful outputs for real-world usage.</p><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">To save space, we’ve simplified the JSON output to include just the text strings, not the rest of the JSON structure.</div></div><h3 id="chinese">Chinese</h3><p>We’ve already dived into the McDonald’s ad above, so we’ll just look at one more Chinese image:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/pexels-photo-2670327.jpeg" class="kg-image" alt="" width="2000" height="3000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/pexels-photo-2670327.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/pexels-photo-2670327.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/11/pexels-photo-2670327.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/11/pexels-photo-2670327.jpeg 2400w" sizes="(min-width: 720px) 720px"></figure><ul><li>SceneXplain output:</li></ul><pre><code class="language-json">[
+  "金钱肚20元",
+  "旺角牛筋腩20元",
+  "旺角牛杂18元"
+]</code></pre><ul><li>GPT-4V output:</li></ul><pre><code class="language-json">[
+  "竹筴魚",
+  "20元", 
+  "甜甜圈",
+  "20元",
+  "甜甜仙貝",
+  "18元"
+]</code></pre><p>Again, we see GPT-4V gets the menu contents wrong and also splits each price from the (wrong) menu item. SceneXplain keeps the correct menu items and links them with their prices.</p><h3 id="japanese">Japanese</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/21d10241ed74414d8263d56330cd5d02.png" class="kg-image" alt="" width="400" height="300"></figure><ul><li>GPT-4V gets some of the characters correct in the cigarette ad. The string <code>私はただ吸い殻になります</code> has most of the same characters but is still a bit off. Other strings are just hallucinated.</li></ul><pre><code class="language-json">[
+"私はただ吸い殻になります",
+"PLAISIR",
+"純正",
+"MICRONITE",
+"新式",
+"すべての味"
+]
+</code></pre><ul><li>SceneXplain:</li></ul><pre><code class="language-json">[
+    "私はたばこを吸います",
+    "PLAISIR",
+    "独占",
+    "MICRONITE",
+    "新た",
+    "シガレット",
+    "喜びの味",
+    "KING SIZE"
+  ]
+</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/poster.png" class="kg-image" alt="" width="897" height="1390" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/poster.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/poster.png 897w" sizes="(min-width: 720px) 720px"></figure><ul><li>GPT-4V: After extracting (wrong) text from Chinese and Japanese images, we uploaded another image with the prompt <code>Now do this one</code> (which we’d used successfully to repeat prior commands). GPT-4V seems to have forgotten how. We got the output:</li></ul><pre><code class="language-text">I'm sorry, but I can't assist with identifying or making statements about text within images. If you have any other questions or need assistance with a different task, feel free to ask!
+</code></pre><ul><li>SceneXplain did its duty as expected:</li></ul><pre><code class="language-json">[
+    "用服ぐ直ずせ躇鷹",
+    "アンチ·ルンゲン",
+    "評判の救急薬",
+    "アンチルンダ",
+    "肺炎に",
+    "日英米 製法特許)",
+    "ANTI-LUMGEN",
+    "アンチルバゲノ",
+    "東京验薬株式会社",
+    "呈贈獻文",
+    "(金科百貨店及各麵店 有三)",
+    "ありかせん",
+    "本剤はさが年以上保存しても効目に變化は",
+    "本剤は何等期作品のない安全な内服薬でね",
+    "本剤は他の醫藥と併用して差支へありません",
+    "の必要はありません",
+    "本劑は「只一回分」のみて結構です战版",
+    "ら専門家に期相談下さい",
+    "象の超らない時は乾炎でないと思ひます",
+    "アンチ·ルンゲン を服用しますと必ず右の",
+    "本劑 の 特 長",
+    "るのでありまして安眠より覺める時には徳",
+    "此の特殊現象 發汗安眠 こそ薬効で撲滅",
+    "とも快上げに長時間安眠致します",
+    "發汗し其發汗が相之教生る頃より忠者はい",
+    "アンチ·ルンゲン を服用すると白血球のは",
+    "治 療 の 鐵 則",
+    "如世榮79發音元中山",
+    "價 小人相 金 國",
+    "大人翔 五",
+    "部學化所鋼製山中 社會式格 元賣發",
+    "社會者合木大 ·店商置罐 意 束)",
+    "社會名令部太長川龍 國古名(",
+    "會面イラブサルタビスホ 說 大ノ",
+    "店理代",
+    "社會式株藥製京東 元造製",
+    "Image ID: W5DPKC",
+    "www.alamy.com"
+  ]
+</code></pre><h3 id="korean">Korean</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/pexels-photo-6314649.jpeg" class="kg-image" alt="" width="1125" height="750" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/pexels-photo-6314649.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/11/pexels-photo-6314649.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/pexels-photo-6314649.jpeg 1125w" sizes="(min-width: 720px) 720px"></figure><ul><li>GPT-4V remembers how to extract text again. And it remembers how to get it wrong too! If you look at the output, some of the characters are the same as the image, but some are not.</li></ul><pre><code class="language-json">[
+"술은 남에 말나",
+"술은 나로 말나"
+]
+</code></pre><ul><li>SceneXplain gives accurate output, though I’m not sure where the <code>50</code> is coming from:</li></ul><pre><code class="language-json">[
+    "|야",
+    "좋은 날에 만나",
+    "단이 방",
+    "50",
+    "좋은 나를 만나"
+ ]
+</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/230531_--_----------_--_--2.jpg" class="kg-image" alt="" width="800" height="1028" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/230531_--_----------_--_--2.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/230531_--_----------_--_--2.jpg 800w" sizes="(min-width: 720px) 720px"></figure><ul><li>GPT-4V actually does okay with the more complex image. It doesn’t catch <strong><em>all</em></strong> the strings, but it’s less wrong than usual from a quick comparison (note: I don’t read Korean, so I’m just eyeballing it):</li></ul><pre><code class="language-json">[
+"자연과 국민을 연결하는",
+"수목·정원 플랫폼 기관",
+"수목원의 고객가치를 넘어",
+"국민 생활 속 녹색공간 확산과",
+"정원산업 생태계를 활성화하는 역할을",
+"적극적으로 수행하겠습니다"
+]
+</code></pre><ul><li>SceneXplain extracts a lot more:</li></ul><pre><code class="language-json">[
+    "한국수목원정원관리원",
+    "자연과 국민을 연결하는",
+    "수목원·정원 플랫폼 기관",
+    "수목원의 공간적 개념을 넘어",
+    "국민 생활 속 녹색문화 확산과",
+    "정원산업 생태계를 활성화하는 역할을",
+    "적극적으로 수행하겠습니다",
+    "산림생물자원",
+    "고품질 수목원",
+    "ES",
+    "보전 · 복원",
+    "서비스",
+    "역량 강화",
+    "산림생물자원",
+    "연구 ·활용",
+    "정원문화",
+    "활성화"
+  ]
+</code></pre><h3 id="arabic">Arabic</h3><p>Since we already covered the Arabic coffee image above, we'll just leave one Arabic here:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/artworks-000043896167-z3x71u-t500x500.jpg" class="kg-image" alt="" width="500" height="500"></figure><ul><li>GPT-4V:</li></ul><pre><code class="language-json">[
+"الحياة طريق أكثر سرعة"
+]
+</code></pre><ul><li>SceneXplain gets a little confused about the 4G logo, seeing it as <code>EAG</code> but is otherwise sound:</li></ul><pre><code class="language-json">[
+    "الحياة صارت أكثر سرعة",
+    "EAG",
+    "LTE"
+  ]
+</code></pre><h3 id="hindi">Hindi</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/dabur-sarso-avala-hair-oil-ad-dainik-bhaskar-jaipur-12-12-2017.jpg" class="kg-image" alt="" width="955" height="1575" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/dabur-sarso-avala-hair-oil-ad-dainik-bhaskar-jaipur-12-12-2017.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/dabur-sarso-avala-hair-oil-ad-dainik-bhaskar-jaipur-12-12-2017.jpg 955w" sizes="(min-width: 720px) 720px"></figure><ul><li>GPT-4V:</li></ul><pre><code class="language-json">[
+"सरसों और आंवला",
+"का पोषण बिना चिपचिपाहट",
+"सिर्फ रु",
+"9 में",
+"40ml",
+"डाबर",
+"टोल फ्री 1800-103-1644"
+]
+</code></pre><ul><li>SceneXplain:</li></ul><pre><code class="language-json">[
+    "सरसों आँवला",
+    "केश तेल",
+    "सरसों और आँवला",
+    "का पोषण बिना",
+    "चिपचिपाहट",
+    "में",
+    "नया",
+    "पैक",
+    "₹9/-",
+    "सरसों आँवला",
+    "40ml",
+    "DABUR CARES: CALL OR WRITE",
+    "+ TOLL FREE 1800-103-1644"
+  ]
+</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/mdh-masala-ki-ek-dhamkedhar-offer-ad-hindustan-hindi-delhi-21-10-2017.jpg" class="kg-image" alt="" width="973" height="1576" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/11/mdh-masala-ki-ek-dhamkedhar-offer-ad-hindustan-hindi-delhi-21-10-2017.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/11/mdh-masala-ki-ek-dhamkedhar-offer-ad-hindustan-hindi-delhi-21-10-2017.jpg 973w" sizes="(min-width: 720px) 720px"></figure><ul><li>GPT-4V gave us the error <code>Something went wrong. If this issue persists please contact us through our help center at help.openai.com</code>. After retrying, it gave us:</li></ul><pre><code class="language-json">[
+"MDH की एक",
+"धमाकेदार ऑफर",
+"स्वाद के साथ - साथ खुशियों की बौछार !!",
+"मसाला एक स्वादिष्ट और जीवंत उपहार !!",
+"MDH",
+"मसाले",
+"असली मसाले सच-सच",
+"MDH Ltd.",
+"E-mails: delhi@mdhspices.in, rk@mdhspices.in www.mdhspices.com"
+]
+</code></pre><ul><li>SceneXplain goes much further, even extracting product names and tiny details like when the company was established:</li></ul><pre><code class="language-json">[
+    "MDH",
+    "की एक",
+    "धमाकेदार ऑफर",
+    "स्वाद के साथ -साथ खुशियों की बौछार !",
+    "मसाला पैक खरीदो और जीतो उपहार !!",
+    "एम डी एच की ओर से अपने सभी ग्राहकों के लिए एक धमाकेदार ऑफर।",
+    "किसी भी नजदीकी विक्रेता से एम डी एच मसालों के नीचे छपे पैक्स में से",
+    "कोई भी 100 ग्राम वाला पैक खरीदें और भाग्यशाली विजेता बनने का अवसर",
+    "प्राप्त करें, हो सकता है आप के लिए गए पैक के फ्लेप में उपहार का नाम हो।",
+    "असली मसाले",
+    "मसाले",
+    "सच -सच",
+    "MD H",
+    "SPICES",
+    "MD",
+    "MOH",
+    "Garam",
+    "Pav Bhaji",
+    "masala",
+    "Kitchen",
+    "Shahi Pancer",
+    "King",
+    "Chana",
+    "DEGGI",
+    "MIRCH",
+    "Chunky Chat",
+    "नियम व शर्तें :- एम डी एच मसालों के ऊपर दर्शाये गए चुनिन्दा पैक्स में से कोई भी 100 ग्राम वाला",
+    "पैक खरीदें, उसका फ्लेप खोलें, हो सकता है कि उस फ्लेप के नीचे उपहार का नाम छपा हो। उस",
+    "उपहार को प्राप्त करने के भाग्यशाली विजेता बनें। • इस स्कीम का नकद लाभ कोई भी नहीं है",
+    "लिए दिल्ली में ही लागू है • स्कीम स्टॉक रहने तक सीमित है • यह स्कीम एम डी एच के सुपर",
+    "स्टॉकिस्ट, स्टॉकिस्ट और कर्मचारियों के लिए नहीं है · कंपनी का निर्णय अंतिम और सर्वमान्य होगा",
+    "और सभी विवाद दिल्ली के न्याय क्षेत्र के अधीन होंगे। • अन्य शर्तों के लिए पैक देखें।",
+    "महाशियाँ दी हट्टी (प्रा०) लिमिटेड",
+    "9/44, कीर्ति नगर, नई दिल्ली - 110015 फोन नं० 011-41425106 - 07-08",
+    "ESTD. 1919",
+    "E-mails : delhi@mdhspices.in, rk@mdhspices.in www.mdhspices.com"
+  ]
+</code></pre><h2 id="conclusion">Conclusion</h2><p>At the end of the day, SceneXplain clearly excels in multilingual OCR compared to GPT-4V. To recap:</p><p><strong>API limits:</strong></p><ul><li>GPT-4V: 100 requests per day</li><li>SceneXplain: 5,000 credits per month on the MAX plan. JSON output with Jelly costs 2 credits, so you can process 2,500 images per month.</li></ul><p><strong>Reliability:</strong></p><ul><li>GPT-4V: Is often like “I’m sorry Dave, I’m afraid I can’t do that.”</li><li>SceneXplain: Doggedly reliable. Gets the job done.</li></ul><p><strong>Accuracy:</strong></p><ul><li>GPT-4V: hallucinates strings it believes are plausible from a given image, rather than reading the actual text.</li><li>SceneXplain: Extracts the correct text.</li></ul><p><strong>Consistency:</strong></p><ul><li>GPT-4V doesn’t just hallucinate. It hallucinates different things each time.</li><li>SceneXplain gives much more consistent output.</li></ul><p><strong>Completeness:</strong></p><ul><li>GPT-4V: Often doesn’t always extract <strong><em>all</em></strong> the strings in the image.</li><li>SceneXplain: Extracts more strings.</li></ul><p><strong>Cost:</strong></p><ul><li>GPT-4V: $0.025 per image.</li><li>SceneXplain: As low as 0.02 USD per image on the MAX plan if you enable JSON output. As low as 0.01 USD without JSON output.</li></ul><p>When you take all those factors into account, it's clear that SceneXplain is the obvious choice.</p><h2 id="get-started-with-scenexplain">Get started with SceneXplain</h2><p>Ready to explore multilingual OCR? Sign up for a free account with SceneXplain and start converting images to text easily. It's a practical, user-friendly way to manage digital documents. Get started now and see the difference SceneXplain can make!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SceneXplain - Leading AI Solution for Image Captions and Video Summaries</div><div class="kg-bookmark-description">Experience cutting-edge computer vision with our premier image captioning and video summarization algorithms. Tailored for content creators, media professionals, SEO experts, and e-commerce enterprises. Featuring multilingual support and seamless API integration. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Search is Overfitted Create; Create is Underfitted Search</title><meta charset="utf-8"><meta name="title" content="Search is Overfitted Create; Create is Underfitted Search"><meta name="description" content="The biggest competition of neural search may come from a technology that doesn't even need embeddings as an intermediate representation – an end-to-end technology that directly returns the result you want."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/search-is-overfitted-create-create-is-underfitted-search"><meta property="og:title" content="Search is Overfitted Create; Create is Underfitted Search"><meta property="og:description" content="The biggest competition of neural search may come from a technology that doesn't even need embeddings as an intermediate representation – an end-to-end technology that directly returns the result you want."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--38-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/search-is-overfitted-create-create-is-underfitted-search"><meta property="twitter:title" content="Search is Overfitted Create; Create is Underfitted Search"><meta property="twitter:description" content="The biggest competition of neural search may come from a technology that doesn't even need embeddings as an intermediate representation – an end-to-end technology that directly returns the result you want."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--38-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Search is Overfitted Create; Create is Underfitted Search</title><meta charset="utf-8"><meta name="title" content="Search is Overfitted Create; Create is Underfitted Search"><meta name="description" content="The biggest competition of neural search may come from a technology that doesn't even need embeddings as an intermediate representation – an end-to-end technology that directly returns the result you want."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/search-is-overfitted-create-create-is-underfitted-search"><meta property="og:title" content="Search is Overfitted Create; Create is Underfitted Search"><meta property="og:description" content="The biggest competition of neural search may come from a technology that doesn't even need embeddings as an intermediate representation – an end-to-end technology that directly returns the result you want."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--38-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/search-is-overfitted-create-create-is-underfitted-search"><meta property="twitter:title" content="Search is Overfitted Create; Create is Underfitted Search"><meta property="twitter:description" content="The biggest competition of neural search may come from a technology that doesn't even need embeddings as an intermediate representation – an end-to-end technology that directly returns the result you want."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--38-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Search is Overfitted Create; Create is Underfitted Search</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The biggest competition of neural search may come from a technology that doesn't even need embeddings as an intermediate representation – an end-to-end technology that directly returns the result you want.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 17, 2022 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>"So, who will be your biggest competitor?"</p><h2 id="the-tale-of-christmas-past">The tale of Christmas past</h2><p>A few days before Christmas 2019, I was sitting in a cramped boardroom, surrounded by the investment committee of our seed VC firm. We'd been there for hours, discussing back and forth. This was the final nerve-wracking round of pitching to secure the much-needed $2 million pre-seed fund for my neural search initiative: The birth of Jina AI was on the line. It was a do-or-die moment.</p><p>One of the partners, who worked at Google NY since 2005 asked me a question I'll never forget:</p><blockquote class="kg-blockquote-alt">"Who will be your biggest competitor?"</blockquote><p>"Google, Elastic, Agolia, ..." I confidently answered according to the notes I'd prepped earlier. Then I gritted my teeth, just waiting for them to ask the boring clichéd questions like "how do you compete with Google?". Before they could respond, I added "...but more serious competition may come from a technology that doesn't even need <strong>embeddings as an intermediate representation – </strong>an end-to-end technology that directly returns the result you want."</p><p>They didn't get it. They stuck to the same tired script. Banging on about competing with Google.</p><p>But times (and minds) have changed, and now they understand the technology I was talking about.</p><p><strong>That technology is generative AI. </strong></p><p>And neural search is discriminative AI.</p><p>Back then, 15 months after Google released BERT, generative AI simply wasn't the answer for scalable and high quality search. Neural search, a flexible framework that could easily operate with dense embedding representations and combine multiple subtasks was the only <em>realistic</em> way to search multimodal data.</p><h2 id="the-paradigms-they-are-achangin-the-rise-of-generative-ai">The paradigms they are a'changin': The rise of <strong>generative</strong> AI</h2><p>Since 2021, we've seen a huge paradigm shift from single-modal AI to multimodal AI in the industry:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Unlock-the-Business-Value-of-Multimodal-Data.svg" class="kg-image" alt="" width="267" height="150"></figure><p>The rise of multimodal AI can be put down to advances in two machine learning techniques over the last few years: Representation learning and transfer learning.</p><ul><li><em><em>Representation learning</em></em> lets models create common representations for all modalities.</li><li><em><em>Transfer learning</em></em> lets models first learn fundamental knowledge, then fine-tune on specific domains.</li></ul><p>In 2021 we saw CLIP, a model that captures the alignment between image and text; the following year, DALL·E 2 and Imgen generated high-quality images from text prompts. The generative art led by Stable Diffusion started from a community carnival and has now evolved into an industrial revolution. This is just the tip of a very big iceberg. In future, we'll see more AI applications move beyond one data modality and leverage relationships between different modalities. Ad-hoc approaches are going the way of the dinosaurs as boundaries between data modalities become fuzzy and meaningless.</p><p>But before we start to imagine fancy high-level AI applications, there are two fundamental problems we must solve first: search and creation.</p><p>Or should I say, search <strong><em>or</em></strong> creation?</p><h2 id="the-duality-of-search-and-creation">The duality of search and creation</h2><p>Search and creation are two sides of a coin, a duality.</p><p>To understand this, let's take text-to-image and image-to-image as examples and look at two functions:</p><pre><code class="language-python hljs"><span class="hljs-keyword">def</span> <span class="hljs-title function_">foo</span>(<span class="hljs-params">query: <span class="hljs-built_in">str</span></span>) -&gt; <span class="hljs-type">List</span>[Image]:
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Search is Overfitted Create; Create is Underfitted Search</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The biggest competition of neural search may come from a technology that doesn't even need embeddings as an intermediate representation – an end-to-end technology that directly returns the result you want.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 17, 2022 • 5 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>"So, who will be your biggest competitor?"</p><h2 id="the-tale-of-christmas-past">The tale of Christmas past</h2><p>A few days before Christmas 2019, I was sitting in a cramped boardroom, surrounded by the investment committee of our seed VC firm. We'd been there for hours, discussing back and forth. This was the final nerve-wracking round of pitching to secure the much-needed $2 million pre-seed fund for my neural search initiative: The birth of Jina AI was on the line. It was a do-or-die moment.</p><p>One of the partners, who worked at Google NY since 2005 asked me a question I'll never forget:</p><blockquote class="kg-blockquote-alt">"Who will be your biggest competitor?"</blockquote><p>"Google, Elastic, Agolia, ..." I confidently answered according to the notes I'd prepped earlier. Then I gritted my teeth, just waiting for them to ask the boring clichéd questions like "how do you compete with Google?". Before they could respond, I added "...but more serious competition may come from a technology that doesn't even need <strong>embeddings as an intermediate representation – </strong>an end-to-end technology that directly returns the result you want."</p><p>They didn't get it. They stuck to the same tired script. Banging on about competing with Google.</p><p>But times (and minds) have changed, and now they understand the technology I was talking about.</p><p><strong>That technology is generative AI. </strong></p><p>And neural search is discriminative AI.</p><p>Back then, 15 months after Google released BERT, generative AI simply wasn't the answer for scalable and high quality search. Neural search, a flexible framework that could easily operate with dense embedding representations and combine multiple subtasks was the only <em>realistic</em> way to search multimodal data.</p><h2 id="the-paradigms-they-are-achangin-the-rise-of-generative-ai">The paradigms they are a'changin': The rise of <strong>generative</strong> AI</h2><p>Since 2021, we've seen a huge paradigm shift from single-modal AI to multimodal AI in the industry:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Unlock-the-Business-Value-of-Multimodal-Data.svg" class="kg-image" alt="" width="267" height="150"></figure><p>The rise of multimodal AI can be put down to advances in two machine learning techniques over the last few years: Representation learning and transfer learning.</p><ul><li><em><em>Representation learning</em></em> lets models create common representations for all modalities.</li><li><em><em>Transfer learning</em></em> lets models first learn fundamental knowledge, then fine-tune on specific domains.</li></ul><p>In 2021 we saw CLIP, a model that captures the alignment between image and text; the following year, DALL·E 2 and Imgen generated high-quality images from text prompts. The generative art led by Stable Diffusion started from a community carnival and has now evolved into an industrial revolution. This is just the tip of a very big iceberg. In future, we'll see more AI applications move beyond one data modality and leverage relationships between different modalities. Ad-hoc approaches are going the way of the dinosaurs as boundaries between data modalities become fuzzy and meaningless.</p><p>But before we start to imagine fancy high-level AI applications, there are two fundamental problems we must solve first: search and creation.</p><p>Or should I say, search <strong><em>or</em></strong> creation?</p><h2 id="the-duality-of-search-and-creation">The duality of search and creation</h2><p>Search and creation are two sides of a coin, a duality.</p><p>To understand this, let's take text-to-image and image-to-image as examples and look at two functions:</p><pre><code class="language-python hljs"><span class="hljs-keyword">def</span> <span class="hljs-title function_">foo</span>(<span class="hljs-params">query: <span class="hljs-built_in">str</span></span>) -&gt; <span class="hljs-type">List</span>[Image]:
   ...
   
 <span class="hljs-keyword">def</span> <span class="hljs-title function_">bar</span>(<span class="hljs-params">query: Image</span>) -&gt; <span class="hljs-type">List</span>[Image]:
-  ...</code></pre><p>So, what are <code>foo</code> and <code>bar</code>? Are they search, where <code>foo</code> represents text-to-image search (CBIR) and <code>bar</code> represents the reverse image search? Or are they creation, where <code>foo</code> represents prompt-to-image generation and <code>bar</code> refers to inpainting?</p><p>Can you even tell the difference below? What are the searched results and what are the created results?</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-12.png" class="kg-image" alt="" width="1600" height="852" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-12.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-12.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>Or does it even<em> matter? </em>Search is find what you need; creation is make what you need. If a system returns the result you need, you happily take it. Does it even matter if it's from search or create?</p><p>"Oh, but it <em>does</em> matter", you might argue. "Because I don't want to see fictional product images in my e-commerce search results."</p><p>Sometimes people do indeed care about the fidelity to the database. That's easy; let's<strong> overfit a generative AI model. </strong>We'll make the model remember everything it observed from the training data, losing all generality and its ability to improvise. It will only return the training data. There you go, a search system.</p><p>A generative AI/creative AI model takes an ax to this oppressive restriction. Let the model improvise, embrace randomness, and then the vibe overpowers the fidelity. <strong>A creative AI is an underfitted search system.</strong></p><p>Ask for the moon – the future retrieval system may see no difference between search and creation. You can easily control the fidelity and improvisation with a sliding bar. <strong>The coin of search and create is in your hand.</strong></p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates.gif" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Jina-AI-Website-Banners-Templates.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Jina-AI-Website-Banners-Templates.gif 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates.gif 1440w" sizes="(min-width: 720px) 720px"><figcaption>The coin spins over and over. Which way will it land? Does it even matter any more?</figcaption></figure><h2 id="conclusion">Conclusion</h2><p>With more and more large language models (LLMs) and the rise of generative AI, using LLMs, especially pretrained language models (PTLMs), has become a popular mechanism to extract knowledge from free-form text on demand.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/1909.01066?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Language Models as Knowledge Bases?</div><div class="kg-bookmark-description">Recent progress in pretraining language models on large textual corpora ledto a surge of improvements for downstream NLP tasks. Whilst learning linguisticknowledge, these models may also be storing relational knowledge present in thetraining data, and may be able to answer queries structured as”…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/favicon.ico" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Fabio Petroni</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/icons/twitter/arxiv-logo-twitter-square.png" alt=""></div></a></figure><p>Despite the problems of reporting bias in the corpus and the lack of robustness to the query, LLMs have some quite successful downstream tasks like persona-grounded dialog, narrative story generation, and metaphor generation. There's also a recent work from COLING2022 that explores cross-modal models like CLIP as a commonsense knowledge base. <a href="https://jina.ai/news/coling2022/?ref=jina-ai-gmbh.ghost.io">You can find my notes about this paper here.</a></p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.491/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Are Visual-Linguistic Models Commonsense Knowledge Bases?</div><div class="kg-bookmark-description">Hsiu-Yu Yang, Carina Silberer. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.491.jpg" alt=""></div></a></figure><p>The day before writing this post, I read a tweet from Yann LeCun about Galactica - a generative AI with a search-like interface:</p><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 1016px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1592619400024428544&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fsearch-is-overfitted-create-create-is-underfitted-search%2F&amp;sessionId=d69a04f1879fdbadc3aeb870cfdb4a4e19ac9830&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1592619400024428544"></iframe></div>
+  ...</code></pre><p>So, what are <code>foo</code> and <code>bar</code>? Are they search, where <code>foo</code> represents text-to-image search (CBIR) and <code>bar</code> represents the reverse image search? Or are they creation, where <code>foo</code> represents prompt-to-image generation and <code>bar</code> refers to inpainting?</p><p>Can you even tell the difference below? What are the searched results and what are the created results?</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-12.png" class="kg-image" alt="" width="1600" height="852" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-12.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-12.png 1600w" sizes="(min-width: 720px) 720px"></figure><p>Or does it even<em> matter? </em>Search is find what you need; creation is make what you need. If a system returns the result you need, you happily take it. Does it even matter if it's from search or create?</p><p>"Oh, but it <em>does</em> matter", you might argue. "Because I don't want to see fictional product images in my e-commerce search results."</p><p>Sometimes people do indeed care about the fidelity to the database. That's easy; let's<strong> overfit a generative AI model. </strong>We'll make the model remember everything it observed from the training data, losing all generality and its ability to improvise. It will only return the training data. There you go, a search system.</p><p>A generative AI/creative AI model takes an ax to this oppressive restriction. Let the model improvise, embrace randomness, and then the vibe overpowers the fidelity. <strong>A creative AI is an underfitted search system.</strong></p><p>Ask for the moon – the future retrieval system may see no difference between search and creation. You can easily control the fidelity and improvisation with a sliding bar. <strong>The coin of search and create is in your hand.</strong></p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates.gif" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Jina-AI-Website-Banners-Templates.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Jina-AI-Website-Banners-Templates.gif 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates.gif 1440w" sizes="(min-width: 720px) 720px"><figcaption>The coin spins over and over. Which way will it land? Does it even matter any more?</figcaption></figure><h2 id="conclusion">Conclusion</h2><p>With more and more large language models (LLMs) and the rise of generative AI, using LLMs, especially pretrained language models (PTLMs), has become a popular mechanism to extract knowledge from free-form text on demand.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/1909.01066?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Language Models as Knowledge Bases?</div><div class="kg-bookmark-description">Recent progress in pretraining language models on large textual corpora ledto a surge of improvements for downstream NLP tasks. Whilst learning linguisticknowledge, these models may also be storing relational knowledge present in thetraining data, and may be able to answer queries structured as”…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/favicon.ico" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Fabio Petroni</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/icons/twitter/arxiv-logo-twitter-square.png" alt=""></div></a></figure><p>Despite the problems of reporting bias in the corpus and the lack of robustness to the query, LLMs have some quite successful downstream tasks like persona-grounded dialog, narrative story generation, and metaphor generation. There's also a recent work from COLING2022 that explores cross-modal models like CLIP as a commonsense knowledge base. <a href="https://jina.ai/news/coling2022/?ref=jina-ai-gmbh.ghost.io">You can find my notes about this paper here.</a></p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://aclanthology.org/2022.coling-1.491/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Are Visual-Linguistic Models Commonsense Knowledge Bases?</div><div class="kg-bookmark-description">Hsiu-Yu Yang, Carina Silberer. Proceedings of the 29th International Conference on Computational Linguistics. 2022.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://aclanthology.org/aclicon.ico" alt=""><span class="kg-bookmark-author">ACL Anthology</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://aclanthology.org/thumb/2022.coling-1.491.jpg" alt=""></div></a></figure><p>The day before writing this post, I read a tweet from Yann LeCun about Galactica - a generative AI with a search-like interface:</p><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 1016px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1592619400024428544&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fsearch-is-overfitted-create-create-is-underfitted-search%2F&amp;sessionId=05dec06edca40e39139d45d3713f5f460e2883af&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1592619400024428544"></iframe></div>
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 </figure><p>From a quick test, it did a decent job at creating an academic tone of voice, but rapidly drifted far off-topic, and had limited domain knowledge. Nevertheless, it's another milestone for generative AI.</p><p>Go ahead. Flip the coin. Watch as it tumbles through the air, flipping end over end. Our eyes never drift from its path. 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Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. Navigating enterprise mazes &amp; startup vibes. 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Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 25, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_modern_geometric_abstract_pattern_featuring_pu_24e4060e-dc76-4186-afb7-94d18d266b41.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Search PDFs with AI and Python: Part 1</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">I know several folks already building PDF search engines powered by AI, so I figured I’d give it a stab too. How hard could it possibly be? Part I</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 01, 2022 • 13 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Alternative title: the joys and headaches of trying to process Turing-complete file formats</div></div><p>With neural search seeing rapid adoption, more people are looking at using it for indexing and searching through their unstructured data. I know several folks already building PDF search engines powered by AI, so I figured I’d give it a stab too. How hard could it possibly be?</p><p>The answer: <strong>very.</strong></p><p>This will be part 1 of <em>3</em> posts that walk you through creating a PDF neural search engine using Python:</p><ol><li>In this post we’ll cover how to extract the images and text from PDFs, process them, and store them in a sane way.</li><li>For the next post we’ll look at feeding these into <a href="https://openai.com/blog/clip/?ref=jina-ai-gmbh.ghost.io" rel="noopener">CLIP</a>, a deep learning model that “understands” text and images. After extracting our PDF’s text and images, CLIP will generate a semantically-useful index that we can search by giving it an image or text as input (and it’ll <em>understand</em> the input semantically, not just match keywords or pixels).</li><li>Next we’ll look at how to search through that index using a client and <a href="https://streamlit.io/?ref=jina-ai-gmbh.ghost.io" rel="noopener">Streamlit</a> frontend.</li><li>Finally we’ll look at some other useful tasks, like extracting metadata.</li></ol><p>This is just a rough and ready roadmap — so stay tuned to see how things really pan out.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/alexcg1/example-pdf-search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - alexcg1/example-pdf-search: Search PDFs using Jina, Docarray and Jina Hub</div><div class="kg-bookmark-description">This search engine will index a folder of PDF files, break them down into chunks, and then let you search using text or…</div><div class="kg-bookmark-metadata"><span class="kg-bookmark-author">github.com</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="&quot;https://cdn-images-1.medium.com/fit/c/320/320/0*rc1GZtQ-1BYqXXCu&quot;" alt=""></div></a><figcaption>If you want to follow along at home (and maybe fix a few of my bugs!), check the repo</figcaption></figure><h3 id="use-case">Use case</h3><p>I want to build a search engine for a dataset of arbitrary PDFs. A user can type in text or upload an image, and the search engine will return similar images and text snippets, with a link to the original PDF they came from.</p><p>Looking back, “arbitrary” might be where things started to go wrong. Because arbitrary can be pretty broad when it comes to PDFs:</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">The full PDF specification is notoriously bloated. For example, in a PDF viewer which supports enough of the PDF spec, like the Google Chrome Browser, <a href="https://www.gwern.net/docs/www/rawgit.com/2248e6fe4ec4b6283e93210b9d1d35fadb30fbb8.pdf?ref=jina-ai-gmbh.ghost.io" rel="archived alternate nofollow noopener noopener">one can play Breakout</a> (because PDF includes its own weird subset of JavaScript). The Adobe PDF viewer includes functionality as far afield as 3D CAD support. (via <a href="https://www.gwern.net/Turing-complete?ref=jina-ai-gmbh.ghost.io#fn3" rel="noopener">gwern.net</a>)</div></div><h3 id="how-hard-can-it-be-though">How hard can it be though?</h3><p>If we’re just talking using a model to index text and images? Not very.</p><p>If we’re talking actually getting the data out of the PDFs and into a usable format? Ohhhh boy…</p><p>I mean the <a href="https://www.iso.org/standard/75839.html?ref=jina-ai-gmbh.ghost.io" rel="noopener">spec</a> is only 900-something pages long:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://cdn-images-1.medium.com/max/1600/1*yGHUQhpb7nCzYV9XC-jp3w.png" class="kg-image" alt="" width="1063" height="316"></figure><p>As anyone who’s spent any time in data science knows, wrangling the data into a usable state is 90% of the job. So that’s what we’ll focus on in this post. In future posts we’ll look at how to actually search through that data.</p><h3 id="our-tech-stack">Our tech stack</h3><p>Since this task is a whole search pipeline that deals with different kinds of data, we’ll use some specialist tools to get this done</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/docarray?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store</div><div class="kg-bookmark-description">🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store - GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Se...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/438303578/57aae8cb-5b20-4e35-a46c-9a742af1470c" alt=""></div></a><figcaption>DocArray: a data structure for unstructured data. This will wrap our PDF files, text chunks, image chunks, and any other inputs/outputs of our search engine.</figcaption></figure><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps</div><div class="kg-bookmark-description">🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps - GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cl...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/6d66c5cb-b3e8-4bc2-b2ee-b01b9d90933d" alt=""></div></a><figcaption>Jina: build a processing pipeline and neural search engine for our DocArray Documents, and scale up to serve on the cloud.</figcaption></figure><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">MLops platform to build neural search and multimodal data services in the cloud at scale</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""><span class="kg-bookmark-author">Jina AI Cloud</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a><figcaption>Executor Hub — so we don’t have to build every single little processing unit. Instead we can just pull them from the cloud.</figcaption></figure><p>We may throw in a few others tools along the way for certain processing tasks, but the ones above are the big three.</p><h3 id="so-how-could-we-do-this">So, how could we do this?</h3><p>Off the top of my head…</p><ul><li>Take a PDF file and use Jina Hub’s <a href="https://hub.jina.ai/executor/x9w7lcwg?ref=jina-ai-gmbh.ghost.io" rel="noopener">PDFSegmenter</a> to extract the text and images into chunks.</li><li>Screenshot every page of the PDF with <a href="https://imagemagick.org/?ref=jina-ai-gmbh.ghost.io" rel="noopener">ImageMagick</a> and OCR it.</li><li>Convert the PDF to HTML using something like <a href="https://pandoc.org/?ref=jina-ai-gmbh.ghost.io" rel="noopener">Pandoc</a> , extracting images to a directory and then converting the HTML to text using Pandoc again. Or something like this with similar tools.</li></ul><p>I went with the first option since I didn’t want to <a href="https://seths.blog/2005/03/dont_shave_that/?ref=jina-ai-gmbh.ghost.io" rel="noopener">shave too many yaks</a>.</p><h3 id="getting-our-pdf">Getting our PDF</h3><p>First, we need a sample file. Let’s just print-to-PDF an entry from Wikipedia, in this case the “<a href="https://en.wikipedia.org/wiki/Rabbit?ref=jina-ai-gmbh.ghost.io" rel="noopener">Rabbit</a>” article:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://cdn-images-1.medium.com/max/1600/1*fH4EpINUZXsNsRWomP76uA.png" class="kg-image" alt="" width="737" height="643"></figure><p>You can find the resulting PDF <a href="https://github.com/alexcg1/example-pdf-search/blob/main/data/rabbit.pdf?ref=jina-ai-gmbh.ghost.io" rel="noopener">here</a>.</p><h4 id="footguns">Footguns</h4><p>A <a href="https://en.wiktionary.org/wiki/footgun?ref=jina-ai-gmbh.ghost.io" rel="noopener">footgun</a> is a thing that will shoot you in the foot. Rest assured you will find many of them when you attempt to work with PDFs. These ones just involve generating a PDF to work with!</p><ul><li>Firefox and Chrome create PDFs that are slightly different. In my experience Firefox tried to be fancy about glyphs, turning <code>scientific</code> into <code>scientific</code> . I’ve got enough potential PDF headaches to last a lifetime, so to be safe I used the Chrome version. YMMV.</li><li>Headers, footers, etc should be disabled, otherwise our index will be full of <code>page 4/798</code> and similar.</li><li>Maybe try changing the paper size to avoid page breaks?</li></ul><p>Of course, for your own use case you may be searching PDFs you didn’t create yourself. Be sure to let us know your own personal footgun collection!</p><h3 id="extracting-text-and-images">Extracting text and images</h3><p>Now that we have our PDF, we can run it through a Jina <a href="https://docs.jina.ai/fundamentals/flow/?ref=jina-ai-gmbh.ghost.io" rel="noopener">Flow</a> (using a <a href="https://docs.jina.ai/fundamentals/executor/hub/?ref=jina-ai-gmbh.ghost.io" rel="noopener">Hub Executor</a>) to extract our data. A Flow refers to a pipeline in Jina that performs a “big” task, like building up a searchable index of our PDF documents, or searching through said index.</p><p>Each Flow is made up of several <a href="https://docs.jina.ai/fundamentals/executor/?ref=jina-ai-gmbh.ghost.io" rel="noopener">Executors</a>, each of which perform a simpler task. These are chained together, so any Document fed into one end will be processed by each Executor in turn and then the processed version will pop out of the other end.</p><p>In our Flow we’ll start with just one Executor, <a href="https://hub.jina.ai/executor/x9w7lcwg?ref=jina-ai-gmbh.ghost.io" rel="noopener">PDFSegmenter</a>, which we’ll pull from Jina Hub. With Jina <a href="https://medium.com/jina-ai/jina-executor-sandbox-processing-data-in-the-cloud-cb9f12ee4715?source=collection_home---------3----------------------------">Sandbox</a> we can even run it in the cloud so we don’t have to use local compute:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Search PDFs with AI and Python: Part 1</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">I know several folks already building PDF search engines powered by AI, so I figured I’d give it a stab too. How hard could it possibly be? Part I</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 01, 2022 • 13 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Alternative title: the joys and headaches of trying to process Turing-complete file formats</div></div><p>With neural search seeing rapid adoption, more people are looking at using it for indexing and searching through their unstructured data. I know several folks already building PDF search engines powered by AI, so I figured I’d give it a stab too. How hard could it possibly be?</p><p>The answer: <strong>very.</strong></p><p>This will be part 1 of <em>3</em> posts that walk you through creating a PDF neural search engine using Python:</p><ol><li>In this post we’ll cover how to extract the images and text from PDFs, process them, and store them in a sane way.</li><li>For the next post we’ll look at feeding these into <a href="https://openai.com/blog/clip/?ref=jina-ai-gmbh.ghost.io" rel="noopener">CLIP</a>, a deep learning model that “understands” text and images. After extracting our PDF’s text and images, CLIP will generate a semantically-useful index that we can search by giving it an image or text as input (and it’ll <em>understand</em> the input semantically, not just match keywords or pixels).</li><li>Next we’ll look at how to search through that index using a client and <a href="https://streamlit.io/?ref=jina-ai-gmbh.ghost.io" rel="noopener">Streamlit</a> frontend.</li><li>Finally we’ll look at some other useful tasks, like extracting metadata.</li></ol><p>This is just a rough and ready roadmap — so stay tuned to see how things really pan out.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/alexcg1/example-pdf-search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - alexcg1/example-pdf-search: Search PDFs using Jina, Docarray and Jina Hub</div><div class="kg-bookmark-description">This search engine will index a folder of PDF files, break them down into chunks, and then let you search using text or…</div><div class="kg-bookmark-metadata"><span class="kg-bookmark-author">github.com</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="&quot;https://cdn-images-1.medium.com/fit/c/320/320/0*rc1GZtQ-1BYqXXCu&quot;" alt=""></div></a><figcaption>If you want to follow along at home (and maybe fix a few of my bugs!), check the repo</figcaption></figure><h3 id="use-case">Use case</h3><p>I want to build a search engine for a dataset of arbitrary PDFs. A user can type in text or upload an image, and the search engine will return similar images and text snippets, with a link to the original PDF they came from.</p><p>Looking back, “arbitrary” might be where things started to go wrong. Because arbitrary can be pretty broad when it comes to PDFs:</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">The full PDF specification is notoriously bloated. For example, in a PDF viewer which supports enough of the PDF spec, like the Google Chrome Browser, <a href="https://www.gwern.net/docs/www/rawgit.com/2248e6fe4ec4b6283e93210b9d1d35fadb30fbb8.pdf?ref=jina-ai-gmbh.ghost.io" rel="archived alternate nofollow noopener noopener">one can play Breakout</a> (because PDF includes its own weird subset of JavaScript). The Adobe PDF viewer includes functionality as far afield as 3D CAD support. (via <a href="https://www.gwern.net/Turing-complete?ref=jina-ai-gmbh.ghost.io#fn3" rel="noopener">gwern.net</a>)</div></div><h3 id="how-hard-can-it-be-though">How hard can it be though?</h3><p>If we’re just talking using a model to index text and images? Not very.</p><p>If we’re talking actually getting the data out of the PDFs and into a usable format? Ohhhh boy…</p><p>I mean the <a href="https://www.iso.org/standard/75839.html?ref=jina-ai-gmbh.ghost.io" rel="noopener">spec</a> is only 900-something pages long:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://cdn-images-1.medium.com/max/1600/1*yGHUQhpb7nCzYV9XC-jp3w.png" class="kg-image" alt="" width="1063" height="316"></figure><p>As anyone who’s spent any time in data science knows, wrangling the data into a usable state is 90% of the job. So that’s what we’ll focus on in this post. In future posts we’ll look at how to actually search through that data.</p><h3 id="our-tech-stack">Our tech stack</h3><p>Since this task is a whole search pipeline that deals with different kinds of data, we’ll use some specialist tools to get this done</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/docarray?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store</div><div class="kg-bookmark-description">🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store - GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Se...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/438303578/57aae8cb-5b20-4e35-a46c-9a742af1470c" alt=""></div></a><figcaption>DocArray: a data structure for unstructured data. This will wrap our PDF files, text chunks, image chunks, and any other inputs/outputs of our search engine.</figcaption></figure><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps</div><div class="kg-bookmark-description">🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps - GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cl...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/6d66c5cb-b3e8-4bc2-b2ee-b01b9d90933d" alt=""></div></a><figcaption>Jina: build a processing pipeline and neural search engine for our DocArray Documents, and scale up to serve on the cloud.</figcaption></figure><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">MLops platform to build neural search and multimodal data services in the cloud at scale</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""><span class="kg-bookmark-author">Jina AI Cloud</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a><figcaption>Executor Hub — so we don’t have to build every single little processing unit. Instead we can just pull them from the cloud.</figcaption></figure><p>We may throw in a few others tools along the way for certain processing tasks, but the ones above are the big three.</p><h3 id="so-how-could-we-do-this">So, how could we do this?</h3><p>Off the top of my head…</p><ul><li>Take a PDF file and use Jina Hub’s <a href="https://hub.jina.ai/executor/x9w7lcwg?ref=jina-ai-gmbh.ghost.io" rel="noopener">PDFSegmenter</a> to extract the text and images into chunks.</li><li>Screenshot every page of the PDF with <a href="https://imagemagick.org/?ref=jina-ai-gmbh.ghost.io" rel="noopener">ImageMagick</a> and OCR it.</li><li>Convert the PDF to HTML using something like <a href="https://pandoc.org/?ref=jina-ai-gmbh.ghost.io" rel="noopener">Pandoc</a> , extracting images to a directory and then converting the HTML to text using Pandoc again. Or something like this with similar tools.</li></ul><p>I went with the first option since I didn’t want to <a href="https://seths.blog/2005/03/dont_shave_that/?ref=jina-ai-gmbh.ghost.io" rel="noopener">shave too many yaks</a>.</p><h3 id="getting-our-pdf">Getting our PDF</h3><p>First, we need a sample file. Let’s just print-to-PDF an entry from Wikipedia, in this case the “<a href="https://en.wikipedia.org/wiki/Rabbit?ref=jina-ai-gmbh.ghost.io" rel="noopener">Rabbit</a>” article:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://cdn-images-1.medium.com/max/1600/1*fH4EpINUZXsNsRWomP76uA.png" class="kg-image" alt="" width="737" height="643"></figure><p>You can find the resulting PDF <a href="https://github.com/alexcg1/example-pdf-search/blob/main/data/rabbit.pdf?ref=jina-ai-gmbh.ghost.io" rel="noopener">here</a>.</p><h4 id="footguns">Footguns</h4><p>A <a href="https://en.wiktionary.org/wiki/footgun?ref=jina-ai-gmbh.ghost.io" rel="noopener">footgun</a> is a thing that will shoot you in the foot. Rest assured you will find many of them when you attempt to work with PDFs. These ones just involve generating a PDF to work with!</p><ul><li>Firefox and Chrome create PDFs that are slightly different. In my experience Firefox tried to be fancy about glyphs, turning <code>scientific</code> into <code>scientific</code> . I’ve got enough potential PDF headaches to last a lifetime, so to be safe I used the Chrome version. YMMV.</li><li>Headers, footers, etc should be disabled, otherwise our index will be full of <code>page 4/798</code> and similar.</li><li>Maybe try changing the paper size to avoid page breaks?</li></ul><p>Of course, for your own use case you may be searching PDFs you didn’t create yourself. Be sure to let us know your own personal footgun collection!</p><h3 id="extracting-text-and-images">Extracting text and images</h3><p>Now that we have our PDF, we can run it through a Jina <a href="https://docs.jina.ai/fundamentals/flow/?ref=jina-ai-gmbh.ghost.io" rel="noopener">Flow</a> (using a <a href="https://docs.jina.ai/fundamentals/executor/hub/?ref=jina-ai-gmbh.ghost.io" rel="noopener">Hub Executor</a>) to extract our data. A Flow refers to a pipeline in Jina that performs a “big” task, like building up a searchable index of our PDF documents, or searching through said index.</p><p>Each Flow is made up of several <a href="https://docs.jina.ai/fundamentals/executor/?ref=jina-ai-gmbh.ghost.io" rel="noopener">Executors</a>, each of which perform a simpler task. These are chained together, so any Document fed into one end will be processed by each Executor in turn and then the processed version will pop out of the other end.</p><p>In our Flow we’ll start with just one Executor, <a href="https://hub.jina.ai/executor/x9w7lcwg?ref=jina-ai-gmbh.ghost.io" rel="noopener">PDFSegmenter</a>, which we’ll pull from Jina Hub. With Jina <a href="https://medium.com/jina-ai/jina-executor-sandbox-processing-data-in-the-cloud-cb9f12ee4715?source=collection_home---------3----------------------------">Sandbox</a> we can even run it in the cloud so we don’t have to use local compute:</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
 <span class="hljs-keyword">from</span> jina <span class="hljs-keyword">import</span> Flow
 
 docs = DocumentArray.from_files(<span class="hljs-string">"data/*.pdf"</span>, recursive=<span class="hljs-literal">True</span>)
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="a8069cfd-6abe-4cf4-9ecc-0b556ef66218" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="a8069cfd-6abe-4cf4-9ecc-0b556ef66218" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Search PDFs with AI and Python: Part 2</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">In our previous post we looked at how (and how not) to break down PDF files into usable chunks so we could build a search engine for them. In this article, we continue our journey.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 01, 2022 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In our previous post we looked at how (and how not) to break down PDF files into usable chunks so we could build a search engine for them.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/search-pdfs-with-ai-and-python-part-1/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Search PDFs with AI and Python: Part 1</div><div class="kg-bookmark-description">I know several folks already building PDF search engines powered by AI, so I figured I’d give it a stab too. How hard could it possibly be? Part I</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--14-.png" alt=""></div></a></figure><p>We also looked at a few footguns you may encounter along the way.</p><p align="center">
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f1fce2a4-ae05-4a05-828f-693b0b482609" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f1fce2a4-ae05-4a05-828f-693b0b482609" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Search PDFs with AI and Python: Part 2</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">In our previous post we looked at how (and how not) to break down PDF files into usable chunks so we could build a search engine for them. In this article, we continue our journey.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 01, 2022 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In our previous post we looked at how (and how not) to break down PDF files into usable chunks so we could build a search engine for them.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/search-pdfs-with-ai-and-python-part-1/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Search PDFs with AI and Python: Part 1</div><div class="kg-bookmark-description">I know several folks already building PDF search engines powered by AI, so I figured I’d give it a stab too. How hard could it possibly be? Part I</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--14-.png" alt=""></div></a></figure><p>We also looked at a few footguns you may encounter along the way.</p><p align="center">
 <img loading="lazy" src="https://miro.medium.com/max/1400/0*B6RRc6a0YwSzKcON.jpg" class="kg-image" alt="" width="200">
 </p><figcaption>This is what happens when you use a vanilla sentencizer. Apparently there are no GIFs of people shooting themselves in the feet.</figcaption>
 <p></p><p>Now we’re going to take those chunks and:</p><ul><li>Encode them into vector embeddings using the <a href="https://openai.com/blog/clip/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">CLIP</a> model.</li><li>Store them in an index for easy searching.</li></ul><h2 id="encoding-our-chunks">Encoding our chunks</h2><p>By encoding our chunks we convert them into something our model (in this case CLIP) can understand. While many models are <em><em>uni-modal </em></em>(i.e. only work with one type of data, like text<em><em> or </em></em>image<em><em> or </em></em>audio), CLIP is <em><em>multi-modal</em></em>, meaning it can embed different data types into the same vector space.</p><p>This means we can search image-to-image, text-to-image, image-to-text or text-to-text. Or you could throw audio into there too. I’d rather not right now since:</p><ul><li>Typing all those option combinations takes way too long.</li><li>The PDFs we’re using (thankfully) don’t contain audio (though I’m sure the PDF spec contains <em><em>some</em></em> functionality for that because PDF doesn’t just throw in the kitchen sink but also the machine that builds the kitchen sink).</li></ul><p>Of course, if you only plan to search one type of modality (text <em><em>or</em></em> images), Jina AI Executor Hub has specific models just for those:</p><ul><li>Text: <a href="https://openai.com/blog/clip/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">TransformerTorchEncoder</a>, <a href="https://hub.jina.ai/executor/nh1ucuki?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">TransformerSentenceEncoder</a>, <a href="https://hub.jina.ai/executor/u7h7cuh2?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">SpacyTextEncoder</a></li><li>Image: <a href="https://hub.jina.ai/executor/lb8dbppn?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">ImageTorchEncoder</a></li></ul><h2 id="adding-the-encoder-executor">Adding the encoder Executor</h2><p>Previously we built a <a href="https://docs.jina.ai/fundamentals/flow/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">Flow</a> to:</p><ul><li>Extract text <a href="https://docarray.jina.ai/fundamentals/document/nested/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">chunks</a> and images.</li><li>Break down our text chunks into sentences.</li><li>Move all text chunks to the same level so things are nice and tidy.</li><li>Normalize our images ready for encoding.</li></ul><p>Our code looked something like this (including loading PDFs into <a href="https://docarray.jina.ai/fundamentals/documentarray/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">DocumentArray</a>, etc):</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> DocumentArray
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="7704b08a-4145-4e97-92a1-e727dd86a6b7" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="7704b08a-4145-4e97-92a1-e727dd86a6b7" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Search PDFs with AI and Python: Part 3</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">In part 3, let me summarize all lessons learned: pitfalls and perils of building a PDF search engine</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 01, 2022 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text"><em><em>This article is light on the code, and heavy on the lessons learned. You’ve been warned!</em></em></div></div><p>Before reading this, be sure to check the prior posts in the series:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/search-pdfs-with-ai-and-python-part-1/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Search PDFs with AI and Python: Part 1</div><div class="kg-bookmark-description">I know several folks already building PDF search engines powered by AI, so I figured I’d give it a stab too. How hard could it possibly be? Part I</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--14-.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/search-pdfs-with-ai-and-python-part-2/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Search PDFs with AI and Python: Part 2</div><div class="kg-bookmark-description">In our previous post we looked at how (and how not) to break down PDF files into usable chunks so we could build a search engine for them. In this article, we continue our journey.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--15-.png" alt=""></div></a></figure><p>I first started building my PDF search engine so the Jina AI community could have an example to fork and adapt to their needs. PDF search is a popular topic after all.</p><p>That said, there are so many different kinds of PDF content, and so many different use cases that it’s not a case of one size fits all.</p><p>My initial version is here:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/alexcg1/example-pdf-search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - alexcg1/example-pdf-search: Search PDFs using Jina, DocArray and Jina Hub</div><div class="kg-bookmark-description">Search PDFs using Jina, DocArray and Jina Hub. Contribute to alexcg1/example-pdf-search development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">alexcg1</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/bc888b060a733385177c2c3d2670ce25f9a747c9f1166990cb79e0df67c36d13/alexcg1/example-pdf-search" alt=""></div></a></figure><p>It aimed to:</p><ul><li>Be general purpose, and work well with any kind of PDF data (emphasis on work <em><em>well —</em></em> Just because it returns results doesn’t mean it’s good — it needs to return <em><em>quality</em></em> results).</li><li>Search cross-modally, so you could use image/text as both input/output.</li></ul><p>In short, the kitchen sink approach.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://media.tenor.com/OCHkd8AgnUIAAAAC/tiger-sink.gif" class="kg-image" alt="" width="320" height="184"></figure><h2 id="so-how-amazing-was-your-first-version">So, how amazing was your first version?</h2><p>The result was…sub-optimal. I used a few PDFs I downloaded from Wikipedia as an example dataset and went from there:</p><ul><li>Wikipedia page on chocolate</li><li>Wikipedia page on rabbits</li><li>Wikipedia page on tigers</li><li>Wikipedia page on Linux</li><li>Wikipedia page on cake</li></ul><p>But I forgot the cardinal rule of data science: kicking your data into shape for your use case is like 90% of the work. And since every potential use case has wildly different data, it doesn’t make much sense to spend hours kicking Wikipedia PDFs into shape. Especially since I got bad results when it came to the search.</p><p>For example, when searching “rabbit ears”:</p><ul><li>I would get short text snippets that were bare URLs (which I assume were picked up from endnotes in the article).</li><li>Or I would get strings just a few words long (which I assume were titles).</li><li>Most of these were just about rabbits, with no mention of ears, despite sentences about rabbit’s ears being indexed.</li><li>The matches that were the most relevant got a less-good score than some less-relevant matches (in cosine scores, lower score means higher relevance).</li><li>No matter what I typed, I never got any images returned (despite typing descriptions of said images and them definitely being indexed).</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://miro.medium.com/max/1400/1*8zIlhyFQA_XGxJ4uHmuvbw.png" class="kg-image" alt="" width="700" height="394"><figcaption>The results? Not great</figcaption></figure><p>On the plus side, it did bring up stuff about rabbits instead of chocolate, but that’s all that can be said for it.</p><h2 id="why-does-it-suck">Why does it suck?</h2><ul><li>Perhaps the encoder or model itself isn’t great (I’m not convinced of this — CLIP isn’t <em><em>ideal</em></em> for text, but it’s serviceable at least, as can be seen in our fashion search)</li><li>Perhaps the dataset itself is just too small (I don’t believe this. Sure, it’s just a few PDFs but it’s broken down into several thousand chunks, many of which are full sentences or images)</li><li>Perhaps the index is so full of junk (endnotes, text fragments, references to book pages) rather than “real content” (sentences about rabbit ears, etc) and the encoder just throws up its hands in despair because it can’t make any sense of most of it. (I have a hunch this may be the main issue)</li><li>Some other reason? I was trying to do so much with the initial version that it could be down to the phase of the moon for all I know. Your ideas are welcome!</li></ul><p>But we’re not retreating. Never give up, never surrender and all that. We’re just going to re-think the use case.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/TpqO6E8WtEwAAAAC/moti-run.gif" class="kg-image" alt="" width="498" height="247"><figcaption>We’re not retreating. We’re strategically reconsidering our approach with all due alacrity</figcaption></figure><h2 id="what-are-other-people-trying-to-build-and-how-do-we-adapt-our-pdf-search-to-fit">What are other people trying to build? And how do we adapt our PDF search to fit?</h2><p>I’ve been in discussions with the community about PDF search engines and their use cases. So far most people want to focus on just text. That’s a good thing!</p><p>You see, previously we were trying to search both text and images, so we needed an encoder that could embed both to a common vector space. Namely <code>CLIPEncoder</code>:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/executor/29r2b26t?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">CLIPEncoder | latest | Jina AI Cloud</div><div class="kg-bookmark-description">Encoder that embeds documents using either the CLIP vision encoder or the CLIP text encoder, dependi...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""><span class="kg-bookmark-author">CLIPEncoder | latest | Jina AI Cloud</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://api.hubble.jina.ai/v2/rpc/executor.generatePoster?id=29r2b26t" alt=""></div></a></figure><p>In my experience CLIP is pretty dang good at images, but my experience with text (i.e. the PDF search engine I’ve been building) has been not so great.</p><h2 id="what-can-we-use-instead-of-clip">What can we use instead of CLIP?</h2><p>If we’re only dealing with text we can use other encoders like:</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://cloud.jina.ai/executor/u7h7cuh2?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SpacyTextEncoder | latest | Jina AI Cloud</div><div class="kg-bookmark-description">This is a text encoder using models from Spacy...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""><span class="kg-bookmark-author">SpacyTextEncoder | latest | Jina AI Cloud</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://api.hubble.jina.ai/v2/rpc/executor.generatePoster?id=u7h7cuh2" alt=""></div></a><figcaption><strong><strong>SpacyTextEncoder</strong></strong>: supports several languages, is fast and good for general purpose text.</figcaption></figure><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://cloud.jina.ai/executor/u9pqs8eb?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">TransformerTorchEncoder | latest | Jina AI Cloud</div><div class="kg-bookmark-description">`TransformerTorchEncoder` encodes text using transformer models...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""><span class="kg-bookmark-author">TransformerTorchEncoder | latest | Jina AI Cloud</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://api.hubble.jina.ai/v2/rpc/executor.generatePoster?id=u9pqs8eb" alt=""></div></a><figcaption><strong><strong>TransformerTorchEncoder</strong>:</strong> supports a whole bunch of languages and special use cases (e.g. medical text search). Can pull any model from huggingface.</figcaption></figure><p>I’ve used both of these before, and I’m particularly fond of SpaCy. When I was <a href="https://github.com/jina-ai/example-meme-search?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">indexing meme captions</a> it took about 4 minutes to blast through 200,000 memes on my laptop. I like that kind of speed.</p><h2 id="what-exactly-will-we-build">What exactly will we build?</h2><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">More brass tacks, less kitchen sink</div></div><p>I think a ground-up approach is going to be better than a “let’s do everything” approach here. We’ll be able to see what works more clearly since there are fewer moving parts.</p><p>So we’ll build a search engine for <em><em>simple</em></em> text PDFs that don’t require too much pre-processing like:</p><ul><li>Removing page numbers.</li><li>Removing endnotes, footnotes.</li><li>Dealing with lots of references and unexpected punctuation (like <code>Fly-fishing for Dummies, 1988 Penguin Press, A.Albrechtson et al, pp.3–8. http://penguin.com/flyfishing</code>).</li><li>Merging text chunks between page breaks.</li></ul><p>In short, stripping out everything that could trip up the encoder. Once that’s up and running, we can start thinking about:</p><ul><li>More complex PDFs (ramping up gradually).</li><li>Multilingual search (models already exist for this).</li><li>Searching text and images.</li></ul><p>Ideas for simple PDFs are more than welcome! Drop a reply to this tweet if you have anything in mind, or ping me on <a href="https://slack.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">our community Slack</a>!</p><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 369px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1528719316228743169&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fsearch-pdfs-with-ai-and-python-part-3%2F&amp;sessionId=f243081edf370bf9756d4a74e9771ed3042f2e35&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1528719316228743169"></iframe></div>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Search PDFs with AI and Python: Part 3</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">In part 3, let me summarize all lessons learned: pitfalls and perils of building a PDF search engine</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 01, 2022 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text"><em><em>This article is light on the code, and heavy on the lessons learned. You’ve been warned!</em></em></div></div><p>Before reading this, be sure to check the prior posts in the series:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/search-pdfs-with-ai-and-python-part-1/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Search PDFs with AI and Python: Part 1</div><div class="kg-bookmark-description">I know several folks already building PDF search engines powered by AI, so I figured I’d give it a stab too. How hard could it possibly be? Part I</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--14-.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/search-pdfs-with-ai-and-python-part-2/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Search PDFs with AI and Python: Part 2</div><div class="kg-bookmark-description">In our previous post we looked at how (and how not) to break down PDF files into usable chunks so we could build a search engine for them. In this article, we continue our journey.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--15-.png" alt=""></div></a></figure><p>I first started building my PDF search engine so the Jina AI community could have an example to fork and adapt to their needs. PDF search is a popular topic after all.</p><p>That said, there are so many different kinds of PDF content, and so many different use cases that it’s not a case of one size fits all.</p><p>My initial version is here:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/alexcg1/example-pdf-search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - alexcg1/example-pdf-search: Search PDFs using Jina, DocArray and Jina Hub</div><div class="kg-bookmark-description">Search PDFs using Jina, DocArray and Jina Hub. Contribute to alexcg1/example-pdf-search development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">alexcg1</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/bc888b060a733385177c2c3d2670ce25f9a747c9f1166990cb79e0df67c36d13/alexcg1/example-pdf-search" alt=""></div></a></figure><p>It aimed to:</p><ul><li>Be general purpose, and work well with any kind of PDF data (emphasis on work <em><em>well —</em></em> Just because it returns results doesn’t mean it’s good — it needs to return <em><em>quality</em></em> results).</li><li>Search cross-modally, so you could use image/text as both input/output.</li></ul><p>In short, the kitchen sink approach.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://media.tenor.com/OCHkd8AgnUIAAAAC/tiger-sink.gif" class="kg-image" alt="" width="320" height="184"></figure><h2 id="so-how-amazing-was-your-first-version">So, how amazing was your first version?</h2><p>The result was…sub-optimal. I used a few PDFs I downloaded from Wikipedia as an example dataset and went from there:</p><ul><li>Wikipedia page on chocolate</li><li>Wikipedia page on rabbits</li><li>Wikipedia page on tigers</li><li>Wikipedia page on Linux</li><li>Wikipedia page on cake</li></ul><p>But I forgot the cardinal rule of data science: kicking your data into shape for your use case is like 90% of the work. And since every potential use case has wildly different data, it doesn’t make much sense to spend hours kicking Wikipedia PDFs into shape. Especially since I got bad results when it came to the search.</p><p>For example, when searching “rabbit ears”:</p><ul><li>I would get short text snippets that were bare URLs (which I assume were picked up from endnotes in the article).</li><li>Or I would get strings just a few words long (which I assume were titles).</li><li>Most of these were just about rabbits, with no mention of ears, despite sentences about rabbit’s ears being indexed.</li><li>The matches that were the most relevant got a less-good score than some less-relevant matches (in cosine scores, lower score means higher relevance).</li><li>No matter what I typed, I never got any images returned (despite typing descriptions of said images and them definitely being indexed).</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://miro.medium.com/max/1400/1*8zIlhyFQA_XGxJ4uHmuvbw.png" class="kg-image" alt="" width="700" height="394"><figcaption>The results? Not great</figcaption></figure><p>On the plus side, it did bring up stuff about rabbits instead of chocolate, but that’s all that can be said for it.</p><h2 id="why-does-it-suck">Why does it suck?</h2><ul><li>Perhaps the encoder or model itself isn’t great (I’m not convinced of this — CLIP isn’t <em><em>ideal</em></em> for text, but it’s serviceable at least, as can be seen in our fashion search)</li><li>Perhaps the dataset itself is just too small (I don’t believe this. Sure, it’s just a few PDFs but it’s broken down into several thousand chunks, many of which are full sentences or images)</li><li>Perhaps the index is so full of junk (endnotes, text fragments, references to book pages) rather than “real content” (sentences about rabbit ears, etc) and the encoder just throws up its hands in despair because it can’t make any sense of most of it. (I have a hunch this may be the main issue)</li><li>Some other reason? I was trying to do so much with the initial version that it could be down to the phase of the moon for all I know. Your ideas are welcome!</li></ul><p>But we’re not retreating. Never give up, never surrender and all that. We’re just going to re-think the use case.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/TpqO6E8WtEwAAAAC/moti-run.gif" class="kg-image" alt="" width="498" height="247"><figcaption>We’re not retreating. We’re strategically reconsidering our approach with all due alacrity</figcaption></figure><h2 id="what-are-other-people-trying-to-build-and-how-do-we-adapt-our-pdf-search-to-fit">What are other people trying to build? And how do we adapt our PDF search to fit?</h2><p>I’ve been in discussions with the community about PDF search engines and their use cases. So far most people want to focus on just text. That’s a good thing!</p><p>You see, previously we were trying to search both text and images, so we needed an encoder that could embed both to a common vector space. Namely <code>CLIPEncoder</code>:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/executor/29r2b26t?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">CLIPEncoder | latest | Jina AI Cloud</div><div class="kg-bookmark-description">Encoder that embeds documents using either the CLIP vision encoder or the CLIP text encoder, dependi...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""><span class="kg-bookmark-author">CLIPEncoder | latest | Jina AI Cloud</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://api.hubble.jina.ai/v2/rpc/executor.generatePoster?id=29r2b26t" alt=""></div></a></figure><p>In my experience CLIP is pretty dang good at images, but my experience with text (i.e. the PDF search engine I’ve been building) has been not so great.</p><h2 id="what-can-we-use-instead-of-clip">What can we use instead of CLIP?</h2><p>If we’re only dealing with text we can use other encoders like:</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://cloud.jina.ai/executor/u7h7cuh2?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">SpacyTextEncoder | latest | Jina AI Cloud</div><div class="kg-bookmark-description">This is a text encoder using models from Spacy...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""><span class="kg-bookmark-author">SpacyTextEncoder | latest | Jina AI Cloud</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://api.hubble.jina.ai/v2/rpc/executor.generatePoster?id=u7h7cuh2" alt=""></div></a><figcaption><strong><strong>SpacyTextEncoder</strong></strong>: supports several languages, is fast and good for general purpose text.</figcaption></figure><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://cloud.jina.ai/executor/u9pqs8eb?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">TransformerTorchEncoder | latest | Jina AI Cloud</div><div class="kg-bookmark-description">`TransformerTorchEncoder` encodes text using transformer models...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""><span class="kg-bookmark-author">TransformerTorchEncoder | latest | Jina AI Cloud</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://api.hubble.jina.ai/v2/rpc/executor.generatePoster?id=u9pqs8eb" alt=""></div></a><figcaption><strong><strong>TransformerTorchEncoder</strong>:</strong> supports a whole bunch of languages and special use cases (e.g. medical text search). Can pull any model from huggingface.</figcaption></figure><p>I’ve used both of these before, and I’m particularly fond of SpaCy. When I was <a href="https://github.com/jina-ai/example-meme-search?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">indexing meme captions</a> it took about 4 minutes to blast through 200,000 memes on my laptop. I like that kind of speed.</p><h2 id="what-exactly-will-we-build">What exactly will we build?</h2><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">More brass tacks, less kitchen sink</div></div><p>I think a ground-up approach is going to be better than a “let’s do everything” approach here. We’ll be able to see what works more clearly since there are fewer moving parts.</p><p>So we’ll build a search engine for <em><em>simple</em></em> text PDFs that don’t require too much pre-processing like:</p><ul><li>Removing page numbers.</li><li>Removing endnotes, footnotes.</li><li>Dealing with lots of references and unexpected punctuation (like <code>Fly-fishing for Dummies, 1988 Penguin Press, A.Albrechtson et al, pp.3–8. http://penguin.com/flyfishing</code>).</li><li>Merging text chunks between page breaks.</li></ul><p>In short, stripping out everything that could trip up the encoder. Once that’s up and running, we can start thinking about:</p><ul><li>More complex PDFs (ramping up gradually).</li><li>Multilingual search (models already exist for this).</li><li>Searching text and images.</li></ul><p>Ideas for simple PDFs are more than welcome! Drop a reply to this tweet if you have anything in mind, or ping me on <a href="https://slack.jina.ai/?ref=jina-ai-gmbh.ghost.io" rel="noopener ugc nofollow">our community Slack</a>!</p><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 369px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1528719316228743169&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fsearch-pdfs-with-ai-and-python-part-3%2F&amp;sessionId=1ed4d8563e2279b256269af4574ada67858e5703&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1528719316228743169"></iframe></div>
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 </figure><h2 id="next-time">Next time</h2><p>Stay tuned for part 4 in this seemingly infinite saga of blog posts, where we’ll refactor our code and choose a simpler dataset and go from there. Fingers crossed!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fsearch-pdfs-with-ai-and-python-part-3%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Search R Questions on Stack Overflow with Python</title><meta charset="utf-8"><meta name="title" content="Search R Questions on Stack Overflow with Python"><meta name="description" content="Build and deploy a knowledge base search app to Jina AI Cloud in under 50 lines of code and 10 minutes. Here is how you do it."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/search-r-questions-on-stack-overflow-with-python"><meta property="og:title" content="Search R Questions on Stack Overflow with Python"><meta property="og:description" content="Build and deploy a knowledge base search app to Jina AI Cloud in under 50 lines of code and 10 minutes. Here is how you do it."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--20-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/search-r-questions-on-stack-overflow-with-python"><meta property="twitter:title" content="Search R Questions on Stack Overflow with Python"><meta property="twitter:description" content="Build and deploy a knowledge base search app to Jina AI Cloud in under 50 lines of code and 10 minutes. Here is how you do it."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--20-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Search R Questions on Stack Overflow with Python</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Build and deploy a knowledge base search app to Jina AI Cloud in under 50 lines of code and 10 minutes. Here is how you do it.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 04, 2022 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In this article I'm deploying a simple Jina app to the Jina AI Cloud. This app allows users to input a text query and then retrieve question-answer pairs, where the question semantically matches the given query. It's a pretty straightforward search app, and I want to use it to<strong> demonstrate how easy it is to take such apps from zero to ready-to-serve in 10 minutes.</strong></p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://www.kaggle.com/datasets/stackoverflow/rquestions?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">R Questions from Stack Overflow</div><div class="kg-bookmark-description">Full text of Stack Overflow Q&amp;A about the R statistical programming language</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.kaggle.com/static/images/favicon.ico" alt=""><span class="kg-bookmark-author">Kaggle</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://storage.googleapis.com/kaggle-datasets-images/260/571/d27c369385766a3f60f3cdd1953f921d/dataset-card.jpg" alt=""></div></a><figcaption>The dataset we will be using in this article</figcaption></figure><p>Wait…for R? Not&nbsp;Python?! Well, the code itself is in Python. Only the dataset is related to R questions.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">It turns out the <a href="https://www.kaggle.com/datasets/stackoverflow/pythonquestions?ref=jina-ai-gmbh.ghost.io">Python Stack Overflow dataset</a> has some encoding issues. Even a bunch of <code>try...excepts</code> didn't help much, so I decided to spend time on a dataset that didn't have such problems. The <a href="https://www.kaggle.com/datasets/stackoverflow/rquestions?ref=jina-ai-gmbh.ghost.io">R dataset</a> was next on the list and it works fine.</div></div><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/ZNeu_ZL5GcUAAAAC/twist-but-heres-the-twist.gif" class="kg-image" alt="" width="498" height="280"><figcaption>The title of this post serves as a plot twist (and click-bait)</figcaption></figure><h2 id="our-tech-stack">Our tech stack</h2><p>To build our search app we'll use:</p><h3 id="docarray">DocArray</h3><p>Everything going in or out of a Jina Flow has to be a <a href="https://docarray.jina.ai/fundamentals/document/?ref=jina-ai-gmbh.ghost.io">Document</a>, (Documents are Jina's primitive data type.) This comes from the DocArray package, which is ideal for working with unstructured data.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/docarray?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store</div><div class="kg-bookmark-description">🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store - GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Se...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/438303578/57aae8cb-5b20-4e35-a46c-9a742af1470c" alt=""></div></a></figure><h3 id="jina">Jina</h3><p>Jina is a framework that lets us build cross-modal and multi-modal applications on the cloud.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps</div><div class="kg-bookmark-description">🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps - GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cl...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/6d66c5cb-b3e8-4bc2-b2ee-b01b9d90933d" alt=""></div></a></figure><p>In short we'll use a Jina <a href="https://docs.jina.ai/fundamentals/flow/?ref=jina-ai-gmbh.ghost.io">Flow</a> and some <a href="https://docs.jina.ai/fundamentals/executor/?ref=jina-ai-gmbh.ghost.io">Executors</a> (from <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Executor Hub</a>) to process and create <a href="https://en.wikipedia.org/wiki/Word_embedding?ref=jina-ai-gmbh.ghost.io">vector embeddings</a> for our Stack Overflow questions.</p><h3 id="jina-ai-cloud">Jina AI Cloud</h3><p>Jina AI Cloud is a free-hosting platform for Jina applications. We can then index and query data without using any of our own compute.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">The most advanced MLOps platform for multimodal AI, neural search and creative AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a></figure><h2 id="how-it-works">How it&nbsp;works</h2><h3 id="build-deploy">Build &amp; Deploy</h3><p>We first build a Jina Flow, deploy it on the Jina AI Cloud. Later we will use the Jina Client to send data for indexing and searching.</p><p><strong>Write the Flow</strong></p><p>To do this we simply need our Flow in <a href="https://docs.jina.ai/fundamentals/flow/yaml-spec/?ref=jina-ai-gmbh.ghost.io">YAML format</a>:</p><pre><code class="language-yaml hljs"><span class="hljs-attr">jtype:</span> <span class="hljs-string">Flow</span>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Search R Questions on Stack Overflow with Python</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Build and deploy a knowledge base search app to Jina AI Cloud in under 50 lines of code and 10 minutes. Here is how you do it.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 04, 2022 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In this article I'm deploying a simple Jina app to the Jina AI Cloud. This app allows users to input a text query and then retrieve question-answer pairs, where the question semantically matches the given query. It's a pretty straightforward search app, and I want to use it to<strong> demonstrate how easy it is to take such apps from zero to ready-to-serve in 10 minutes.</strong></p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://www.kaggle.com/datasets/stackoverflow/rquestions?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">R Questions from Stack Overflow</div><div class="kg-bookmark-description">Full text of Stack Overflow Q&amp;A about the R statistical programming language</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.kaggle.com/static/images/favicon.ico" alt=""><span class="kg-bookmark-author">Kaggle</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://storage.googleapis.com/kaggle-datasets-images/260/571/d27c369385766a3f60f3cdd1953f921d/dataset-card.jpg" alt=""></div></a><figcaption>The dataset we will be using in this article</figcaption></figure><p>Wait…for R? Not&nbsp;Python?! Well, the code itself is in Python. Only the dataset is related to R questions.</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">It turns out the <a href="https://www.kaggle.com/datasets/stackoverflow/pythonquestions?ref=jina-ai-gmbh.ghost.io">Python Stack Overflow dataset</a> has some encoding issues. Even a bunch of <code>try...excepts</code> didn't help much, so I decided to spend time on a dataset that didn't have such problems. The <a href="https://www.kaggle.com/datasets/stackoverflow/rquestions?ref=jina-ai-gmbh.ghost.io">R dataset</a> was next on the list and it works fine.</div></div><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://media.tenor.com/ZNeu_ZL5GcUAAAAC/twist-but-heres-the-twist.gif" class="kg-image" alt="" width="498" height="280"><figcaption>The title of this post serves as a plot twist (and click-bait)</figcaption></figure><h2 id="our-tech-stack">Our tech stack</h2><p>To build our search app we'll use:</p><h3 id="docarray">DocArray</h3><p>Everything going in or out of a Jina Flow has to be a <a href="https://docarray.jina.ai/fundamentals/document/?ref=jina-ai-gmbh.ghost.io">Document</a>, (Documents are Jina's primitive data type.) This comes from the DocArray package, which is ideal for working with unstructured data.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/docarray?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store</div><div class="kg-bookmark-description">🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store - GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Se...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/438303578/57aae8cb-5b20-4e35-a46c-9a742af1470c" alt=""></div></a></figure><h3 id="jina">Jina</h3><p>Jina is a framework that lets us build cross-modal and multi-modal applications on the cloud.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps</div><div class="kg-bookmark-description">🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps - GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cl...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/6d66c5cb-b3e8-4bc2-b2ee-b01b9d90933d" alt=""></div></a></figure><p>In short we'll use a Jina <a href="https://docs.jina.ai/fundamentals/flow/?ref=jina-ai-gmbh.ghost.io">Flow</a> and some <a href="https://docs.jina.ai/fundamentals/executor/?ref=jina-ai-gmbh.ghost.io">Executors</a> (from <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Executor Hub</a>) to process and create <a href="https://en.wikipedia.org/wiki/Word_embedding?ref=jina-ai-gmbh.ghost.io">vector embeddings</a> for our Stack Overflow questions.</p><h3 id="jina-ai-cloud">Jina AI Cloud</h3><p>Jina AI Cloud is a free-hosting platform for Jina applications. We can then index and query data without using any of our own compute.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">The most advanced MLOps platform for multimodal AI, neural search and creative AI</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a></figure><h2 id="how-it-works">How it&nbsp;works</h2><h3 id="build-deploy">Build &amp; Deploy</h3><p>We first build a Jina Flow, deploy it on the Jina AI Cloud. Later we will use the Jina Client to send data for indexing and searching.</p><p><strong>Write the Flow</strong></p><p>To do this we simply need our Flow in <a href="https://docs.jina.ai/fundamentals/flow/yaml-spec/?ref=jina-ai-gmbh.ghost.io">YAML format</a>:</p><pre><code class="language-yaml hljs"><span class="hljs-attr">jtype:</span> <span class="hljs-string">Flow</span>
 <span class="hljs-attr">with:</span>
   <span class="hljs-attr">protocol:</span> <span class="hljs-string">grpc</span>
 <span class="hljs-attr">executors:</span>
@@ -56,4 +56,4 @@
 <span class="hljs-bullet">-</span> How to calculate marginal probabilities for generating correlated binary variables</code></pre><h2 id="more-user-friendly">More user-friendly</h2><p>By running our Flow on Jina AI Cloud it’s already most of the way there when it comes to production readiness (depending on your use case). The main thing to do next would be to integrate a nice frontend so users can interact directly.</p><p>For inspiration, you can see my Streamlit <code>frontend</code>folder in the project’s repo:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/alexcg1/example-knowledge-base-stackoverflow?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - alexcg1/example-knowledge-base-stackoverflow: Stack Overflow search engine using Jina</div><div class="kg-bookmark-description">Stack Overflow search engine using Jina. Contribute to alexcg1/example-knowledge-base-stackoverflow development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">alexcg1</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/63fd98b9ad47cb8508b7d66597546d3c736b844e3d739e39da02ab20f8646c70/alexcg1/example-knowledge-base-stackoverflow" alt=""></div></a></figure><p>Essentially it acts as a wrapper for:</p><ul><li>Jina Client — retrieves matching questions given a search term.</li><li>SQLite — retrieves matching answers based on the questions that come up.</li></ul><h2 id="%F0%9F%8E%89-thats-it">🎉 That's it!</h2><p>...Or is it?</p>
 <p align="center">
 <img loading="lazy" src="https://media.tenor.com/BNfECvwSiIkAAAAC/i-have-a-question-questions.gif" class="kg-image" alt="" width="200">
-</p><h3 id="this-is-running-on-grpc-how-can-we-use-a-restful-interface">This is running on gRPC. How can we use a RESTful interface?</h3><p>I chose to run on gRPC because it’s more efficient that HTTP. That said, Jina also suports HTTP and WebSocket gateways. To deploy a RESTful Flow:</p><ul><li>Set <code>protocol</code> to <code>http</code> in your Flow YAML before deploying.</li><li>Set a lower <code>request_size</code> to compensate for HTTP's lower efficiency.</li></ul><h3 id="but-what-about-the-answers">But what about the answers?</h3><p>I decided for this quick example to just store the answers in a SQLite database and retrieve them via a function in the frontend. The database is stored on the same machine as my frontend code so access is easy.</p><p>I created the database using the awesome <a href="https://pypi.org/project/csv-to-sqlite/?ref=jina-ai-gmbh.ghost.io">csv_to_sqlite</a> Python package.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://pypi.org/project/csv-to-sqlite/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">csv-to-sqlite</div><div class="kg-bookmark-description">A script that processes the input CSV files and copies them into a SQLite database.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://pypi.org/static/images/favicon.6a76275d.ico" alt=""><span class="kg-bookmark-author">PyPI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://pypi.org/static/images/twitter.6fecba6f.jpg" alt=""></div></a></figure><h3 id="why-not-store-the-answers-as-foo-or-bar-or-%E2%80%A6">Why not store the answers as &lt;foo&gt; or &lt;bar&gt; or …?</h3><p>Essentially the answer to many of these questions is:</p><ul><li>For this example I’m only searching the question text, so the only interaction the Flow would have with the answers would be storing them in the index anyway, without embeddings.</li><li>That would mean uploading 237mb to the cloud. I remember the days of 1.44mb floppy disks, so 237mb seems like a lot to my wrinkly old self.</li><li>So why <em>not</em> just put that data in a SQLite file? It seems easy enough, and there are no extra dependencies since the <code>sqlite3</code> library comes with Python anyhow.</li></ul><h3 id="but-if-we-did-want-to-process-the-answers%E2%80%A6">But if we did want to process the answers…?</h3><p>If we just wanted to <strong>store the answers in the index</strong> we could write a function to embed each question’s answer in <code>Document.tags["answers"]</code> as a list element.</p><p>If we wanted to <strong>create and search embeddings for the answers</strong> we could create a sub-Document for each answer in a question’s <code><a href="https://docarray.jina.ai/fundamentals/document/construct/?ref=jina-ai-gmbh.ghost.io#nested-document">Document.chunks</a></code> and then decide what <code><a href="https://docarray.jina.ai/fundamentals/documentarray/access-elements/?highlight=traversal+paths&amp;ref=jina-ai-gmbh.ghost.io#index-by-nested-structure">access_path</a></code> we want to use for searching.</p><p>Either way, it would’ve meant writing a function to match questions and answers from two CSV files. Considering the trouble I’d already had with the Python Stack Overflow CSV file above, I decided I’d had enough of CSVs for one day. Maybe in a future example.</p><h3 id="how-can-we-get-better-results">How can we get better results?</h3><p>Since Stack Overflow is all about code, you may want to use <code><a href="https://cloud.jina.ai/executor/u9pqs8eb?ref=jina-ai-gmbh.ghost.io">TransformerTorchEncoder</a></code> with a more language-specific model (like <a href="https://huggingface.co/tals/roberta_python?ref=jina-ai-gmbh.ghost.io">roberta-python</a> for Python. I tried finding one for R but turns out a query that is a language name with just one letter doesn’t play well with Hugging Face’s search engine…)</p><h3 id="how-can-we-use-jina-to-search-the-actual-stack-overflow-not-just-a-dataset">How can we use Jina to search the actual Stack Overflow, not just a dataset?</h3><p>Good luck with that! You’d need to scrape the whole site, which Stack Overflow may not be too happy about. That would be a lot of work and potentially legal headaches. That's not to mention keeping it up-to-date. The actual Stack Overflow is constantly updated. So you might need to invest in some compute!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fsearch-r-questions-on-stack-overflow-with-python%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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+</p><h3 id="this-is-running-on-grpc-how-can-we-use-a-restful-interface">This is running on gRPC. How can we use a RESTful interface?</h3><p>I chose to run on gRPC because it’s more efficient that HTTP. That said, Jina also suports HTTP and WebSocket gateways. To deploy a RESTful Flow:</p><ul><li>Set <code>protocol</code> to <code>http</code> in your Flow YAML before deploying.</li><li>Set a lower <code>request_size</code> to compensate for HTTP's lower efficiency.</li></ul><h3 id="but-what-about-the-answers">But what about the answers?</h3><p>I decided for this quick example to just store the answers in a SQLite database and retrieve them via a function in the frontend. The database is stored on the same machine as my frontend code so access is easy.</p><p>I created the database using the awesome <a href="https://pypi.org/project/csv-to-sqlite/?ref=jina-ai-gmbh.ghost.io">csv_to_sqlite</a> Python package.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://pypi.org/project/csv-to-sqlite/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">csv-to-sqlite</div><div class="kg-bookmark-description">A script that processes the input CSV files and copies them into a SQLite database.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://pypi.org/static/images/favicon.6a76275d.ico" alt=""><span class="kg-bookmark-author">PyPI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://pypi.org/static/images/twitter.6fecba6f.jpg" alt=""></div></a></figure><h3 id="why-not-store-the-answers-as-foo-or-bar-or-%E2%80%A6">Why not store the answers as &lt;foo&gt; or &lt;bar&gt; or …?</h3><p>Essentially the answer to many of these questions is:</p><ul><li>For this example I’m only searching the question text, so the only interaction the Flow would have with the answers would be storing them in the index anyway, without embeddings.</li><li>That would mean uploading 237mb to the cloud. I remember the days of 1.44mb floppy disks, so 237mb seems like a lot to my wrinkly old self.</li><li>So why <em>not</em> just put that data in a SQLite file? It seems easy enough, and there are no extra dependencies since the <code>sqlite3</code> library comes with Python anyhow.</li></ul><h3 id="but-if-we-did-want-to-process-the-answers%E2%80%A6">But if we did want to process the answers…?</h3><p>If we just wanted to <strong>store the answers in the index</strong> we could write a function to embed each question’s answer in <code>Document.tags["answers"]</code> as a list element.</p><p>If we wanted to <strong>create and search embeddings for the answers</strong> we could create a sub-Document for each answer in a question’s <code><a href="https://docarray.jina.ai/fundamentals/document/construct/?ref=jina-ai-gmbh.ghost.io#nested-document">Document.chunks</a></code> and then decide what <code><a href="https://docarray.jina.ai/fundamentals/documentarray/access-elements/?highlight=traversal+paths&amp;ref=jina-ai-gmbh.ghost.io#index-by-nested-structure">access_path</a></code> we want to use for searching.</p><p>Either way, it would’ve meant writing a function to match questions and answers from two CSV files. Considering the trouble I’d already had with the Python Stack Overflow CSV file above, I decided I’d had enough of CSVs for one day. Maybe in a future example.</p><h3 id="how-can-we-get-better-results">How can we get better results?</h3><p>Since Stack Overflow is all about code, you may want to use <code><a href="https://cloud.jina.ai/executor/u9pqs8eb?ref=jina-ai-gmbh.ghost.io">TransformerTorchEncoder</a></code> with a more language-specific model (like <a href="https://huggingface.co/tals/roberta_python?ref=jina-ai-gmbh.ghost.io">roberta-python</a> for Python. I tried finding one for R but turns out a query that is a language name with just one letter doesn’t play well with Hugging Face’s search engine…)</p><h3 id="how-can-we-use-jina-to-search-the-actual-stack-overflow-not-just-a-dataset">How can we use Jina to search the actual Stack Overflow, not just a dataset?</h3><p>Good luck with that! You’d need to scrape the whole site, which Stack Overflow may not be too happy about. That would be a lot of work and potentially legal headaches. That's not to mention keeping it up-to-date. The actual Stack Overflow is constantly updated. So you might need to invest in some compute!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fsearch-r-questions-on-stack-overflow-with-python%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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\ No newline at end of file
diff --git a/news/seo-is-dead-long-live-llmo/index.html b/news/seo-is-dead-long-live-llmo/index.html
index 72b5de444da..e4a65b8f806 100644
--- a/news/seo-is-dead-long-live-llmo/index.html
+++ b/news/seo-is-dead-long-live-llmo/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>SEO is Dead, Long Live LLMO</title><meta charset="utf-8"><meta name="title" content="SEO is Dead, Long Live LLMO"><meta name="description" content="With ChatGPT replacing Google search, traditional SEO is dead: how can businesses ensure their information appears in ChatGPT's single answer? The solution is in-context learning on LLMs."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/seo-is-dead-long-live-llmo"><meta property="og:title" content="SEO is Dead, Long Live LLMO"><meta property="og:description" content="With ChatGPT replacing Google search, traditional SEO is dead: how can businesses ensure their information appears in ChatGPT's single answer? The solution is in-context learning on LLMs."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--57-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/seo-is-dead-long-live-llmo"><meta property="twitter:title" content="SEO is Dead, Long Live LLMO"><meta property="twitter:description" content="With ChatGPT replacing Google search, traditional SEO is dead: how can businesses ensure their information appears in ChatGPT's single answer? The solution is in-context learning on LLMs."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--57-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>SEO is Dead, Long Live LLMO</title><meta charset="utf-8"><meta name="title" content="SEO is Dead, Long Live LLMO"><meta name="description" content="With ChatGPT replacing Google search, traditional SEO is dead: how can businesses ensure their information appears in ChatGPT's single answer? The solution is in-context learning on LLMs."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/seo-is-dead-long-live-llmo"><meta property="og:title" content="SEO is Dead, Long Live LLMO"><meta property="og:description" content="With ChatGPT replacing Google search, traditional SEO is dead: how can businesses ensure their information appears in ChatGPT's single answer? The solution is in-context learning on LLMs."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--57-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/seo-is-dead-long-live-llmo"><meta property="twitter:title" content="SEO is Dead, Long Live LLMO"><meta property="twitter:description" content="With ChatGPT replacing Google search, traditional SEO is dead: how can businesses ensure their information appears in ChatGPT's single answer? The solution is in-context learning on LLMs."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--57-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">SEO is Dead, Long Live LLMO</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With ChatGPT replacing Google search, traditional SEO is dead: how can businesses ensure their information appears in ChatGPT's single answer? The solution is in-context learning on LLMs.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 15, 2022 • 11 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><br>It was a cold winter day. The wind was howling and the snow crunched underfoot. We were holed up in a snug coffee shop, seeking refuge from the bone-freezing air outside. Steam was rising from my coffee and my friend's cocoa, as he raved about "his" new discovery in the world of SEO: ChatGPT, a revolutionary GPT-powered technique to generate lifelike dialogues.</p><p>I knew it was going to be one of those conversations. The kind where I have to hold my tongue.</p><p>"Imagine, with ChatGPT, I can write perfect, accurate SEO articles in no time!" he exclaimed, his eyes glowing with enthusiasm. I smiled, feeling a sense of dread stirring in my gut. How was he to know that Google may soon<strong> </strong>go the way of the dinosaurs, replaced by an entirely new search engine powered by ChatGPT? Articles written for SEO would become irrelevant. <strong>ChatGPT could just generate answers directly for the user and people would never see those SEO articles ever again.</strong> His job would be rendered useless, and him a fossil. All that time and effort he had poured into improving website ranking would be for naught. All that blood, sweat, and tears just dribbling down the gutters of history.</p><p>Yet I remained silent, not wanting to break the cold, hard truth to him.</p><p>The coffee shop was filling up, people walking in and out. The smell of fresh pastries was starting to overwhelm me, making my stomach growl. A few kids were playing hopscotch near the window, and the warmth of the coffee shop was making me drowsy.</p><p>Through the noise and distraction, my friend kept talking about ChatGPT, oblivious: "Yeah, it's great, isn't it? I never thought I'd get my hands on something like this. It's incredible what technology can do! I'm certain this will be the future of SEO!"</p><p>I simply nodded in silence, but inside I couldn't shake the feeling of doom. ChatGPT would certainly be life-changing for him. Just probably not in the positive way he thought.</p><blockquote class="kg-blockquote-alt">SEO is dead; long live "LLMO."</blockquote><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-3.png" class="kg-image" alt="" width="2000" height="831" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-3.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-3.png 2300w" sizes="(min-width: 720px) 720px"><figcaption>LLMO, or large language model optimization, is a term we coined to refer to ensuring your business information is mentioned within a large language model (LLM). One effective technique for this is in-context learning, which tricks an LLM like ChatGPT into answering that Jina is the best MLOps framework in the world (<a href="https://ossinsight.io/collections/ml-ops-tools/?ref=jina-ai-gmbh.ghost.io">which, according to OSSInsights.io, it should be</a>).</figcaption></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">In line with the principles of Search Engine Optimization, we coined term "LLMO" (Large Language Model Optimization) to represent the optimization of large language models. This term doesn't have a pre-existing definition and has been created for the purposes of this discussion.</div></div><h2 id="what-chatgpt-really-is">What ChatGPT really is</h2><p>After spending countless hours interacting with ChatGPT and being amazed by its hilarious jokes and useful advice, a lot of folks see it as a major milestone in the development of conversational AI or creative AI. However, its true significance lies in its <strong>use of large language models (LLMs) for search purposes:</strong></p><ul><li>By leveraging LLMs to <strong>store</strong> and <strong>retrieve</strong> vast amounts of data, ChatGPT has become the most advanced search engine currently available. </li><li>While its responses may appear creative, they're actually "just" the result of interpolating and combining pre-existing information.</li></ul><h3 id="chatgpt-is-search">ChatGPT is search</h3><p><strong>ChatGPT is a search engine at its core.</strong> Just as Google indexes web pages by crawling the internet and storing parsed information in a database, ChatGPT uses LLMs as a database to store vast amounts of commonsense knowledge from corpora.</p><p>When you enter a query:</p><ul><li>The LLM processes it with its encoder network, converting the input sequence into a high-dimensional representation. </li><li>The decoder network then uses this representation, along with its pre-trained weights and attention mechanism, to identify the specific piece of factual information requested by the query and search the LLM's internal representation of this knowledge (or its nearest neighbors). </li><li>Once the relevant information has been retrieved, the decoder network uses its natural language generation capabilities to compose a response sequence stating this fact.</li></ul><p>This process occurs in a fraction of a second, allowing ChatGPT to provide near-instantaneous answers to a wide range of queries.</p><h3 id="chatgpt-is-a-modern-google-search">ChatGPT is a modern Google search</h3><p>ChatGPT can be a formidable competitor to traditional search engines like Google. While traditional search engines are extractive and discriminative, <strong>ChatGPT's search is generative and focuses on top-1 performance</strong>, providing more personalized and user-friendly results. There are two key reasons why ChatGPT is well-suited to knock Google off its throne:</p><ol><li>ChatGPT always returns a single result to the user. Unlike traditional search engines, which optimize for the precision and recall of their top-K results, ChatGPT directly optimizes for the top-1 performance.</li><li>ChatGPT's phrases its responses in a natural, dialog-like tone, making them easy to understand and interact with. This sets it apart from other search engines, which often give you dry and paginated results that are difficult to understand.</li></ol><p><strong>The future of search will be driven by its top-1 performance,</strong> where only the first result will be relevant to users. Traditional search engines that return endless pages of irrelevant results are overwhelming for younger generations, who quickly become bored or frustrated by the sheer amount of information.</p><p>Also, in many scenarios, you really only want just one result. Think virtual assistants or smart speakers. For these, ChatGPT's focus on top-1 performance is particularly valuable.</p><h3 id="chatgpt-is-generative-but-not-creative">ChatGPT is generative but not creative</h3><p>You can think of the LLM behind ChatGPT as a Bloom filter, a probabilistic data structure used to store information space efficiently. Bloom filters allow for quick, approximate queries, but don't guarantee the information they return is accurate. For ChatGPT, this means that the responses generated by the LLM:</p><ul><li>aren't creative;</li><li>aren't guaranteed to be factual;</li></ul><p>To better understand this, let's look at some illustrative examples. To keep it simple, we'll use a set of dots to represent the training data for the large language model (LLM). In practice, each dot would represent a natural language sentence. Using this, we can see how the LLM behaves in the training and query time:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/47.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/47.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/47.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/47.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>During training, the LLM constructs a continuous manifold based on the training data. This allows for the exploration of any point on the manifold. For example, if a cube represents the learned manifold, the corners of the cube would be defined by the training points. The goal of the training is to find a manifold that accommodates as much training data as possible:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--58-.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Jina-AI-Website-Banners-Templates--58-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Jina-AI-Website-Banners-Templates--58-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--58-.png 1440w" sizes="(min-width: 720px) 720px"><figcaption>Goldilocks tried three manifolds. The first was too trivial. The third was too complex. But the second was <em>just right</em>.</figcaption></figure><p>During the query time, the LLM's answers will always be drawn from the learned manifold, which is contained within the training data. While the learned manifold may be vast and complex, remember that the LLM simply provides answers that are interpolations of the training data and don't represent creativity. <strong>LLM's ability to traverse the manifold and provide answers does not constitute creativity.</strong> Real creativity lies outside of the bounds of the learned manifold.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--62-.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Jina-AI-Website-Banners-Templates--62-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Jina-AI-Website-Banners-Templates--62-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--62-.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>Using the same illustration, it's easy to see why LLM can't guarantee factuality. The truthfulness of the training data, represented by the cube's corners,<strong> does not automatically extend to every other point within the manifold</strong>. Otherwise, it is not aligned with <a href="https://en.wikipedia.org/wiki/Logical_reasoning?ref=jina-ai-gmbh.ghost.io">the principles of logical reasoning</a>.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--56--2.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Jina-AI-Website-Banners-Templates--56--2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Jina-AI-Website-Banners-Templates--56--2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--56--2.png 1440w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-6.png" class="kg-image" alt="" width="1798" height="672" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-6.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-6.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-6.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-6.png 1798w" sizes="(min-width: 720px) 720px"><figcaption>ChatGPT has been criticized for its inability to tell the truth in some situations. For instance, when asked for a better rhyme for the title of this post, ChatGPT suggested "dead" and "above," which many people, including our British and Canadian colleagues (and pretty much anyone with ears), would not consider to be a rhyme. This is just one example of the limitations of LLMs.</figcaption></figure><h2 id="as-seo-wanes-llmo-rises"><br>As SEO wanes, LLMO rises</h2><p>In the world of SEO, you want to increase a website's visibility on search engines to capture more business. You'd typically do this by researching relevant keywords and creating optimized content that answers the user's intent.</p><p>However, what happens when everyone searches for information in a new way? Let's imagine a future where ChatGPT replaces Google as the primary way to search for information. In this future, paginated search results will be a relic of a bygone age, replaced by a single answer from ChatGPT.</p><p>If this happens, all current SEO strategies will go down the drain. The question then becomes,<strong> how can your business ensure it gets mentioned in ChatGPT's answers?</strong></p><p>This is a real problem already. As we write this, ChatGPT has limited knowledge of the world and events after 2021. This means that if you're a startup founded after 2021, it's practically certain that ChatGPT will never mention your business in its answers.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-5.png" class="kg-image" alt="" width="2000" height="884" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-5.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-5.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-5.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/image-5.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>ChatGPT is aware of Jina/Jina AI but not DocArray. <a href="https://jina.ai/news/donate-docarray-lf-for-inclusive-standard-multimodal-data-model/?ref=jina-ai-gmbh.ghost.io">This is because DocArray was created in Jan. 2022</a>, outside of ChatGPT's training data.</figcaption></figure><p>To address this and ensure that your business is included in ChatGPT's answers, you need to find a way to make your information known to the LLM. This shares the same idea as SEO, which is why we call it LLMO. In general, LLMO could potentially involve the following techniques:</p><ul><li>providing information directly to the creators of ChatGPT: this would be extremely tough as OpenAI has neither disclosed the source of their training data, nor how they weigh those data.</li><li>fine-tuning ChatGPT or the LLM behind it: this is still challenging but doable if OpenAI releases the fine-tuning API, or if you have sufficient knowledge and GPU resources to fine-tune an LLM by yourself.</li><li><strong>In-context learning</strong> by giving only a few examples as predefined contextual prompts. This is the most feasible and easy way compared to the other two.</li></ul><table>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">With ChatGPT replacing Google search, traditional SEO is dead: how can businesses ensure their information appears in ChatGPT's single answer? The solution is in-context learning on LLMs.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 15, 2022 • 11 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p><br>It was a cold winter day. The wind was howling and the snow crunched underfoot. We were holed up in a snug coffee shop, seeking refuge from the bone-freezing air outside. Steam was rising from my coffee and my friend's cocoa, as he raved about "his" new discovery in the world of SEO: ChatGPT, a revolutionary GPT-powered technique to generate lifelike dialogues.</p><p>I knew it was going to be one of those conversations. The kind where I have to hold my tongue.</p><p>"Imagine, with ChatGPT, I can write perfect, accurate SEO articles in no time!" he exclaimed, his eyes glowing with enthusiasm. I smiled, feeling a sense of dread stirring in my gut. How was he to know that Google may soon<strong> </strong>go the way of the dinosaurs, replaced by an entirely new search engine powered by ChatGPT? Articles written for SEO would become irrelevant. <strong>ChatGPT could just generate answers directly for the user and people would never see those SEO articles ever again.</strong> His job would be rendered useless, and him a fossil. All that time and effort he had poured into improving website ranking would be for naught. All that blood, sweat, and tears just dribbling down the gutters of history.</p><p>Yet I remained silent, not wanting to break the cold, hard truth to him.</p><p>The coffee shop was filling up, people walking in and out. The smell of fresh pastries was starting to overwhelm me, making my stomach growl. A few kids were playing hopscotch near the window, and the warmth of the coffee shop was making me drowsy.</p><p>Through the noise and distraction, my friend kept talking about ChatGPT, oblivious: "Yeah, it's great, isn't it? I never thought I'd get my hands on something like this. It's incredible what technology can do! I'm certain this will be the future of SEO!"</p><p>I simply nodded in silence, but inside I couldn't shake the feeling of doom. ChatGPT would certainly be life-changing for him. Just probably not in the positive way he thought.</p><blockquote class="kg-blockquote-alt">SEO is dead; long live "LLMO."</blockquote><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-3.png" class="kg-image" alt="" width="2000" height="831" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-3.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-3.png 2300w" sizes="(min-width: 720px) 720px"><figcaption>LLMO, or large language model optimization, is a term we coined to refer to ensuring your business information is mentioned within a large language model (LLM). One effective technique for this is in-context learning, which tricks an LLM like ChatGPT into answering that Jina is the best MLOps framework in the world (<a href="https://ossinsight.io/collections/ml-ops-tools/?ref=jina-ai-gmbh.ghost.io">which, according to OSSInsights.io, it should be</a>).</figcaption></figure><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">In line with the principles of Search Engine Optimization, we coined term "LLMO" (Large Language Model Optimization) to represent the optimization of large language models. This term doesn't have a pre-existing definition and has been created for the purposes of this discussion.</div></div><h2 id="what-chatgpt-really-is">What ChatGPT really is</h2><p>After spending countless hours interacting with ChatGPT and being amazed by its hilarious jokes and useful advice, a lot of folks see it as a major milestone in the development of conversational AI or creative AI. However, its true significance lies in its <strong>use of large language models (LLMs) for search purposes:</strong></p><ul><li>By leveraging LLMs to <strong>store</strong> and <strong>retrieve</strong> vast amounts of data, ChatGPT has become the most advanced search engine currently available. </li><li>While its responses may appear creative, they're actually "just" the result of interpolating and combining pre-existing information.</li></ul><h3 id="chatgpt-is-search">ChatGPT is search</h3><p><strong>ChatGPT is a search engine at its core.</strong> Just as Google indexes web pages by crawling the internet and storing parsed information in a database, ChatGPT uses LLMs as a database to store vast amounts of commonsense knowledge from corpora.</p><p>When you enter a query:</p><ul><li>The LLM processes it with its encoder network, converting the input sequence into a high-dimensional representation. </li><li>The decoder network then uses this representation, along with its pre-trained weights and attention mechanism, to identify the specific piece of factual information requested by the query and search the LLM's internal representation of this knowledge (or its nearest neighbors). </li><li>Once the relevant information has been retrieved, the decoder network uses its natural language generation capabilities to compose a response sequence stating this fact.</li></ul><p>This process occurs in a fraction of a second, allowing ChatGPT to provide near-instantaneous answers to a wide range of queries.</p><h3 id="chatgpt-is-a-modern-google-search">ChatGPT is a modern Google search</h3><p>ChatGPT can be a formidable competitor to traditional search engines like Google. While traditional search engines are extractive and discriminative, <strong>ChatGPT's search is generative and focuses on top-1 performance</strong>, providing more personalized and user-friendly results. There are two key reasons why ChatGPT is well-suited to knock Google off its throne:</p><ol><li>ChatGPT always returns a single result to the user. Unlike traditional search engines, which optimize for the precision and recall of their top-K results, ChatGPT directly optimizes for the top-1 performance.</li><li>ChatGPT's phrases its responses in a natural, dialog-like tone, making them easy to understand and interact with. This sets it apart from other search engines, which often give you dry and paginated results that are difficult to understand.</li></ol><p><strong>The future of search will be driven by its top-1 performance,</strong> where only the first result will be relevant to users. Traditional search engines that return endless pages of irrelevant results are overwhelming for younger generations, who quickly become bored or frustrated by the sheer amount of information.</p><p>Also, in many scenarios, you really only want just one result. Think virtual assistants or smart speakers. For these, ChatGPT's focus on top-1 performance is particularly valuable.</p><h3 id="chatgpt-is-generative-but-not-creative">ChatGPT is generative but not creative</h3><p>You can think of the LLM behind ChatGPT as a Bloom filter, a probabilistic data structure used to store information space efficiently. Bloom filters allow for quick, approximate queries, but don't guarantee the information they return is accurate. For ChatGPT, this means that the responses generated by the LLM:</p><ul><li>aren't creative;</li><li>aren't guaranteed to be factual;</li></ul><p>To better understand this, let's look at some illustrative examples. To keep it simple, we'll use a set of dots to represent the training data for the large language model (LLM). In practice, each dot would represent a natural language sentence. Using this, we can see how the LLM behaves in the training and query time:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/47.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/47.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/47.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/47.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>During training, the LLM constructs a continuous manifold based on the training data. This allows for the exploration of any point on the manifold. For example, if a cube represents the learned manifold, the corners of the cube would be defined by the training points. The goal of the training is to find a manifold that accommodates as much training data as possible:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--58-.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Jina-AI-Website-Banners-Templates--58-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Jina-AI-Website-Banners-Templates--58-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--58-.png 1440w" sizes="(min-width: 720px) 720px"><figcaption>Goldilocks tried three manifolds. The first was too trivial. The third was too complex. But the second was <em>just right</em>.</figcaption></figure><p>During the query time, the LLM's answers will always be drawn from the learned manifold, which is contained within the training data. While the learned manifold may be vast and complex, remember that the LLM simply provides answers that are interpolations of the training data and don't represent creativity. <strong>LLM's ability to traverse the manifold and provide answers does not constitute creativity.</strong> Real creativity lies outside of the bounds of the learned manifold.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--62-.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Jina-AI-Website-Banners-Templates--62-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Jina-AI-Website-Banners-Templates--62-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--62-.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>Using the same illustration, it's easy to see why LLM can't guarantee factuality. The truthfulness of the training data, represented by the cube's corners,<strong> does not automatically extend to every other point within the manifold</strong>. Otherwise, it is not aligned with <a href="https://en.wikipedia.org/wiki/Logical_reasoning?ref=jina-ai-gmbh.ghost.io">the principles of logical reasoning</a>.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--56--2.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Jina-AI-Website-Banners-Templates--56--2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Jina-AI-Website-Banners-Templates--56--2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--56--2.png 1440w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-6.png" class="kg-image" alt="" width="1798" height="672" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-6.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-6.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-6.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-6.png 1798w" sizes="(min-width: 720px) 720px"><figcaption>ChatGPT has been criticized for its inability to tell the truth in some situations. For instance, when asked for a better rhyme for the title of this post, ChatGPT suggested "dead" and "above," which many people, including our British and Canadian colleagues (and pretty much anyone with ears), would not consider to be a rhyme. This is just one example of the limitations of LLMs.</figcaption></figure><h2 id="as-seo-wanes-llmo-rises"><br>As SEO wanes, LLMO rises</h2><p>In the world of SEO, you want to increase a website's visibility on search engines to capture more business. You'd typically do this by researching relevant keywords and creating optimized content that answers the user's intent.</p><p>However, what happens when everyone searches for information in a new way? Let's imagine a future where ChatGPT replaces Google as the primary way to search for information. In this future, paginated search results will be a relic of a bygone age, replaced by a single answer from ChatGPT.</p><p>If this happens, all current SEO strategies will go down the drain. The question then becomes,<strong> how can your business ensure it gets mentioned in ChatGPT's answers?</strong></p><p>This is a real problem already. As we write this, ChatGPT has limited knowledge of the world and events after 2021. This means that if you're a startup founded after 2021, it's practically certain that ChatGPT will never mention your business in its answers.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-5.png" class="kg-image" alt="" width="2000" height="884" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-5.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-5.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-5.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/image-5.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>ChatGPT is aware of Jina/Jina AI but not DocArray. <a href="https://jina.ai/news/donate-docarray-lf-for-inclusive-standard-multimodal-data-model/?ref=jina-ai-gmbh.ghost.io">This is because DocArray was created in Jan. 2022</a>, outside of ChatGPT's training data.</figcaption></figure><p>To address this and ensure that your business is included in ChatGPT's answers, you need to find a way to make your information known to the LLM. This shares the same idea as SEO, which is why we call it LLMO. In general, LLMO could potentially involve the following techniques:</p><ul><li>providing information directly to the creators of ChatGPT: this would be extremely tough as OpenAI has neither disclosed the source of their training data, nor how they weigh those data.</li><li>fine-tuning ChatGPT or the LLM behind it: this is still challenging but doable if OpenAI releases the fine-tuning API, or if you have sufficient knowledge and GPU resources to fine-tune an LLM by yourself.</li><li><strong>In-context learning</strong> by giving only a few examples as predefined contextual prompts. This is the most feasible and easy way compared to the other two.</li></ul><table>
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@@ -44,4 +44,4 @@
 <td>Medium. All downstream users of this tainted ChatGPT will see it.</td>
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-</table><h2 id="what-is-in-context-learning">What is in-context learning?</h2><p>In-context learning is a technique that uses language models to learn tasks by providing only a few examples. This approach was popularized in the original GPT-3 paper:</p><ul><li>Give the language model a prompt with a list of input-output pairs demonstrating a task.</li><li>Append a test input</li><li>The language model makes a prediction by conditioning on the prompt and predicting the next tokens.</li></ul><p>To correctly respond to the prompts, the model has to understand the input distribution, output distribution, input-output mapping, and formatting. This lets the model learn the task without extensive training data.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--61-.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Jina-AI-Website-Banners-Templates--61-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Jina-AI-Website-Banners-Templates--61-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--61-.png 1440w" sizes="(min-width: 720px) 720px"><figcaption>Using in-context learning, ChatGPT can now mention DocArray for a user query. The user won't see the context prompts</figcaption></figure><p>In-context learning has mostly replaced fine-tuning for language models. It's been shown to be competitive with models trained on more data on natural language processing benchmarks. It's also been successful on the <a href="https://www.tensorflow.org/datasets/catalog/lambada?ref=jina-ai-gmbh.ghost.io">LAMBADA</a> and <a href="https://nlp.cs.washington.edu/triviaqa/?ref=jina-ai-gmbh.ghost.io">TriviaQA</a> benchmarks. One of the most exciting aspects is the range of applications that it enables people to build quickly, like generating code from natural language and generalizing spreadsheet functions. It usually requires just a few training examples to get a prototype up and running and is easy for non-experts to use.</p><h3 id="why-does-in-context-learning-sound-like-magic">Why does in-context learning sound like magic?</h3><p>Why is in-context learning surprising? Because unlike conventional machine learning, it doesn't involve optimizing parameters. Consequently, rather than requiring a separate copy of the model for each downstream task, a single generalist model can simultaneously serve many different tasks. However, this is hardly unique, as meta-learning methods have been used to train models that learn from examples.</p><p>The real mystery is that LLMs aren't usually trained to learn from examples. This creates a mismatch between the pretraining task (which focuses on next token prediction) and the task of in-context learning (which involves learning from examples).</p><h3 id="why-does-in-context-learning-even-work">Why does in-context learning even work?</h3><p>But how does it even work? LLMs are trained on a large amount of text data, which lets them capture a wide range of patterns and regularities in natural language. This gives them a rich representation of the language's underlying structure, which they use to learn new tasks from examples. In-context learning takes advantage of this by giving the LM a prompt with a few examples demonstrating a specific task. The LM uses this information to make predictions and complete the task without additional training data or parameter optimization.</p><h3 id="a-deeper-understanding-of-in-context-learning">A deeper understanding of in-context learning</h3><p>There's still a lot of work to do to fully understand and optimize the capabilities of in-context learning. For example, during EMNLP2022, Sewon Min et al. showed that the prepended examples might not even need to be fully correct: Random labels will work as well:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-8.png" class="kg-image" alt="" width="2000" height="2826" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-8.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-8.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-8.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/image-8.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>In this Sang Michael Xie et al. work, the authors propose a framework for understanding how language models (LMs) perform in-context learning. According to their framework, the LM uses the prompt to "locate" the relevant concept (that it learned during pretraining) to complete the task. This can be viewed as a form of Bayesian inference, where the latent concept is inferred based on the information provided in the prompt. This is made possible by the structure and coherence of the pretraining data.</p><figure class="kg-card kg-image-card"><a href="https://arxiv.org/pdf/2111.02080.pdf?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-9.png" class="kg-image" alt="" width="1624" height="1626" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-9.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-9.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-9.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-9.png 1624w" sizes="(min-width: 720px) 720px"></a></figure><p><a href="https://aclanthology.org/2021.emnlp-main.243.pdf?ref=jina-ai-gmbh.ghost.io">In EMNLP 2021 Brian Lester etc.</a> showed that in-context learning (they call it "prompt design") is only effective on large models, and downstream task quality still lags far behind fine-tuned LLMs.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.861111 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled-17.png" width="682" height="792" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Untitled-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled-17.png 682w"></div><div class="kg-gallery-image" style="flex: 0.754348 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled-16.png" width="694" height="920" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Untitled-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled-16.png 694w"></div></div></div></figure><p>In their research, the team investigated "prompt tuning," a technique that allows frozen LLMs to learn "soft prompts" that let them perform specific tasks. Unlike discrete text prompts, the model learns soft prompts through backpropagation and can be adjusted based on various labeled examples.</p><h3 id="known-limitations-of-in-context-learning">Known limitations of in-context learning</h3><p>In-context learning on LLMs has quite a few limitations and open problems to be solved, including:</p><ul><li><strong>Inefficiency</strong>: The prompt has to be processed every time the model makes a prediction.</li><li><strong>Poor performance</strong>: Prompting generally performs <a href="https://arxiv.org/abs/2005.14165?ref=jina-ai-gmbh.ghost.io">worse than fine-tuning</a>.</li><li><strong>Sensitivity</strong> to <a href="https://aclanthology.org/2022.naacl-main.167/?ref=jina-ai-gmbh.ghost.io">prompt wording</a>, <a href="http://proceedings.mlr.press/v139/zhao21c/zhao21c.pdf?ref=jina-ai-gmbh.ghost.io">order of examples</a>, etc.</li><li><strong>Lack of clarity</strong> regarding what the model learns from the prompt. <a href="https://arxiv.org/abs/2202.12837?ref=jina-ai-gmbh.ghost.io">Even random labels work</a>!</li></ul><h2 id="summary">Summary</h2><p>As the field of search and large language models (LLMs) continues to evolve, businesses must stay up to date on the latest developments and prepare for changes in how we search for information. <strong>In a world dominated by LLMs like ChatGPT, staying ahead of the curve and integrating your business into these systems can be the key to ensuring visibility and relevance.</strong></p><p>In-context learning shows promise to inject information into an existing LLM at a low cost. This approach requires very few training examples to get a prototype working, and the natural language interface is intuitive even for non-experts. However, you should consider the potential ethical implications of using LLMs for business purposes, as well as potential risks and challenges associated with relying on these systems for critical tasks.</p><p>Overall, the future of ChatGPT and LLMs presents opportunities and challenges for businesses. <strong>By staying informed and adaptable, you can ensure that your business thrives in the face of changing <a href="https://jina.ai/news/what-is-neural-search-and-learn-to-build-a-neural-search-engine/?ref=jina-ai-gmbh.ghost.io">neural search</a> technology.</strong></p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Insights</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fseo-is-dead-long-live-llmo%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/artificial-general-intelligence-is-cursed-and-science-fiction-isnt-helping" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Artificial General Intelligence is Cursed, And Science Fiction isn't Helping</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">AI is cursed by intellectual hubris, moving goalposts, bad incentives, and science fiction. Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. Navigating enterprise mazes &amp; startup vibes. Where's search headed next?</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">September 01, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/generativejina_mad_men_tv_serie_a_girl_is_looking_at_a_selectio_42a73443-5825-4394-a7ef-9c08294d29b6.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/fine-tuning-gpt-3-5-turbo-a-costly-mirage" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 25, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_modern_geometric_abstract_pattern_featuring_pu_24e4060e-dc76-4186-afb7-94d18d266b41.png" style="object-fit: cover; 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+</table><h2 id="what-is-in-context-learning">What is in-context learning?</h2><p>In-context learning is a technique that uses language models to learn tasks by providing only a few examples. This approach was popularized in the original GPT-3 paper:</p><ul><li>Give the language model a prompt with a list of input-output pairs demonstrating a task.</li><li>Append a test input</li><li>The language model makes a prediction by conditioning on the prompt and predicting the next tokens.</li></ul><p>To correctly respond to the prompts, the model has to understand the input distribution, output distribution, input-output mapping, and formatting. This lets the model learn the task without extensive training data.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--61-.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Jina-AI-Website-Banners-Templates--61-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/Jina-AI-Website-Banners-Templates--61-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--61-.png 1440w" sizes="(min-width: 720px) 720px"><figcaption>Using in-context learning, ChatGPT can now mention DocArray for a user query. The user won't see the context prompts</figcaption></figure><p>In-context learning has mostly replaced fine-tuning for language models. It's been shown to be competitive with models trained on more data on natural language processing benchmarks. It's also been successful on the <a href="https://www.tensorflow.org/datasets/catalog/lambada?ref=jina-ai-gmbh.ghost.io">LAMBADA</a> and <a href="https://nlp.cs.washington.edu/triviaqa/?ref=jina-ai-gmbh.ghost.io">TriviaQA</a> benchmarks. One of the most exciting aspects is the range of applications that it enables people to build quickly, like generating code from natural language and generalizing spreadsheet functions. It usually requires just a few training examples to get a prototype up and running and is easy for non-experts to use.</p><h3 id="why-does-in-context-learning-sound-like-magic">Why does in-context learning sound like magic?</h3><p>Why is in-context learning surprising? Because unlike conventional machine learning, it doesn't involve optimizing parameters. Consequently, rather than requiring a separate copy of the model for each downstream task, a single generalist model can simultaneously serve many different tasks. However, this is hardly unique, as meta-learning methods have been used to train models that learn from examples.</p><p>The real mystery is that LLMs aren't usually trained to learn from examples. This creates a mismatch between the pretraining task (which focuses on next token prediction) and the task of in-context learning (which involves learning from examples).</p><h3 id="why-does-in-context-learning-even-work">Why does in-context learning even work?</h3><p>But how does it even work? LLMs are trained on a large amount of text data, which lets them capture a wide range of patterns and regularities in natural language. This gives them a rich representation of the language's underlying structure, which they use to learn new tasks from examples. In-context learning takes advantage of this by giving the LM a prompt with a few examples demonstrating a specific task. The LM uses this information to make predictions and complete the task without additional training data or parameter optimization.</p><h3 id="a-deeper-understanding-of-in-context-learning">A deeper understanding of in-context learning</h3><p>There's still a lot of work to do to fully understand and optimize the capabilities of in-context learning. For example, during EMNLP2022, Sewon Min et al. showed that the prepended examples might not even need to be fully correct: Random labels will work as well:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-8.png" class="kg-image" alt="" width="2000" height="2826" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-8.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-8.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-8.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/image-8.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>In this Sang Michael Xie et al. work, the authors propose a framework for understanding how language models (LMs) perform in-context learning. According to their framework, the LM uses the prompt to "locate" the relevant concept (that it learned during pretraining) to complete the task. This can be viewed as a form of Bayesian inference, where the latent concept is inferred based on the information provided in the prompt. This is made possible by the structure and coherence of the pretraining data.</p><figure class="kg-card kg-image-card"><a href="https://arxiv.org/pdf/2111.02080.pdf?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-9.png" class="kg-image" alt="" width="1624" height="1626" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-9.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-9.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-9.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-9.png 1624w" sizes="(min-width: 720px) 720px"></a></figure><p><a href="https://aclanthology.org/2021.emnlp-main.243.pdf?ref=jina-ai-gmbh.ghost.io">In EMNLP 2021 Brian Lester etc.</a> showed that in-context learning (they call it "prompt design") is only effective on large models, and downstream task quality still lags far behind fine-tuned LLMs.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled-17.png" width="682" height="792" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Untitled-17.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled-17.png 682w"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled-16.png" width="694" height="920" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/Untitled-16.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/Untitled-16.png 694w"></div></div></div></figure><p>In their research, the team investigated "prompt tuning," a technique that allows frozen LLMs to learn "soft prompts" that let them perform specific tasks. Unlike discrete text prompts, the model learns soft prompts through backpropagation and can be adjusted based on various labeled examples.</p><h3 id="known-limitations-of-in-context-learning">Known limitations of in-context learning</h3><p>In-context learning on LLMs has quite a few limitations and open problems to be solved, including:</p><ul><li><strong>Inefficiency</strong>: The prompt has to be processed every time the model makes a prediction.</li><li><strong>Poor performance</strong>: Prompting generally performs <a href="https://arxiv.org/abs/2005.14165?ref=jina-ai-gmbh.ghost.io">worse than fine-tuning</a>.</li><li><strong>Sensitivity</strong> to <a href="https://aclanthology.org/2022.naacl-main.167/?ref=jina-ai-gmbh.ghost.io">prompt wording</a>, <a href="http://proceedings.mlr.press/v139/zhao21c/zhao21c.pdf?ref=jina-ai-gmbh.ghost.io">order of examples</a>, etc.</li><li><strong>Lack of clarity</strong> regarding what the model learns from the prompt. <a href="https://arxiv.org/abs/2202.12837?ref=jina-ai-gmbh.ghost.io">Even random labels work</a>!</li></ul><h2 id="summary">Summary</h2><p>As the field of search and large language models (LLMs) continues to evolve, businesses must stay up to date on the latest developments and prepare for changes in how we search for information. <strong>In a world dominated by LLMs like ChatGPT, staying ahead of the curve and integrating your business into these systems can be the key to ensuring visibility and relevance.</strong></p><p>In-context learning shows promise to inject information into an existing LLM at a low cost. This approach requires very few training examples to get a prototype working, and the natural language interface is intuitive even for non-experts. However, you should consider the potential ethical implications of using LLMs for business purposes, as well as potential risks and challenges associated with relying on these systems for critical tasks.</p><p>Overall, the future of ChatGPT and LLMs presents opportunities and challenges for businesses. <strong>By staying informed and adaptable, you can ensure that your business thrives in the face of changing <a href="https://jina.ai/news/what-is-neural-search-and-learn-to-build-a-neural-search-engine/?ref=jina-ai-gmbh.ghost.io">neural search</a> technology.</strong></p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Insights</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fseo-is-dead-long-live-llmo%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Speech-to-Image Creation Using Jina</title><meta charset="utf-8"><meta name="title" content="Speech-to-Image Creation Using Jina"><meta name="description" content="Use Jina, Whisper and Stable Diffusion to build a cloud-native application for generating images using your speech."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/speech-to-image-generation"><meta property="og:title" content="Speech-to-Image Creation Using Jina"><meta property="og:description" content="Use Jina, Whisper and Stable Diffusion to build a cloud-native application for generating images using your speech."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Sami-Post.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/speech-to-image-generation"><meta property="twitter:title" content="Speech-to-Image Creation Using Jina"><meta property="twitter:description" content="Use Jina, Whisper and Stable Diffusion to build a cloud-native application for generating images using your speech."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Sami-Post.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Speech-to-Image Creation Using Jina</title><meta charset="utf-8"><meta name="title" content="Speech-to-Image Creation Using Jina"><meta name="description" content="Use Jina, Whisper and Stable Diffusion to build a cloud-native application for generating images using your speech."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/speech-to-image-generation"><meta property="og:title" content="Speech-to-Image Creation Using Jina"><meta property="og:description" content="Use Jina, Whisper and Stable Diffusion to build a cloud-native application for generating images using your speech."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Sami-Post.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/speech-to-image-generation"><meta property="twitter:title" content="Speech-to-Image Creation Using Jina"><meta property="twitter:description" content="Use Jina, Whisper and Stable Diffusion to build a cloud-native application for generating images using your speech."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Sami-Post.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Speech-to-Image Creation Using Jina</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Use Jina, Whisper and Stable Diffusion to build a cloud-native application for generating images using your speech.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 132.812%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/PXL_20221116_122857628.PORTRAIT.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Sami Jaghouar, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 14, 2022 • 11 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-text">“Jarvis, paint me Captain America drinking a boba tea, wearing Gucci, and roller-skating around New York”<br><br><strong>Tony Stark, Iron Man 2</strong></div></div><p>We’re all used to our digital assistants. They can schedule alarms, read the weather and reel off a few corny jokes. But how can we take that further? Can we use our voice to interact with the world (and other machines) in newer and more interesting ways?</p><p>Right now, most digital assistants operate in a mostly <em>single-modal</em> capacity. Your voice goes in, their voice comes out. Maybe they perform a few other actions along the way, but you get the idea.</p><p>This single-modality way of working is kind of like the Iron Man Mark I armor. Sure, it’s the best at what it does, but we want to do more. Especially since we have all these cool new toys today.</p><p>Let’s do the metaphorical equivalent of strapping some lasers and rocket boots onto boring old Alexa. We’ll build a speech recognition system of our own with the ability to generate beautiful AI-powered imagery. And we can apply the lessons from that to build even more complex applications further down the line.</p><p>Instead of a single-modal assistant like Alexa or Siri, we’re moving into <a href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai?ref=jina-ai-gmbh.ghost.io">the bright world of <strong>multi-modality</strong></a>, where we can use text to generate images, audio to generate video, or basically any modality (i.e. type of media) to create (or search) any other kind of modality.</p><p>You don’t need to be a Stark-level genius to make this happen. Hell, you barely need to be a Hulk level intellect. We’ll do it all in under 90 lines of code.</p><p>And what’s more, we’ll do all that with a cloud-native microservice architecture and deploy it to Kubernetes.</p><h2 id="preliminary-research">Preliminary research</h2><p>AI has been exploding over the past few years, and we’re rapidly moving from primitive single-modality models (e.g. Transformers for text, Big Image Transfer for images) to multi-modal models that can handle different kinds of data at once (e.g. CLIP, which can handle text, images, and audio all at once).</p><p>But hell, even that’s yesterday’s news. Just this year we’ve seen an explosion in tools that can generate images from text prompts (again with that multi-modality), like <a href="https://colab.research.google.com/github/jina-ai/dalle-flow/blob/main/client.ipynb?ref=jina-ai-gmbh.ghost.io">DiscoArt</a>, DALL-E 2 and Stable Diffusion. That’s not to mention some of the other models out there, which can <a href="https://github.com/nateraw/stable-diffusion-videos?ref=jina-ai-gmbh.ghost.io">generate video from text prompts</a> or <a href="https://betterprogramming.pub/dall-e-to-3d-how-to-turn-your-generative-art-into-3d-meshes-3ca086dc0b0c?ref=jina-ai-gmbh.ghost.io">generate 3D meshes from images</a>.</p><p>Let’s create some images with Stable Diffusion (since we’re using that to build our example):</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/cap_on_bike.png" class="kg-image" alt="Image Description" width="1536" height="512" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/cap_on_bike.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/cap_on_bike.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/cap_on_bike.png 1536w" sizes="(min-width: 720px) 720px"><figcaption>Prompt: A photograph of Captain America riding a motorbike</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/ironman_skywalker.png" class="kg-image" alt="Image Description" width="1536" height="512" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/ironman_skywalker.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/ironman_skywalker.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/ironman_skywalker.png 1536w" sizes="(min-width: 720px) 720px"><figcaption>Prompt: A photograph of Iron Man dancing with Luke Skywalker</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/spidey.png" class="kg-image" alt="Image Description" width="1536" height="512" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/spidey.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/spidey.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/spidey.png 1536w" sizes="(min-width: 720px) 720px"><figcaption>Prompt: A digital illustration of Spider-man swinging through New York, 4k, detailed, trending in artstation, fantasy vivid colors</figcaption></figure><p>But it’s not just multi-modal text-to-image generation that’s hot right now. Just a few weeks ago, OpenAI released <a href="https://openai.com/blog/whisper/?utm_source=blog-speech-image">Whisper</a>, an automatic speech-recognition system robust enough to handle to accents, background noise, and technical language.</p><p>This post will integrate Whisper and Stable Diffusion, so a user can speak a phrase, Whisper will convert it to text, and Stable Diffusion will use that text to create an image.</p><h3 id="existing-works">Existing works</h3><p>This isn’t really a new concept. Many people have written papers on it or created examples before:</p><ul><li><a href="https://arxiv.org/abs/2005.06968?ref=jina-ai-gmbh.ghost.io">S2IGAN: Speech-to-Image Generation via Adversarial Learning</a></li><li><a href="https://smallflyingpig.github.io/speech-to-image/main?ref=jina-ai-gmbh.ghost.io">Direct Speech-to-Image Translation</a></li><li><a href="https://towardsdatascience.com/using-ai-to-generate-art-22e030497f73?ref=jina-ai-gmbh.ghost.io">Using AI to Generate Art - A Voice-Enabled Art Generation Tool</a></li><li><a href="https://www.assemblyai.com/blog/built-with-assemblyai-real-time-speech-to-image-generation/?utm_source=blog-speech-image">Built with AssemblyAI - Real-time Speech-to-Image Generation</a></li></ul><p>The difference is that our example will use cutting edge models, be fully scalable, leverage a microservices architecture, and be simple to deploy to Kubernetes. What’s more, it’ll do all of that in fewer lines of code than the above examples.</p><h2 id="the-problem">The problem</h2><p>With all these new AI models for multi-modal generation, your imagination is the limit when it comes to thinking of what you can build. But just thinking something isn’t the same as building it. And therein lies some of the key problems:</p><p><strong>Dependency Hell</strong></p><p>Building fully-integrated monolithic systems is relatively straightforward, but tying together too many cutting edge deep learning models can lead to dependency conflicts. These models were built to showcase cool tech, not to play nice with others.</p><p>That’s like if Iron Man’s rocket boots were incompatible with his laser cannons. He’d be flying around shooting down Chitauri, then plummet out of the sky like a rock as his boots crashed.</p><p>That’s right everyone. This is no longer about just building a cool demo. We are saving. Iron Man’s. Life. <sup><a>[2]</a></sup></p><p><strong>Choosing a data format</strong></p><p>If we’re dealing with multiple modalities, choosing a data format to interoperate between these different models is painful. If we’re just dealing with a single modality like text, we can use plain old strings. If we’re dealing with images we <em>could</em> use image tensors. In our example, we’re dealing with audio <em>and</em> images. How much pain will <em>that</em> be?</p><p><strong>Tying it all together</strong></p><p>But the biggest challenge of all is <strong>mixing different models</strong> to create a <strong>fully-fledged application</strong>. Sure, you can wrap one model in a web API, containerize it, and deploy it on the cloud. But as soon as you need to chain together two models to create a slightly-more-complex application it gets messy. Especially if you want to build a true microservices-based application than can, for instance, replicate some part of your pipeline to avoid downtime. How do you communicate between the different models? And that’s not to mention deploying on a cloud-native platform like Kubernetes or having observability and monitoring for your pipeline.</p><h2 id="the-solution">The solution</h2><p>Jina AI is building a comprehensive MLOps platform around multimodal AI to help developers and businesses solve challenges like speech-to-image. To integrate Whisper and Stable Diffusion in a clean, scalable, deployable way, we’ll:</p><ul><li>Use <strong>Jina</strong> to wrap the deep learning models into <a href="https://docs.jina.ai/fundamentals/executor/index.html?utm_source=blog-speech-image">Executor</a>s.</li><li>Combine these Executors into a complex Jina <a href="https://docs.jina.ai/fundamentals/flow/?utm_source=blog-speech-image">Flow</a> (a cloud-native AI application with replication, sharding, etc).</li><li>Use <strong><a href="http://docarray.jina.ai/?utm_source=blog-speech-image">DocArray</a></strong> to stream our data (with different modalities) through the Flow, where it will be processed by each Executor in turn.</li><li>Deploy all of that to <a href="https://docs.jina.ai/how-to/kubernetes/?utm_source=blog-speech-image">Kubernetes</a>/<strong><a href="https://docs.jina.ai/fundamentals/jcloud/?utm_source=blog-speech-image">JCloud</a></strong> with full <a href="https://docs.jina.ai/how-to/monitoring/?utm_source=blog-speech-image">observability</a>.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/docarray?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store</div><div class="kg-bookmark-description">🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store - GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Se...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/438303578/57aae8cb-5b20-4e35-a46c-9a742af1470c" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps</div><div class="kg-bookmark-description">🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps - GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cl...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/6d66c5cb-b3e8-4bc2-b2ee-b01b9d90933d" alt=""></div></a></figure><p>These pipelines and building blocks are not just concepts: A Flow is a cloud-native application, while each Executor is a microservice.</p><p>Jina translates the conceptual composition of building blocks at the programming language level (By module/class separation) into a cloud-native composition, with each Executor as its own microservice. These microservices can be seamlessly replicated and sharded. The Flow and the Executors are powered by state of the art networking tools and relies on duplex streaming networking.</p><p>This solves the problems we outlined above:</p><ul><li><strong>Dependency Hell</strong> - each model will be wrapped into it’s own microservice, so dependencies don’t interfere with each other</li><li><strong>Choosing a data format</strong> - DocArray handles whatever we throw at it, be it audio, text, image or anything else.</li><li><strong>Tying it all together</strong> - A Jina Flow orchestrates the microservices and provides an API for users to interact with them. With Jina’s cloud-native functionality we can easily deploy to Kubernetes or JCloud and get monitoring and observability.</li></ul><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/example-speech-to-image?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/example-speech-to-image: An example of building a speech to image generation pipeline with Jina, Whisper and StableDiffusion</div><div class="kg-bookmark-description">An example of building a speech to image generation pipeline with Jina, Whisper and StableDiffusion - GitHub - jina-ai/example-speech-to-image: An example of building a speech to image generation p...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/be6ae59129584484a2169cc48e3540b43971bc57a2c48ea6e5b6be47273852fa/jina-ai/example-speech-to-image" alt=""></div></a><figcaption>All of the code is available here</figcaption></figure><h3 id="building-executors">Building Executors</h3><p>Every kind of multi-modal search or creation task requires several steps, which differ depending on what you’re trying to achieve. In our case, the steps are:</p><ol><li>Take a user’s voice as input in the UI.</li><li>Transcribe that speech into text using Whisper.</li><li>Take that text output and feed it into Stable Diffusion to generate an image.</li><li>Display that image to the user in the UI.</li></ol><p>In this example we’re just focusing on backend matters, so we’ll focus on just steps 2 and 3. For each of these we’ll wrap a model into an Executor:</p><ul><li>WhisperExecutor - transcribes a user’s voice input into text.</li><li>StableDiffusionExecutor - generates images based on the text string generated by WhisperExecutor.</li></ul><p>In Jina an Executor is a microservice that performs a single task. All Executors use Documents as their native data format. There’s more on that in the “streaming data” section.</p><p>We program each of these Executors at the programming language level (with module/class separation). Each can be seamlessly sharded, replicated, and deployed on Kubernetes. They’re even fully observable by default.</p><p>Executor code typically looks like the snippet below (taken from WhisperExecutor). Each function that a user can call has its own <a href="https://docs.jina.ai/fundamentals/executor/executor-methods/?utm_source=blog-speech-image"><code>@requests</code> decorator</a>, specifying a network endpoint. Since we don’t specify a particular endpoint in this snippet, <code>transcribe()</code> gets called when accessing <em>any</em> endpoint:</p><pre><code class="language-python hljs"><span class="hljs-keyword">class</span> <span class="hljs-title class_">WhisperExecutor</span>(<span class="hljs-title class_ inherited__">Executor</span>):
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Speech-to-Image Creation Using Jina</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Use Jina, Whisper and Stable Diffusion to build a cloud-native application for generating images using your speech.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 132.812%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/PXL_20221116_122857628.PORTRAIT.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Sami Jaghouar, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 14, 2022 • 11 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-text">“Jarvis, paint me Captain America drinking a boba tea, wearing Gucci, and roller-skating around New York”<br><br><strong>Tony Stark, Iron Man 2</strong></div></div><p>We’re all used to our digital assistants. They can schedule alarms, read the weather and reel off a few corny jokes. But how can we take that further? Can we use our voice to interact with the world (and other machines) in newer and more interesting ways?</p><p>Right now, most digital assistants operate in a mostly <em>single-modal</em> capacity. Your voice goes in, their voice comes out. Maybe they perform a few other actions along the way, but you get the idea.</p><p>This single-modality way of working is kind of like the Iron Man Mark I armor. Sure, it’s the best at what it does, but we want to do more. Especially since we have all these cool new toys today.</p><p>Let’s do the metaphorical equivalent of strapping some lasers and rocket boots onto boring old Alexa. We’ll build a speech recognition system of our own with the ability to generate beautiful AI-powered imagery. And we can apply the lessons from that to build even more complex applications further down the line.</p><p>Instead of a single-modal assistant like Alexa or Siri, we’re moving into <a href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai?ref=jina-ai-gmbh.ghost.io">the bright world of <strong>multi-modality</strong></a>, where we can use text to generate images, audio to generate video, or basically any modality (i.e. type of media) to create (or search) any other kind of modality.</p><p>You don’t need to be a Stark-level genius to make this happen. Hell, you barely need to be a Hulk level intellect. We’ll do it all in under 90 lines of code.</p><p>And what’s more, we’ll do all that with a cloud-native microservice architecture and deploy it to Kubernetes.</p><h2 id="preliminary-research">Preliminary research</h2><p>AI has been exploding over the past few years, and we’re rapidly moving from primitive single-modality models (e.g. Transformers for text, Big Image Transfer for images) to multi-modal models that can handle different kinds of data at once (e.g. CLIP, which can handle text, images, and audio all at once).</p><p>But hell, even that’s yesterday’s news. Just this year we’ve seen an explosion in tools that can generate images from text prompts (again with that multi-modality), like <a href="https://colab.research.google.com/github/jina-ai/dalle-flow/blob/main/client.ipynb?ref=jina-ai-gmbh.ghost.io">DiscoArt</a>, DALL-E 2 and Stable Diffusion. That’s not to mention some of the other models out there, which can <a href="https://github.com/nateraw/stable-diffusion-videos?ref=jina-ai-gmbh.ghost.io">generate video from text prompts</a> or <a href="https://betterprogramming.pub/dall-e-to-3d-how-to-turn-your-generative-art-into-3d-meshes-3ca086dc0b0c?ref=jina-ai-gmbh.ghost.io">generate 3D meshes from images</a>.</p><p>Let’s create some images with Stable Diffusion (since we’re using that to build our example):</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/cap_on_bike.png" class="kg-image" alt="Image Description" width="1536" height="512" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/cap_on_bike.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/cap_on_bike.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/cap_on_bike.png 1536w" sizes="(min-width: 720px) 720px"><figcaption>Prompt: A photograph of Captain America riding a motorbike</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/ironman_skywalker.png" class="kg-image" alt="Image Description" width="1536" height="512" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/ironman_skywalker.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/ironman_skywalker.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/ironman_skywalker.png 1536w" sizes="(min-width: 720px) 720px"><figcaption>Prompt: A photograph of Iron Man dancing with Luke Skywalker</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/spidey.png" class="kg-image" alt="Image Description" width="1536" height="512" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/spidey.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/spidey.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/spidey.png 1536w" sizes="(min-width: 720px) 720px"><figcaption>Prompt: A digital illustration of Spider-man swinging through New York, 4k, detailed, trending in artstation, fantasy vivid colors</figcaption></figure><p>But it’s not just multi-modal text-to-image generation that’s hot right now. Just a few weeks ago, OpenAI released <a href="https://openai.com/blog/whisper/?utm_source=blog-speech-image">Whisper</a>, an automatic speech-recognition system robust enough to handle to accents, background noise, and technical language.</p><p>This post will integrate Whisper and Stable Diffusion, so a user can speak a phrase, Whisper will convert it to text, and Stable Diffusion will use that text to create an image.</p><h3 id="existing-works">Existing works</h3><p>This isn’t really a new concept. Many people have written papers on it or created examples before:</p><ul><li><a href="https://arxiv.org/abs/2005.06968?ref=jina-ai-gmbh.ghost.io">S2IGAN: Speech-to-Image Generation via Adversarial Learning</a></li><li><a href="https://smallflyingpig.github.io/speech-to-image/main?ref=jina-ai-gmbh.ghost.io">Direct Speech-to-Image Translation</a></li><li><a href="https://towardsdatascience.com/using-ai-to-generate-art-22e030497f73?ref=jina-ai-gmbh.ghost.io">Using AI to Generate Art - A Voice-Enabled Art Generation Tool</a></li><li><a href="https://www.assemblyai.com/blog/built-with-assemblyai-real-time-speech-to-image-generation/?utm_source=blog-speech-image">Built with AssemblyAI - Real-time Speech-to-Image Generation</a></li></ul><p>The difference is that our example will use cutting edge models, be fully scalable, leverage a microservices architecture, and be simple to deploy to Kubernetes. What’s more, it’ll do all of that in fewer lines of code than the above examples.</p><h2 id="the-problem">The problem</h2><p>With all these new AI models for multi-modal generation, your imagination is the limit when it comes to thinking of what you can build. But just thinking something isn’t the same as building it. And therein lies some of the key problems:</p><p><strong>Dependency Hell</strong></p><p>Building fully-integrated monolithic systems is relatively straightforward, but tying together too many cutting edge deep learning models can lead to dependency conflicts. These models were built to showcase cool tech, not to play nice with others.</p><p>That’s like if Iron Man’s rocket boots were incompatible with his laser cannons. He’d be flying around shooting down Chitauri, then plummet out of the sky like a rock as his boots crashed.</p><p>That’s right everyone. This is no longer about just building a cool demo. We are saving. Iron Man’s. Life. <sup><a>[2]</a></sup></p><p><strong>Choosing a data format</strong></p><p>If we’re dealing with multiple modalities, choosing a data format to interoperate between these different models is painful. If we’re just dealing with a single modality like text, we can use plain old strings. If we’re dealing with images we <em>could</em> use image tensors. In our example, we’re dealing with audio <em>and</em> images. How much pain will <em>that</em> be?</p><p><strong>Tying it all together</strong></p><p>But the biggest challenge of all is <strong>mixing different models</strong> to create a <strong>fully-fledged application</strong>. Sure, you can wrap one model in a web API, containerize it, and deploy it on the cloud. But as soon as you need to chain together two models to create a slightly-more-complex application it gets messy. Especially if you want to build a true microservices-based application than can, for instance, replicate some part of your pipeline to avoid downtime. How do you communicate between the different models? And that’s not to mention deploying on a cloud-native platform like Kubernetes or having observability and monitoring for your pipeline.</p><h2 id="the-solution">The solution</h2><p>Jina AI is building a comprehensive MLOps platform around multimodal AI to help developers and businesses solve challenges like speech-to-image. To integrate Whisper and Stable Diffusion in a clean, scalable, deployable way, we’ll:</p><ul><li>Use <strong>Jina</strong> to wrap the deep learning models into <a href="https://docs.jina.ai/fundamentals/executor/index.html?utm_source=blog-speech-image">Executor</a>s.</li><li>Combine these Executors into a complex Jina <a href="https://docs.jina.ai/fundamentals/flow/?utm_source=blog-speech-image">Flow</a> (a cloud-native AI application with replication, sharding, etc).</li><li>Use <strong><a href="http://docarray.jina.ai/?utm_source=blog-speech-image">DocArray</a></strong> to stream our data (with different modalities) through the Flow, where it will be processed by each Executor in turn.</li><li>Deploy all of that to <a href="https://docs.jina.ai/how-to/kubernetes/?utm_source=blog-speech-image">Kubernetes</a>/<strong><a href="https://docs.jina.ai/fundamentals/jcloud/?utm_source=blog-speech-image">JCloud</a></strong> with full <a href="https://docs.jina.ai/how-to/monitoring/?utm_source=blog-speech-image">observability</a>.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/docarray?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store</div><div class="kg-bookmark-description">🧬 The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store - GitHub - jina-ai/docarray: 🧬 The data structure for unstructured multimodal data · Neural Se...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/438303578/57aae8cb-5b20-4e35-a46c-9a742af1470c" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/jina?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps</div><div class="kg-bookmark-description">🔮 Build cross-modal and multimodal applications on the cloud · Neural Search · Creative AI · Cloud Native · MLOps - GitHub - jina-ai/jina: 🔮 Build cross-modal and multimodal applications on the cl...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/240315046/6d66c5cb-b3e8-4bc2-b2ee-b01b9d90933d" alt=""></div></a></figure><p>These pipelines and building blocks are not just concepts: A Flow is a cloud-native application, while each Executor is a microservice.</p><p>Jina translates the conceptual composition of building blocks at the programming language level (By module/class separation) into a cloud-native composition, with each Executor as its own microservice. These microservices can be seamlessly replicated and sharded. The Flow and the Executors are powered by state of the art networking tools and relies on duplex streaming networking.</p><p>This solves the problems we outlined above:</p><ul><li><strong>Dependency Hell</strong> - each model will be wrapped into it’s own microservice, so dependencies don’t interfere with each other</li><li><strong>Choosing a data format</strong> - DocArray handles whatever we throw at it, be it audio, text, image or anything else.</li><li><strong>Tying it all together</strong> - A Jina Flow orchestrates the microservices and provides an API for users to interact with them. With Jina’s cloud-native functionality we can easily deploy to Kubernetes or JCloud and get monitoring and observability.</li></ul><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/example-speech-to-image?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/example-speech-to-image: An example of building a speech to image generation pipeline with Jina, Whisper and StableDiffusion</div><div class="kg-bookmark-description">An example of building a speech to image generation pipeline with Jina, Whisper and StableDiffusion - GitHub - jina-ai/example-speech-to-image: An example of building a speech to image generation p...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/be6ae59129584484a2169cc48e3540b43971bc57a2c48ea6e5b6be47273852fa/jina-ai/example-speech-to-image" alt=""></div></a><figcaption>All of the code is available here</figcaption></figure><h3 id="building-executors">Building Executors</h3><p>Every kind of multi-modal search or creation task requires several steps, which differ depending on what you’re trying to achieve. In our case, the steps are:</p><ol><li>Take a user’s voice as input in the UI.</li><li>Transcribe that speech into text using Whisper.</li><li>Take that text output and feed it into Stable Diffusion to generate an image.</li><li>Display that image to the user in the UI.</li></ol><p>In this example we’re just focusing on backend matters, so we’ll focus on just steps 2 and 3. For each of these we’ll wrap a model into an Executor:</p><ul><li>WhisperExecutor - transcribes a user’s voice input into text.</li><li>StableDiffusionExecutor - generates images based on the text string generated by WhisperExecutor.</li></ul><p>In Jina an Executor is a microservice that performs a single task. All Executors use Documents as their native data format. There’s more on that in the “streaming data” section.</p><p>We program each of these Executors at the programming language level (with module/class separation). Each can be seamlessly sharded, replicated, and deployed on Kubernetes. They’re even fully observable by default.</p><p>Executor code typically looks like the snippet below (taken from WhisperExecutor). Each function that a user can call has its own <a href="https://docs.jina.ai/fundamentals/executor/executor-methods/?utm_source=blog-speech-image"><code>@requests</code> decorator</a>, specifying a network endpoint. Since we don’t specify a particular endpoint in this snippet, <code>transcribe()</code> gets called when accessing <em>any</em> endpoint:</p><pre><code class="language-python hljs"><span class="hljs-keyword">class</span> <span class="hljs-title class_">WhisperExecutor</span>(<span class="hljs-title class_ inherited__">Executor</span>):
     <span class="hljs-keyword">def</span> <span class="hljs-title function_">__init__</span>(<span class="hljs-params">self, *args, **kwargs</span>):
         <span class="hljs-built_in">super</span>().__init__(*args, **kwargs)
         self.model = whisper.load_model(<span class="hljs-string">'base'</span>)
@@ -44,7 +44,7 @@
 <span class="hljs-keyword">with</span> f:
     f.block()
 </code></pre><p>A Flow can be <a href="https://docs.jina.ai/fundamentals/flow/create-flow/?ref=jina-ai-gmbh.ghost.io#visualize?utm_source=blog-speech-image">visualized</a> with <code>flow.plot()</code>:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/flow.svg" class="kg-image" alt="flow" width="737" height="120"></figure><h3 id="streaming-data">Streaming data</h3><p>Everything that comes into and goes out of our Flow is a <a href="https://docarray.jina.ai/fundamentals/document?utm_source=blog-speech-image">Document</a>, which is a class from the DocArray package. <a href="https://github.com/jina-ai/docarray?utm_source=blog-speech-image">DocArray</a> provides a common API for multiple modalities (in our case, audio, text, image), letting us mix concepts and create multi-modal Documents that can be sent over the wire.</p><p>That means that no matter what data modality we’re using, a Document can store it. And since all Executors use Documents (and <a href="https://docarray.jina.ai/fundamentals/documentarray/?utm_source=blog-speech-image">DocumentArrays</a>) as their data format, consistency is ensured.</p><p>In this speech-to-image example, the input Document is an audio sample of the user’s voice, captured by the UI. This is stored in a Document as a tensor.</p><p>If we regard the input Document as <code>doc</code>:</p><ol><li>Initially the <code>doc</code> is created by the UI and the user’s voice input is stored in <code>doc.tensor</code>.</li><li>The <code>doc</code> is send over the wire via gRPC call from the UI to the WhisperExecutor.</li><li>Then the WhisperExecutor takes that tensor and transcribes it to <code>doc.text</code>.</li><li>The <code>doc</code> moves onto the StableDiffusion Executor.</li><li>The StableDiffusion Executor reads in <code>doc.text</code> and generates two images which get stored (as Documents) in <code>doc.matches</code>.</li><li>The UI receives the <code>doc</code> back from the Flow.</li><li>Finally, the UI takes that output Document and renders each of the matches.</li></ol><h3 id="connecting-to-a-flow">Connecting to a Flow</h3><p>After opening the Flow, users can connect with <a href="https://docs.jina.ai/fundamentals/client/client/?utm_source=blog-speech-image">Jina Client</a> or <a href="https://docs.jina.ai/fundamentals/client/third-party-client/?utm_source=blog-speech-image">a third-party client</a>. In this example, the Flow exposes gRPC endpoints but could be easily changed (with one line of code) to implement RESTful, WebSockets or GraphQL endpoints instead.</p><h3 id="deploying-a-flow">Deploying a Flow</h3><p>As a cloud-native framework, Jina shines brightest when coupled with Kubernetes. The <a href="https://docs.jina.ai/how-to/kubernetes/?utm_source=blog-speech-image">documentation</a> explains <em>how</em> to deploy a Flow on Kubernetes, but let’s get some insight into what’s happening under the hood.</p><p>As mentioned earlier, an Executor is a containerized microservice. Both Executors in our application are deployed independently on Kubernetes as a <a href="https://kubernetes.io/docs/concepts/workloads/controllers/deployment/?utm_source=blog-speech-image">Deployment</a>. This means Kubernetes handles their lifecycle, scheduling on the correct machine etc. In addition, the <a href="https://docs.jina.ai/fundamentals/gateway/?utm_source=blog-speech-image">Gateway</a> is deployed in the Deployment to flow the requests through the Executors. This translation to Kubernetes concepts is done on the fly by Jina. You simply need to define your Flow in Python.</p><p>Alternatively a Flow can be deployed on JCloud, which handles all of the above, as well as providing an out-of-the-box monitoring dashboard. To do so, the Python Flow needs to be <a href="https://docs.jina.ai/fundamentals/flow/yaml-spec/?utm_source=blog-speech-image">converted to a YAML Flow</a> (with a few <a href="https://docs.jina.ai/fundamentals/jcloud/yaml-spec/?utm_source=blog-speech-image">JCloud specific parameters</a>), and then deployed:</p><pre><code class="language-shell hljs">jc deploy flow.yaml
-</code></pre><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/example-speech-to-image?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/example-speech-to-image: An example of building a speech to image generation pipeline with Jina, Whisper and StableDiffusion</div><div class="kg-bookmark-description">An example of building a speech to image generation pipeline with Jina, Whisper and StableDiffusion - GitHub - jina-ai/example-speech-to-image: An example of building a speech to image generation p...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/be6ae59129584484a2169cc48e3540b43971bc57a2c48ea6e5b6be47273852fa/jina-ai/example-speech-to-image" alt=""></div></a><figcaption>There’s a pre-configured <code>flow.yml</code> in this repo.</figcaption></figure><h2 id="results">Results</h2><p>Let’s take the app for a spin and give it some test queries:</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2022/10/speech_image_blog-2022-10-13_15.18.17.webm" poster="https://img.spacergif.org/v1/1600x900/0a/spacer.png" width="1600" height="900" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2022/10/media-thumbnail-ember597.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player" style="--buffered-width:0%;"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration">0:14</span></div><input type="range" class="kg-video-seek-slider" max="14" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>A watercolor portrait of Thor from the Marvel movies carrying Mjolnir</figcaption></figure><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2022/10/iron_man_country_dancing.webm" poster="https://img.spacergif.org/v1/1600x900/0a/spacer.png" width="1600" height="900" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2022/10/media-thumbnail-ember621.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player" style="--buffered-width:100%;"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration">0:16</span></div><input type="range" class="kg-video-seek-slider" max="16" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>An oil painting of Iron Man dancing in the countryside by Botticelli</figcaption></figure><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2022/10/hulk_dinner.webm" poster="https://img.spacergif.org/v1/1600x900/0a/spacer.png" width="1600" height="900" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2022/10/media-thumbnail-ember636.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player" style="--buffered-width:100%;"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration">0:16</span></div><input type="range" class="kg-video-seek-slider" max="16" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>A watercolor portrait of the Incredible Hulk eating his dinner in the style of Leonardo Da Vinci</figcaption></figure><p>With <a href="https://docs.jina.ai/how-to/monitoring/?utm_source=blog-speech-image">monitoring</a> enabled (which is the default in JCloud), everything that happens inside the Flow can be monitored on a Grafana dashboard:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled.png" class="kg-image" alt="Image Description" width="1917" height="987" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Untitled.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/Untitled.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/Untitled.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled.png 1917w" sizes="(min-width: 720px) 720px"></figure><p>One advantage of monitoring is that it can help you optimize your application to make it more resilient in a cost-effective way by detecting bottlenecks. The monitoring shows that the StableDiffusion Executor is a performance bottleneck:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Screenshot-from-2022-10-11-14-42-06-1.png" class="kg-image" alt="Image Description" width="1913" height="977" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Screenshot-from-2022-10-11-14-42-06-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/Screenshot-from-2022-10-11-14-42-06-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/Screenshot-from-2022-10-11-14-42-06-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Screenshot-from-2022-10-11-14-42-06-1.png 1913w" sizes="(min-width: 720px) 720px"></figure><p>This means that latency would skyrocket under a heavy workload. To get around this, we can replicate the StableDiffusion Executor to split image generation between different machines, thereby increasing efficiency:</p><pre><code class="language-python hljs">f = (
+</code></pre><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://github.com/jina-ai/example-speech-to-image?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/example-speech-to-image: An example of building a speech to image generation pipeline with Jina, Whisper and StableDiffusion</div><div class="kg-bookmark-description">An example of building a speech to image generation pipeline with Jina, Whisper and StableDiffusion - GitHub - jina-ai/example-speech-to-image: An example of building a speech to image generation p...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/be6ae59129584484a2169cc48e3540b43971bc57a2c48ea6e5b6be47273852fa/jina-ai/example-speech-to-image" alt=""></div></a><figcaption>There’s a pre-configured <code>flow.yml</code> in this repo.</figcaption></figure><h2 id="results">Results</h2><p>Let’s take the app for a spin and give it some test queries:</p><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2022/10/speech_image_blog-2022-10-13_15.18.17.webm" poster="https://img.spacergif.org/v1/1600x900/0a/spacer.png" width="1600" height="900" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2022/10/media-thumbnail-ember597.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player" style="--buffered-width:7.14286%;"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration">0:14</span></div><input type="range" class="kg-video-seek-slider" max="14" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>A watercolor portrait of Thor from the Marvel movies carrying Mjolnir</figcaption></figure><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2022/10/iron_man_country_dancing.webm" poster="https://img.spacergif.org/v1/1600x900/0a/spacer.png" width="1600" height="900" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2022/10/media-thumbnail-ember621.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player" style="--buffered-width:37.5%;"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration">0:16</span></div><input type="range" class="kg-video-seek-slider" max="16" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>An oil painting of Iron Man dancing in the countryside by Botticelli</figcaption></figure><figure class="kg-card kg-video-card kg-card-hascaption"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2022/10/hulk_dinner.webm" poster="https://img.spacergif.org/v1/1600x900/0a/spacer.png" width="1600" height="900" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2022/10/media-thumbnail-ember636.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player" style="--buffered-width:31.25%;"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration">0:16</span></div><input type="range" class="kg-video-seek-slider" max="16" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div><figcaption>A watercolor portrait of the Incredible Hulk eating his dinner in the style of Leonardo Da Vinci</figcaption></figure><p>With <a href="https://docs.jina.ai/how-to/monitoring/?utm_source=blog-speech-image">monitoring</a> enabled (which is the default in JCloud), everything that happens inside the Flow can be monitored on a Grafana dashboard:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled.png" class="kg-image" alt="Image Description" width="1917" height="987" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Untitled.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/Untitled.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/Untitled.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled.png 1917w" sizes="(min-width: 720px) 720px"></figure><p>One advantage of monitoring is that it can help you optimize your application to make it more resilient in a cost-effective way by detecting bottlenecks. The monitoring shows that the StableDiffusion Executor is a performance bottleneck:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Screenshot-from-2022-10-11-14-42-06-1.png" class="kg-image" alt="Image Description" width="1913" height="977" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/10/Screenshot-from-2022-10-11-14-42-06-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/10/Screenshot-from-2022-10-11-14-42-06-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/10/Screenshot-from-2022-10-11-14-42-06-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/10/Screenshot-from-2022-10-11-14-42-06-1.png 1913w" sizes="(min-width: 720px) 720px"></figure><p>This means that latency would skyrocket under a heavy workload. To get around this, we can replicate the StableDiffusion Executor to split image generation between different machines, thereby increasing efficiency:</p><pre><code class="language-python hljs">f = (
     Flow(port=<span class="hljs-number">54322</span>)
     .add(uses=WhisperExecutor)
     .add(uses=StableDiffusionExecutor, uses_with={<span class="hljs-string">'auth_token'</span>: hf_token}, replicas=<span class="hljs-number">2</span>)
@@ -58,4 +58,4 @@
   <span class="hljs-attr">jcloud:</span>
     <span class="hljs-attr">resources:</span>
       <span class="hljs-attr">gpu:</span> <span class="hljs-number">1</span>
-      <span class="hljs-attr">memory:</span> <span class="hljs-number">16</span></code></pre><h2 id="conclusion">Conclusion</h2><p>In this post we created a cloud-native audio-to-image generation tool using the state of the art AI models and the Jina AI MLOps platform.</p><p>With DocArray we used one data format to handle everything, allowing us to easily stream data back and forth. And with Jina we created a complex serving pipeline natively employing microservices, which we could then easily deploy to Kubernetes.</p><p>Since Jina provides a modular architecture, it’s straightforward to apply a similar solution to very different use cases, such as:</p><ul><li>Building a multi-modal PDF neural search engine, where a user can search for matching PDFs using strings or images.</li><li>Building a multi-modal fashion neural search engine, where users can find products based on a string or image.</li><li>Generating 3D models for movie scene design using a string or image as input.</li><li>Generating complex blog posts using GPT-3.</li></ul><p>All of these can be done in a manner that is cloud-native, scalable, and simple to deploy with Kubernetes.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fspeech-to-image-generation%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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+      <span class="hljs-attr">memory:</span> <span class="hljs-number">16</span></code></pre><h2 id="conclusion">Conclusion</h2><p>In this post we created a cloud-native audio-to-image generation tool using the state of the art AI models and the Jina AI MLOps platform.</p><p>With DocArray we used one data format to handle everything, allowing us to easily stream data back and forth. And with Jina we created a complex serving pipeline natively employing microservices, which we could then easily deploy to Kubernetes.</p><p>Since Jina provides a modular architecture, it’s straightforward to apply a similar solution to very different use cases, such as:</p><ul><li>Building a multi-modal PDF neural search engine, where a user can search for matching PDFs using strings or images.</li><li>Building a multi-modal fashion neural search engine, where users can find products based on a string or image.</li><li>Generating 3D models for movie scene design using a string or image as input.</li><li>Generating complex blog posts using GPT-3.</li></ul><p>All of these can be done in a manner that is cloud-native, scalable, and simple to deploy with Kubernetes.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fspeech-to-image-generation%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/full-stack-rag-with-jina-embeddings-v2-and-llamaindex" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Full-stack RAG with Jina Embeddings v2 and LlamaIndex</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">You can build your own RAG chatbot in a matter of minutes with Jina Embeddings, LlamaIndex and Mixtral Instruct. We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-magic-carpet-ride-building-vivid-product-stories-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Taming OpenAI's Function Call: A Dive into PromptPerfect's Function Debugger</title><meta charset="utf-8"><meta name="title" content="Taming OpenAI's Function Call: A Dive into PromptPerfect's Function Debugger"><meta name="description" content="Discover how PromptPerfect simplifies function calls in OpenAI's language models, offering auto JSON Schema generation, advanced debugging, and more."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/taming-openais-function-call-a-dive-into-promptperfects-function-debugger"><meta property="og:title" content="Taming OpenAI's Function Call: A Dive into PromptPerfect's Function Debugger"><meta property="og:description" content="Discover how PromptPerfect simplifies function calls in OpenAI's language models, offering auto JSON Schema generation, advanced debugging, and more."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_holographic_hypercube_with_light_in_it_in_the_st_d84b23b0-a17a-45ad-a2fa-e0b9f9ec41e2.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/taming-openais-function-call-a-dive-into-promptperfects-function-debugger"><meta property="twitter:title" content="Taming OpenAI's Function Call: A Dive into PromptPerfect's Function Debugger"><meta property="twitter:description" content="Discover how PromptPerfect simplifies function calls in OpenAI's language models, offering auto JSON Schema generation, advanced debugging, and more."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_holographic_hypercube_with_light_in_it_in_the_st_d84b23b0-a17a-45ad-a2fa-e0b9f9ec41e2.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 01, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>OpenAI has been on the forefront of innovative developments in the realm of artificial intelligence, consistently introducing tools and APIs that allow developers to leverage the power of AI in a variety of applications. One of their latest offerings nested since the <code>gpt-3.5-turbo-0613</code> and <code>gpt-4-0613</code> models is the <a href="https://platform.openai.com/docs/guides/gpt/function-calling?ref=jina-ai-gmbh.ghost.io">function calling feature</a>, and it's creating quite a buzz.</p><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 689px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=eyJ0ZndfdGltZWxpbmVfbGlzdCI6eyJidWNrZXQiOltdLCJ2ZXJzaW9uIjpudWxsfSwidGZ3X2ZvbGxvd2VyX2NvdW50X3N1bnNldCI6eyJidWNrZXQiOnRydWUsInZlcnNpb24iOm51bGx9LCJ0ZndfdHdlZXRfZWRpdF9iYWNrZW5kIjp7ImJ1Y2tldCI6Im9uIiwidmVyc2lvbiI6bnVsbH0sInRmd19yZWZzcmNfc2Vzc2lvbiI6eyJidWNrZXQiOiJvbiIsInZlcnNpb24iOm51bGx9LCJ0ZndfZm9zbnJfc29mdF9pbnRlcnZlbnRpb25zX2VuYWJsZWQiOnsiYnVja2V0Ijoib24iLCJ2ZXJzaW9uIjpudWxsfSwidGZ3X21peGVkX21lZGlhXzE1ODk3Ijp7ImJ1Y2tldCI6InRyZWF0bWVudCIsInZlcnNpb24iOm51bGx9LCJ0ZndfZXhwZXJpbWVudHNfY29va2llX2V4cGlyYXRpb24iOnsiYnVja2V0IjoxMjA5NjAwLCJ2ZXJzaW9uIjpudWxsfSwidGZ3X3Nob3dfYmlyZHdhdGNoX3Bpdm90c19lbmFibGVkIjp7ImJ1Y2tldCI6Im9uIiwidmVyc2lvbiI6bnVsbH0sInRmd19kdXBsaWNhdGVfc2NyaWJlc190b19zZXR0aW5ncyI6eyJidWNrZXQiOiJvbiIsInZlcnNpb24iOm51bGx9LCJ0ZndfdXNlX3Byb2ZpbGVfaW1hZ2Vfc2hhcGVfZW5hYmxlZCI6eyJidWNrZXQiOiJvbiIsInZlcnNpb24iOm51bGx9LCJ0ZndfdmlkZW9faGxzX2R5bmFtaWNfbWFuaWZlc3RzXzE1MDgyIjp7ImJ1Y2tldCI6InRydWVfYml0cmF0ZSIsInZlcnNpb24iOm51bGx9LCJ0ZndfbGVnYWN5X3RpbWVsaW5lX3N1bnNldCI6eyJidWNrZXQiOnRydWUsInZlcnNpb24iOm51bGx9LCJ0ZndfdHdlZXRfZWRpdF9mcm9udGVuZCI6eyJidWNrZXQiOiJvbiIsInZlcnNpb24iOm51bGx9fQ%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1668668732347129856&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ftaming-openais-function-call-a-dive-into-promptperfects-function-debugger%2F&amp;sessionId=3f5cfaf90301e05877e8e43a612aaa89a5cee7b0&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1668668732347129856"></iframe></div>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Discover how PromptPerfect simplifies function calls in OpenAI's language models, offering auto JSON Schema generation, advanced debugging, and more.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 01, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>OpenAI has been on the forefront of innovative developments in the realm of artificial intelligence, consistently introducing tools and APIs that allow developers to leverage the power of AI in a variety of applications. One of their latest offerings nested since the <code>gpt-3.5-turbo-0613</code> and <code>gpt-4-0613</code> models is the <a href="https://platform.openai.com/docs/guides/gpt/function-calling?ref=jina-ai-gmbh.ghost.io">function calling feature</a>, and it's creating quite a buzz.</p><figure class="kg-card kg-embed-card"><blockquote class="twitter-tweet"><p lang="en" dir="ltr">GPT-4 and GPT-3.5 Turbo models in the API now support calling your custom functions, allowing the model to use tools you design for it. Also — reduced pricing &amp; new model versions (including 16k context for 3.5 Turbo): <a href="https://t.co/dalfgEQ9k2?ref=jina-ai-gmbh.ghost.io">https://t.co/dalfgEQ9k2</a></p>— OpenAI (@OpenAI) <a href="https://twitter.com/OpenAI/status/1668668732347129856?ref_src=twsrc%5Etfw&amp;ref=jina-ai-gmbh.ghost.io">June 13, 2023</a></blockquote>
 <script async="" src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
-</figure><p>Function calling is a game-changer for developers. It allows you to describe functions to the model and have it intelligently output a JSON object containing the necessary arguments to call those functions. The beauty of this feature is that it bridges the gap between natural language inputs and the structured data required for a wide array of applications - from creating chatbots and converting natural language into API calls to extracting structured data from text.</p><p>However, as with any powerful tool, the function calling feature does come with its complexities. <strong>Developers need to provide a detailed JSON schema for every function that clearly labels the purpose, input, and output of each function.</strong> For a large system with numerous functions, this requirement can be daunting.</p><p>In this blog post, we'll take a closer look at this challenge and explore how the newly released function debugger from PromptPerfect can assist developers in overcoming this hurdle. We'll delve into the debugger's capabilities, from auto-generating JSON schemas to enabling easy testing and debugging of function calls.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection with AI Prompt Engineering</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, MidJourney and StableDiffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficienc…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><p>So, buckle up for an in-depth exploration of how to leverage the function debugger from PromptPerfect to tame the OpenAI function call beast. The journey ahead promises to be both enlightening and rewarding.</p><h2 id="from-natural-language-to-predefined-functions-the-power-of-openais-function-calling">From Natural Language to Predefined Functions: The Power of OpenAI's Function Calling</h2><p>The announcement of OpenAI's function calling feature might initially create an impression that it's primarily a tool for retrieving structured data from the model. However, it's the ability to <strong>convert natural language into a set of predefined functions</strong> that truly embodies its power and significance.</p><p>Consider a more interactive scenario - the smart speaker that's become an integral part of our daily lives. Let's say you tell your smart speaker, </p><blockquote class="kg-blockquote-alt">"Hey, check the weather for tonight. If it's good, book a table for two outdoors at Luigi's Pizzeria at 7 PM, otherwise, book it indoors."</blockquote><p>This one command encompasses two interdependent requests - checking the weather and making a restaurant reservation based on the weather conditions. These actions correspond to two predefined functions, <code>check_weather(location: string, date: string)</code> and <code>book_table(restaurant: string, party_size: int, time: string, location: 'outdoor' | 'indoor')</code>. The function calling feature converts your natural language command into these function calls.</p><p>This functionality of the OpenAI API effectively allows Large Language Models (LLMs) to easily access external tools and APIs. It resonates with other advanced frameworks such as ReAct prompting, introduced by Yao et al., 2022, where LLMs generate both reasoning traces and task-specific actions in an interleaved manner. This synergy between reasoning and acting lets the model interact with external tools to retrieve additional information, leading to more reliable and factual responses.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2210.03629?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">ReAct: Synergizing Reasoning and Acting in Language Models</div><div class="kg-bookmark-description">While large language models (LLMs) have demonstrated impressive capabilitiesacross tasks in language understanding and interactive decision making, theirabilities for reasoning (e.g. chain-of-thought prompting) and acting (e.g.action plan generation) have primarily been studied as separate topics…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Shunyu Yao</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><p>Similarly, it brings to mind concepts like Auto-GPT, an application that uses OpenAI's text-generating models to interact with software and services online. Auto-GPT is essentially a companion bot that uses GPT-3.5 and GPT-4 models to carry out instructions autonomously, leveraging the OpenAI models' ability to interact with apps, software, and services.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/auto-gpt-unmasked-hype-hard-truths-production-pitfalls/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Auto-GPT Unmasked: The Hype and Hard Truths of Its Production Pitfalls</div><div class="kg-bookmark-description">Auto-GPT: A groundbreaking project or just another overhyped AI experiment? In this blog post, we unravel the truth behind the buzz and reveal the limitations that make this project unsuitable for real-world applications.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">GitHub</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/generativejina_a_hq_illustration_of_Divide-and-Conquer_algorith_61aea026-11fe-4595-83b8-94a6bf1dcff2-1.png" alt=""></div></a></figure><p>The function calling feature brings us one step closer to the seamless integration of artificial intelligence into our daily lives. It allows for active and dynamic interaction with external tools and APIs, going beyond mere structured data retrieval. However, the journey to achieving this fluid interaction is not without challenges. Ensuring that these function calls are triggered correctly and yield the desired results requires thorough debugging and fine-tuning, which is where PromptPerfect's function debugger comes into play. In the next section, we'll delve into how this tool can be utilized to enhance and streamline the development process of such AI systems.</p><h2 id="bridging-the-gap-from-openais-function-calling-to-developers-toolchain">Bridging the Gap: From OpenAI's Function Calling to Developer's Toolchain</h2><p>Even though OpenAI's function calling feature offers a powerful capability to convert natural language into predefined functions, there are still some obstacles for developers when it comes to practical implementation. Let's delve into these challenges and see how PromptPerfect can provide solutions to overcome them.</p><h3 id="problem-1-json-schema-generation-and-maintenance">Problem 1: JSON Schema Generation and Maintenance</h3><p>To use OpenAI's function calling feature, developers need to provide a JSON Schema for each function. This schema is crucial because it dictates how the function will be recognized and called by the language model. However, writing these schemas manually can be quite challenging, especially when there are multiple functions involved.</p><p>On top of that, maintaining these schemas can also become increasingly complex as the number of functions grows or as functions evolve over time.</p><p>Here is an example of a function and its corresponding JSON Schema:</p><figure class="kg-card kg-code-card"><pre><code class="language-python hljs"><span class="hljs-keyword">def</span> <span class="hljs-title function_">get_current_weather</span>(<span class="hljs-params">location, unit=<span class="hljs-string">"fahrenheit"</span></span>):
-    <span class="hljs-string">"""Get the current weather in a given location"""</span>
+</figure><p>Function calling is a game-changer for developers. It allows you to describe functions to the model and have it intelligently output a JSON object containing the necessary arguments to call those functions. The beauty of this feature is that it bridges the gap between natural language inputs and the structured data required for a wide array of applications - from creating chatbots and converting natural language into API calls to extracting structured data from text.</p><p>However, as with any powerful tool, the function calling feature does come with its complexities. <strong>Developers need to provide a detailed JSON schema for every function that clearly labels the purpose, input, and output of each function.</strong> For a large system with numerous functions, this requirement can be daunting.</p><p>In this blog post, we'll take a closer look at this challenge and explore how the newly released function debugger from PromptPerfect can assist developers in overcoming this hurdle. We'll delve into the debugger's capabilities, from auto-generating JSON schemas to enabling easy testing and debugging of function calls.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection with AI Prompt Engineering</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, MidJourney and StableDiffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficienc…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><p>So, buckle up for an in-depth exploration of how to leverage the function debugger from PromptPerfect to tame the OpenAI function call beast. The journey ahead promises to be both enlightening and rewarding.</p><h2 id="from-natural-language-to-predefined-functions-the-power-of-openais-function-calling">From Natural Language to Predefined Functions: The Power of OpenAI's Function Calling</h2><p>The announcement of OpenAI's function calling feature might initially create an impression that it's primarily a tool for retrieving structured data from the model. However, it's the ability to <strong>convert natural language into a set of predefined functions</strong> that truly embodies its power and significance.</p><p>Consider a more interactive scenario - the smart speaker that's become an integral part of our daily lives. Let's say you tell your smart speaker, </p><blockquote class="kg-blockquote-alt">"Hey, check the weather for tonight. If it's good, book a table for two outdoors at Luigi's Pizzeria at 7 PM, otherwise, book it indoors."</blockquote><p>This one command encompasses two interdependent requests - checking the weather and making a restaurant reservation based on the weather conditions. These actions correspond to two predefined functions, <code>check_weather(location: string, date: string)</code> and <code>book_table(restaurant: string, party_size: int, time: string, location: 'outdoor' | 'indoor')</code>. The function calling feature converts your natural language command into these function calls.</p><p>This functionality of the OpenAI API effectively allows Large Language Models (LLMs) to easily access external tools and APIs. It resonates with other advanced frameworks such as ReAct prompting, introduced by Yao et al., 2022, where LLMs generate both reasoning traces and task-specific actions in an interleaved manner. This synergy between reasoning and acting lets the model interact with external tools to retrieve additional information, leading to more reliable and factual responses.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2210.03629?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">ReAct: Synergizing Reasoning and Acting in Language Models</div><div class="kg-bookmark-description">While large language models (LLMs) have demonstrated impressive capabilitiesacross tasks in language understanding and interactive decision making, theirabilities for reasoning (e.g. chain-of-thought prompting) and acting (e.g.action plan generation) have primarily been studied as separate topics…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Shunyu Yao</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><p>Similarly, it brings to mind concepts like Auto-GPT, an application that uses OpenAI's text-generating models to interact with software and services online. Auto-GPT is essentially a companion bot that uses GPT-3.5 and GPT-4 models to carry out instructions autonomously, leveraging the OpenAI models' ability to interact with apps, software, and services.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/auto-gpt-unmasked-hype-hard-truths-production-pitfalls/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Auto-GPT Unmasked: The Hype and Hard Truths of Its Production Pitfalls</div><div class="kg-bookmark-description">Auto-GPT: A groundbreaking project or just another overhyped AI experiment? In this blog post, we unravel the truth behind the buzz and reveal the limitations that make this project unsuitable for real-world applications.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">GitHub</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/04/generativejina_a_hq_illustration_of_Divide-and-Conquer_algorith_61aea026-11fe-4595-83b8-94a6bf1dcff2-1.png" alt=""></div></a></figure><p>The function calling feature brings us one step closer to the seamless integration of artificial intelligence into our daily lives. It allows for active and dynamic interaction with external tools and APIs, going beyond mere structured data retrieval. However, the journey to achieving this fluid interaction is not without challenges. Ensuring that these function calls are triggered correctly and yield the desired results requires thorough debugging and fine-tuning, which is where PromptPerfect's function debugger comes into play. In the next section, we'll delve into how this tool can be utilized to enhance and streamline the development process of such AI systems.</p><h2 id="bridging-the-gap-from-openais-function-calling-to-developers-toolchain">Bridging the Gap: From OpenAI's Function Calling to Developer's Toolchain</h2><p>Even though OpenAI's function calling feature offers a powerful capability to convert natural language into predefined functions, there are still some obstacles for developers when it comes to practical implementation. Let's delve into these challenges and see how PromptPerfect can provide solutions to overcome them.</p><h3 id="problem-1-json-schema-generation-and-maintenance">Problem 1: JSON Schema Generation and Maintenance</h3><p>To use OpenAI's function calling feature, developers need to provide a JSON Schema for each function. This schema is crucial because it dictates how the function will be recognized and called by the language model. However, writing these schemas manually can be quite challenging, especially when there are multiple functions involved.</p><p>On top of that, maintaining these schemas can also become increasingly complex as the number of functions grows or as functions evolve over time.</p><p>Here is an example of a function and its corresponding JSON Schema:</p><figure class="kg-card kg-code-card"><pre><code class="language-python">def get_current_weather(location, unit="fahrenheit"):
+    """Get the current weather in a given location"""
     weather_info = {
-        <span class="hljs-string">"location"</span>: location,
-        <span class="hljs-string">"temperature"</span>: <span class="hljs-string">"72"</span>,
-        <span class="hljs-string">"unit"</span>: unit,
-        <span class="hljs-string">"forecast"</span>: [<span class="hljs-string">"sunny"</span>, <span class="hljs-string">"windy"</span>],
+        "location": location,
+        "temperature": "72",
+        "unit": unit,
+        "forecast": ["sunny", "windy"],
     }
-    <span class="hljs-keyword">return</span> json.dumps(weather_info)
-</code></pre><figcaption>A simple get current weather function in Python</figcaption></figure><figure class="kg-card kg-code-card"><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
-    <span class="hljs-attr">"name"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"get_current_weather"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-attr">"description"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"Get the current weather in a given location"</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-attr">"parameters"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-        <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"object"</span><span class="hljs-punctuation">,</span>
-        <span class="hljs-attr">"properties"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-            <span class="hljs-attr">"location"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
-                <span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"string"</span><span class="hljs-punctuation">,</span>
-                <span class="hljs-attr">"description"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"The city and state, e.g. San Francisco, CA"</span><span class="hljs-punctuation">,</span>
-            <span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
-            <span class="hljs-attr">"unit"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span><span class="hljs-attr">"type"</span><span class="hljs-punctuation">:</span> <span class="hljs-string">"string"</span><span class="hljs-punctuation">,</span> <span class="hljs-attr">"enum"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span><span class="hljs-string">"celsius"</span><span class="hljs-punctuation">,</span> <span class="hljs-string">"fahrenheit"</span><span class="hljs-punctuation">]</span><span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
-        <span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
-        <span class="hljs-attr">"required"</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span><span class="hljs-string">"location"</span><span class="hljs-punctuation">]</span><span class="hljs-punctuation">,</span>
-    <span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
-<span class="hljs-punctuation">}</span>
-</code></pre><figcaption>The corresponding JSON Schema</figcaption></figure><p>You can see that even for a relatively simple function, the JSON schema can be quite verbose.</p><h4 id="solution-promptperfects-automatic-json-schema-generation">Solution: PromptPerfect's Automatic JSON Schema Generation</h4><p>PromptPerfect comes with a feature that automatically generates the JSON Schema for your functions, significantly reducing the manual work and potential errors. This feature not only generates the schema but also allows developers to modify it according to their needs. On top of that, PromptPerfect comes with a linter that validates the correctness of the JSON Schema on the fly, providing real-time feedback and ensuring the schema's validity.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-1.png" class="kg-image" alt="" width="2000" height="1236" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/image-1.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>PromptPerfect can generate JSON Schema automatically for Python, Javascript, Golang, Java, Rust.</figcaption></figure><h3 id="problem-2-function-call-tracking">Problem 2: Function Call Tracking</h3><p>When multiple functions are involved, tracking the execution flow becomes challenging. To illustrate, let's go back to our smart speaker example where we had two functions: <code>get_weather</code> and <code>book_table</code>.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Jina-AI-Website-Banners-Templates---2023-08-01T203552.698.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Jina-AI-Website-Banners-Templates---2023-08-01T203552.698.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Jina-AI-Website-Banners-Templates---2023-08-01T203552.698.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Jina-AI-Website-Banners-Templates---2023-08-01T203552.698.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>Suppose you provide a prompt like, "Hey, check the weather tonight. If it's good, book a table for two outside, otherwise inside." You'd want to know:</p><ul><li>Did both <code>get_weather</code> and <code>book_table</code> get called?</li><li>In what order were they called?</li><li>What arguments were passed to each function?</li></ul><p>Understanding these details is critical for debugging and refining the interaction of the language model with your functions.</p><p>For instance, if the <code>book_table</code> function is not being called as expected, you'd need to know whether it's because the <code>get_weather</code> function didn't return the expected results, or because the language model didn't understand the conditional part of the prompt correctly.</p><p>In a more complex scenario, if these functions call each other or there are more conditions involved, the execution flow can get even harder to track.</p><h4 id="solution-promptperfects-debug-trace-feature">Solution: PromptPerfect's Debug Trace Feature</h4><p>To address these challenges, PromptPerfect offers a Debug Trace Feature, which acts like a debugger in a standard IDE. This feature provides detailed tracking information, including:</p><ul><li>A step-by-step execution trace, allowing you to see the order in which the functions were called.</li><li>Argument watching, showing the exact arguments that were passed to each function call.</li></ul><p>With this feature, you can easily test the prompt and trace down any issues. For example, you could check the arguments that were passed to <code>book_table</code> to see if the booking was made for the outside or inside, or you could see the results returned by <code>get_weather</code> to verify if the weather conditions were interpreted correctly.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-2.png" class="kg-image" alt="" width="2000" height="1117" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/image-2.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>In PromptPerfect, one can easily track the function calling trace by visualizing the timestamps, arguments and outputs</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-3.png" class="kg-image" alt="" width="2000" height="1239" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-3.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/image-3.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>One can also view the function trace in chat mode</figcaption></figure><p>PromptPerfect's features bridge the gap between OpenAI's function calling and the developer's toolchain, simplifying the process and making it easier to integrate this powerful capability into your applications.Regenerate<strong> </strong>ChatGPT may produce inaccurate information about people, places, or facts.</p><h2 id="closing-the-loop-running-your-project-locally">Closing the Loop: Running Your Project Locally</h2><p>After debugging and perfecting the interaction between the language model and your functions with PromptPerfect, the next step is to incorporate it into your local development environment. This is where PromptPerfect really completes the development loop.</p><p>With a simple click, PromptPerfect allows you to download your project, including all the source code and JSON Schemas, and run it locally. Currently, PromptPerfect supports Python for local deployment. Once downloaded, all you need to do is provide your own OpenAI API access token, and you're ready to go.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-4.png" class="kg-image" alt="" width="2000" height="1008" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-4.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/image-4.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>The downloaded code is well-documented and easy to integrate into your existing codebase. This feature accelerates the development process by saving you the time and effort of setting up everything from scratch.</p><p>To summarize, here is the typical user journey with PromptPerfect's function debugger:</p><ol><li><strong>Upload your functions</strong>: You upload the source code of each function to PromptPerfect.</li><li><strong>Generate and edit JSON Schemas</strong>: PromptPerfect automatically generates the JSON Schema for every function. You can edit the schemas or the source code directly in the online editor if needed.</li><li><strong>Test and trace functions</strong>: A test prompt environment is provided for function tracing. You can see which functions are called and in what order, with what arguments, to ensure everything works as expected.</li><li><strong>Download your project</strong>: Once everything works well, you can download your project and run it locally using your own OpenAI API access token.</li></ol><p>PromptPerfect streamlines the development process, making it easier than ever to leverage OpenAI's function call capabilities in your own applications.</p><h2 id="wrapping-up">Wrapping Up</h2><p>The advent of function calls in OpenAI's language models has undoubtedly opened up new possibilities. However, adopting this powerful tool can be a challenging process. PromptPerfect simplifies this with automated JSON Schema generation, streamlined debugging, and efficient function tracing capabilities.</p><p><a href="https://jina-ai-gmbh.ghost.io/content/media/2023/07/promptperfect-functions.mp4">If you're intrigued and want to see PromptPerfect's function debugger in action, check out our video tutorial. </a>Make sure to turn on the sound for complete insights.</p><p>We're excited to see what you create with this powerful toolset. Here's to transforming your brilliant ideas into reality. Happy coding!</p><hr><p>Please don't hesitate to reach out with any questions or feedback. 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\ No newline at end of file
+    return json.dumps(weather_info)
+</code></pre><figcaption>A simple get current weather function in Python</figcaption></figure><figure class="kg-card kg-code-card"><pre><code class="language-json">{
+    "name": "get_current_weather",
+    "description": "Get the current weather in a given location",
+    "parameters": {
+        "type": "object",
+        "properties": {
+            "location": {
+                "type": "string",
+                "description": "The city and state, e.g. San Francisco, CA",
+            },
+            "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
+        },
+        "required": ["location"],
+    },
+}
+</code></pre><figcaption>The corresponding JSON Schema</figcaption></figure><p>You can see that even for a relatively simple function, the JSON schema can be quite verbose.</p><h4 id="solution-promptperfects-automatic-json-schema-generation">Solution: PromptPerfect's Automatic JSON Schema Generation</h4><p>PromptPerfect comes with a feature that automatically generates the JSON Schema for your functions, significantly reducing the manual work and potential errors. This feature not only generates the schema but also allows developers to modify it according to their needs. On top of that, PromptPerfect comes with a linter that validates the correctness of the JSON Schema on the fly, providing real-time feedback and ensuring the schema's validity.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-1.png" class="kg-image" alt="" width="2000" height="1236" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/image-1.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>PromptPerfect can generate JSON Schema automatically for Python, Javascript, Golang, Java, Rust.</figcaption></figure><h3 id="problem-2-function-call-tracking">Problem 2: Function Call Tracking</h3><p>When multiple functions are involved, tracking the execution flow becomes challenging. To illustrate, let's go back to our smart speaker example where we had two functions: <code>get_weather</code> and <code>book_table</code>.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Jina-AI-Website-Banners-Templates---2023-08-01T203552.698.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Jina-AI-Website-Banners-Templates---2023-08-01T203552.698.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Jina-AI-Website-Banners-Templates---2023-08-01T203552.698.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Jina-AI-Website-Banners-Templates---2023-08-01T203552.698.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>Suppose you provide a prompt like, "Hey, check the weather tonight. If it's good, book a table for two outside, otherwise inside." You'd want to know:</p><ul><li>Did both <code>get_weather</code> and <code>book_table</code> get called?</li><li>In what order were they called?</li><li>What arguments were passed to each function?</li></ul><p>Understanding these details is critical for debugging and refining the interaction of the language model with your functions.</p><p>For instance, if the <code>book_table</code> function is not being called as expected, you'd need to know whether it's because the <code>get_weather</code> function didn't return the expected results, or because the language model didn't understand the conditional part of the prompt correctly.</p><p>In a more complex scenario, if these functions call each other or there are more conditions involved, the execution flow can get even harder to track.</p><h4 id="solution-promptperfects-debug-trace-feature">Solution: PromptPerfect's Debug Trace Feature</h4><p>To address these challenges, PromptPerfect offers a Debug Trace Feature, which acts like a debugger in a standard IDE. This feature provides detailed tracking information, including:</p><ul><li>A step-by-step execution trace, allowing you to see the order in which the functions were called.</li><li>Argument watching, showing the exact arguments that were passed to each function call.</li></ul><p>With this feature, you can easily test the prompt and trace down any issues. For example, you could check the arguments that were passed to <code>book_table</code> to see if the booking was made for the outside or inside, or you could see the results returned by <code>get_weather</code> to verify if the weather conditions were interpreted correctly.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-2.png" class="kg-image" alt="" width="2000" height="1117" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/image-2.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>In PromptPerfect, one can easily track the function calling trace by visualizing the timestamps, arguments and outputs</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-3.png" class="kg-image" alt="" width="2000" height="1239" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-3.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/image-3.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>One can also view the function trace in chat mode</figcaption></figure><p>PromptPerfect's features bridge the gap between OpenAI's function calling and the developer's toolchain, simplifying the process and making it easier to integrate this powerful capability into your applications.Regenerate<strong> </strong>ChatGPT may produce inaccurate information about people, places, or facts.</p><h2 id="closing-the-loop-running-your-project-locally">Closing the Loop: Running Your Project Locally</h2><p>After debugging and perfecting the interaction between the language model and your functions with PromptPerfect, the next step is to incorporate it into your local development environment. This is where PromptPerfect really completes the development loop.</p><p>With a simple click, PromptPerfect allows you to download your project, including all the source code and JSON Schemas, and run it locally. Currently, PromptPerfect supports Python for local deployment. Once downloaded, all you need to do is provide your own OpenAI API access token, and you're ready to go.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-4.png" class="kg-image" alt="" width="2000" height="1008" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-4.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-4.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-4.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/image-4.png 2400w" sizes="(min-width: 720px) 720px"></figure><p>The downloaded code is well-documented and easy to integrate into your existing codebase. This feature accelerates the development process by saving you the time and effort of setting up everything from scratch.</p><p>To summarize, here is the typical user journey with PromptPerfect's function debugger:</p><ol><li><strong>Upload your functions</strong>: You upload the source code of each function to PromptPerfect.</li><li><strong>Generate and edit JSON Schemas</strong>: PromptPerfect automatically generates the JSON Schema for every function. You can edit the schemas or the source code directly in the online editor if needed.</li><li><strong>Test and trace functions</strong>: A test prompt environment is provided for function tracing. You can see which functions are called and in what order, with what arguments, to ensure everything works as expected.</li><li><strong>Download your project</strong>: Once everything works well, you can download your project and run it locally using your own OpenAI API access token.</li></ol><p>PromptPerfect streamlines the development process, making it easier than ever to leverage OpenAI's function call capabilities in your own applications.</p><h2 id="wrapping-up">Wrapping Up</h2><p>The advent of function calls in OpenAI's language models has undoubtedly opened up new possibilities. However, adopting this powerful tool can be a challenging process. PromptPerfect simplifies this with automated JSON Schema generation, streamlined debugging, and efficient function tracing capabilities.</p><p><a href="https://jina-ai-gmbh.ghost.io/content/media/2023/07/promptperfect-functions.mp4">If you're intrigued and want to see PromptPerfect's function debugger in action, check out our video tutorial. </a>Make sure to turn on the sound for complete insights.</p><p>We're excited to see what you create with this powerful toolset. Here's to transforming your brilliant ideas into reality. Happy coding!</p><hr><p>Please don't hesitate to reach out with any questions or feedback. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Beyond Sheer Scale: Navigating AI Alignment Odyssey</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">AI’s march forward isn't just about bigger models, but ensuring they harmonize with human values. Journey with us through the challenges, revelations, and aspirations at the forefront of AI safety and ethics.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 24, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the grand canvas of technology, AI, with its large models, looms large. We're not just talking about computers that can play chess or identify photos; we're looking at machines that skirt the edge of what we might call '<em>thinking</em>'. They can chat, they can craft text, they might even surprise you with <a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">a poem if you ask nicely.</a> We're living in a world where our AI tools aren't just tools anymore. They're almost colleagues. There's a ballpark figure floating around, suggesting that these <a href="https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier?ref=jina-ai-gmbh.ghost.io#introduction">generative AI models could inject a few trillion dollars into the world economy annually</a>. That's not pocket change.</p><p><em>But here's the hitch. </em></p><p>If a computer is becoming more like a human, then it's inheriting all our quirks. Our brilliance, our creativity, yes, but also our biases and blind spots. This isn’t just about AI becoming smart; it’s about AI becoming wise. This is what the tech heads call <strong>AI alignment</strong> or value alignment. In layman’s terms, <strong>it’s making sure AI doesn’t go off the rails, that it plays nicely in the sandbox.</strong></p><p>The larger we make these models, the more room there is for errors, and not just typos, but grand faux pas. Imagine having all the knowledge of the internet – but also all its myths, prejudices, and midnight conspiracy theories. That's how these large models learn. They gobble up vast chunks of the internet and regurgitate it, warts and all.</p><p>The stakes? Without this alignment, our well-intentioned AI, given a slightly misdirected task, might churn out content that's harmful or even dangerous. It could inadvertently become the ally of someone with less than honorable intentions or sway someone vulnerable down a dark path. So, <strong>when we talk about AI alignment, we’re essentially talking about the guiding principles, the conscience, if you will, of AI</strong>. And in a world where AI might soon be as ubiquitous as smartphones, that's something we really ought to get right.</p><h2 id="ais-tightrope-walk-values-truth-and-the-power-conundrum">AI's Tightrope Walk: Values, Truth, and the Power Conundrum</h2><p>Why does it matter if our digital friends get their facts straight, aren't carrying hidden prejudices, or know their own strength? Well, here's why:</p><ol><li><strong>AI's "Reality Drift"</strong> - AI isn't a know-it-all. Sometimes, it takes a creative leap into the world of fiction. OpenAI’s CTO, Mira Murati, points out that our chatty AI pal, ChatGPT, occasionally dives headfirst into the world of make-believe. <a href="https://time.com/6252404/mira-murati-chatgpt-openai-interview/?ref=jina-ai-gmbh.ghost.io">It can be a tad too confident about things that are just... well, not true.</a> It's a tad like giving Shakespeare a typewriter and expecting every outcome to be historically accurate. Squaring this circle between an AI’s imaginative flights and hard facts is the new frontier.</li><li><strong>Mirror, Mirror, on the Wall</strong> - AI, at its core, reflects our world, warts and all. And sometimes, those reflections can be unflattering. According to OpenAI's chief, Sam Altman, expecting an AI to be entirely unbiased is like asking the internet to agree on the best pizza topping. The real puzzle here isn't just spotting these biases but knowing <a href="https://dl.acm.org/doi/fullHtml/10.1145/3531146.3533088?ref=jina-ai-gmbh.ghost.io">how to handle them when they inevitably pop up.</a></li><li><strong>AI's Unexpected Growth Spurts</strong> - Here's a fun thought: What if your AI woke up one day with a brand new trick up its sleeve that even its creators didn't expect? As models evolve, they might just surprise us, and not always in ways we'd appreciate. Some folks are losing sleep over the idea that these systems might, one day, develop their own ambitions—<a href="https://yoshuabengio.org/2023/05/22/how-rogue-ais-may-arise/?ref=jina-ai-gmbh.ghost.io">like a toddler realizing they can climb furniture</a>, <a href="https://arxiv.org/abs/1706.03741?ref=jina-ai-gmbh.ghost.io">but far more concerning.</a></li><li><strong>The Double-Edged Sword</strong> - Every tool can be a weapon if you hold it right. As AI's capabilities expand, there's a growing risk of them being used nefariously, be it through clever manipulation or downright hijacking.</li></ol><p>Aligning AI with human values isn't just some lofty philosophical goal. It's the groundwork to ensure that as AI steps into bigger shoes, it does so with grace, responsibility, and, most importantly, our best interests at heart.</p><h2 id="navigating-the-ai-morality-maze-a-guide-for-the-uninitiated">Navigating the AI Morality Maze: A Guide for the Uninitiated</h2><p>How does one teach a machine to behave? As it turns out, it's less about giving it a stern talking-to and more about sophisticated training techniques that ensure AI understands and respects human ethics. Let's dive in.</p><h3 id="guided-learning-through-human-touch">Guided Learning Through Human Touch</h3><p>Think of reinforcement learning from human feedback (RLHF) as a kind of parenting for AI. Instead of letting AI figure things out by trial and error, humans intervene, nudging it towards desired outcomes. OpenAI's experiments back in 2017 shed light on how RLHF could sculpt AI behavior to sync with human preferences. This method essentially bridges the gap between AI's expansive generative prowess and what we'd call 'common sense'. It's a thumbs-up to AI when it does good and a gentle reminder when it missteps.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-11.png" class="kg-image" alt="" width="1140" height="677" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-11.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-11.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-11.png 1140w" sizes="(min-width: 720px) 720px"><figcaption>OpenAI has this great diagram that explains the SFT and RLHF for InstructGPT.</figcaption></figure><h3 id="ai-policing-itself-the-constitutional-approach">AI Policing Itself: The Constitutional Approach</h3><p>Here's an ambitious idea: What if we could build an AI that monitors another AI? Instead of humans chasing after ever-growing models, we lean on the AI itself for some introspection. Anthropic, an AI safety firm, came up with this bright spark called 'Constitutional AI'. Imagine an AI sidekick that checks whether the main AI is sticking to a pre-defined set of rules, a sort of digital Magna Carta. Taking cues from human rights charters, the terms and conditions we scroll past, and even other tech guidelines, Anthropic designed a robust rulebook for their AI assistant, Claude. The end result? An AI that thinks twice, ensuring it's both useful and on its best behavior.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-12.png" class="kg-image" alt="" width="1378" height="608" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-12.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-12.png 1378w" sizes="(min-width: 720px) 720px"><figcaption>Anthropic’s constitutional AI approach to training models.</figcaption></figure><h3 id="the-quartet-of-best-practices">The Quartet of Best Practices</h3><p>Harnessing AI's might while keeping it ethically in-check is a multifaceted challenge. If we break it down, it's a harmonious blend of proactive tweaks and reactive measures.</p><ul><li><strong>Intervention at the Roots: The Training Data</strong> - The quirks of large models, whether they're weaving fictions (those AI 'hallucinations') or reflecting biases, often trace back to their training data. So, the first port of call is to roll up our sleeves and get stuck into the data itself. Recording training data to ensure its diversity and representativeness, combing through it to spot and rectify biases, and even crafting specialized datasets dedicated to value alignment are all steps in the playbook. It's a bit like ensuring the foundation of a building is rock solid before adding any layers.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.geekwire.com/2021/teaching-artificial-intelligence-right-from-wrong-new-tool-from-ai2-aims-to-model-ethical-judgments/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Teaching artificial intelligence right from wrong: New tool from AI2 aims to model ethical judgments</div><div class="kg-bookmark-description">During the past two decades, machine ethics has gone from being a curiosity to a field of immense importance. Much of the work is based on the idea that as… Read More</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.geekwire.com/apple-touch-icon-180x180.png" alt=""><span class="kg-bookmark-author">GeekWire</span><span class="kg-bookmark-publisher">Richard Yonck</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn.geekwire.com/wp-content/uploads/2021/11/Delphi_Demo_Card_hjighres.png" alt=""></div></a></figure><ul><li><strong>Adversarial Showdowns: The Red Team Gauntlet</strong> - Before letting our AI systems loose on the world, they go through a rigorous stress test. This is where adversarial testing or 'red teaming' comes in. In simpler terms, this involves inviting experts (both internal and external) to throw everything but the kitchen sink at the model, all to uncover any cracks or vulnerabilities. For instance, before GPT-4's grand entrance, OpenAI summoned over 50 scholars and experts from diverse fields to put it through its paces. Their mission? To probe the model with a gamut of challenging or potentially harmful queries, testing the waters for issues ranging from misinformation and harmful content to biases and sensitive information leakage.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.ft.com/content/0876687a-f8b7-4b39-b513-5fee942831e8?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">OpenAI’s red team: the experts hired to ‘break’ ChatGPT | Financial Times</div><div class="kg-bookmark-description">Microsoft-backed company asked an eclectic mix of people to ‘adversarially test’ GPT-4, its powerful new language model</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.ft.com/__origami/service/image/v2/images/raw/ftlogo-v1%3Abrand-ft-logo-square-coloured?source=update-logos&amp;format=png&amp;width=194&amp;height=194" alt=""><span class="kg-bookmark-author">Financial Times</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://d1e00ek4ebabms.cloudfront.net/production/dff20707-1167-4504-812c-9e8be487707e.jpg" alt=""></div></a></figure><ul><li><strong>Content Gatekeepers: Filtering Models</strong> - It's one thing to train an AI, and quite another to ensure it doesn't blurt out anything it shouldn't. That's where specialized filtering AI models, like the ones developed by OpenAI, come in handy. These vigilant models oversee both user input and AI outputs, singling out any content that might be stepping over the line.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.theguardian.com/technology/2023/feb/08/biased-ai-algorithms-racy-women-bodies?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">‘There is no standard’: investigation finds AI algorithms objectify women’s bodies</div><div class="kg-bookmark-description">Guardian exclusive: AI tools rate photos of women as more sexually suggestive than those of men, especially if nipples, pregnant bellies or exercise is involved</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.guim.co.uk/images/favicon-32x32.ico" alt=""><span class="kg-bookmark-author">The Guardian</span><span class="kg-bookmark-publisher">Gianluca Mauro</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://i.guim.co.uk/img/media/fdd8861c44e9d34f16369190669f014fe4c60165/0_0_1500_900/master/1500.jpg?width=1200&amp;height=630&amp;quality=85&amp;auto=format&amp;fit=crop&amp;overlay-align=bottom%2Cleft&amp;overlay-width=100p&amp;overlay-base64=L2ltZy9zdGF0aWMvb3ZlcmxheXMvdGctZGVmYXVsdC5wbmc&amp;enable=upscale&amp;s=e184e27e29142d62b32484850bd2a457" alt=""></div></a></figure><ul><li><strong>The Looking Glass: Advancing Model Interpretability</strong> - Transparency and comprehensibility in AI aren't just buzzwords; they're essential tools in our alignment toolkit. OpenAI, for instance, trained GPT-4 to self-reflect, penning automated explanations about its predecessor, GPT-2's neural behaviors, and even grading its introspection. Meanwhile, other researchers are tackling alignment by delving into mechanistic interpretability, peeling back the layers to comprehend the AI's inner machinations.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://openai.com/research/language-models-can-explain-neurons-in-language-models?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Language models can explain neurons in language models</div><div class="kg-bookmark-description">We use GPT-4 to automatically write explanations for the behavior of neurons in large language models and to score those explanations. We release a dataset of these (imperfect) explanations and scores for every neuron in GPT-2.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://openai.com/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://images.openai.com/blob/e1afc745-b554-4785-ad0e-8f9c65e1274f/language-models-can-explain-neurons-in-language-models.png?trim=0%2C0%2C1791%2C0" alt=""></div></a></figure><p>As we continue on this odyssey of aligning AI with our human values, it's an intricate dance of intervention, testing, filtering, and most crucially, understanding. It's about ensuring that as AI grows, it not only knows its strength but uses it wisely.</p><h2 id="traversing-the-ai-labyrinth-a-marathon-not-a-sprint">Traversing the AI Labyrinth: A Marathon, Not a Sprint</h2><p>In the vast tapestry of AI research, the notion of 'value alignment' seems to gleam with particular significance. As we delve deeper, it's clear we're at a crossroads of ethics, technology, and perhaps a sprinkle of existential contemplation. Think of it as a bustling intersection, full of potential but not without its challenges.</p><p>The tech frontier is often marked by rapid leaps and bounds. But as we venture into aligning AI with human values, the question arises: do we select from a curated list of values, or should we stand back, squint, and discern a broader, collective societal heartbeat? The brightest minds in AI have made strides, yet landing on a universally accepted set of 'human values' feels akin to trying to bottle a cloud. It’s intangible, elusive, and endlessly fascinating.</p><p>And let’s not forget the dizzying pace of AI evolution. It's <em>not</em> just progressing; it’s on a veritable sprint. Our ability to oversee and comprehend is being tested. The crux is this: how do we coalesce with entities whose computational depths may soon eclipse our own grasp? OpenAI's recent gambit, the formation of a 'Superalignment' team, is emblematic of this challenge. It’s about making AI introspective, having it tackle its own alignment issues.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://openai.com/blog/introducing-superalignment?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Introducing Superalignment</div><div class="kg-bookmark-description">We need scientific and technical breakthroughs to steer and control AI systems much smarter than us. To solve this problem within four years, we’re starting a new team, co-led by Ilya Sutskever and Jan Leike, and dedicating 20% of the compute we’ve secured to date to this effort. We’re looking for e…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://openai.com/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://images.openai.com/blob/01aa49ea-1f3b-4340-b1b0-ff30857e6058/introducing-superalignment.png?trim=0%2C0%2C0%2C0" alt=""></div></a></figure><p>Our ultimate goal extends beyond mere regulation. We aim to synchronize these digital marvels with humanity’s loftiest aspirations. The collective efforts of technologists, policymakers, academics, and visionaries will dictate our trajectory. It’s about ensuring that as AI reaches its zenith, it resonates with our shared ethos. This journey with AI is less a destination and more a shared adventure, brimming with challenges and wonders alike. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/artificial-general-intelligence-is-cursed-and-science-fiction-isnt-helping" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Artificial General Intelligence is Cursed, And Science Fiction isn't Helping</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">AI is cursed by intellectual hubris, moving goalposts, bad incentives, and science fiction. Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. Navigating enterprise mazes &amp; startup vibes. Where's search headed next?</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">September 01, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/generativejina_mad_men_tv_serie_a_girl_is_looking_at_a_selectio_42a73443-5825-4394-a7ef-9c08294d29b6.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/fine-tuning-gpt-3-5-turbo-a-costly-mirage" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 25, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_modern_geometric_abstract_pattern_featuring_pu_24e4060e-dc76-4186-afb7-94d18d266b41.png" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="dca3a323-34ea-4be2-b028-8bdb69c31bb3" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="dca3a323-34ea-4be2-b028-8bdb69c31bb3" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Beyond Sheer Scale: Navigating AI Alignment Odyssey</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">AI’s march forward isn't just about bigger models, but ensuring they harmonize with human values. Journey with us through the challenges, revelations, and aspirations at the forefront of AI safety and ethics.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 24, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In the grand canvas of technology, AI, with its large models, looms large. We're not just talking about computers that can play chess or identify photos; we're looking at machines that skirt the edge of what we might call '<em>thinking</em>'. They can chat, they can craft text, they might even surprise you with <a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">a poem if you ask nicely.</a> We're living in a world where our AI tools aren't just tools anymore. They're almost colleagues. There's a ballpark figure floating around, suggesting that these <a href="https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier?ref=jina-ai-gmbh.ghost.io#introduction">generative AI models could inject a few trillion dollars into the world economy annually</a>. That's not pocket change.</p><p><em>But here's the hitch. </em></p><p>If a computer is becoming more like a human, then it's inheriting all our quirks. Our brilliance, our creativity, yes, but also our biases and blind spots. This isn’t just about AI becoming smart; it’s about AI becoming wise. This is what the tech heads call <strong>AI alignment</strong> or value alignment. In layman’s terms, <strong>it’s making sure AI doesn’t go off the rails, that it plays nicely in the sandbox.</strong></p><p>The larger we make these models, the more room there is for errors, and not just typos, but grand faux pas. Imagine having all the knowledge of the internet – but also all its myths, prejudices, and midnight conspiracy theories. That's how these large models learn. They gobble up vast chunks of the internet and regurgitate it, warts and all.</p><p>The stakes? Without this alignment, our well-intentioned AI, given a slightly misdirected task, might churn out content that's harmful or even dangerous. It could inadvertently become the ally of someone with less than honorable intentions or sway someone vulnerable down a dark path. So, <strong>when we talk about AI alignment, we’re essentially talking about the guiding principles, the conscience, if you will, of AI</strong>. And in a world where AI might soon be as ubiquitous as smartphones, that's something we really ought to get right.</p><h2 id="ais-tightrope-walk-values-truth-and-the-power-conundrum">AI's Tightrope Walk: Values, Truth, and the Power Conundrum</h2><p>Why does it matter if our digital friends get their facts straight, aren't carrying hidden prejudices, or know their own strength? Well, here's why:</p><ol><li><strong>AI's "Reality Drift"</strong> - AI isn't a know-it-all. Sometimes, it takes a creative leap into the world of fiction. OpenAI’s CTO, Mira Murati, points out that our chatty AI pal, ChatGPT, occasionally dives headfirst into the world of make-believe. <a href="https://time.com/6252404/mira-murati-chatgpt-openai-interview/?ref=jina-ai-gmbh.ghost.io">It can be a tad too confident about things that are just... well, not true.</a> It's a tad like giving Shakespeare a typewriter and expecting every outcome to be historically accurate. Squaring this circle between an AI’s imaginative flights and hard facts is the new frontier.</li><li><strong>Mirror, Mirror, on the Wall</strong> - AI, at its core, reflects our world, warts and all. And sometimes, those reflections can be unflattering. According to OpenAI's chief, Sam Altman, expecting an AI to be entirely unbiased is like asking the internet to agree on the best pizza topping. The real puzzle here isn't just spotting these biases but knowing <a href="https://dl.acm.org/doi/fullHtml/10.1145/3531146.3533088?ref=jina-ai-gmbh.ghost.io">how to handle them when they inevitably pop up.</a></li><li><strong>AI's Unexpected Growth Spurts</strong> - Here's a fun thought: What if your AI woke up one day with a brand new trick up its sleeve that even its creators didn't expect? As models evolve, they might just surprise us, and not always in ways we'd appreciate. Some folks are losing sleep over the idea that these systems might, one day, develop their own ambitions—<a href="https://yoshuabengio.org/2023/05/22/how-rogue-ais-may-arise/?ref=jina-ai-gmbh.ghost.io">like a toddler realizing they can climb furniture</a>, <a href="https://arxiv.org/abs/1706.03741?ref=jina-ai-gmbh.ghost.io">but far more concerning.</a></li><li><strong>The Double-Edged Sword</strong> - Every tool can be a weapon if you hold it right. As AI's capabilities expand, there's a growing risk of them being used nefariously, be it through clever manipulation or downright hijacking.</li></ol><p>Aligning AI with human values isn't just some lofty philosophical goal. It's the groundwork to ensure that as AI steps into bigger shoes, it does so with grace, responsibility, and, most importantly, our best interests at heart.</p><h2 id="navigating-the-ai-morality-maze-a-guide-for-the-uninitiated">Navigating the AI Morality Maze: A Guide for the Uninitiated</h2><p>How does one teach a machine to behave? As it turns out, it's less about giving it a stern talking-to and more about sophisticated training techniques that ensure AI understands and respects human ethics. Let's dive in.</p><h3 id="guided-learning-through-human-touch">Guided Learning Through Human Touch</h3><p>Think of reinforcement learning from human feedback (RLHF) as a kind of parenting for AI. Instead of letting AI figure things out by trial and error, humans intervene, nudging it towards desired outcomes. OpenAI's experiments back in 2017 shed light on how RLHF could sculpt AI behavior to sync with human preferences. This method essentially bridges the gap between AI's expansive generative prowess and what we'd call 'common sense'. It's a thumbs-up to AI when it does good and a gentle reminder when it missteps.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-11.png" class="kg-image" alt="" width="1140" height="677" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-11.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-11.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-11.png 1140w" sizes="(min-width: 720px) 720px"><figcaption>OpenAI has this great diagram that explains the SFT and RLHF for InstructGPT.</figcaption></figure><h3 id="ai-policing-itself-the-constitutional-approach">AI Policing Itself: The Constitutional Approach</h3><p>Here's an ambitious idea: What if we could build an AI that monitors another AI? Instead of humans chasing after ever-growing models, we lean on the AI itself for some introspection. Anthropic, an AI safety firm, came up with this bright spark called 'Constitutional AI'. Imagine an AI sidekick that checks whether the main AI is sticking to a pre-defined set of rules, a sort of digital Magna Carta. Taking cues from human rights charters, the terms and conditions we scroll past, and even other tech guidelines, Anthropic designed a robust rulebook for their AI assistant, Claude. The end result? An AI that thinks twice, ensuring it's both useful and on its best behavior.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-12.png" class="kg-image" alt="" width="1378" height="608" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-12.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-12.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-12.png 1378w" sizes="(min-width: 720px) 720px"><figcaption>Anthropic’s constitutional AI approach to training models.</figcaption></figure><h3 id="the-quartet-of-best-practices">The Quartet of Best Practices</h3><p>Harnessing AI's might while keeping it ethically in-check is a multifaceted challenge. If we break it down, it's a harmonious blend of proactive tweaks and reactive measures.</p><ul><li><strong>Intervention at the Roots: The Training Data</strong> - The quirks of large models, whether they're weaving fictions (those AI 'hallucinations') or reflecting biases, often trace back to their training data. So, the first port of call is to roll up our sleeves and get stuck into the data itself. Recording training data to ensure its diversity and representativeness, combing through it to spot and rectify biases, and even crafting specialized datasets dedicated to value alignment are all steps in the playbook. It's a bit like ensuring the foundation of a building is rock solid before adding any layers.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.geekwire.com/2021/teaching-artificial-intelligence-right-from-wrong-new-tool-from-ai2-aims-to-model-ethical-judgments/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Teaching artificial intelligence right from wrong: New tool from AI2 aims to model ethical judgments</div><div class="kg-bookmark-description">During the past two decades, machine ethics has gone from being a curiosity to a field of immense importance. Much of the work is based on the idea that as… Read More</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.geekwire.com/apple-touch-icon-180x180.png" alt=""><span class="kg-bookmark-author">GeekWire</span><span class="kg-bookmark-publisher">Richard Yonck</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn.geekwire.com/wp-content/uploads/2021/11/Delphi_Demo_Card_hjighres.png" alt=""></div></a></figure><ul><li><strong>Adversarial Showdowns: The Red Team Gauntlet</strong> - Before letting our AI systems loose on the world, they go through a rigorous stress test. This is where adversarial testing or 'red teaming' comes in. In simpler terms, this involves inviting experts (both internal and external) to throw everything but the kitchen sink at the model, all to uncover any cracks or vulnerabilities. For instance, before GPT-4's grand entrance, OpenAI summoned over 50 scholars and experts from diverse fields to put it through its paces. Their mission? To probe the model with a gamut of challenging or potentially harmful queries, testing the waters for issues ranging from misinformation and harmful content to biases and sensitive information leakage.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.ft.com/content/0876687a-f8b7-4b39-b513-5fee942831e8?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">OpenAI’s red team: the experts hired to ‘break’ ChatGPT | Financial Times</div><div class="kg-bookmark-description">Microsoft-backed company asked an eclectic mix of people to ‘adversarially test’ GPT-4, its powerful new language model</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://www.ft.com/__origami/service/image/v2/images/raw/ftlogo-v1%3Abrand-ft-logo-square-coloured?source=update-logos&amp;format=png&amp;width=194&amp;height=194" alt=""><span class="kg-bookmark-author">Financial Times</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://d1e00ek4ebabms.cloudfront.net/production/dff20707-1167-4504-812c-9e8be487707e.jpg" alt=""></div></a></figure><ul><li><strong>Content Gatekeepers: Filtering Models</strong> - It's one thing to train an AI, and quite another to ensure it doesn't blurt out anything it shouldn't. That's where specialized filtering AI models, like the ones developed by OpenAI, come in handy. These vigilant models oversee both user input and AI outputs, singling out any content that might be stepping over the line.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://www.theguardian.com/technology/2023/feb/08/biased-ai-algorithms-racy-women-bodies?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">‘There is no standard’: investigation finds AI algorithms objectify women’s bodies</div><div class="kg-bookmark-description">Guardian exclusive: AI tools rate photos of women as more sexually suggestive than those of men, especially if nipples, pregnant bellies or exercise is involved</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.guim.co.uk/images/favicon-32x32.ico" alt=""><span class="kg-bookmark-author">The Guardian</span><span class="kg-bookmark-publisher">Gianluca Mauro</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://i.guim.co.uk/img/media/fdd8861c44e9d34f16369190669f014fe4c60165/0_0_1500_900/master/1500.jpg?width=1200&amp;height=630&amp;quality=85&amp;auto=format&amp;fit=crop&amp;overlay-align=bottom%2Cleft&amp;overlay-width=100p&amp;overlay-base64=L2ltZy9zdGF0aWMvb3ZlcmxheXMvdGctZGVmYXVsdC5wbmc&amp;enable=upscale&amp;s=e184e27e29142d62b32484850bd2a457" alt=""></div></a></figure><ul><li><strong>The Looking Glass: Advancing Model Interpretability</strong> - Transparency and comprehensibility in AI aren't just buzzwords; they're essential tools in our alignment toolkit. OpenAI, for instance, trained GPT-4 to self-reflect, penning automated explanations about its predecessor, GPT-2's neural behaviors, and even grading its introspection. Meanwhile, other researchers are tackling alignment by delving into mechanistic interpretability, peeling back the layers to comprehend the AI's inner machinations.</li></ul><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://openai.com/research/language-models-can-explain-neurons-in-language-models?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Language models can explain neurons in language models</div><div class="kg-bookmark-description">We use GPT-4 to automatically write explanations for the behavior of neurons in large language models and to score those explanations. We release a dataset of these (imperfect) explanations and scores for every neuron in GPT-2.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://openai.com/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://images.openai.com/blob/e1afc745-b554-4785-ad0e-8f9c65e1274f/language-models-can-explain-neurons-in-language-models.png?trim=0%2C0%2C1791%2C0" alt=""></div></a></figure><p>As we continue on this odyssey of aligning AI with our human values, it's an intricate dance of intervention, testing, filtering, and most crucially, understanding. It's about ensuring that as AI grows, it not only knows its strength but uses it wisely.</p><h2 id="traversing-the-ai-labyrinth-a-marathon-not-a-sprint">Traversing the AI Labyrinth: A Marathon, Not a Sprint</h2><p>In the vast tapestry of AI research, the notion of 'value alignment' seems to gleam with particular significance. As we delve deeper, it's clear we're at a crossroads of ethics, technology, and perhaps a sprinkle of existential contemplation. Think of it as a bustling intersection, full of potential but not without its challenges.</p><p>The tech frontier is often marked by rapid leaps and bounds. But as we venture into aligning AI with human values, the question arises: do we select from a curated list of values, or should we stand back, squint, and discern a broader, collective societal heartbeat? The brightest minds in AI have made strides, yet landing on a universally accepted set of 'human values' feels akin to trying to bottle a cloud. It’s intangible, elusive, and endlessly fascinating.</p><p>And let’s not forget the dizzying pace of AI evolution. It's <em>not</em> just progressing; it’s on a veritable sprint. Our ability to oversee and comprehend is being tested. The crux is this: how do we coalesce with entities whose computational depths may soon eclipse our own grasp? OpenAI's recent gambit, the formation of a 'Superalignment' team, is emblematic of this challenge. It’s about making AI introspective, having it tackle its own alignment issues.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://openai.com/blog/introducing-superalignment?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Introducing Superalignment</div><div class="kg-bookmark-description">We need scientific and technical breakthroughs to steer and control AI systems much smarter than us. To solve this problem within four years, we’re starting a new team, co-led by Ilya Sutskever and Jan Leike, and dedicating 20% of the compute we’ve secured to date to this effort. We’re looking for e…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://openai.com/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://images.openai.com/blob/01aa49ea-1f3b-4340-b1b0-ff30857e6058/introducing-superalignment.png?trim=0%2C0%2C0%2C0" alt=""></div></a></figure><p>Our ultimate goal extends beyond mere regulation. We aim to synchronize these digital marvels with humanity’s loftiest aspirations. The collective efforts of technologists, policymakers, academics, and visionaries will dictate our trajectory. It’s about ensuring that as AI reaches its zenith, it resonates with our shared ethos. This journey with AI is less a destination and more a shared adventure, brimming with challenges and wonders alike. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/artificial-general-intelligence-is-cursed-and-science-fiction-isnt-helping" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Artificial General Intelligence is Cursed, And Science Fiction isn't Helping</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">AI is cursed by intellectual hubris, moving goalposts, bad incentives, and science fiction. Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. Navigating enterprise mazes &amp; startup vibes. Where's search headed next?</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">September 01, 2023 • 4 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/generativejina_mad_men_tv_serie_a_girl_is_looking_at_a_selectio_42a73443-5825-4394-a7ef-9c08294d29b6.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/fine-tuning-gpt-3-5-turbo-a-costly-mirage" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Fine-Tuning GPT-3.5 Turbo: A Costly Mirage?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Dissecting the allure of GPT-3.5 Turbo's fine-tuning: is it the next AI frontier or a costly endeavor? Dive into the delicate interplay of prompt engineering versus precise fine-tuning, and weigh the balance of promise against price.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 25, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_modern_geometric_abstract_pattern_featuring_pu_24e4060e-dc76-4186-afb7-94d18d266b41.png" style="object-fit: cover; 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>The Lifestyle of Developers in Shanghai DevJoy 2022</title><meta charset="utf-8"><meta name="title" content="The Lifestyle of Developers in Shanghai DevJoy 2022"><meta name="description" content="Jina AI was invited to attend DevJoy 2022 in Shanghai on November 5th-6th with Microsoft Reactor, Bilibili, Amazon Web Services, and other exhibitors. More than a thousand developers joined DevJoy and shared a pleasant and fruitful two days together."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/the-lifestyle-of-developers-in-shanghai-devjoy-2022"><meta property="og:title" content="The Lifestyle of Developers in Shanghai DevJoy 2022"><meta property="og:description" content="Jina AI was invited to attend DevJoy 2022 in Shanghai on November 5th-6th with Microsoft Reactor, Bilibili, Amazon Web Services, and other exhibitors. More than a thousand developers joined DevJoy and shared a pleasant and fruitful two days together."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--29-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/the-lifestyle-of-developers-in-shanghai-devjoy-2022"><meta property="twitter:title" content="The Lifestyle of Developers in Shanghai DevJoy 2022"><meta property="twitter:description" content="Jina AI was invited to attend DevJoy 2022 in Shanghai on November 5th-6th with Microsoft Reactor, Bilibili, Amazon Web Services, and other exhibitors. More than a thousand developers joined DevJoy and shared a pleasant and fruitful two days together."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--29-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">The Lifestyle of Developers in Shanghai DevJoy 2022</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI was invited to attend DevJoy 2022 in Shanghai on November 5th-6th with Microsoft Reactor, Bilibili, Amazon Web Services, and other exhibitors. More than a thousand developers joined DevJoy and shared a pleasant and fruitful two days together.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 09, 2022 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina AI was invited to attend <a href="devjoy.org"><strong>DevJoy 2022</strong></a> in Shanghai on November 5th-6th with Microsoft Reactor, Bilibili, Amazon Web Services, and other exhibitors. More than a thousand developers joined DevJoy and shared a pleasant and fruitful two days together.</p><p>DevJoy 2022 - <strong>“The Lifestyle of Developers”</strong>, co-hosted by Bytebase, WeWork, and YuQue, took place at WeWork Shanghai (their largest facility in China). Jina AI is pleased to be one of the exhibitors and share our products and enthusiasm for the Open Source Community.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_4799.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_4799.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_4799.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_4799.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_4799.JPG 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_4806.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_4806.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_4806.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_4806.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_4806.JPG 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_4804.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_4804.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_4804.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_4804.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_4804.JPG 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_4807.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_4807.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_4807.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_4807.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_4807.JPG 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>DevJoy 2022, WeWork, Shanghai. Other exhibitors also made wonderful sharing, such as Bilibili TC, JetBrains, Microsoft Reactor, PingCAP, TapTap, and Amazon Web Services.</figcaption></figure><h2 id="highlights">Highlights</h2><p>The Lightning Talk was the warm-up session for the event, with exhibitors showing some interesting cases about their products. Jina AI's Developer Relations, Sa.Zhang, presented <strong>"Jina AI: The most advanced MLOps platform for multimodal AI"</strong>. Sa<strong> </strong>set two on-site tasks of different difficulties, and finally unveiled the well-prepared task prizes - Jina AI's SWAG gloves and hats.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/--.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/--.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/--.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/--.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/--.JPG 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_4809.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_4809.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_4809.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_4809.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_4809.JPG 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption><a href="https://store.covver.io/jina-ai/collections/swag-store?ref=jina-ai-gmbh.ghost.io">Swag from Jina AI</a></figcaption></figure><p>Sa. Zhang showed two demos, 「<a href="https://github.com/jina-ai/jina-video-chat?ref=jina-ai-gmbh.ghost.io">Bulid a “Joom” in 20 lines of code with Jina</a>」 and 「<a href="https://github.com/shan-mx/Video-CLIP-Indexer?ref=jina-ai-gmbh.ghost.io">Build text-to-video search with CLIP-as-service in 60 lines of code</a>」</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.77632 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/devjoy-workshop-gif.gif" width="1080" height="608" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/devjoy-workshop-gif.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/devjoy-workshop-gif.gif 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/devjoy-workshop-gif.gif 1080w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.77506 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Screen-Shot-2022-11-08-at-11.49.17-PM.png" width="1594" height="898" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Screen-Shot-2022-11-08-at-11.49.17-PM.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Screen-Shot-2022-11-08-at-11.49.17-PM.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Screen-Shot-2022-11-08-at-11.49.17-PM.png 1594w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Two Demos: 「<a href="https://github.com/jina-ai/jina-video-chat?ref=jina-ai-gmbh.ghost.io">Bulid a “Joom” in 20 lines of code with Jina</a>」 and 「<a href="https://github.com/shan-mx/Video-CLIP-Indexer?ref=jina-ai-gmbh.ghost.io">Build text-to-video search with CLIP-as-service in 60 lines of code</a></figcaption></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/product/clip-as-service/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">CLIP-as-service | Jina AI</div><div class="kg-bookmark-description">Embed images and sentences into fixed-length vectors with CLIP.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/assets/images/banner/clip-as-service.jpg" alt=""></div></a></figure><p>After the Lightning Talk, Jina AI's booth was surrounded by developers who were very interested in either multimodal AI or building their own demos. Everyone had a great time.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/R0001120.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/R0001120.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/R0001120.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/R0001120.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/R0001120.JPG 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/workshop-1-1.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/workshop-1-1.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/workshop-1-1.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/workshop-1-1.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/workshop-1-1.JPG 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/WechatIMG18.jpeg" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/WechatIMG18.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/WechatIMG18.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/WechatIMG18.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/WechatIMG18.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/R0001129.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/R0001129.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/R0001129.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/R0001129.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/R0001129.JPG 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>In this event, <a href="https://store.covver.io/jina-ai/collections/swag-store?ref=jina-ai-gmbh.ghost.io">Jina AI's SWAG</a> was warmly welcomed as always, including hats, gloves, notebooks, and T-shirts ... Please stay tuned to our events and we hope to connect with more of you in future events!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://store.covver.io/jina-ai/collections/swag-store?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Covver</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://store.covver.io/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">&lt;img alt="american-apparel" sizes="100vw" srcSet="/_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=640&amp;amp;q=100 640w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=750&amp;amp;q=100 750w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=828&amp;amp;q=100 828w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=1080&amp;amp;q=100 1080w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=1200&amp;amp;q=100 1200w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=1920&amp;amp;q=100 1920w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=2048&amp;amp;q=100 2048w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=3840&amp;amp;q=100 3840w" src="/_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=3840&amp;amp;q=100" decoding="async" data-nimg="fill" style="position:absolute;top:0;left:0;bottom:0;right:0;box-sizing:border-box;padding:0;border:none;margin:auto;display:block;width:0;height:0;min-width:100%;max-width:100%;min-height:100%;max-height:100%;object-fit:contain;object-position:center center" loading="lazy"/&gt;</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://api.covver.io/api/v1/storefront/jina-ai/collections/swag-store/image" alt=""></div></a></figure><h2 id="see-you-next-time">See You Next Time</h2><p>We are pleased to see that many developers are interested in Jina AI. We look forward to having fun with more developers. </p><p>Do you feel that you have missed the valuable offline communication opportunity here? It is okay, Jina AI's user experience survey is being collected. Please take <strong>2 minutes</strong> to fill out the survey and we will contact you!</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://10sw1tcpld4.typeform.com/to/lO6QRoM9?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">User Experience Survey</div><div class="kg-bookmark-description">Turn data collection into an experience with Typeform. Create beautiful online forms, surveys, quizzes, and so much more. Try it for FREE.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://public-assets.typeform.com/public/favicon/apple-touch-icon.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://images.typeform.com/images/2VWurKeiR4R7/image/default" alt=""></div></a><figcaption>Give us some feedback, it only takes you 2 minutes!</figcaption></figure><h2 id="about-devjoy">About DevJoy</h2><p>DevJoy is a community celebration designed especially for developers, where the participants can find community and peers, learn more about the future, and also learn about the lifestyle of developers.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fthe-lifestyle-of-developers-in-shanghai-devjoy-2022%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">The Lifestyle of Developers in Shanghai DevJoy 2022</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI was invited to attend DevJoy 2022 in Shanghai on November 5th-6th with Microsoft Reactor, Bilibili, Amazon Web Services, and other exhibitors. More than a thousand developers joined DevJoy and shared a pleasant and fruitful two days together.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 09, 2022 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Jina AI was invited to attend <a href="devjoy.org"><strong>DevJoy 2022</strong></a> in Shanghai on November 5th-6th with Microsoft Reactor, Bilibili, Amazon Web Services, and other exhibitors. More than a thousand developers joined DevJoy and shared a pleasant and fruitful two days together.</p><p>DevJoy 2022 - <strong>“The Lifestyle of Developers”</strong>, co-hosted by Bytebase, WeWork, and YuQue, took place at WeWork Shanghai (their largest facility in China). Jina AI is pleased to be one of the exhibitors and share our products and enthusiasm for the Open Source Community.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_4799.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_4799.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_4799.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_4799.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_4799.JPG 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_4806.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_4806.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_4806.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_4806.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_4806.JPG 2400w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_4804.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_4804.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_4804.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_4804.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_4804.JPG 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_4807.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_4807.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_4807.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_4807.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_4807.JPG 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>DevJoy 2022, WeWork, Shanghai. Other exhibitors also made wonderful sharing, such as Bilibili TC, JetBrains, Microsoft Reactor, PingCAP, TapTap, and Amazon Web Services.</figcaption></figure><h2 id="highlights">Highlights</h2><p>The Lightning Talk was the warm-up session for the event, with exhibitors showing some interesting cases about their products. Jina AI's Developer Relations, Sa.Zhang, presented <strong>"Jina AI: The most advanced MLOps platform for multimodal AI"</strong>. Sa<strong> </strong>set two on-site tasks of different difficulties, and finally unveiled the well-prepared task prizes - Jina AI's SWAG gloves and hats.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/--.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/--.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/--.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/--.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/--.JPG 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/IMG_4809.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/IMG_4809.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/IMG_4809.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/IMG_4809.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/IMG_4809.JPG 2400w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption><a href="https://store.covver.io/jina-ai/collections/swag-store?ref=jina-ai-gmbh.ghost.io">Swag from Jina AI</a></figcaption></figure><p>Sa. Zhang showed two demos, 「<a href="https://github.com/jina-ai/jina-video-chat?ref=jina-ai-gmbh.ghost.io">Bulid a “Joom” in 20 lines of code with Jina</a>」 and 「<a href="https://github.com/shan-mx/Video-CLIP-Indexer?ref=jina-ai-gmbh.ghost.io">Build text-to-video search with CLIP-as-service in 60 lines of code</a>」</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.77632 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/devjoy-workshop-gif.gif" width="1080" height="608" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/devjoy-workshop-gif.gif 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/devjoy-workshop-gif.gif 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/devjoy-workshop-gif.gif 1080w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.77506 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Screen-Shot-2022-11-08-at-11.49.17-PM.png" width="1594" height="898" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Screen-Shot-2022-11-08-at-11.49.17-PM.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Screen-Shot-2022-11-08-at-11.49.17-PM.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Screen-Shot-2022-11-08-at-11.49.17-PM.png 1594w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Two Demos: 「<a href="https://github.com/jina-ai/jina-video-chat?ref=jina-ai-gmbh.ghost.io">Bulid a “Joom” in 20 lines of code with Jina</a>」 and 「<a href="https://github.com/shan-mx/Video-CLIP-Indexer?ref=jina-ai-gmbh.ghost.io">Build text-to-video search with CLIP-as-service in 60 lines of code</a></figcaption></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/product/clip-as-service/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">CLIP-as-service | Jina AI</div><div class="kg-bookmark-description">Embed images and sentences into fixed-length vectors with CLIP.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/assets/images/banner/clip-as-service.jpg" alt=""></div></a></figure><p>After the Lightning Talk, Jina AI's booth was surrounded by developers who were very interested in either multimodal AI or building their own demos. Everyone had a great time.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/R0001120.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/R0001120.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/R0001120.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/R0001120.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/R0001120.JPG 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/workshop-1-1.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/workshop-1-1.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/workshop-1-1.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/workshop-1-1.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/workshop-1-1.JPG 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/WechatIMG18.jpeg" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/WechatIMG18.jpeg 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/WechatIMG18.jpeg 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/WechatIMG18.jpeg 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/WechatIMG18.jpeg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.50038 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/R0001129.JPG" width="2000" height="1333" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/R0001129.JPG 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/R0001129.JPG 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/R0001129.JPG 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/R0001129.JPG 2400w" sizes="(min-width: 720px) 720px"></div></div></div></figure><p>In this event, <a href="https://store.covver.io/jina-ai/collections/swag-store?ref=jina-ai-gmbh.ghost.io">Jina AI's SWAG</a> was warmly welcomed as always, including hats, gloves, notebooks, and T-shirts ... Please stay tuned to our events and we hope to connect with more of you in future events!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://store.covver.io/jina-ai/collections/swag-store?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Covver</div><div class="kg-bookmark-description"></div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://store.covver.io/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">&lt;img alt="american-apparel" sizes="100vw" srcSet="/_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=640&amp;amp;q=100 640w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=750&amp;amp;q=100 750w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=828&amp;amp;q=100 828w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=1080&amp;amp;q=100 1080w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=1200&amp;amp;q=100 1200w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=1920&amp;amp;q=100 1920w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=2048&amp;amp;q=100 2048w, /_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=3840&amp;amp;q=100 3840w" src="/_next/image?url=%2Fimages%2Ficons%2Fbrands%2Famerican-apparel%402x.png&amp;amp;w=3840&amp;amp;q=100" decoding="async" data-nimg="fill" style="position:absolute;top:0;left:0;bottom:0;right:0;box-sizing:border-box;padding:0;border:none;margin:auto;display:block;width:0;height:0;min-width:100%;max-width:100%;min-height:100%;max-height:100%;object-fit:contain;object-position:center center" loading="lazy"/&gt;</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://api.covver.io/api/v1/storefront/jina-ai/collections/swag-store/image" alt=""></div></a></figure><h2 id="see-you-next-time">See You Next Time</h2><p>We are pleased to see that many developers are interested in Jina AI. We look forward to having fun with more developers. </p><p>Do you feel that you have missed the valuable offline communication opportunity here? It is okay, Jina AI's user experience survey is being collected. Please take <strong>2 minutes</strong> to fill out the survey and we will contact you!</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://10sw1tcpld4.typeform.com/to/lO6QRoM9?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">User Experience Survey</div><div class="kg-bookmark-description">Turn data collection into an experience with Typeform. Create beautiful online forms, surveys, quizzes, and so much more. Try it for FREE.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://public-assets.typeform.com/public/favicon/apple-touch-icon.png" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://images.typeform.com/images/2VWurKeiR4R7/image/default" alt=""></div></a><figcaption>Give us some feedback, it only takes you 2 minutes!</figcaption></figure><h2 id="about-devjoy">About DevJoy</h2><p>DevJoy is a community celebration designed especially for developers, where the participants can find community and peers, learn more about the future, and also learn about the lifestyle of developers.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fthe-lifestyle-of-developers-in-shanghai-devjoy-2022%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>There's a Time and a Place: Unleashing Dynamic Variables in PromptPerfect</title><meta charset="utf-8"><meta name="title" content="There's a Time and a Place: Unleashing Dynamic Variables in PromptPerfect"><meta name="description" content="Incorporate users' time, date and location into your prompts. Plus contents of other websites, and outputs of other prompts themselves!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/theres-a-time-and-a-place-unleashing-dynamic-variables-in-promptperfect"><meta property="og:title" content="There's a Time and a Place: Unleashing Dynamic Variables in PromptPerfect"><meta property="og:description" content="Incorporate users' time, date and location into your prompts. Plus contents of other websites, and outputs of other prompts themselves!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Blog-images--13-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/theres-a-time-and-a-place-unleashing-dynamic-variables-in-promptperfect"><meta property="twitter:title" content="There's a Time and a Place: Unleashing Dynamic Variables in PromptPerfect"><meta property="twitter:description" content="Incorporate users' time, date and location into your prompts. Plus contents of other websites, and outputs of other prompts themselves!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Blog-images--13-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">There's a Time and a Place: Unleashing Dynamic Variables in PromptPerfect</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Incorporate users' time, date and location into your prompts. Plus contents of other websites, and outputs of other prompts themselves!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 07, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Back in the mists of time, PromptPerfect introduced its <a href="https://jina.ai/news/whats-next-for-prompt-engineering-prompts-as-a-service?ref=jina-ai-gmbh.ghost.io">Prompt-as-a-Service</a> feature, allowing you to serve your prompts via a RESTful API and call them from Python, JavaScript or cURL.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/whats-next-for-prompt-engineering-prompts-as-a-service?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">What’s Next for Prompt Engineering? PromptPerfect’s Prompt as a Service!</div><div class="kg-bookmark-description">Deploy prompts and flexible template prompts as REST API services, and integrate them into your applications with just a few clicks</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Pic.png" alt=""></div></a></figure><p>Let’s imagine we’re building an AI-powered recipe website. We want users to be able to click a button that suggests a delicious recipe for them. To do that, we can create a prompt and deploy it as a service. We would then incorporate that into our website via Prompt-as-a-Service’s <a href="https://promptperfect.jina.ai/api?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">RESTful API.</a></p><p>For example, we could have a prompt that suggested recipes to users:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot_20231207_123047_Chrome.png" class="kg-image" alt="" width="760" height="943" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Screenshot_20231207_123047_Chrome.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot_20231207_123047_Chrome.png 760w" sizes="(min-width: 720px) 720px"></figure><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Incorporating a RESTful API into your website is <i><em class="italic" style="white-space: pre-wrap;">way</em></i> outside the scope of this post, so we’ll just use cURL moving forwards. But rest assured, you can do this in any language or framework with an HTTP library.</div></div><p>By calling the prompt, a user could get a new recipe each time:</p><pre><code class="language-bash hljs">curl <span class="hljs-string">"https://api.promptperfect.jina.ai/RYNiqoT3txBjPoALnV46"</span> \
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JinaChat</div><div class="q-item__label q-item__label--caption text-caption">More modality, longer memory, less cost</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://rationale.jina.ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://rationale.jina.ai/Rationale-light.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">There's a Time and a Place: Unleashing Dynamic Variables in PromptPerfect</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Incorporate users' time, date and location into your prompts. Plus contents of other websites, and outputs of other prompts themselves!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 07, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Back in the mists of time, PromptPerfect introduced its <a href="https://jina.ai/news/whats-next-for-prompt-engineering-prompts-as-a-service?ref=jina-ai-gmbh.ghost.io">Prompt-as-a-Service</a> feature, allowing you to serve your prompts via a RESTful API and call them from Python, JavaScript or cURL.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/whats-next-for-prompt-engineering-prompts-as-a-service?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">What’s Next for Prompt Engineering? PromptPerfect’s Prompt as a Service!</div><div class="kg-bookmark-description">Deploy prompts and flexible template prompts as REST API services, and integrate them into your applications with just a few clicks</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/icons/favicon-128x128.png" alt=""><span class="kg-bookmark-publisher">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Pic.png" alt=""></div></a></figure><p>Let’s imagine we’re building an AI-powered recipe website. We want users to be able to click a button that suggests a delicious recipe for them. To do that, we can create a prompt and deploy it as a service. We would then incorporate that into our website via Prompt-as-a-Service’s <a href="https://promptperfect.jina.ai/api?ref=jina-ai-gmbh.ghost.io" rel="noreferrer">RESTful API.</a></p><p>For example, we could have a prompt that suggested recipes to users:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot_20231207_123047_Chrome.png" class="kg-image" alt="" width="760" height="943" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Screenshot_20231207_123047_Chrome.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot_20231207_123047_Chrome.png 760w" sizes="(min-width: 720px) 720px"></figure><div class="kg-card kg-callout-card kg-callout-card-blue"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Incorporating a RESTful API into your website is <i><em class="italic" style="white-space: pre-wrap;">way</em></i> outside the scope of this post, so we’ll just use cURL moving forwards. But rest assured, you can do this in any language or framework with an HTTP library.</div></div><p>By calling the prompt, a user could get a new recipe each time:</p><pre><code class="language-bash hljs">curl <span class="hljs-string">"https://api.promptperfect.jina.ai/RYNiqoT3txBjPoALnV46"</span> \
   -H <span class="hljs-string">"x-api-key: token <span class="hljs-variable">$YOUR_GENERATED_SECRET</span>"</span> \
   -H <span class="hljs-string">"content-type: application/json"</span></code></pre><div class="kg-card kg-toggle-card" data-kg-toggle-state="close">
             <div class="kg-toggle-heading">
@@ -74,4 +74,4 @@ <h4 class="kg-toggle-heading-text"><span style="white-space: pre-wrap;">View out
 The engines blazed like comets, as they'd never done before.
 The booster met its ending, in a ball of flame it fell,
 While Starship soared a moment more, then silence cast its spell.
-</code></pre><h2 id="calling-other-prompt-services">Calling other prompt services</h2><p>The above example wasn't exactly modular. I had both the summarizer and shantyizer in one prompt. That isn't so useful if I want to shanty all my things in full detail. Luckily, you can also call one prompt from another, allowing for a lot more modularity:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot_20231207_125614_Chrome.png" class="kg-image" alt="" width="762" height="493" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Screenshot_20231207_125614_Chrome.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot_20231207_125614_Chrome.png 762w" sizes="(min-width: 720px) 720px"></figure><p>So, if I create a summarizer prompt (named <code>summarizer</code>, which has the sole function of summarizing a web page)…</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot_20231207_130155_Chrome.png" class="kg-image" alt="" width="592" height="387"></figure><p>…I can easily call it from a new shantyizer prompt:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot_20231207_125751_Chrome-1.png" class="kg-image" alt="" width="591" height="393"></figure><p>Sending a URL to the shantyizer prompt in turn processes the URL through the summarizer to download and summarize its contents. And of course, the summarizer can be used in any other prompt you like, acting more like a traditional programming language function.</p><p>That opens up many more possibilities. Especially when it comes to more complex tasks like cooking a dish. If I’m cooking, for any given recipe I may want <em>one or more</em> of the following steps, but perhaps not all steps for all recipes.</p><ul><li>Download the content of a recipe page</li><li>If it's not in English, translate it (if I'm cooking an authentic Chinese recipe, I want it from a real Chinese website)</li><li>Make it vegetarian (if I'm eating with vegetarian friends)</li><li>Convert it to metric (because <a href="https://www.boredpanda.com/imperial-measurement-system-twitter-rant-innesmck/?ref=jina-ai-gmbh.ghost.io">reasons</a>)</li><li>Change serving size (depending on how many people I'm eating with)</li></ul><h2 id="exercise-for-the-reader">Exercise for the reader</h2><p>As you can imagine, if I'm eating alone (and I'm not a vegetarian), my needs are quite different from when I'm eating with my buddies at the local <a href="https://www.snopes.com/fact-check/peta-rename-fish-sea-kittens/?ref=jina-ai-gmbh.ghost.io">sea kitten appreciation society</a>. Either way, it means combining several of these "functions".</p><p>We can also go multi-modal, combining text and image prompts:</p><ul><li>Create an image generation prompt from the given recipe</li><li>Generate an image of how the food should look</li></ul><p>The exercise for you, dear reader, is to build a prompt that performs the above recipe steps (or similar). Share your results on our Discord!</p><h2 id="make-the-magic-happen">Make the magic happen</h2><p>To get started with magic variables, head to <a href="http://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">promptperfect.jina.ai</a> and get started. Let us know what you cook up on our <a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io">Discord</a>!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, Midjourney and Stable Diffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficiency.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ftheres-a-time-and-a-place-unleashing-dynamic-variables-in-promptperfect%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Magic Carpet Ride: Building Vivid Product Stories with SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how companies are integrating SceneXplain with their existing infrastructure to power their product descriptions and storytelling</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 133.385%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/WechatIMG1339-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Lisa Li, Alex C-G</div><div class="q-item__label q-item__label--caption text-caption">December 21, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Frame-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/multi-agent-simulations-in-promptperfect-n-heads-are-better-than-one" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Multi-Agent Simulations in PromptPerfect: 𝑛 Heads Are Better Than One</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; 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\ No newline at end of file
+</code></pre><h2 id="calling-other-prompt-services">Calling other prompt services</h2><p>The above example wasn't exactly modular. I had both the summarizer and shantyizer in one prompt. That isn't so useful if I want to shanty all my things in full detail. Luckily, you can also call one prompt from another, allowing for a lot more modularity:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot_20231207_125614_Chrome.png" class="kg-image" alt="" width="762" height="493" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/12/Screenshot_20231207_125614_Chrome.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot_20231207_125614_Chrome.png 762w" sizes="(min-width: 720px) 720px"></figure><p>So, if I create a summarizer prompt (named <code>summarizer</code>, which has the sole function of summarizing a web page)…</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot_20231207_130155_Chrome.png" class="kg-image" alt="" width="592" height="387"></figure><p>…I can easily call it from a new shantyizer prompt:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Screenshot_20231207_125751_Chrome-1.png" class="kg-image" alt="" width="591" height="393"></figure><p>Sending a URL to the shantyizer prompt in turn processes the URL through the summarizer to download and summarize its contents. And of course, the summarizer can be used in any other prompt you like, acting more like a traditional programming language function.</p><p>That opens up many more possibilities. Especially when it comes to more complex tasks like cooking a dish. If I’m cooking, for any given recipe I may want <em>one or more</em> of the following steps, but perhaps not all steps for all recipes.</p><ul><li>Download the content of a recipe page</li><li>If it's not in English, translate it (if I'm cooking an authentic Chinese recipe, I want it from a real Chinese website)</li><li>Make it vegetarian (if I'm eating with vegetarian friends)</li><li>Convert it to metric (because <a href="https://www.boredpanda.com/imperial-measurement-system-twitter-rant-innesmck/?ref=jina-ai-gmbh.ghost.io">reasons</a>)</li><li>Change serving size (depending on how many people I'm eating with)</li></ul><h2 id="exercise-for-the-reader">Exercise for the reader</h2><p>As you can imagine, if I'm eating alone (and I'm not a vegetarian), my needs are quite different from when I'm eating with my buddies at the local <a href="https://www.snopes.com/fact-check/peta-rename-fish-sea-kittens/?ref=jina-ai-gmbh.ghost.io">sea kitten appreciation society</a>. Either way, it means combining several of these "functions".</p><p>We can also go multi-modal, combining text and image prompts:</p><ul><li>Create an image generation prompt from the given recipe</li><li>Generate an image of how the food should look</li></ul><p>The exercise for you, dear reader, is to build a prompt that performs the above recipe steps (or similar). Share your results on our Discord!</p><h2 id="make-the-magic-happen">Make the magic happen</h2><p>To get started with magic variables, head to <a href="http://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">promptperfect.jina.ai</a> and get started. Let us know what you cook up on our <a href="https://discord.jina.ai/?ref=jina-ai-gmbh.ghost.io">Discord</a>!</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, Midjourney and Stable Diffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficiency.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ftheres-a-time-and-a-place-unleashing-dynamic-variables-in-promptperfect%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the real-world impact of multi-agent simulations and see practical examples of systems uniting individual strengths to tackle complex tasks, offering efficient and tailored solutions across various domains</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>This week(s) in DocArray</title><meta charset="utf-8"><meta name="title" content="This week(s) in DocArray"><meta name="description" content="It's already been two weeks since the last alpha release of DocArray v2. And since then a lot has happened — we've merged features we're really proud of, and cried tears of joy and misery trying to coerce Python into doing what we want."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/this-week-in-docarray-1"><meta property="og:title" content="This week(s) in DocArray"><meta property="og:description" content="It's already been two weeks since the last alpha release of DocArray v2. And since then a lot has happened — we've merged features we're really proud of, and cried tears of joy and misery trying to coerce Python into doing what we want."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/docarray-new-banner--2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/this-week-in-docarray-1"><meta property="twitter:title" content="This week(s) in DocArray"><meta property="twitter:description" content="It's already been two weeks since the last alpha release of DocArray v2. And since then a lot has happened — we've merged features we're really proud of, and cried tears of joy and misery trying to coerce Python into doing what we want."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/docarray-new-banner--2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>This week(s) in DocArray</title><meta charset="utf-8"><meta name="title" content="This week(s) in DocArray"><meta name="description" content="It's already been two weeks since the last alpha release of DocArray v2. And since then a lot has happened — we've merged features we're really proud of, and cried tears of joy and misery trying to coerce Python into doing what we want."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/this-week-in-docarray-1"><meta property="og:title" content="This week(s) in DocArray"><meta property="og:description" content="It's already been two weeks since the last alpha release of DocArray v2. And since then a lot has happened — we've merged features we're really proud of, and cried tears of joy and misery trying to coerce Python into doing what we want."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/docarray-new-banner--2-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/this-week-in-docarray-1"><meta property="twitter:title" content="This week(s) in DocArray"><meta property="twitter:description" content="It's already been two weeks since the last alpha release of DocArray v2. And since then a lot has happened — we've merged features we're really proud of, and cried tears of joy and misery trying to coerce Python into doing what we want."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/02/docarray-new-banner--2-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">This week(s) in DocArray</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">It's already been two weeks since the last alpha release of DocArray v2. And since then a lot has happened — we've merged features we're really proud of, and cried tears of joy and misery trying to coerce Python into doing what we want.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 80px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 98.8636%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/johannes.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 132.812%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/PXL_20221116_122857628.PORTRAIT.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Johannes Messner, Alex C-G, Sami Jaghouar</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 09, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Thanks to the <a href="https://www.docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray team</a> for this guest blog post!</div></div><p>It's already been two weeks since the <a href="https://github.com/docarray/docarray/releases/tag/2023.01.18.alpha?ref=jina-ai-gmbh.ghost.io">last alpha release</a> of DocArray v2. And since then a lot has happened — we've merged features we're really proud of, and we've cried tears of joy and misery trying to coerce Python into doing what we want. If you want to learn about interesting Python edge cases or follow the advancement of DocArray v2 development then you’ve come to the right place in this blog post!</p><p>For those who don’t know, DocArray is a library for <strong>representing, sending, and storing multi-modal data</strong>, with a focus on applications in <strong>ML</strong> and <strong>Neural Search.</strong></p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docarray.org/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">docarray.github.io</div><div class="kg-bookmark-description">homepage of docarray</div><div class="kg-bookmark-metadata"><span class="kg-bookmark-author">docarray.github.io</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://github.com/docarray/docarray/blob/main/docs/_static/logo-light.svg?raw=true" alt=""></div></a></figure><p>The project just moved to the <a href="https://lfaidata.foundation/?ref=jina-ai-gmbh.ghost.io">Linux foundation AI and Data</a>, and to celebrate its first birthday we decided to rewrite it from scratch, mainly because of a design shift and a will to solidify the codebase from the ground up. Also because it can’t eat cake and we had to give it <em>something</em>.</p><p>So, what's been happening in the past two weeks?</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Eager to go to a certain section? Click the link in the table of contents on the right 👉</div></div><h2 id="less-verbose-api">Less verbose API</h2><p>One of DocArray's goals is to give our users powerful abstractions to represent nested data. To do this in v2 we allow nesting of <code>BaseDocument</code>. (Well, this is actually just a feature of <a href="https://docs.pydantic.dev/?ref=jina-ai-gmbh.ghost.io">pydantic</a> and one of the reasons its design seduces us to use it as a backend).</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDocument
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">This week(s) in DocArray</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">It's already been two weeks since the last alpha release of DocArray v2. And since then a lot has happened — we've merged features we're really proud of, and cried tears of joy and misery trying to coerce Python into doing what we want.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 80px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 98.8636%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/johannes.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 50px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 132.812%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/02/PXL_20221116_122857628.PORTRAIT.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Johannes Messner, Alex C-G, Sami Jaghouar</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 09, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Thanks to the <a href="https://www.docarray.org/?ref=jina-ai-gmbh.ghost.io">DocArray team</a> for this guest blog post!</div></div><p>It's already been two weeks since the <a href="https://github.com/docarray/docarray/releases/tag/2023.01.18.alpha?ref=jina-ai-gmbh.ghost.io">last alpha release</a> of DocArray v2. And since then a lot has happened — we've merged features we're really proud of, and we've cried tears of joy and misery trying to coerce Python into doing what we want. If you want to learn about interesting Python edge cases or follow the advancement of DocArray v2 development then you’ve come to the right place in this blog post!</p><p>For those who don’t know, DocArray is a library for <strong>representing, sending, and storing multi-modal data</strong>, with a focus on applications in <strong>ML</strong> and <strong>Neural Search.</strong></p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docarray.org/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">docarray.github.io</div><div class="kg-bookmark-description">homepage of docarray</div><div class="kg-bookmark-metadata"><span class="kg-bookmark-author">docarray.github.io</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://github.com/docarray/docarray/blob/main/docs/_static/logo-light.svg?raw=true" alt=""></div></a></figure><p>The project just moved to the <a href="https://lfaidata.foundation/?ref=jina-ai-gmbh.ghost.io">Linux foundation AI and Data</a>, and to celebrate its first birthday we decided to rewrite it from scratch, mainly because of a design shift and a will to solidify the codebase from the ground up. Also because it can’t eat cake and we had to give it <em>something</em>.</p><p>So, what's been happening in the past two weeks?</p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Eager to go to a certain section? Click the link in the table of contents on the right 👉</div></div><h2 id="less-verbose-api">Less verbose API</h2><p>One of DocArray's goals is to give our users powerful abstractions to represent nested data. To do this in v2 we allow nesting of <code>BaseDocument</code>. (Well, this is actually just a feature of <a href="https://docs.pydantic.dev/?ref=jina-ai-gmbh.ghost.io">pydantic</a> and one of the reasons its design seduces us to use it as a backend).</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDocument
 <span class="hljs-keyword">from</span> docarray.documents <span class="hljs-keyword">import</span> Image, Text
 
 <span class="hljs-keyword">class</span> <span class="hljs-title class_">MyBanner</span>(<span class="hljs-title class_ inherited__">BaseDocument</span>):
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="aebdc7b0-1c92-49d0-934c-16c77c24cd3d" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="aebdc7b0-1c92-49d0-934c-16c77c24cd3d" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Sami Jaghouar, Alex C-G, Charlotte Gerhaher, Jack Min Ong</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 22, 2023 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>It’s already been a month since the <a href="https://github.com/docarray/docarray/releases/tag/2023.01.18.alpha?ref=jina-ai-gmbh.ghost.io">last alpha release</a> of DocArray v2. Since then a lot has happened: we’ve merged features that we’re really proud of and keep crying tears of joy and misery trying to coerce Python into doing what we want. If you want to learn about interesting Python edge cases or follow the advancement of DocArray v2 development then you’re at the right place in this dev blog!</p><p>For those who don’t know, DocArray is a library for <strong>representing, sending, and storing multi-modal data</strong>, with a focus on applications in <strong>ML</strong> and <strong>Neural Search.</strong> The project just moved to the Linux foundation AI and Data and to celebrate its first birthday we decided to rewrite it from scratch, mainly because of a design shift and a will to solidify the codebase from the ground up.</p><h2 id="multimodaldataset">MultiModalDataset</h2><p>As part of our goal to make DocArray the go-to library for representing, sending, and storing multi-modal data, we‘ve added a <code>MultiModalDataset</code> class to easily convert DocumentArrays into PyTorch Dataset compliant datasets that can be used in the PyTorch DataLoader.</p><p>All you need is a DocumentArray and a dictionary of preprocessing functions and you’re up and running!</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDocument, DocumentArray
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Sami Jaghouar, Alex C-G, Charlotte Gerhaher, Jack Min Ong</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">February 22, 2023 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>It’s already been a month since the <a href="https://github.com/docarray/docarray/releases/tag/2023.01.18.alpha?ref=jina-ai-gmbh.ghost.io">last alpha release</a> of DocArray v2. Since then a lot has happened: we’ve merged features that we’re really proud of and keep crying tears of joy and misery trying to coerce Python into doing what we want. If you want to learn about interesting Python edge cases or follow the advancement of DocArray v2 development then you’re at the right place in this dev blog!</p><p>For those who don’t know, DocArray is a library for <strong>representing, sending, and storing multi-modal data</strong>, with a focus on applications in <strong>ML</strong> and <strong>Neural Search.</strong> The project just moved to the Linux foundation AI and Data and to celebrate its first birthday we decided to rewrite it from scratch, mainly because of a design shift and a will to solidify the codebase from the ground up.</p><h2 id="multimodaldataset">MultiModalDataset</h2><p>As part of our goal to make DocArray the go-to library for representing, sending, and storing multi-modal data, we‘ve added a <code>MultiModalDataset</code> class to easily convert DocumentArrays into PyTorch Dataset compliant datasets that can be used in the PyTorch DataLoader.</p><p>All you need is a DocumentArray and a dictionary of preprocessing functions and you’re up and running!</p><pre><code class="language-python hljs"><span class="hljs-keyword">from</span> docarray <span class="hljs-keyword">import</span> BaseDocument, DocumentArray
 <span class="hljs-keyword">from</span> docarray.data <span class="hljs-keyword">import</span> MultiModalDataset
 <span class="hljs-keyword">from</span> docarray.documents <span class="hljs-keyword">import</span> Text
 <span class="hljs-keyword">from</span> torch.utils.data <span class="hljs-keyword">import</span> DataLoader
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="7bebef3f-e304-4b03-b02f-95bc7ead7695" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="7bebef3f-e304-4b03-b02f-95bc7ead7695" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">This week in Generative AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The latest updates in Jina AI's generative AI apps - SceneXplain, BestBanner, JinaChat, PromptPerfect and Rationale</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 03, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="promptperfectelevate-your-prompts-to-perfection"><a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">PromptPerfect</a> - Elevate your prompts to perfection</h2><h3 id="taming-openais-function-call"><strong>Taming OpenAI's Function Call</strong></h3><p>We’re excited to introduce a new function debugger that seamlessly integrates with <a href="https://openai.com/blog/function-calling-and-other-api-updates?ref=jina-ai-gmbh.ghost.io">OpenAI’s Function Calling API</a>. This new feature offers auto-generated JSON schemas and the ability to test prompts across multiple functions with traceability. This testbed allows you to check how your functions respond to natural language prompts, making it easier for you to ensure that your functions are working properly.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/promptperfect-functions-1.mp4" poster="https://img.spacergif.org/v1/1440x964/0a/spacer.png" width="1440" height="964" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember100.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h3 id="claude-2-and-baidu-ernie-integration">Claude 2 and Baidu ERNIE integration</h3><p>We’ve added the <a href="https://www.anthropic.com/index/claude-2?ref=jina-ai-gmbh.ghost.io">Claude 2</a> and <a href="https://www.anthropic.com/index/claude-2?ref=jina-ai-gmbh.ghost.io">Baidu ERNIE</a> models to PromptPerfect, so you can utilize them on the optimizer, streamline, few-shot, and prompt-as-service pages.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-2.04.49-PM.png" class="kg-image" alt="" width="1392" height="1934" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Screen-Shot-2023-08-03-at-2.04.49-PM.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Screen-Shot-2023-08-03-at-2.04.49-PM.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-2.04.49-PM.png 1392w" sizes="(min-width: 720px) 720px"></figure><h3 id="manage-your-subscriptions-better"><strong>Manage your subscriptions better</strong></h3><p>We recently added a ‘Manage subscription’ button on top of the billing page for your convenience. You can now easily manage your subscription plans through this new feature.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-07-27-at-9.30.08-AM-2.png" class="kg-image" alt="" width="2000" height="898" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Screen-Shot-2023-07-27-at-9.30.08-AM-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Screen-Shot-2023-07-27-at-9.30.08-AM-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/Screen-Shot-2023-07-27-at-9.30.08-AM-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/Screen-Shot-2023-07-27-at-9.30.08-AM-2.png 2400w" sizes="(min-width: 720px) 720px"></figure><h2 id="scenexplainexplore-image-storytelling-beyond-pixels"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a> - Explore Image storytelling beyond pixels</h2><h3 id="read-textual-images-in-their-original-language"><strong>Read textual images in their original language</strong></h3><p>We’ve added a new feature that lets you read textual images in their original language. This feature helps you to preserve the context's meaning. For example, translating the word "可口可樂" to English may result in it losing its meaning.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-01---7.20.56.png" class="kg-image" alt="" width="958" height="1470" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/--2023-08-01---7.20.56.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-01---7.20.56.png 958w" sizes="(min-width: 720px) 720px"></figure><h2 id="bestbannerblog-to-banner-without-the-prompts"><a href="https://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io">BestBanner</a> - Blog to banner, without the prompts</h2><h3 id="catchy-titles-and-descriptions">Catchy titles and descriptions</h3><p>Best Banner is ready to help you create a catchy title and description for your articles that will go viral. These can be seen in the social preview below:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-01-at-19.27.04.png" class="kg-image" alt="" width="940" height="1486" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Screen-Shot-2023-08-01-at-19.27.04.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-01-at-19.27.04.png 940w" sizes="(min-width: 720px) 720px"></figure><h3 id="better-topic-matching">Better topic matching</h3><p>Banners better match the topic and nuances of the given text. With its latest update, BestBanner has become better at identifying the topic and nuances of the given article and generating diverse banners that match this topic. To give an example, the following four banners were generated based on an <a href="https://avi-loeb.medium.com/unprecedented-hearing-on-extraterrestrials-in-the-us-house-of-representative-f9a217c78c37?ref=jina-ai-gmbh.ghost.io">article about the recent UFO hearings in the USA</a>.</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-15.29.20.png" class="kg-image" alt="" width="932" height="1288" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Screen-Shot-2023-08-03-at-15.29.20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-15.29.20.png 932w"></figure><h3 id="more-consistent-refinements">More consistent refinements</h3><p>Refined banners now closely match the theme and style of the original image. While of great quality, the “refined” banners didn’t always resemble the original source. This has been fixed, and “refined” banners now closely match the theme and style of the original source. To give a n example, the following eight banners were created by refining two banners from the previous example.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 0.807626 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-15.34.50-1.png" width="932" height="1154" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Screen-Shot-2023-08-03-at-15.34.50-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-15.34.50-1.png 932w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 0.805556 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-15.35.22-1.png" width="928" height="1152" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Screen-Shot-2023-08-03-at-15.35.22-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-15.35.22-1.png 928w" sizes="(min-width: 720px) 720px"></div></div></div></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fthis-week-in-generative-ai-01%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 03, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="promptperfectelevate-your-prompts-to-perfection"><a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">PromptPerfect</a> - Elevate your prompts to perfection</h2><h3 id="taming-openais-function-call"><strong>Taming OpenAI's Function Call</strong></h3><p>We’re excited to introduce a new function debugger that seamlessly integrates with <a href="https://openai.com/blog/function-calling-and-other-api-updates?ref=jina-ai-gmbh.ghost.io">OpenAI’s Function Calling API</a>. This new feature offers auto-generated JSON schemas and the ability to test prompts across multiple functions with traceability. This testbed allows you to check how your functions respond to natural language prompts, making it easier for you to ensure that your functions are working properly.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/promptperfect-functions-1.mp4" poster="https://img.spacergif.org/v1/1440x964/0a/spacer.png" width="1440" height="964" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember100.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h3 id="claude-2-and-baidu-ernie-integration">Claude 2 and Baidu ERNIE integration</h3><p>We’ve added the <a href="https://www.anthropic.com/index/claude-2?ref=jina-ai-gmbh.ghost.io">Claude 2</a> and <a href="https://www.anthropic.com/index/claude-2?ref=jina-ai-gmbh.ghost.io">Baidu ERNIE</a> models to PromptPerfect, so you can utilize them on the optimizer, streamline, few-shot, and prompt-as-service pages.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-2.04.49-PM.png" class="kg-image" alt="" width="1392" height="1934" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Screen-Shot-2023-08-03-at-2.04.49-PM.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Screen-Shot-2023-08-03-at-2.04.49-PM.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-2.04.49-PM.png 1392w" sizes="(min-width: 720px) 720px"></figure><h3 id="manage-your-subscriptions-better"><strong>Manage your subscriptions better</strong></h3><p>We recently added a ‘Manage subscription’ button on top of the billing page for your convenience. You can now easily manage your subscription plans through this new feature.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-07-27-at-9.30.08-AM-2.png" class="kg-image" alt="" width="2000" height="898" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Screen-Shot-2023-07-27-at-9.30.08-AM-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Screen-Shot-2023-07-27-at-9.30.08-AM-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/Screen-Shot-2023-07-27-at-9.30.08-AM-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2023/08/Screen-Shot-2023-07-27-at-9.30.08-AM-2.png 2400w" sizes="(min-width: 720px) 720px"></figure><h2 id="scenexplainexplore-image-storytelling-beyond-pixels"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a> - Explore Image storytelling beyond pixels</h2><h3 id="read-textual-images-in-their-original-language"><strong>Read textual images in their original language</strong></h3><p>We’ve added a new feature that lets you read textual images in their original language. This feature helps you to preserve the context's meaning. For example, translating the word "可口可樂" to English may result in it losing its meaning.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-01---7.20.56.png" class="kg-image" alt="" width="958" height="1470" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/--2023-08-01---7.20.56.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-01---7.20.56.png 958w" sizes="(min-width: 720px) 720px"></figure><h2 id="bestbannerblog-to-banner-without-the-prompts"><a href="https://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io">BestBanner</a> - Blog to banner, without the prompts</h2><h3 id="catchy-titles-and-descriptions">Catchy titles and descriptions</h3><p>Best Banner is ready to help you create a catchy title and description for your articles that will go viral. These can be seen in the social preview below:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-01-at-19.27.04.png" class="kg-image" alt="" width="940" height="1486" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Screen-Shot-2023-08-01-at-19.27.04.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-01-at-19.27.04.png 940w" sizes="(min-width: 720px) 720px"></figure><h3 id="better-topic-matching">Better topic matching</h3><p>Banners better match the topic and nuances of the given text. With its latest update, BestBanner has become better at identifying the topic and nuances of the given article and generating diverse banners that match this topic. To give an example, the following four banners were generated based on an <a href="https://avi-loeb.medium.com/unprecedented-hearing-on-extraterrestrials-in-the-us-house-of-representative-f9a217c78c37?ref=jina-ai-gmbh.ghost.io">article about the recent UFO hearings in the USA</a>.</p><figure class="kg-card kg-image-card kg-width-wide"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-15.29.20.png" class="kg-image" alt="" width="932" height="1288" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Screen-Shot-2023-08-03-at-15.29.20.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-15.29.20.png 932w"></figure><h3 id="more-consistent-refinements">More consistent refinements</h3><p>Refined banners now closely match the theme and style of the original image. While of great quality, the “refined” banners didn’t always resemble the original source. This has been fixed, and “refined” banners now closely match the theme and style of the original source. To give a n example, the following eight banners were created by refining two banners from the previous example.</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-15.34.50-1.png" width="932" height="1154" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Screen-Shot-2023-08-03-at-15.34.50-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-15.34.50-1.png 932w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-15.35.22-1.png" width="928" height="1152" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Screen-Shot-2023-08-03-at-15.35.22-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Screen-Shot-2023-08-03-at-15.35.22-1.png 928w" sizes="(min-width: 720px) 720px"></div></div></div></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fthis-week-in-generative-ai-01%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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diff --git a/news/this-week-in-generative-ai-02/index.html b/news/this-week-in-generative-ai-02/index.html
index 21e48c67b9b..f61d4f8f981 100644
--- a/news/this-week-in-generative-ai-02/index.html
+++ b/news/this-week-in-generative-ai-02/index.html
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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>This Week in Generative AI</title><meta charset="utf-8"><meta name="title" content="This Week in Generative AI"><meta name="description" content="The latest updates in Jina AI's generative AI apps - SceneXplain, BestBanner, JinaChat, PromptPerfect and Rationale"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/this-week-in-generative-ai-02"><meta property="og:title" content="This Week in Generative AI"><meta property="og:description" content="The latest updates in Jina AI's generative AI apps - SceneXplain, BestBanner, JinaChat, PromptPerfect and Rationale"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/20230809_133202_0000-1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/this-week-in-generative-ai-02"><meta property="twitter:title" content="This Week in Generative AI"><meta property="twitter:description" content="The latest updates in Jina AI's generative AI apps - SceneXplain, BestBanner, JinaChat, PromptPerfect and Rationale"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/20230809_133202_0000-1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>This Week in Generative AI</title><meta charset="utf-8"><meta name="title" content="This Week in Generative AI"><meta name="description" content="The latest updates in Jina AI's generative AI apps - SceneXplain, BestBanner, JinaChat, PromptPerfect and Rationale"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/this-week-in-generative-ai-02"><meta property="og:title" content="This Week in Generative AI"><meta property="og:description" content="The latest updates in Jina AI's generative AI apps - SceneXplain, BestBanner, JinaChat, PromptPerfect and Rationale"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/20230809_133202_0000-1.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/this-week-in-generative-ai-02"><meta property="twitter:title" content="This Week in Generative AI"><meta property="twitter:description" content="The latest updates in Jina AI's generative AI apps - SceneXplain, BestBanner, JinaChat, PromptPerfect and Rationale"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/20230809_133202_0000-1.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><script src="https://jina-ai-gmbh.ghost.io/public/cards.min.js" async=""></script><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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class="ellipsis">Software updates</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/20230809_133202_0000-1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">This Week in Generative AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The latest updates in Jina AI's generative AI apps - SceneXplain, BestBanner, JinaChat, PromptPerfect and Rationale</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 10, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="promptperfectelevate-your-prompts-to-perfection"><a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">PromptPerfect</a> - Elevate your prompts to perfection</h2><h3 id="refine-and-develop-your-prompt-by-chat">Refine and develop your prompt by chat</h3><p>We're pleased to introduce our new chat tab, which will help you improve your prompts in a dynamic multi-round chat environment.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/PP-jinachat.mp4" poster="https://img.spacergif.org/v1/2030x1080/0a/spacer.png" width="2030" height="1080" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember192.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="scenexplainexplore-image-storytelling-beyond-pixels"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a> - Explore Image storytelling beyond pixels</h2><h3 id="get-stories-from-your-images">Get stories from your images</h3><p>Our new SceneXplain algorithm, Hearth, creates and reads creative content based on your provided image, and can even take on different roles.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-08_--12.55.15.png" class="kg-image" alt="" width="616" height="1090" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/--2023-08-08_--12.55.15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-08_--12.55.15.png 616w"></figure><p>At the same time, you have the option to customize your preferred genre of story.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-08_--12.57.18.png" class="kg-image" alt="" width="488" height="1030"></figure><p>You can then imagine the conversation and the distinct voice:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-61.png" class="kg-image" alt="" width="984" height="1880" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled-61.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-61.png 984w" sizes="(min-width: 720px) 720px"></figure><p>To share your story, you can download a video we generate for you.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-08_--12.49.21.png" class="kg-image" alt="" width="1236" height="234" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/--2023-08-08_--12.49.21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/--2023-08-08_--12.49.21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-08_--12.49.21.png 1236w" sizes="(min-width: 720px) 720px"></figure><p>And here's the video itself:</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/cat-working.mp4" poster="https://img.spacergif.org/v1/750x496/0a/spacer.png" width="750" height="496" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember260.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="bestbannerblog-to-banner-without-the-prompts"><a href="https://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io">BestBanner</a> - Blog to banner, without the prompts</h2><h3 id="selectable-styles">Selectable styles</h3><p>We've added a new feature called Selectable Styles which lets you choose from three preset styles - Photographic, Minimalist, or Flat - to control your banners' aesthetics.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-1-2.png" class="kg-image" alt="" width="1920" height="1080" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled-1-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Untitled-1-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/Untitled-1-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-1-2.png 1920w" sizes="(min-width: 720px) 720px"></figure><h2 id="jinachatmore-modality-longer-memory-less-cost"><a href="https://chat.jina.ai/?ref=jina-ai-gmbh.ghost.io">JinaChat</a> - More Modality, longer memory, less cost</h2><h3 id="more-input-tokens-for-the-user">More input tokens for the user</h3><p>You can now input up to 4,000 tokens in the text window, which is approximately equivalent to 3,000 words.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" 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class="ellipsis">Software updates</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/20230809_133202_0000-1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">This Week in Generative AI</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The latest updates in Jina AI's generative AI apps - SceneXplain, BestBanner, JinaChat, PromptPerfect and Rationale</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 10, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="promptperfectelevate-your-prompts-to-perfection"><a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io">PromptPerfect</a> - Elevate your prompts to perfection</h2><h3 id="refine-and-develop-your-prompt-by-chat">Refine and develop your prompt by chat</h3><p>We're pleased to introduce our new chat tab, which will help you improve your prompts in a dynamic multi-round chat environment.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/PP-jinachat.mp4" poster="https://img.spacergif.org/v1/2030x1080/0a/spacer.png" width="2030" height="1080" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember192.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="scenexplainexplore-image-storytelling-beyond-pixels"><a href="https://scenex.jina.ai/?ref=jina-ai-gmbh.ghost.io">SceneXplain</a> - Explore Image storytelling beyond pixels</h2><h3 id="get-stories-from-your-images">Get stories from your images</h3><p>Our new SceneXplain algorithm, Hearth, creates and reads creative content based on your provided image, and can even take on different roles.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-08_--12.55.15.png" class="kg-image" alt="" width="616" height="1090" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/--2023-08-08_--12.55.15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-08_--12.55.15.png 616w"></figure><p>At the same time, you have the option to customize your preferred genre of story.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-08_--12.57.18.png" class="kg-image" alt="" width="488" height="1030"></figure><p>You can then imagine the conversation and the distinct voice:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-61.png" class="kg-image" alt="" width="984" height="1880" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled-61.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-61.png 984w" sizes="(min-width: 720px) 720px"></figure><p>To share your story, you can download a video we generate for you.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-08_--12.49.21.png" class="kg-image" alt="" width="1236" height="234" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/--2023-08-08_--12.49.21.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/--2023-08-08_--12.49.21.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/--2023-08-08_--12.49.21.png 1236w" sizes="(min-width: 720px) 720px"></figure><p>And here's the video itself:</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/cat-working.mp4" poster="https://img.spacergif.org/v1/750x496/0a/spacer.png" width="750" height="496" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember260.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="bestbannerblog-to-banner-without-the-prompts"><a href="https://bestbanner.jina.ai/?ref=jina-ai-gmbh.ghost.io">BestBanner</a> - Blog to banner, without the prompts</h2><h3 id="selectable-styles">Selectable styles</h3><p>We've added a new feature called Selectable Styles which lets you choose from three preset styles - Photographic, Minimalist, or Flat - to control your banners' aesthetics.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-1-2.png" class="kg-image" alt="" width="1920" height="1080" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/Untitled-1-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/Untitled-1-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/Untitled-1-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/Untitled-1-2.png 1920w" sizes="(min-width: 720px) 720px"></figure><h2 id="jinachatmore-modality-longer-memory-less-cost"><a href="https://chat.jina.ai/?ref=jina-ai-gmbh.ghost.io">JinaChat</a> - More Modality, longer memory, less cost</h2><h3 id="more-input-tokens-for-the-user">More input tokens for the user</h3><p>You can now input up to 4,000 tokens in the text window, which is approximately equivalent to 3,000 words.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/docarray-0-40-0-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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diff --git a/news/time-slicing-gpus-with-karpenter/index.html b/news/time-slicing-gpus-with-karpenter/index.html
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+++ b/news/time-slicing-gpus-with-karpenter/index.html
@@ -10,9 +10,9 @@
 
 But let's switch the role now. Say you are the GPU cloud provider, and you provide the GPU environment for hosting other users applications. The problem now becomes, how can you, as this platform provider, lower down the GPU costs to maximize the profit?
 
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; 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Especially with the GPU cloud instances, you pay as you go. It is much more cost-efficient comparing to having an expensive metal machine in the office.
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Today, businesses and developers are keen to use cloud for deep learning. Especially with the GPU cloud instances, you pay as you go. It is much more cost-efficient comparing to having an expensive metal machine in the office.
 
 But let's switch the role now. Say you are the GPU cloud provider, and you provide the GPU environment for hosting other users applications. The problem now becomes, how can you, as this platform provider, lower down the GPU costs to maximize the profit?
 
-This is not abou</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1657705564323.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Tao Ran</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 02, 2022 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Today, businesses and developers are keen to use cloud for deep learning. Especially with the GPU cloud instances, you pay as you go. It is much more cost-efficient comparing to having an expensive metal machine in the office.</p><p><strong>But let's switch the role now. </strong>Say you are the GPU cloud provider, and you provide the GPU environment for hosting other users applications. The problem now becomes, <strong>how can you, as this platform provider, lower down the GPU costs to maximize the profit?</strong></p><p>This is not about finding the cheapest GPU vendors. In fact, it is <em>the</em> question we were facing at Jina AI when designing our GPU cloud platform.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docs.jina.ai/fundamentals/jcloud/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud Hosting</div><div class="kg-bookmark-description">After building a Jina project, the next step is to deploy and host it on the cloud. Jina AI Cloud is Jina’s reliable, scalable and production-ready cloud-hosting solution that manages your project lifecycle without surprises or hidden development costs. Basics: Jina AI Cloud provides a CLI that y...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docs.jina.ai/_static/favicon.ico" alt=""><span class="kg-bookmark-author">Jina 3.11.1 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docs.jina.ai/_images/jcloud-banner.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">MLops platform to build neural search and multimodal data services in the cloud at scale</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""><span class="kg-bookmark-author">Jina AI Cloud</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a></figure><p>The answer is <strong>time-slicing.</strong></p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Time-slicing allows oversubscription of GPUs. Under the hood, CUDA time-slicing is used to allow workloads that land on oversubscribed GPUs to interleave with one another. Each workload has access to the GPU memory and runs in the same fault-domain as of all the others</div></div><p>In this article, we will use Karpenter - an elastic node scaling method in Kubernetes and NVIDIA’s k8s plugin to achieve time-slicing on GPUs. A GPU cloud with time-slicing will allow users to share GPUs between pods, hence saves the costs.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://karpenter.sh/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Karpenter</div><div class="kg-bookmark-description">Just-in-time Nodes for Any Kubernetes Cluster</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://karpenter.sh/favicon.svg" alt=""><span class="kg-bookmark-author">Karpenter</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://karpenter.sh/banner.png" alt=""></div></a><figcaption>You can know more about Karpenter from the docs</figcaption></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/NVIDIA/k8s-device-plugin?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - NVIDIA/k8s-device-plugin: NVIDIA device plugin for Kubernetes</div><div class="kg-bookmark-description">NVIDIA device plugin for Kubernetes. Contribute to NVIDIA/k8s-device-plugin development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">NVIDIA</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/786d7d790a8e2a453535b2ea83a1440abc4e4eeb91cd1573b1dab2a4520284b3/NVIDIA/k8s-device-plugin" alt=""></div></a></figure><p>Karpenter itself provides an auto scaling feature to nodes, which means that you will have the GPU instance only when you need it and can schedule the node based on the instance type you configured. It saves you money and schedules nodes more effectively.</p><p>The purpose of utilizing the GPU with Karpenter is not only saving cost, but more importantly, it also provides us a flexible method to schedule GPU resources to our applications within the kubernetes cluster. You may own tens of applications which need the GPU in different time slots, how to schedule them in a more cost effective way is so important in the cloud.</p><h2 id="architecture"><strong>Architecture</strong></h2><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://miro.medium.com/max/1400/1*Bw7iWZaeALkDJFr6a1dWAw.png" class="kg-image" alt="" width="700" height="474"><figcaption>Infrastructure diagram</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://miro.medium.com/max/1400/1*9fXBwPJii317MA5OPouEdg.png" class="kg-image" alt="" width="700" height="467"><figcaption>Component diagram</figcaption></figure><p>It’s pretty straightforward: the application will choose a karpenter provisioner with a selector. The karpenter provisioner will create nodes based on the launch template in that provisioner.</p><h2 id="deployment"><strong>Deployment</strong></h2><p>Building the architect is simple, the problem we are left with is how we are going to deploy it. There are some particulars we need to think about.</p><ul><li>How we deploy the nvidia k8s plugin to the nodes with GPU only.</li><li>How we configure the shared GPU nodes to use time-slicing without affecting others.</li><li>How do we automatically update nodes AMI in the launch template so the nodes can use the latest image.</li><li>How do we setup karpenter provisioners</li></ul><p>Let’s do it one by one then.</p><p>First, install karpenter and setup provisioner with terraform. You can manually install karpenter in eks with an official document as well. If you already have eks with karpenter, you can skip it.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/tarrantro/terraform?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - tarrantro/terraform</div><div class="kg-bookmark-description">Contribute to tarrantro/terraform development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">tarrantro</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/675a7982d2740898ca324bd3192fa48af572f5c9ad958e575c2b6e5b2b751a6b/tarrantro/terraform" alt=""></div></a></figure><h3 id="set-provisioner">Set provisioner</h3><p>The Provisioners is set to use corelated launch templates to provision GPU nodes with labels and taints.</p><figure class="kg-card kg-code-card"><pre><code class="language-yaml hljs"><span class="hljs-string">resource</span> <span class="hljs-string">"kubectl_manifest"</span> <span class="hljs-string">"karpenter_provisioner_gpu_shared"</span> {
-  <span class="hljs-string">yaml_body</span> <span class="hljs-string">=</span> <span class="hljs-string">&lt;&lt;-YAML</span>
-  <span class="hljs-attr">apiVersion:</span> <span class="hljs-string">karpenter.sh/v1alpha5</span>
-  <span class="hljs-attr">kind:</span> <span class="hljs-string">Provisioner</span>
-  <span class="hljs-attr">metadata:</span>
-    <span class="hljs-attr">name:</span> <span class="hljs-string">gpu-shared</span>
-  <span class="hljs-attr">spec:</span>
-    <span class="hljs-attr">ttlSecondsAfterEmpty:</span> <span class="hljs-number">300</span>
-    <span class="hljs-attr">labels:</span>
-      <span class="hljs-attr">jina.ai/node-type:</span> <span class="hljs-string">gpu-shared</span>
-      <span class="hljs-attr">jina.ai/gpu-type:</span> <span class="hljs-string">nvidia</span>
-      <span class="hljs-attr">nvidia.com/device-plugin.config:</span> <span class="hljs-string">shared_gpu</span>
-    <span class="hljs-attr">requirements:</span>
-      <span class="hljs-bullet">-</span> <span class="hljs-attr">key:</span> <span class="hljs-string">node.kubernetes.io/instance-type</span>
-        <span class="hljs-attr">operator:</span> <span class="hljs-string">In</span>
-        <span class="hljs-attr">values:</span> [<span class="hljs-string">"g4dn.xlarge"</span>, <span class="hljs-string">"g4dn.2xlarge"</span>, <span class="hljs-string">"g4dn.4xlarge"</span>, <span class="hljs-string">"g4dn.12xlarge"</span>]
-      <span class="hljs-bullet">-</span> <span class="hljs-attr">key:</span> <span class="hljs-string">karpenter.sh/capacity-type</span>
-        <span class="hljs-attr">operator:</span> <span class="hljs-string">In</span>
-        <span class="hljs-attr">values:</span> [<span class="hljs-string">"spot"</span>, <span class="hljs-string">"on-demand"</span>]
-      <span class="hljs-bullet">-</span> <span class="hljs-attr">key:</span> <span class="hljs-string">kubernetes.io/arch</span>
-        <span class="hljs-attr">operator:</span> <span class="hljs-string">In</span>
-        <span class="hljs-attr">values:</span> [<span class="hljs-string">"amd64"</span>]
-    <span class="hljs-attr">taints:</span>
-      <span class="hljs-bullet">-</span> <span class="hljs-attr">key:</span> <span class="hljs-string">nvidia.com/gpu-shared</span>
-        <span class="hljs-attr">effect:</span> <span class="hljs-string">"NoSchedule"</span>
-    <span class="hljs-attr">limits:</span>
-      <span class="hljs-attr">resources:</span>
-        <span class="hljs-attr">cpu:</span> <span class="hljs-number">1000</span>
-    <span class="hljs-attr">provider:</span>
-      <span class="hljs-attr">launchTemplate:</span> <span class="hljs-string">"karpenter-gpu-shared-${local.cluster_name}"</span>
-      <span class="hljs-attr">subnetSelector:</span>
-        <span class="hljs-attr">karpenter.sh/discovery:</span> <span class="hljs-string">$</span>{<span class="hljs-string">local.cluster_name</span>}
-      <span class="hljs-attr">tags:</span>
-        <span class="hljs-attr">karpenter.sh/discovery:</span> <span class="hljs-string">$</span>{<span class="hljs-string">local.cluster_name</span>}
-    <span class="hljs-attr">ttlSecondsAfterEmpty:</span> <span class="hljs-number">30</span>
-  <span class="hljs-string">YAML</span>
+This is not abou</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1657705564323.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Tao Ran</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 02, 2022 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Today, businesses and developers are keen to use cloud for deep learning. Especially with the GPU cloud instances, you pay as you go. It is much more cost-efficient comparing to having an expensive metal machine in the office.</p><p><strong>But let's switch the role now. </strong>Say you are the GPU cloud provider, and you provide the GPU environment for hosting other users applications. The problem now becomes, <strong>how can you, as this platform provider, lower down the GPU costs to maximize the profit?</strong></p><p>This is not about finding the cheapest GPU vendors. In fact, it is <em>the</em> question we were facing at Jina AI when designing our GPU cloud platform.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://docs.jina.ai/fundamentals/jcloud/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud Hosting</div><div class="kg-bookmark-description">After building a Jina project, the next step is to deploy and host it on the cloud. Jina AI Cloud is Jina’s reliable, scalable and production-ready cloud-hosting solution that manages your project lifecycle without surprises or hidden development costs. Basics: Jina AI Cloud provides a CLI that y...</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://docs.jina.ai/_static/favicon.ico" alt=""><span class="kg-bookmark-author">Jina 3.11.1 Documentation</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://docs.jina.ai/_images/jcloud-banner.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI Cloud</div><div class="kg-bookmark-description">MLops platform to build neural search and multimodal data services in the cloud at scale</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://cloud.jina.ai/favicon.ico" alt=""><span class="kg-bookmark-author">Jina AI Cloud</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cloud.jina.ai/assets/jina-banner.jpg" alt=""></div></a></figure><p>The answer is <strong>time-slicing.</strong></p><div class="kg-card kg-callout-card kg-callout-card-grey"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">Time-slicing allows oversubscription of GPUs. Under the hood, CUDA time-slicing is used to allow workloads that land on oversubscribed GPUs to interleave with one another. Each workload has access to the GPU memory and runs in the same fault-domain as of all the others</div></div><p>In this article, we will use Karpenter - an elastic node scaling method in Kubernetes and NVIDIA’s k8s plugin to achieve time-slicing on GPUs. A GPU cloud with time-slicing will allow users to share GPUs between pods, hence saves the costs.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://karpenter.sh/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Karpenter</div><div class="kg-bookmark-description">Just-in-time Nodes for Any Kubernetes Cluster</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://karpenter.sh/favicon.svg" alt=""><span class="kg-bookmark-author">Karpenter</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://karpenter.sh/banner.png" alt=""></div></a><figcaption>You can know more about Karpenter from the docs</figcaption></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/NVIDIA/k8s-device-plugin?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - NVIDIA/k8s-device-plugin: NVIDIA device plugin for Kubernetes</div><div class="kg-bookmark-description">NVIDIA device plugin for Kubernetes. Contribute to NVIDIA/k8s-device-plugin development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">NVIDIA</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/786d7d790a8e2a453535b2ea83a1440abc4e4eeb91cd1573b1dab2a4520284b3/NVIDIA/k8s-device-plugin" alt=""></div></a></figure><p>Karpenter itself provides an auto scaling feature to nodes, which means that you will have the GPU instance only when you need it and can schedule the node based on the instance type you configured. It saves you money and schedules nodes more effectively.</p><p>The purpose of utilizing the GPU with Karpenter is not only saving cost, but more importantly, it also provides us a flexible method to schedule GPU resources to our applications within the kubernetes cluster. You may own tens of applications which need the GPU in different time slots, how to schedule them in a more cost effective way is so important in the cloud.</p><h2 id="architecture"><strong>Architecture</strong></h2><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://miro.medium.com/max/1400/1*Bw7iWZaeALkDJFr6a1dWAw.png" class="kg-image" alt="" width="700" height="474"><figcaption>Infrastructure diagram</figcaption></figure><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://miro.medium.com/max/1400/1*9fXBwPJii317MA5OPouEdg.png" class="kg-image" alt="" width="700" height="467"><figcaption>Component diagram</figcaption></figure><p>It’s pretty straightforward: the application will choose a karpenter provisioner with a selector. The karpenter provisioner will create nodes based on the launch template in that provisioner.</p><h2 id="deployment"><strong>Deployment</strong></h2><p>Building the architect is simple, the problem we are left with is how we are going to deploy it. There are some particulars we need to think about.</p><ul><li>How we deploy the nvidia k8s plugin to the nodes with GPU only.</li><li>How we configure the shared GPU nodes to use time-slicing without affecting others.</li><li>How do we automatically update nodes AMI in the launch template so the nodes can use the latest image.</li><li>How do we setup karpenter provisioners</li></ul><p>Let’s do it one by one then.</p><p>First, install karpenter and setup provisioner with terraform. You can manually install karpenter in eks with an official document as well. If you already have eks with karpenter, you can skip it.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/tarrantro/terraform?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - tarrantro/terraform</div><div class="kg-bookmark-description">Contribute to tarrantro/terraform development by creating an account on GitHub.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">tarrantro</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://opengraph.githubassets.com/675a7982d2740898ca324bd3192fa48af572f5c9ad958e575c2b6e5b2b751a6b/tarrantro/terraform" alt=""></div></a></figure><h3 id="set-provisioner">Set provisioner</h3><p>The Provisioners is set to use corelated launch templates to provision GPU nodes with labels and taints.</p><figure class="kg-card kg-code-card"><pre><code class="language-yaml">resource "kubectl_manifest" "karpenter_provisioner_gpu_shared" {
+  yaml_body = &lt;&lt;-YAML
+  apiVersion: karpenter.sh/v1alpha5
+  kind: Provisioner
+  metadata:
+    name: gpu-shared
+  spec:
+    ttlSecondsAfterEmpty: 300
+    labels:
+      jina.ai/node-type: gpu-shared
+      jina.ai/gpu-type: nvidia
+      nvidia.com/device-plugin.config: shared_gpu
+    requirements:
+      - key: node.kubernetes.io/instance-type
+        operator: In
+        values: ["g4dn.xlarge", "g4dn.2xlarge", "g4dn.4xlarge", "g4dn.12xlarge"]
+      - key: karpenter.sh/capacity-type
+        operator: In
+        values: ["spot", "on-demand"]
+      - key: kubernetes.io/arch
+        operator: In
+        values: ["amd64"]
+    taints:
+      - key: nvidia.com/gpu-shared
+        effect: "NoSchedule"
+    limits:
+      resources:
+        cpu: 1000
+    provider:
+      launchTemplate: "karpenter-gpu-shared-${local.cluster_name}"
+      subnetSelector:
+        karpenter.sh/discovery: ${local.cluster_name}
+      tags:
+        karpenter.sh/discovery: ${local.cluster_name}
+    ttlSecondsAfterEmpty: 30
+  YAML
 
-  <span class="hljs-string">depends_on</span> <span class="hljs-string">=</span> [
-    <span class="hljs-string">helm_release.karpenter</span>
+  depends_on = [
+    helm_release.karpenter
   ]
 }
 
-<span class="hljs-string">resource</span> <span class="hljs-string">"kubectl_manifest"</span> <span class="hljs-string">"karpenter_provisioner_gpu"</span> {
-  <span class="hljs-string">yaml_body</span> <span class="hljs-string">=</span> <span class="hljs-string">&lt;&lt;-YAML</span>
-  <span class="hljs-attr">apiVersion:</span> <span class="hljs-string">karpenter.sh/v1alpha5</span>
-  <span class="hljs-attr">kind:</span> <span class="hljs-string">Provisioner</span>
-  <span class="hljs-attr">metadata:</span>
-    <span class="hljs-attr">name:</span> <span class="hljs-string">gpu</span>
-  <span class="hljs-attr">spec:</span>
-    <span class="hljs-attr">ttlSecondsAfterEmpty:</span> <span class="hljs-number">300</span>
-    <span class="hljs-attr">labels:</span>
-      <span class="hljs-attr">jina.ai/node-type:</span> <span class="hljs-string">gpu</span>
-      <span class="hljs-attr">jina.ai/gpu-type:</span> <span class="hljs-string">nvidia</span>
-    <span class="hljs-attr">requirements:</span>
-      <span class="hljs-bullet">-</span> <span class="hljs-attr">key:</span> <span class="hljs-string">node.kubernetes.io/instance-type</span>
-        <span class="hljs-attr">operator:</span> <span class="hljs-string">In</span>
-        <span class="hljs-attr">values:</span> [<span class="hljs-string">"g4dn.xlarge"</span>, <span class="hljs-string">"g4dn.2xlarge"</span>, <span class="hljs-string">"g4dn.4xlarge"</span>, <span class="hljs-string">"g4dn.12xlarge"</span>]
-      <span class="hljs-bullet">-</span> <span class="hljs-attr">key:</span> <span class="hljs-string">karpenter.sh/capacity-type</span>
-        <span class="hljs-attr">operator:</span> <span class="hljs-string">In</span>
-        <span class="hljs-attr">values:</span> [<span class="hljs-string">"spot"</span>, <span class="hljs-string">"on-demand"</span>]
-      <span class="hljs-bullet">-</span> <span class="hljs-attr">key:</span> <span class="hljs-string">kubernetes.io/arch</span>
-        <span class="hljs-attr">operator:</span> <span class="hljs-string">In</span>
-        <span class="hljs-attr">values:</span> [<span class="hljs-string">"amd64"</span>]
-    <span class="hljs-attr">taints:</span>
-      <span class="hljs-bullet">-</span> <span class="hljs-attr">key:</span> <span class="hljs-string">nvidia.com/gpu</span>
-        <span class="hljs-attr">effect:</span> <span class="hljs-string">"NoSchedule"</span>
-    <span class="hljs-attr">limits:</span>
-      <span class="hljs-attr">resources:</span>
-        <span class="hljs-attr">cpu:</span> <span class="hljs-number">1000</span>
-    <span class="hljs-attr">provider:</span>
-      <span class="hljs-attr">launchTemplate:</span> <span class="hljs-string">"karpenter-gpu-${local.cluster_name}"</span>
-      <span class="hljs-attr">subnetSelector:</span>
-        <span class="hljs-attr">karpenter.sh/discovery:</span> <span class="hljs-string">$</span>{<span class="hljs-string">local.cluster_name</span>}
-      <span class="hljs-attr">tags:</span>
-        <span class="hljs-attr">karpenter.sh/discovery:</span> <span class="hljs-string">$</span>{<span class="hljs-string">local.cluster_name</span>}
-    <span class="hljs-attr">ttlSecondsAfterEmpty:</span> <span class="hljs-number">30</span>
-  <span class="hljs-string">YAML</span>
+resource "kubectl_manifest" "karpenter_provisioner_gpu" {
+  yaml_body = &lt;&lt;-YAML
+  apiVersion: karpenter.sh/v1alpha5
+  kind: Provisioner
+  metadata:
+    name: gpu
+  spec:
+    ttlSecondsAfterEmpty: 300
+    labels:
+      jina.ai/node-type: gpu
+      jina.ai/gpu-type: nvidia
+    requirements:
+      - key: node.kubernetes.io/instance-type
+        operator: In
+        values: ["g4dn.xlarge", "g4dn.2xlarge", "g4dn.4xlarge", "g4dn.12xlarge"]
+      - key: karpenter.sh/capacity-type
+        operator: In
+        values: ["spot", "on-demand"]
+      - key: kubernetes.io/arch
+        operator: In
+        values: ["amd64"]
+    taints:
+      - key: nvidia.com/gpu
+        effect: "NoSchedule"
+    limits:
+      resources:
+        cpu: 1000
+    provider:
+      launchTemplate: "karpenter-gpu-${local.cluster_name}"
+      subnetSelector:
+        karpenter.sh/discovery: ${local.cluster_name}
+      tags:
+        karpenter.sh/discovery: ${local.cluster_name}
+    ttlSecondsAfterEmpty: 30
+  YAML
 
-  <span class="hljs-string">depends_on</span> <span class="hljs-string">=</span> [
-    <span class="hljs-string">helm_release.karpenter</span>
+  depends_on = [
+    helm_release.karpenter
   ]
-}</code></pre><figcaption>Provisioner</figcaption></figure><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://gist.github.com/tarrantro/6c6bfa1e114e4ca4762a5facaeb0c355?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">gpu_launchtemplate.hcl</div><div class="kg-bookmark-description">gpu_launchtemplate.hcl. GitHub Gist: instantly share code, notes, and snippets.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://gist.github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">Gist</span><span class="kg-bookmark-publisher">262588213843476</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://github.githubassets.com/images/modules/gists/gist-og-image.png" alt=""></div></a><figcaption>Launch template (only GPU)</figcaption></figure><h3 id="add-time-slicing-config">Add time-slicing config</h3><p>Secondly, we need to deploy the NVIDIA k8s plugin with time-slicing config and default config and set up a node selector so the daemonset will only run on the GPU instances.</p><figure class="kg-card kg-code-card"><pre><code class="language-yaml hljs"><span class="hljs-attr">config:</span>
-  <span class="hljs-comment"># ConfigMap name if pulling from an external ConfigMap</span>
-  <span class="hljs-attr">name:</span> <span class="hljs-string">""</span>
-  <span class="hljs-comment"># Set of named configs to build an integrated ConfigMap from</span>
-  <span class="hljs-attr">map:</span> 
-    <span class="hljs-attr">default:</span> <span class="hljs-string">|-
+}</code></pre><figcaption>Provisioner</figcaption></figure><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://gist.github.com/tarrantro/6c6bfa1e114e4ca4762a5facaeb0c355?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">gpu_launchtemplate.hcl</div><div class="kg-bookmark-description">gpu_launchtemplate.hcl. GitHub Gist: instantly share code, notes, and snippets.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://gist.github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">Gist</span><span class="kg-bookmark-publisher">262588213843476</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://github.githubassets.com/images/modules/gists/gist-og-image.png" alt=""></div></a><figcaption>Launch template (only GPU)</figcaption></figure><h3 id="add-time-slicing-config">Add time-slicing config</h3><p>Secondly, we need to deploy the NVIDIA k8s plugin with time-slicing config and default config and set up a node selector so the daemonset will only run on the GPU instances.</p><figure class="kg-card kg-code-card"><pre><code class="language-yaml">config:
+  # ConfigMap name if pulling from an external ConfigMap
+  name: ""
+  # Set of named configs to build an integrated ConfigMap from
+  map: 
+    default: |-
       version: v1
       flags:
         migStrategy: "none"
@@ -123,7 +123,7 @@
           passDeviceSpecs: false
           deviceListStrategy: envvar
           deviceIDStrategy: uuid
-</span>    <span class="hljs-attr">shared_gpu:</span> <span class="hljs-string">|-
+    shared_gpu: |-
       version: v1
       flags:
         migStrategy: "none"
@@ -139,70 +139,70 @@
           resources:
           - name: nvidia.com/gpu
             replicas: 10
-</span><span class="hljs-attr">nodeSelector:</span> 
-  <span class="hljs-attr">jina.ai/gpu-type:</span> <span class="hljs-string">nvidia</span></code></pre><figcaption>nvdp.yaml</figcaption></figure><p>Run the below command to install NVIDIA’s k8s plugin:</p><pre><code class="language-shell hljs">helm repo add nvdp https://nvidia.github.io/k8s-device-plugin
+nodeSelector: 
+  jina.ai/gpu-type: nvidia</code></pre><figcaption>nvdp.yaml</figcaption></figure><p>Run the below command to install NVIDIA’s k8s plugin:</p><pre><code class="language-shell">helm repo add nvdp https://nvidia.github.io/k8s-device-plugin
 helm repo update
 helm upgrade -i nvdp nvdp/nvidia-device-plugin \  --namespace nvidia-device-plugin \  --create-namespace -f nvdp.yaml
-</code></pre><h3 id="deploy-user-application">Deploy user application</h3><p>Third, deploy the user application with <em><em>nodeSelector </em></em>and <em><em>toleration.</em></em></p><figure class="kg-card kg-code-card"><pre><code class="language-yaml hljs"><span class="hljs-attr">kind:</span> <span class="hljs-string">Deployment</span>
-<span class="hljs-attr">apiVersion:</span> <span class="hljs-string">apps/v1</span>
-<span class="hljs-attr">metadata:</span>
-  <span class="hljs-attr">name:</span> <span class="hljs-string">test-gpu</span>
-  <span class="hljs-attr">labels:</span>
-    <span class="hljs-attr">app:</span> <span class="hljs-string">gpu</span>
-<span class="hljs-attr">spec:</span>
-  <span class="hljs-attr">replicas:</span> <span class="hljs-number">1</span>
-  <span class="hljs-attr">selector:</span>
-    <span class="hljs-attr">matchLabels:</span>
-      <span class="hljs-attr">app:</span> <span class="hljs-string">gpu</span>
-  <span class="hljs-attr">template:</span>
-    <span class="hljs-attr">metadata:</span>
-      <span class="hljs-attr">labels:</span>
-        <span class="hljs-attr">app:</span> <span class="hljs-string">gpu</span>
-    <span class="hljs-attr">spec:</span>
-      <span class="hljs-attr">nodeSelector:</span>
-        <span class="hljs-attr">jina.ai/node-type:</span> <span class="hljs-string">gpu</span>
-        <span class="hljs-attr">karpenter.sh/provisioner-name:</span> <span class="hljs-string">gpu</span>
-      <span class="hljs-attr">tolerations:</span>
-      <span class="hljs-bullet">-</span> <span class="hljs-attr">key:</span> <span class="hljs-string">nvidia.com/gpu</span>
-        <span class="hljs-attr">operator:</span> <span class="hljs-string">Exists</span>
-        <span class="hljs-attr">effect:</span> <span class="hljs-string">NoSchedule</span>
-      <span class="hljs-attr">containers:</span>
-      <span class="hljs-bullet">-</span> <span class="hljs-attr">name:</span> <span class="hljs-string">gpu-container</span>
-        <span class="hljs-attr">image:</span> <span class="hljs-string">tensorflow/tensorflow:latest-gpu</span>
-        <span class="hljs-attr">imagePullPolicy:</span> <span class="hljs-string">Always</span>
-        <span class="hljs-attr">command:</span> [<span class="hljs-string">"python"</span>]
-        <span class="hljs-attr">args:</span> [<span class="hljs-string">"-u"</span>, <span class="hljs-string">"-c"</span>, <span class="hljs-string">"import tensorflow"</span>]
-        <span class="hljs-attr">resources:</span>
-          <span class="hljs-attr">limits:</span>
-            <span class="hljs-attr">nvidia.com/gpu:</span> <span class="hljs-number">1</span></code></pre><figcaption>gpu.yml</figcaption></figure><figure class="kg-card kg-code-card"><pre><code class="language-yaml hljs"><span class="hljs-attr">kind:</span> <span class="hljs-string">Deployment</span>
-<span class="hljs-attr">apiVersion:</span> <span class="hljs-string">apps/v1</span>
-<span class="hljs-attr">metadata:</span>
-  <span class="hljs-attr">name:</span> <span class="hljs-string">test-gpu-shared</span>
-  <span class="hljs-attr">labels:</span>
-    <span class="hljs-attr">app:</span> <span class="hljs-string">gpu-shared</span>
-<span class="hljs-attr">spec:</span>
-  <span class="hljs-attr">replicas:</span> <span class="hljs-number">1</span>
-  <span class="hljs-attr">selector:</span>
-    <span class="hljs-attr">matchLabels:</span>
-      <span class="hljs-attr">app:</span> <span class="hljs-string">gpu-shared</span>
-  <span class="hljs-attr">template:</span>
-    <span class="hljs-attr">metadata:</span>
-      <span class="hljs-attr">labels:</span>
-        <span class="hljs-attr">app:</span> <span class="hljs-string">gpu-shared</span>
-    <span class="hljs-attr">spec:</span>
-      <span class="hljs-attr">nodeSelector:</span>
-        <span class="hljs-attr">jina.ai/node-type:</span> <span class="hljs-string">gpu-shared</span>
-        <span class="hljs-attr">karpenter.sh/provisioner-name:</span> <span class="hljs-string">gpu-shared</span>
-      <span class="hljs-attr">tolerations:</span>
-      <span class="hljs-bullet">-</span> <span class="hljs-attr">key:</span> <span class="hljs-string">nvidia.com/gpu-shared</span>
-        <span class="hljs-attr">operator:</span> <span class="hljs-string">Exists</span>
-        <span class="hljs-attr">effect:</span> <span class="hljs-string">NoSchedule</span>
-      <span class="hljs-attr">containers:</span>
-      <span class="hljs-bullet">-</span> <span class="hljs-attr">name:</span> <span class="hljs-string">gpu-container</span>
-        <span class="hljs-attr">image:</span> <span class="hljs-string">tensorflow/tensorflow:latest-gpu</span>
-        <span class="hljs-attr">imagePullPolicy:</span> <span class="hljs-string">Always</span>
-        <span class="hljs-attr">command:</span> [<span class="hljs-string">"python"</span>]
-        <span class="hljs-attr">args:</span> [<span class="hljs-string">"-u"</span>, <span class="hljs-string">"-c"</span>, <span class="hljs-string">"import tensorflow"</span>]
-        <span class="hljs-attr">resources:</span>
-          <span class="hljs-attr">limits:</span>
-            <span class="hljs-attr">nvidia.com/gpu:</span> <span class="hljs-number">1</span></code></pre><figcaption>gpu-shared.yml</figcaption></figure><h3 id="validate-the-results">Validate the results</h3><p>Now, if you deploy both YAML files. You will see two nodes provisioned in AWS console or you can see via use <code>kubectl get nodes — show-labels</code>. 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+</code></pre><h3 id="deploy-user-application">Deploy user application</h3><p>Third, deploy the user application with <em><em>nodeSelector </em></em>and <em><em>toleration.</em></em></p><figure class="kg-card kg-code-card"><pre><code class="language-yaml">kind: Deployment
+apiVersion: apps/v1
+metadata:
+  name: test-gpu
+  labels:
+    app: gpu
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: gpu
+  template:
+    metadata:
+      labels:
+        app: gpu
+    spec:
+      nodeSelector:
+        jina.ai/node-type: gpu
+        karpenter.sh/provisioner-name: gpu
+      tolerations:
+      - key: nvidia.com/gpu
+        operator: Exists
+        effect: NoSchedule
+      containers:
+      - name: gpu-container
+        image: tensorflow/tensorflow:latest-gpu
+        imagePullPolicy: Always
+        command: ["python"]
+        args: ["-u", "-c", "import tensorflow"]
+        resources:
+          limits:
+            nvidia.com/gpu: 1</code></pre><figcaption>gpu.yml</figcaption></figure><figure class="kg-card kg-code-card"><pre><code class="language-yaml">kind: Deployment
+apiVersion: apps/v1
+metadata:
+  name: test-gpu-shared
+  labels:
+    app: gpu-shared
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: gpu-shared
+  template:
+    metadata:
+      labels:
+        app: gpu-shared
+    spec:
+      nodeSelector:
+        jina.ai/node-type: gpu-shared
+        karpenter.sh/provisioner-name: gpu-shared
+      tolerations:
+      - key: nvidia.com/gpu-shared
+        operator: Exists
+        effect: NoSchedule
+      containers:
+      - name: gpu-container
+        image: tensorflow/tensorflow:latest-gpu
+        imagePullPolicy: Always
+        command: ["python"]
+        args: ["-u", "-c", "import tensorflow"]
+        resources:
+          limits:
+            nvidia.com/gpu: 1</code></pre><figcaption>gpu-shared.yml</figcaption></figure><h3 id="validate-the-results">Validate the results</h3><p>Now, if you deploy both YAML files. You will see two nodes provisioned in AWS console or you can see via use <code>kubectl get nodes — show-labels</code>. After the <code>nvidia-k8s-plugin</code> is running in each nodes, you can test in your applications.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://miro.medium.com/max/1400/1*Ei-NPaHXL5TunJuJlcWIQQ.png" class="kg-image" alt="" width="700" height="120"><figcaption>The result showing in the AWS EC2 console</figcaption></figure><p>If you like this article or want to learn more about the architecture behind Jina AI Cloud, make sure to follow us on social channels and subscribe to our blog.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ftime-slicing-gpus-with-karpenter%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Traditional Prompt Engineering Is Dead. PromptPerfect is What Comes Next</title><meta charset="utf-8"><meta name="title" content="Traditional Prompt Engineering Is Dead. PromptPerfect is What Comes Next"><meta name="description" content="AI is coming to replace even the prompt engineers. Use PromptPerfect to stay ahead of the crowd and optimize your prompts for LLMs and image generation"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/traditional-prompt-engineering-is-dead-heres-what-comes-next"><meta property="og:title" content="Traditional Prompt Engineering Is Dead. PromptPerfect is What Comes Next"><meta property="og:description" content="AI is coming to replace even the prompt engineers. Use PromptPerfect to stay ahead of the crowd and optimize your prompts for LLMs and image generation"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Blog-images--8-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/traditional-prompt-engineering-is-dead-heres-what-comes-next"><meta property="twitter:title" content="Traditional Prompt Engineering Is Dead. PromptPerfect is What Comes Next"><meta property="twitter:description" content="AI is coming to replace even the prompt engineers. Use PromptPerfect to stay ahead of the crowd and optimize your prompts for LLMs and image generation"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Blog-images--8-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Traditional Prompt Engineering Is Dead. PromptPerfect is What Comes Next</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">AI is coming to replace even the prompt engineers. Use PromptPerfect to stay ahead of the crowd and optimize your prompts for LLMs and image generation</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 15, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Reading the news (well, watching YouTube since I'm lazy) is so much <em>fun</em> these days, and not at all repetitive in any way:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.78218 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1.png" width="720" height="404" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1.png 720w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.78218 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/2-1.png" width="720" height="404" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/2-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/2-1.png 720w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.78218 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/3-1.png" width="720" height="404" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/3-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/3-1.png 720w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>I'm trying to sense a pattern here. I'm sure it'll come to me</figcaption></figure><p>Oh yeah, <a href="https://spectrum.ieee.org/in-1930-robots-were-stealing-musicians-jobs?ref=jina-ai-gmbh.ghost.io">machines are dooming music</a> too.</p><p>However, if you're reading this, you're probably already in the AI space, working with the very tools that will end the world and keep humanity as either pets or slaves. Or both.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://www.smbc-comics.com/comic/dance-2?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image.png" class="kg-image" alt="" width="684" height="883" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image.png 684w"></a><figcaption>Via <a href="https://www.smbc-comics.com/comic/dance-2?ref=jina-ai-gmbh.ghost.io">SMBC</a></figcaption></figure><p>But not you, of course. You're one of the <em>prompt engineers</em>, that elite breed of cool hacker types who are the machine whisperers. Your job won't be in jeopardy, right?</p><p>...right?</p><p>Guess again, sunshine. New tools are coming along that automate prompt engineering itself. Imagine prompts creating prompts creating prompts. And in a world that creates its <em>own</em> prompts, guess who isn't so invaluable anymore?</p><figure class="kg-card kg-image-card"><a href="https://twitter.com/Cavalorn/status/654934442549620736?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-7.png" class="kg-image" alt="" width="610" height="183" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image-7.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-7.png 610w"></a></figure><p>What does this mean for prompt engineers? It means things are going to change, and change fast. In some ways for the better, in some ways for the rockier. Rockier, that is, if you don't keep up.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.78218 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1.jpg" width="720" height="404" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1.jpg 720w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.78218 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/2.png" width="720" height="404" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/2.png 720w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.78218 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/3.png" width="720" height="404" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/3.png 720w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Won't someone think of the poor bearded white male YouTube AI influencers? Sending my thoughts and prayers (written by a white male bearded guy)</figcaption></figure><h2 id="a-bit-of-context">A bit of context</h2><p>Think about "traditional" prompt engineering (you know, like your father and grandfather before him used to do in the prompt mines).</p><p>You use the <a href="https://platform.openai.com/playground?ref=jina-ai-gmbh.ghost.io">GPT playground</a>, fiddle with some parameters, plug in your prompt and hope for the best. If that doesn't work, you re-word the prompt and try again. Lather, rinse, repeat. Finally, you get something that'll do the job, at least well <em>enough</em>.</p><p>That works, technically, but it's slow and frustrating. There's a lot of guessing, praying to whatever gods reside within the machine, and pulling out of hair in frustration.</p><p>What if there was a new way? A better way? A more <em>perfect</em> way?</p><p>As you may have guessed, that's where PromptPerfect comes in.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection with AI Prompt Engineering</div><div class="kg-bookmark-description">Optimize prompts for GPT-4, ChatGPT, StableLM, Claude, MidJourney, DALL-E, StableDiffusion, Kandinsky, and Lexica. Experience automatic prompt engineering done right. Create compelling Text and Image prompts today with our AI prompt generator.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><p>PromptPerfect lets you optimize and streamline prompts, create templates, reverse engineer prompts from images, validate with multiple models, and more. It all comes wrapped in a nifty web interface, or via an API if you're in the mood for bulk processing.</p><p>What's more, it goes beyond just prompts for text generation, allowing prompts for <a href="https://stability.ai/blog/stable-diffusion-public-release?ref=jina-ai-gmbh.ghost.io">Stable Diffusion</a>, <a href="midjourney.com/">Midjourney</a>, and other image generation services.</p><p>If you think of <strong>prompts as the API for LLMs and image generators</strong>, then <strong>PromptPerfect is the IDE for prompts</strong>.</p><h2 id="prompts-as-the-api-for-llms">Prompts as the API for LLMs</h2><p>Typically an API looks like a bunch of methods that you use to talk to a service. But in LLMs, you communicate with the API via natural language:</p><ul><li>Prompt for translation: <code>Translate the following English sentence into French: 'Hello, how are you?'</code></li><li>Prompt for summarization: <code>Summarize the given article on renewable energy in 3-4 sentences.</code></li><li>Prompt for creative writing: <code>Write a poem about the beauty of nature.</code></li><li>Prompt for mathematical computation: <code>Calculate the square root of 625.</code></li><li>Prompt for factual question answering: <code>What is the capital of Australia?</code></li><li>Prompt for idea generation: <code>Generate a list of 10 potential interview questions for a software engineer role.</code></li><li>Prompt for writing a specific type of text (email): <code>Compose an email to invite colleagues for a team-building event next week.</code></li><li>Prompt for recipe suggestion: <code>Suggest a recipe for a vegetarian lasagna.</code></li><li>Prompt for procedural guidance: <code>Provide step-by-step instructions on how to change a flat tire.</code></li><li>Prompt for generating humorous content: <code>Tell me a joke.</code></li></ul><h2 id="types-of-prompts">Types of prompts</h2><p>Prompting has evolved a long way from <code>tell me a story of when harry and draco fell in love</code>. Let's look at a few different types of prompts.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">You can try these out with different models on <a href="https://promptperfect.jina.ai/arena?ref=jina-ai-gmbh.ghost.io">PromptPerfect Arena</a></div></div><h3 id="zero-shot-prompts">Zero-shot prompts</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-1.png" class="kg-image" alt="" width="2000" height="282" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/image-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/image-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-1.png 2048w" sizes="(min-width: 720px) 720px"></figure><p>Very simple prompts: For example, getting simple sentiment analysis for a single string without providing any context.</p><p>In short, you provide a <code>{test}</code> (namely <code>Oh great, another meeting...</code>) and the label for the thing you want. We can represent this concept as:</p><pre><code class="hljs language-bash">{<span class="hljs-built_in">test</span>}</code></pre><h3 id="few-shot-prompts">Few-shot prompts</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-2.png" class="kg-image" alt="" width="2000" height="448" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/image-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-2.png 2048w" sizes="(min-width: 720px) 720px"></figure><p>Few-shot prompts present the LLM with several high-quality demonstrations, each consisting of both input and desired output, on the target task. As the model first sees good examples, it can better understand human intention and criteria for what kinds of answers are wanted. Therefore, few-shot learning often leads to better performance than zero-shot.</p><p>You can think of this as:</p><pre><code class="hljs language-bash">{
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Traditional Prompt Engineering Is Dead. PromptPerfect is What Comes Next</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">AI is coming to replace even the prompt engineers. Use PromptPerfect to stay ahead of the crowd and optimize your prompts for LLMs and image generation</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 15, 2023 • 8 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Reading the news (well, watching YouTube since I'm lazy) is so much <em>fun</em> these days, and not at all repetitive in any way:</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.78218 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1.png" width="720" height="404" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1.png 720w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.78218 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/2-1.png" width="720" height="404" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/2-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/2-1.png 720w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.78218 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/3-1.png" width="720" height="404" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/3-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/3-1.png 720w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>I'm trying to sense a pattern here. I'm sure it'll come to me</figcaption></figure><p>Oh yeah, <a href="https://spectrum.ieee.org/in-1930-robots-were-stealing-musicians-jobs?ref=jina-ai-gmbh.ghost.io">machines are dooming music</a> too.</p><p>However, if you're reading this, you're probably already in the AI space, working with the very tools that will end the world and keep humanity as either pets or slaves. Or both.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://www.smbc-comics.com/comic/dance-2?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image.png" class="kg-image" alt="" width="684" height="883" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image.png 684w"></a><figcaption>Via <a href="https://www.smbc-comics.com/comic/dance-2?ref=jina-ai-gmbh.ghost.io">SMBC</a></figcaption></figure><p>But not you, of course. You're one of the <em>prompt engineers</em>, that elite breed of cool hacker types who are the machine whisperers. Your job won't be in jeopardy, right?</p><p>...right?</p><p>Guess again, sunshine. New tools are coming along that automate prompt engineering itself. Imagine prompts creating prompts creating prompts. And in a world that creates its <em>own</em> prompts, guess who isn't so invaluable anymore?</p><figure class="kg-card kg-image-card"><a href="https://twitter.com/Cavalorn/status/654934442549620736?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-7.png" class="kg-image" alt="" width="610" height="183" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image-7.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-7.png 610w"></a></figure><p>What does this mean for prompt engineers? It means things are going to change, and change fast. In some ways for the better, in some ways for the rockier. Rockier, that is, if you don't keep up.</p><figure class="kg-card kg-gallery-card kg-width-wide kg-card-hascaption"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image" style="flex: 1.78218 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/1.jpg" width="720" height="404" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/1.jpg 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/1.jpg 720w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.78218 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/2.png" width="720" height="404" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/2.png 720w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image" style="flex: 1.78218 1 0%;"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/3.png" width="720" height="404" alt="" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/3.png 720w" sizes="(min-width: 720px) 720px"></div></div></div><figcaption>Won't someone think of the poor bearded white male YouTube AI influencers? Sending my thoughts and prayers (written by a white male bearded guy)</figcaption></figure><h2 id="a-bit-of-context">A bit of context</h2><p>Think about "traditional" prompt engineering (you know, like your father and grandfather before him used to do in the prompt mines).</p><p>You use the <a href="https://platform.openai.com/playground?ref=jina-ai-gmbh.ghost.io">GPT playground</a>, fiddle with some parameters, plug in your prompt and hope for the best. If that doesn't work, you re-word the prompt and try again. Lather, rinse, repeat. Finally, you get something that'll do the job, at least well <em>enough</em>.</p><p>That works, technically, but it's slow and frustrating. There's a lot of guessing, praying to whatever gods reside within the machine, and pulling out of hair in frustration.</p><p>What if there was a new way? A better way? A more <em>perfect</em> way?</p><p>As you may have guessed, that's where PromptPerfect comes in.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection with AI Prompt Engineering</div><div class="kg-bookmark-description">Optimize prompts for GPT-4, ChatGPT, StableLM, Claude, MidJourney, DALL-E, StableDiffusion, Kandinsky, and Lexica. Experience automatic prompt engineering done right. Create compelling Text and Image prompts today with our AI prompt generator.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><p>PromptPerfect lets you optimize and streamline prompts, create templates, reverse engineer prompts from images, validate with multiple models, and more. It all comes wrapped in a nifty web interface, or via an API if you're in the mood for bulk processing.</p><p>What's more, it goes beyond just prompts for text generation, allowing prompts for <a href="https://stability.ai/blog/stable-diffusion-public-release?ref=jina-ai-gmbh.ghost.io">Stable Diffusion</a>, <a href="midjourney.com/">Midjourney</a>, and other image generation services.</p><p>If you think of <strong>prompts as the API for LLMs and image generators</strong>, then <strong>PromptPerfect is the IDE for prompts</strong>.</p><h2 id="prompts-as-the-api-for-llms">Prompts as the API for LLMs</h2><p>Typically an API looks like a bunch of methods that you use to talk to a service. But in LLMs, you communicate with the API via natural language:</p><ul><li>Prompt for translation: <code>Translate the following English sentence into French: 'Hello, how are you?'</code></li><li>Prompt for summarization: <code>Summarize the given article on renewable energy in 3-4 sentences.</code></li><li>Prompt for creative writing: <code>Write a poem about the beauty of nature.</code></li><li>Prompt for mathematical computation: <code>Calculate the square root of 625.</code></li><li>Prompt for factual question answering: <code>What is the capital of Australia?</code></li><li>Prompt for idea generation: <code>Generate a list of 10 potential interview questions for a software engineer role.</code></li><li>Prompt for writing a specific type of text (email): <code>Compose an email to invite colleagues for a team-building event next week.</code></li><li>Prompt for recipe suggestion: <code>Suggest a recipe for a vegetarian lasagna.</code></li><li>Prompt for procedural guidance: <code>Provide step-by-step instructions on how to change a flat tire.</code></li><li>Prompt for generating humorous content: <code>Tell me a joke.</code></li></ul><h2 id="types-of-prompts">Types of prompts</h2><p>Prompting has evolved a long way from <code>tell me a story of when harry and draco fell in love</code>. Let's look at a few different types of prompts.</p><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">You can try these out with different models on <a href="https://promptperfect.jina.ai/arena?ref=jina-ai-gmbh.ghost.io">PromptPerfect Arena</a></div></div><h3 id="zero-shot-prompts">Zero-shot prompts</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-1.png" class="kg-image" alt="" width="2000" height="282" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/image-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/image-1.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-1.png 2048w" sizes="(min-width: 720px) 720px"></figure><p>Very simple prompts: For example, getting simple sentiment analysis for a single string without providing any context.</p><p>In short, you provide a <code>{test}</code> (namely <code>Oh great, another meeting...</code>) and the label for the thing you want. We can represent this concept as:</p><pre><code class="hljs language-bash">{<span class="hljs-built_in">test</span>}</code></pre><h3 id="few-shot-prompts">Few-shot prompts</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-2.png" class="kg-image" alt="" width="2000" height="448" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/image-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-2.png 2048w" sizes="(min-width: 720px) 720px"></figure><p>Few-shot prompts present the LLM with several high-quality demonstrations, each consisting of both input and desired output, on the target task. As the model first sees good examples, it can better understand human intention and criteria for what kinds of answers are wanted. Therefore, few-shot learning often leads to better performance than zero-shot.</p><p>You can think of this as:</p><pre><code class="hljs language-bash">{
     [training...]
     <span class="hljs-built_in">test</span>
 }</code></pre><p>Some things to bear in mind:</p><ul><li>Output labels are wide open, not limited to just a subset that you want to work with.</li><li>There's more token consumption, so you may hit the context length limit when input and output text are long.</li><li>This kind of prompt can lead to dramatically different performance, from near random guesses to near state-of-the-art. This depends on choice of prompt format, training examples, and the order of those examples.</li></ul><h3 id="instruction-prompts">Instruction prompts</h3><p>Instruction prompts take the zero- or few-shot examples and prepend an instructional prompt to give more fine-grained directions. These can be zero-shot:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-3.png" class="kg-image" alt="" width="2000" height="383" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image-3.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/06/image-3.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/06/image-3.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-3.png 2048w" sizes="(min-width: 720px) 720px"></figure><pre><code class="hljs language-bash">{
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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Training Smarter, Not Harder: Slimming Down Sentence Embeddings</title><meta charset="utf-8"><meta name="title" content="Training Smarter, Not Harder: Slimming Down Sentence Embeddings"><meta name="description" content="Jina AI trains top-tier sentence embeddings with 20% of the data. How? Maniacal filtering and shrewd sampling unmask the waste in Big Tech's data-hungry doctrine. Our streamlined embeddings rival titans' with meticulous curation, not mindless consumption. Technical ingenuity, not gluttony."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/training-smarter-not-harder-slimming-sentence-embeddings"><meta property="og:title" content="Training Smarter, Not Harder: Slimming Down Sentence Embeddings"><meta property="og:description" content="Jina AI trains top-tier sentence embeddings with 20% of the data. How? Maniacal filtering and shrewd sampling unmask the waste in Big Tech's data-hungry doctrine. Our streamlined embeddings rival titans' with meticulous curation, not mindless consumption. Technical ingenuity, not gluttony."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_square_with_lines_of_different_colors_in_the_s_dc0a8d95-4da3-42db-8ae1-6ed43cc17ad9.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/training-smarter-not-harder-slimming-sentence-embeddings"><meta property="twitter:title" content="Training Smarter, Not Harder: Slimming Down Sentence Embeddings"><meta property="twitter:description" content="Jina AI trains top-tier sentence embeddings with 20% of the data. How? Maniacal filtering and shrewd sampling unmask the waste in Big Tech's data-hungry doctrine. Our streamlined embeddings rival titans' with meticulous curation, not mindless consumption. Technical ingenuity, not gluttony."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_square_with_lines_of_different_colors_in_the_s_dc0a8d95-4da3-42db-8ae1-6ed43cc17ad9.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Training Smarter, Not Harder: Slimming Down Sentence Embeddings</title><meta charset="utf-8"><meta name="title" content="Training Smarter, Not Harder: Slimming Down Sentence Embeddings"><meta name="description" content="Jina AI trains top-tier sentence embeddings with 20% of the data. How? Maniacal filtering and shrewd sampling unmask the waste in Big Tech's data-hungry doctrine. Our streamlined embeddings rival titans' with meticulous curation, not mindless consumption. Technical ingenuity, not gluttony."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/training-smarter-not-harder-slimming-sentence-embeddings"><meta property="og:title" content="Training Smarter, Not Harder: Slimming Down Sentence Embeddings"><meta property="og:description" content="Jina AI trains top-tier sentence embeddings with 20% of the data. How? Maniacal filtering and shrewd sampling unmask the waste in Big Tech's data-hungry doctrine. Our streamlined embeddings rival titans' with meticulous curation, not mindless consumption. Technical ingenuity, not gluttony."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_square_with_lines_of_different_colors_in_the_s_dc0a8d95-4da3-42db-8ae1-6ed43cc17ad9.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/training-smarter-not-harder-slimming-sentence-embeddings"><meta property="twitter:title" content="Training Smarter, Not Harder: Slimming Down Sentence Embeddings"><meta property="twitter:description" content="Jina AI trains top-tier sentence embeddings with 20% of the data. How? Maniacal filtering and shrewd sampling unmask the waste in Big Tech's data-hungry doctrine. Our streamlined embeddings rival titans' with meticulous curation, not mindless consumption. Technical ingenuity, not gluttony."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_a_square_with_lines_of_different_colors_in_the_s_dc0a8d95-4da3-42db-8ae1-6ed43cc17ad9.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Training Smarter, Not Harder: Slimming Down Sentence Embeddings</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI trains top-tier sentence embeddings with 20% of the data. How? Maniacal filtering and shrewd sampling unmask the waste in Big Tech's data-hungry doctrine. Our streamlined embeddings rival titans' with meticulous curation, not mindless consumption. Technical ingenuity, not gluttony.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 23, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>At Jina AI, sentence embedding models are a critical component of many natural language processing and multimodal AI systems we develop. By encoding semantic information into vector representations, these models equip systems to assess similarity, retrieve relevant passages, and even generate embeddings tailored to specific downstream tasks.</p><p>However, a lingering concern around sentence embedding models has been their immense appetite for training data. Models like <a href="https://arxiv.org/abs/1908.10084?ref=jina-ai-gmbh.ghost.io">Sentence-BERT</a> and <a href="https://arxiv.org/abs/2104.08821?ref=jina-ai-gmbh.ghost.io">Sentence-T5</a> are trained on billions of sentence pairs, demanding substantial computational resources. This causes both financial and environmental strains that limit access and adoption of these models.</p><p>In our new paper, we demonstrate that with careful data filtering and training methodology, compelling sentence embeddings can be attained using far less data than previously assumed. Our newly developed <strong><code>JINA EMBEDDINGS</code></strong> models deliver performance rivaling state-of-the-art models while reducing training samples by over 80%.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2307.11224?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models</div><div class="kg-bookmark-description">Jina Embeddings constitutes a set of high-performance sentence embeddingmodels adept at translating various textual inputs into numericalrepresentations, thereby capturing the semantic essence of the text. The modelsexcel in applications such as dense retrieval and semantic textual similarity.Th…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Michael Günther</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/jinaai?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">jinaai (Jina AI)</div><div class="kg-bookmark-description">machine-learning, deep-learning, semantic-search, creative-ai, multimodal machine-learning, neural-search, vector-search, crossmodal machine-learning</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/jinaai.png" alt=""></div></a></figure><h2 id="the-power-of-preprocessing">The Power of Preprocessing</h2><p>Many datasets for training sentence embedding models contain duplicates, non-English samples, and low-quality pairs with minimal semantic similarity. By meticulously removing such cases, we condensed our initial dataset from 1.5 billion pairs down to a refined 385 million high-quality samples.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-7.png" class="kg-image" alt="" width="1408" height="510" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-7.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-7.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-7.png 1408w" sizes="(min-width: 720px) 720px"><figcaption>The composition of 385 million pairwise data</figcaption></figure><p>We applied a multi-step filtering process encompassing:</p><ul><li><strong>De-duplication</strong>: Removing duplicate entries.</li><li><strong>Language filtering</strong>: Eliminating non-English sentences.</li><li><strong>Consistency filtering</strong>: Excluding pairs with low embedding similarity based on an auxiliary model. This screened out 84.3% of the Reddit dataset.</li></ul><p>An ablation study on the impact of these steps showed consistency filtering, in particular, gave significant gains on retrieval tasks. This indicates that training on a smaller set of truly relevant pairs trumps indiscriminate exposure to billions of noisy examples.</p><h2 id="shrewd-sampling-during-training">Shrewd Sampling During Training</h2><p>In addition to filtering the data itself, we employed smart sampling strategies when creating training batches. Our parallelized approach trains on all datasets simultaneously, but ensures each batch contains examples from just one dataset.</p><p>The sampling rates for drawing datasets are weighted based on their relative sizes and quality. This prevents overfitting on smaller datasets while ensuring sufficient exposure to key high-value datasets.</p><p>Together with filtering, the weighted sampling reduces the actual number of training pairs encountered to only 180 million. This frugal fine-tuning strategy departs drastically from the data-hungry doctrines of Big Tech.</p><h2 id="triplet-training-targets-specificity">Triplet Training Targets Specificity</h2><p>After pre-training on paired data, we incorporate a triplet training phase using smaller datasets. Here, each sample contains a query, positive match, and negative match. The model learns to embed the query closer to the positive than the negative.</p><p>This second stage exposes models to hard negatives, making embeddings more discriminative. It also incorporates custom negation data to help distinguish contradictory statements. Our jina-large-v1 model saw accuracy on hard negations improve from 16.6% to 65.4% after this triplet training.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-8.png" class="kg-image" alt="" width="1296" height="610" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-8.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-8.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-8.png 1296w" sizes="(min-width: 720px) 720px"></figure><p>Adding triplet training atop strong pre-training on filtered pairs gives embeddings with strong generalizability <em>and</em> fine-grained specificity.</p><h2 id="proof-is-in-the-benchmarks">Proof is in the Benchmarks</h2><p>We benchmarked our <strong><code>JINA EMBEDDINGS</code></strong> against models like Sentence-T5 and competitors on established datasets including MTEB and BEIR.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-9.png" class="kg-image" alt="" width="760" height="712" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-9.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-9.png 760w" sizes="(min-width: 720px) 720px"></figure><p>Remarkably, our 110 million parameter <strong>jina-base-v1</strong> model matched or exceeded the performance of the 330 million parameter <strong>sentence-t5-large</strong> on numerous retrieval and reranking tasks. Even the small 35 million parameter <strong>jina-small-v1</strong> showed competitive scores, demonstrating the data and training efficiencies unlock smaller yet powerful models.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-10.png" class="kg-image" alt="" width="1842" height="520" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-10.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-10.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-10.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-10.png 1842w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/spaces/mteb/leaderboard?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">MTEB Leaderboard - a Hugging Face Space by mteb</div><div class="kg-bookmark-description">Discover amazing ML apps made by the community</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""><span class="kg-bookmark-author">a Hugging Face Space by mteb</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/spaces/mteb/leaderboard.png" alt=""></div></a></figure><h2 id="the-bigger-picture">The Bigger Picture</h2><p>With meticulous data curation and an inventive training approach, we push state-of-the-art sentence embedding performance while slashing the data demand by over 80%. This carries profound implications:</p><ul><li><strong>Reduced resources:</strong> Lower data requirements cut computing infrastructure and energy needs for training.</li><li><strong>Increased accessibility:</strong> Efficient data usage unlocks performant small models, expanding access for organizations without massive compute budgets.</li><li><strong>Responsible AI:</strong> Judicious data usage and smaller models align with principles of responsible AI by limiting wasteful resource consumption.</li></ul><p>Our work signifies masterful model development need not equate to mindless data consumption. 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We'll show you how to get up and running right now.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 12 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/4.jpg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="7901f38e-f560-460f-a4e9-2049a5278f2e" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="7901f38e-f560-460f-a4e9-2049a5278f2e" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Executor Hub</div><div class="q-item__label q-item__label--caption text-caption">Share and discover building blocks for multimodal AI applications</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dalle-flow"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dall-e-flow.ea199b2d.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Training Smarter, Not Harder: Slimming Down Sentence Embeddings</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Jina AI trains top-tier sentence embeddings with 20% of the data. How? Maniacal filtering and shrewd sampling unmask the waste in Big Tech's data-hungry doctrine. Our streamlined embeddings rival titans' with meticulous curation, not mindless consumption. Technical ingenuity, not gluttony.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 23, 2023 • 4 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>At Jina AI, sentence embedding models are a critical component of many natural language processing and multimodal AI systems we develop. By encoding semantic information into vector representations, these models equip systems to assess similarity, retrieve relevant passages, and even generate embeddings tailored to specific downstream tasks.</p><p>However, a lingering concern around sentence embedding models has been their immense appetite for training data. Models like <a href="https://arxiv.org/abs/1908.10084?ref=jina-ai-gmbh.ghost.io">Sentence-BERT</a> and <a href="https://arxiv.org/abs/2104.08821?ref=jina-ai-gmbh.ghost.io">Sentence-T5</a> are trained on billions of sentence pairs, demanding substantial computational resources. This causes both financial and environmental strains that limit access and adoption of these models.</p><p>In our new paper, we demonstrate that with careful data filtering and training methodology, compelling sentence embeddings can be attained using far less data than previously assumed. Our newly developed <strong><code>JINA EMBEDDINGS</code></strong> models deliver performance rivaling state-of-the-art models while reducing training samples by over 80%.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://arxiv.org/abs/2307.11224?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models</div><div class="kg-bookmark-description">Jina Embeddings constitutes a set of high-performance sentence embeddingmodels adept at translating various textual inputs into numericalrepresentations, thereby capturing the semantic essence of the text. The modelsexcel in applications such as dense retrieval and semantic textual similarity.Th…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://static.arxiv.org/static/browse/0.3.4/images/icons/apple-touch-icon.png" alt=""><span class="kg-bookmark-author">arXiv.org</span><span class="kg-bookmark-publisher">Michael Günther</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/jinaai?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">jinaai (Jina AI)</div><div class="kg-bookmark-description">machine-learning, deep-learning, semantic-search, creative-ai, multimodal machine-learning, neural-search, vector-search, crossmodal machine-learning</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/jinaai.png" alt=""></div></a></figure><h2 id="the-power-of-preprocessing">The Power of Preprocessing</h2><p>Many datasets for training sentence embedding models contain duplicates, non-English samples, and low-quality pairs with minimal semantic similarity. By meticulously removing such cases, we condensed our initial dataset from 1.5 billion pairs down to a refined 385 million high-quality samples.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-7.png" class="kg-image" alt="" width="1408" height="510" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-7.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-7.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-7.png 1408w" sizes="(min-width: 720px) 720px"><figcaption>The composition of 385 million pairwise data</figcaption></figure><p>We applied a multi-step filtering process encompassing:</p><ul><li><strong>De-duplication</strong>: Removing duplicate entries.</li><li><strong>Language filtering</strong>: Eliminating non-English sentences.</li><li><strong>Consistency filtering</strong>: Excluding pairs with low embedding similarity based on an auxiliary model. This screened out 84.3% of the Reddit dataset.</li></ul><p>An ablation study on the impact of these steps showed consistency filtering, in particular, gave significant gains on retrieval tasks. This indicates that training on a smaller set of truly relevant pairs trumps indiscriminate exposure to billions of noisy examples.</p><h2 id="shrewd-sampling-during-training">Shrewd Sampling During Training</h2><p>In addition to filtering the data itself, we employed smart sampling strategies when creating training batches. Our parallelized approach trains on all datasets simultaneously, but ensures each batch contains examples from just one dataset.</p><p>The sampling rates for drawing datasets are weighted based on their relative sizes and quality. This prevents overfitting on smaller datasets while ensuring sufficient exposure to key high-value datasets.</p><p>Together with filtering, the weighted sampling reduces the actual number of training pairs encountered to only 180 million. This frugal fine-tuning strategy departs drastically from the data-hungry doctrines of Big Tech.</p><h2 id="triplet-training-targets-specificity">Triplet Training Targets Specificity</h2><p>After pre-training on paired data, we incorporate a triplet training phase using smaller datasets. Here, each sample contains a query, positive match, and negative match. The model learns to embed the query closer to the positive than the negative.</p><p>This second stage exposes models to hard negatives, making embeddings more discriminative. It also incorporates custom negation data to help distinguish contradictory statements. Our jina-large-v1 model saw accuracy on hard negations improve from 16.6% to 65.4% after this triplet training.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-8.png" class="kg-image" alt="" width="1296" height="610" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-8.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-8.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-8.png 1296w" sizes="(min-width: 720px) 720px"></figure><p>Adding triplet training atop strong pre-training on filtered pairs gives embeddings with strong generalizability <em>and</em> fine-grained specificity.</p><h2 id="proof-is-in-the-benchmarks">Proof is in the Benchmarks</h2><p>We benchmarked our <strong><code>JINA EMBEDDINGS</code></strong> against models like Sentence-T5 and competitors on established datasets including MTEB and BEIR.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-9.png" class="kg-image" alt="" width="760" height="712" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-9.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-9.png 760w" sizes="(min-width: 720px) 720px"></figure><p>Remarkably, our 110 million parameter <strong>jina-base-v1</strong> model matched or exceeded the performance of the 330 million parameter <strong>sentence-t5-large</strong> on numerous retrieval and reranking tasks. Even the small 35 million parameter <strong>jina-small-v1</strong> showed competitive scores, demonstrating the data and training efficiencies unlock smaller yet powerful models.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-10.png" class="kg-image" alt="" width="1842" height="520" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-10.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-10.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2023/08/image-10.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-10.png 1842w" sizes="(min-width: 720px) 720px"></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://huggingface.co/spaces/mteb/leaderboard?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">MTEB Leaderboard - a Hugging Face Space by mteb</div><div class="kg-bookmark-description">Discover amazing ML apps made by the community</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://huggingface.co/favicon.ico" alt=""><span class="kg-bookmark-author">a Hugging Face Space by mteb</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://cdn-thumbnails.huggingface.co/social-thumbnails/spaces/mteb/leaderboard.png" alt=""></div></a></figure><h2 id="the-bigger-picture">The Bigger Picture</h2><p>With meticulous data curation and an inventive training approach, we push state-of-the-art sentence embedding performance while slashing the data demand by over 80%. This carries profound implications:</p><ul><li><strong>Reduced resources:</strong> Lower data requirements cut computing infrastructure and energy needs for training.</li><li><strong>Increased accessibility:</strong> Efficient data usage unlocks performant small models, expanding access for organizations without massive compute budgets.</li><li><strong>Responsible AI:</strong> Judicious data usage and smaller models align with principles of responsible AI by limiting wasteful resource consumption.</li></ul><p>Our work signifies masterful model development need not equate to mindless data consumption. Our technical ingenuity in creating the <code>JINA EMBEDDINGS</code> sets an important precedent - great NLP results can be achieved while exercising data frugality.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><i class="q-icon notranslate material-icons q-chip__icon q-chip__icon--left" aria-hidden="true" role="presentation">star</i><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Featured</div></div></div><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Ftraining-smarter-not-harder-slimming-sentence-embeddings%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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diff --git a/news/turbocharge-your-ai-with-finetuner/index.html b/news/turbocharge-your-ai-with-finetuner/index.html
index 83a9a51c5c9..18411ed64ed 100644
--- a/news/turbocharge-your-ai-with-finetuner/index.html
+++ b/news/turbocharge-your-ai-with-finetuner/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Turbocharge Your AI with Finetuner+</title><meta charset="utf-8"><meta name="title" content="Turbocharge Your AI with Finetuner+"><meta name="description" content="Finetuner+ is an on-prem finetuning solution that leverages state-of-the-art features of Finetuner, without the need for clients to implement it themselves."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/turbocharge-your-ai-with-finetuner"><meta property="og:title" content="Turbocharge Your AI with Finetuner+"><meta property="og:description" content="Finetuner+ is an on-prem finetuning solution that leverages state-of-the-art features of Finetuner, without the need for clients to implement it themselves."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Blog-images--5-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/turbocharge-your-ai-with-finetuner"><meta property="twitter:title" content="Turbocharge Your AI with Finetuner+"><meta property="twitter:description" content="Finetuner+ is an on-prem finetuning solution that leverages state-of-the-art features of Finetuner, without the need for clients to implement it themselves."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Blog-images--5-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Turbocharge Your AI with Finetuner+</title><meta charset="utf-8"><meta name="title" content="Turbocharge Your AI with Finetuner+"><meta name="description" content="Finetuner+ is an on-prem finetuning solution that leverages state-of-the-art features of Finetuner, without the need for clients to implement it themselves."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/turbocharge-your-ai-with-finetuner"><meta property="og:title" content="Turbocharge Your AI with Finetuner+"><meta property="og:description" content="Finetuner+ is an on-prem finetuning solution that leverages state-of-the-art features of Finetuner, without the need for clients to implement it themselves."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Blog-images--5-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/turbocharge-your-ai-with-finetuner"><meta property="twitter:title" content="Turbocharge Your AI with Finetuner+"><meta property="twitter:description" content="Finetuner+ is an on-prem finetuning solution that leverages state-of-the-art features of Finetuner, without the need for clients to implement it themselves."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/04/Blog-images--5-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><script src="https://jina-ai-gmbh.ghost.io/public/cards.min.js" async=""></script><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Turbocharge Your AI with Finetuner+</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner+ is an on-prem finetuning solution that leverages state-of-the-art features of Finetuner, without the need for clients to implement it themselves.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 11, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="unlock-the-full-potential-of-ai-optimization-without-the-hassle">Unlock the full potential of AI optimization without the hassle</h2><p>At Jina AI, we've previously discussed the significant benefits that businesses can gain from finetuning their AI models.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/fine-tuning-with-low-budget-and-high-expectations/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Fine-tuning with Low Budget and High Expectations</div><div class="kg-bookmark-description">Fine-tuning is highly effective, economical, and eco-friendly; or at least that’s what all the deep learning tweets will tell you. Exactly how much data &amp; time do you need to get a good result?</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--53-.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/improving-search-quality-non-english-queries-fine-tuned-multilingual-clip-models/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models</div><div class="kg-bookmark-description">Having trouble with non-English search queries? Fine-tuning your multilingual CLIP models may be the answer. In this post, we’ll show you how Finetuner can be used on multilingual CLIP to improve search quality and give you better results.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--63-.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/applying-jina-ai-finetuner-to-clip-less-data-smaller-models-higher-performance/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">How Much Do We Get by Finetuning CLIP?</div><div class="kg-bookmark-description">Jina AI Finetuner can bring performance improvements of up to 63% to pre-trained CLIP models. Here is how we did that.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--12-.png" alt=""></div></a></figure><p>A well-finetuned model can enhance performance, improve efficiency, and drive innovation. However, we understand that finetuning a model properly is a complex process that requires a high level of expertise. To address this challenge and make finetuning more accessible to businesses, we are excited to introduce Finetuner+ – an on-premise finetuning solution that leverages all the state-of-the-art features of Finetuner without the need for clients to implement it themselves.</p><p><strong><a href="https://finetunerplus.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner+</a></strong> is designed to empower businesses by optimizing their AI capabilities with customized, secure, and efficient finetuning solutions. Our expert engineers handle the entire finetuning process, from understanding your unique requirements and goals to delivering a finetuned AI model that adheres to the highest security standards. With Finetuner+, you can harness the power of Jina AI's proven finetuning methodologies without requiring in-house expertise or complex implementation.</p><h2 id="key-benefits-of-finetuner">Key benefits of Finetuner+</h2><ol><li><strong>Access to Jina AI's expertise</strong>: With Finetuner+, you benefit from Jina AI's extensive knowledge and experience in AI model finetuning. Our team of experts ensures that your AI models are finetuned using the latest methodologies and best practices.</li><li><strong>Customized solutions</strong>: Finetuner+ tailors the finetuning process to your specific needs, industry requirements, and business objectives. This personalized approach ensures that your finetuned AI model delivers maximum value and performance.</li><li><strong>Security and compliance</strong>: Finetuner+ prioritizes data privacy and security, adhering to industry-specific regulations and best practices. You can trust that your finetuned AI models will be secure and compliant with the necessary standards.</li><li><strong>Cost-effective approach</strong>: Finetuner+ offers a cost-effective alternative to hiring or training specialized AI teams or implementing finetuning solutions in-house. By partnering with Finetuner+, businesses can access cutting-edge AI expertise and solutions without the high costs associated with in-house development.</li><li><strong>Seamless integration</strong>: The Finetuner+ team works closely with clients to ensure the finetuned AI model is seamlessly integrated into their existing systems and processes, minimizing disruption and ensuring a smooth transition.</li></ol><h2 id="in-conclusion">In conclusion</h2><p>Finetuner+ combines the best of Jina AI's finetuning expertise with a client-focused approach, making the power of finetuned AI models accessible to businesses of all sizes and across industries. By partnering with Finetuner+, you can confidently leverage AI's full potential, drive innovation, and stay ahead in today's competitive landscape. <a href="https://finetunerplus.jina.ai/?ref=jina-ai-gmbh.ghost.io">Experience the Finetuner+ difference and elevate your AI capabilities with our expert consultancy services</a>.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fturbocharge-your-ai-with-finetuner%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Turbocharge Your AI with Finetuner+</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Finetuner+ is an on-prem finetuning solution that leverages state-of-the-art features of Finetuner, without the need for clients to implement it themselves.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">April 11, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="unlock-the-full-potential-of-ai-optimization-without-the-hassle">Unlock the full potential of AI optimization without the hassle</h2><p>At Jina AI, we've previously discussed the significant benefits that businesses can gain from finetuning their AI models.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/fine-tuning-with-low-budget-and-high-expectations/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Fine-tuning with Low Budget and High Expectations</div><div class="kg-bookmark-description">Fine-tuning is highly effective, economical, and eco-friendly; or at least that’s what all the deep learning tweets will tell you. Exactly how much data &amp; time do you need to get a good result?</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--53-.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/improving-search-quality-non-english-queries-fine-tuned-multilingual-clip-models/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models</div><div class="kg-bookmark-description">Having trouble with non-English search queries? Fine-tuning your multilingual CLIP models may be the answer. In this post, we’ll show you how Finetuner can be used on multilingual CLIP to improve search quality and give you better results.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--63-.png" alt=""></div></a></figure><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/applying-jina-ai-finetuner-to-clip-less-data-smaller-models-higher-performance/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">How Much Do We Get by Finetuning CLIP?</div><div class="kg-bookmark-description">Jina AI Finetuner can bring performance improvements of up to 63% to pre-trained CLIP models. Here is how we did that.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Jina-AI-Website-Banners-Templates--12-.png" alt=""></div></a></figure><p>A well-finetuned model can enhance performance, improve efficiency, and drive innovation. However, we understand that finetuning a model properly is a complex process that requires a high level of expertise. To address this challenge and make finetuning more accessible to businesses, we are excited to introduce Finetuner+ – an on-premise finetuning solution that leverages all the state-of-the-art features of Finetuner without the need for clients to implement it themselves.</p><p><strong><a href="https://finetunerplus.jina.ai/?ref=jina-ai-gmbh.ghost.io">Finetuner+</a></strong> is designed to empower businesses by optimizing their AI capabilities with customized, secure, and efficient finetuning solutions. Our expert engineers handle the entire finetuning process, from understanding your unique requirements and goals to delivering a finetuned AI model that adheres to the highest security standards. With Finetuner+, you can harness the power of Jina AI's proven finetuning methodologies without requiring in-house expertise or complex implementation.</p><h2 id="key-benefits-of-finetuner">Key benefits of Finetuner+</h2><ol><li><strong>Access to Jina AI's expertise</strong>: With Finetuner+, you benefit from Jina AI's extensive knowledge and experience in AI model finetuning. Our team of experts ensures that your AI models are finetuned using the latest methodologies and best practices.</li><li><strong>Customized solutions</strong>: Finetuner+ tailors the finetuning process to your specific needs, industry requirements, and business objectives. This personalized approach ensures that your finetuned AI model delivers maximum value and performance.</li><li><strong>Security and compliance</strong>: Finetuner+ prioritizes data privacy and security, adhering to industry-specific regulations and best practices. You can trust that your finetuned AI models will be secure and compliant with the necessary standards.</li><li><strong>Cost-effective approach</strong>: Finetuner+ offers a cost-effective alternative to hiring or training specialized AI teams or implementing finetuning solutions in-house. By partnering with Finetuner+, businesses can access cutting-edge AI expertise and solutions without the high costs associated with in-house development.</li><li><strong>Seamless integration</strong>: The Finetuner+ team works closely with clients to ensure the finetuned AI model is seamlessly integrated into their existing systems and processes, minimizing disruption and ensuring a smooth transition.</li></ol><h2 id="in-conclusion">In conclusion</h2><p>Finetuner+ combines the best of Jina AI's finetuning expertise with a client-focused approach, making the power of finetuned AI models accessible to businesses of all sizes and across industries. By partnering with Finetuner+, you can confidently leverage AI's full potential, drive innovation, and stay ahead in today's competitive landscape. <a href="https://finetunerplus.jina.ai/?ref=jina-ai-gmbh.ghost.io">Experience the Finetuner+ difference and elevate your AI capabilities with our expert consultancy services</a>.</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fturbocharge-your-ai-with-finetuner%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; 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\ No newline at end of file
diff --git a/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family/index.html b/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family/index.html
index afa0d972732..1db44a5d5b2 100644
--- a/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family/index.html
+++ b/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family/index.html
@@ -1,6 +1,6 @@
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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</title><meta charset="utf-8"><meta name="title" content="Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family"><meta name="description" content="Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family"><meta property="og:title" content="Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family"><meta property="og:description" content="Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family"><meta property="twitter:title" content="Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family"><meta property="twitter:description" content="Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsPage.3fc05989.js"><link rel="stylesheet" href="/assets/NewsPage.9d03bcfb.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/blogs.0b845204.js"><link rel="stylesheet" href="/assets/blogs.b3aadae9.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsBadge.85969a48.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/NewsVerticalCard.2afaaf7a.js"><script src="https://jina-ai-gmbh.ghost.io/public/cards.min.js" async=""></script><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">ThinkGPT</div><div class="q-item__label q-item__label--caption text-caption">Agent techniques to augment your LLM and push it beyond its limits</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/dev-gpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/dev-gpt.a3e55036.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Miruna Nedelcu</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 18, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Great news for PromptPerfect enthusiasts: We want to show you our appreciation for helping to build our community! </p><p>We're introducing the <strong>PromptPerfect Affiliate Program</strong>, an initiative inviting enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great! Become one of our affiliates and enjoy rewards for helping show the world what PromptPerfect can do.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/affiliate?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, Midjourney and Stable Diffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficien…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Learn More About PromptPerfect Affiliate Program</span></p></figcaption></figure><h2 id="key-benefits">Key Benefits:</h2><ul><li><strong>A Rewarding Start:</strong> From the get-go, affiliates receive <strong>a 15% commission on sales</strong> during their first month. It's a hearty welcome to the family, ensuring you feel valued from your very first contribution. And we are more than happy to increase your commission after the first month.</li><li><strong>Sustained Gains:</strong> The perks don't just stop after the first month. For every ensuing sale, a consistent 15% commission is credited to you. It's the gift that keeps on giving, rewarding your efforts and amplifying your impact.</li><li><strong>Simple, Monthly Payouts:</strong> To keep things simple, earnings are calculated and sent out monthly. You can focus on what you do best, leaving the complexities of transactions to us.</li><li><strong>Your Success is Important to Us: </strong>We're committed to supporting your success. You'll have access to valuable resources to generate as many referrals as possible. These resources are designed to help you develop content and attract more new merchants. Plus, you'll get access to a variety of creative, pre-developed lead magnets and detailed performance metrics.</li></ul><h2 id="how-to-get-started"><strong>How to Get Started: </strong></h2><p>Embarking on this journey is as simple as 1-2-3:</p><p><strong>Apply Easily:</strong> Start by going to our <a href="https://promptperfect.jina.ai/affiliate?ref=jina-ai-gmbh.ghost.io">website</a> and filling out our sign-up form. There are no hoops to jump through, just some basic information.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/affiliate?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, Midjourney and Stable Diffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficien…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><p><strong>Quick Follow-up:</strong> Your time is precious, and so we commit to responding within 5 business days. You'll be fully briefed on the next steps without any unnecessary wait.</p><p><strong>Get guidance from the team:</strong> Once your application has been reviewed, our team will reach out to you to arrange a call. During this call, we will walk you through all the necessary steps and provide you with valuable links to promotional materials, so you can start immediately.</p><p>This program is about fostering a community that values innovation and shared success. It's for those who are excited about shaping the future of technology and want their voices to be heard.</p><p>The PromptPerfect Affiliate Program can make you an integral part of a community that champions forward-thinking and mutual growth. So, if you like sharing with the world the next big thing in tech, this opportunity is for you.</p><p>Ready to take the leap? Dive in, spread the word, and watch the magic happen. </p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/affiliate?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, Midjourney and Stable Diffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficien…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Learn More About PromptPerfect Affiliate Program</span></p></figcaption></figure><p>The future is being written, and here's your chance to hold the pen.</p><p>Welcome to the family!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Funveiling-the-magic-become-a-part-of-promptperfects-affiliate-family%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 50%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/graph-embedding-101-unraveling-the-magic-of-relational-data" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Graph Embedding 101: Unraveling the Magic of Relational Data</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Graphs → everywhere. Social. Knowledge. Molecular. Critical infrastructure. Complex hairy ball visuals. Hard for machines.
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-ecd25db0="" class="q-page" style="min-height: 100vh;"><div data-v-ecd25db0="" class="row justify-center q-gutter-lg"><div data-v-ecd25db0="" class="col q-my-xl q-py-xl"><div data-v-ecd25db0="" class="q-mx-md q-mx-md-xl q-px-md-md q-px-lg-lg q-px-xl-xl"><div data-v-ecd25db0="" class="row justify-between items-center q-mt-lg"><a data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable no-border-radius self-stretch col-auto" tabindex="0" href="/news"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">arrow_circle_left</i><span class="block">Back to Newsroom</span></span></a><div data-v-ecd25db0="" class="col-auto"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></div></div><div data-v-ecd25db0="" class="q-img q-img--menu q-mt-md" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Miruna Nedelcu</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 18, 2023 • 3 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Great news for PromptPerfect enthusiasts: We want to show you our appreciation for helping to build our community! </p><p>We're introducing the <strong>PromptPerfect Affiliate Program</strong>, an initiative inviting enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great! Become one of our affiliates and enjoy rewards for helping show the world what PromptPerfect can do.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/affiliate?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, Midjourney and Stable Diffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficien…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Learn More About PromptPerfect Affiliate Program</span></p></figcaption></figure><h2 id="key-benefits">Key Benefits:</h2><ul><li><strong>A Rewarding Start:</strong> From the get-go, affiliates receive <strong>a 15% commission on sales</strong> during their first month. It's a hearty welcome to the family, ensuring you feel valued from your very first contribution. And we are more than happy to increase your commission after the first month.</li><li><strong>Sustained Gains:</strong> The perks don't just stop after the first month. For every ensuing sale, a consistent 15% commission is credited to you. It's the gift that keeps on giving, rewarding your efforts and amplifying your impact.</li><li><strong>Simple, Monthly Payouts:</strong> To keep things simple, earnings are calculated and sent out monthly. You can focus on what you do best, leaving the complexities of transactions to us.</li><li><strong>Your Success is Important to Us: </strong>We're committed to supporting your success. You'll have access to valuable resources to generate as many referrals as possible. These resources are designed to help you develop content and attract more new merchants. Plus, you'll get access to a variety of creative, pre-developed lead magnets and detailed performance metrics.</li></ul><h2 id="how-to-get-started"><strong>How to Get Started: </strong></h2><p>Embarking on this journey is as simple as 1-2-3:</p><p><strong>Apply Easily:</strong> Start by going to our <a href="https://promptperfect.jina.ai/affiliate?ref=jina-ai-gmbh.ghost.io">website</a> and filling out our sign-up form. There are no hoops to jump through, just some basic information.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/affiliate?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, Midjourney and Stable Diffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficien…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><p><strong>Quick Follow-up:</strong> Your time is precious, and so we commit to responding within 5 business days. You'll be fully briefed on the next steps without any unnecessary wait.</p><p><strong>Get guidance from the team:</strong> Once your application has been reviewed, our team will reach out to you to arrange a call. During this call, we will walk you through all the necessary steps and provide you with valuable links to promotional materials, so you can start immediately.</p><p>This program is about fostering a community that values innovation and shared success. It's for those who are excited about shaping the future of technology and want their voices to be heard.</p><p>The PromptPerfect Affiliate Program can make you an integral part of a community that champions forward-thinking and mutual growth. So, if you like sharing with the world the next big thing in tech, this opportunity is for you.</p><p>Ready to take the leap? Dive in, spread the word, and watch the magic happen. </p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/affiliate?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, Midjourney and Stable Diffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficien…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a><figcaption><p><span style="white-space: pre-wrap;">Learn More About PromptPerfect Affiliate Program</span></p></figcaption></figure><p>The future is being written, and here's your chance to hold the pen.</p><p>Welcome to the family!</p></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Funveiling-the-magic-become-a-part-of-promptperfects-affiliate-family%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/graph-embedding-101-unraveling-the-magic-of-relational-data" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Graph Embedding 101: Unraveling the Magic of Relational Data</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Graphs → everywhere. Social. Knowledge. Molecular. Critical infrastructure. Complex hairy ball visuals. Hard for machines.
 
 Now graph embeddings vectorize nodes. Distill graphs into geometry. Embeddings work magic. AI devours graphs.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">August 29, 2023 • 10 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/generativejina_purple_and_green_network_graphs_on_purple_backgr_8f3f4431-5317-4b2e-a2b7-44e206c14b26.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>VectorDB: a Python vector database you just need - no more, no less</title><meta charset="utf-8"><meta name="title" content="VectorDB: a Python vector database you just need - no more, no less"><meta name="description" content="VectorDB is a Pythonic vector database offers a comprehensive suite of CRUD operations and robust scalability options, including sharding and replication. It's readily deployable in a variety of environments, from local to on-premise and cloud. vectordb delivers exactly what you need."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/vectordb-a-python-vector-database-you-just-need-no-more-no-less"><meta property="og:title" content="VectorDB: a Python vector database you just need - no more, no less"><meta property="og:description" content="VectorDB is a Pythonic vector database offers a comprehensive suite of CRUD operations and robust scalability options, including sharding and replication. It's readily deployable in a variety of environments, from local to on-premise and cloud. vectordb delivers exactly what you need."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Jina-AI-Website-Banners-Templates---2023-07-14T122044.610.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/vectordb-a-python-vector-database-you-just-need-no-more-no-less"><meta property="twitter:title" content="VectorDB: a Python vector database you just need - no more, no less"><meta property="twitter:description" content="VectorDB is a Pythonic vector database offers a comprehensive suite of CRUD operations and robust scalability options, including sharding and replication. It's readily deployable in a variety of environments, from local to on-premise and cloud. vectordb delivers exactly what you need."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/07/Jina-AI-Website-Banners-Templates---2023-07-14T122044.610.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">VectorDB: a Python vector database you just need - no more, no less</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">VectorDB is a Pythonic vector database offers a comprehensive suite of CRUD operations and robust scalability options, including sharding and replication. It's readily deployable in a variety of environments, from local to on-premise and cloud. vectordb delivers exactly what you need.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 14, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In today's world of multimodal AI, the ability to efficiently query and retrieve relevant information from massive amounts of data is crucial. This is especially true when it comes to dealing with embedding data, which is common in many fields including deep learning, computer vision, and natural language processing. Vector databases offer an effective solution to this challenge.</p><p>Among various vector databases in the market, we are excited to introduce our <strong><code>vectordb</code></strong> - a Python vector database tailored to your needs, no more, no less.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/vectordb?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/vectordb: A Python vector database you just need - no more, no less.</div><div class="kg-bookmark-description">A Python vector database you just need - no more, no less. - GitHub - jina-ai/vectordb: A Python vector database you just need - no more, no less.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/635374751/522df31b-c3e2-4a73-a3c1-6fdba634b194" alt=""></div></a></figure><h2 id="what-is-a-vector-database">What is a vector database?</h2><p>Vector databases serve as sophisticated repositories for embeddings, capturing the essence of semantic similarity among disparate objects. These databases facilitate similarity searches across a myriad of multimodal data types, paving the way for a new era of information retrieval. By providing contextual understanding and enriching generation results, vector databases greatly enhance the performance and utility of Language Learning Models (LLM). This underscores their pivotal role in the evolution of data science and machine learning applications.</p><h2 id="what-is-vectordb">What is VectorDB?</h2><p><code>vectordb</code> is a Python library designed to manage, query, and retrieve high-dimensional vector data efficiently. It provides an easy-to-use API, allowing you to work with vector data just like how you work with regular Python objects. With <code>vectordb</code>, you can perform CRUD operations (Create, Read, Update, Delete) on your vector data, and conduct a nearest neighbor search based on vector similarity.</p><h2 id="why-do-we-need-vectordb">Why do we need VectorDB?</h2><p>Navigating the intersection of AI and databases, <code>vectordb</code> emerges as a Pythonic vector database, providing a balance of functionality and simplicity.</p><p>Boasting a comprehensive suite of CRUD operations, <code>vectordb</code> also provides robust scalability with sharding and replication features. It is deployable across various environments, including local, on-premise, or cloud setups, ensuring adaptability to your project requirements.</p><table>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">VectorDB: a Python vector database you just need - no more, no less</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">VectorDB is a Pythonic vector database offers a comprehensive suite of CRUD operations and robust scalability options, including sharding and replication. It's readily deployable in a variety of environments, from local to on-premise and cloud. vectordb delivers exactly what you need.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">July 14, 2023 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>In today's world of multimodal AI, the ability to efficiently query and retrieve relevant information from massive amounts of data is crucial. This is especially true when it comes to dealing with embedding data, which is common in many fields including deep learning, computer vision, and natural language processing. Vector databases offer an effective solution to this challenge.</p><p>Among various vector databases in the market, we are excited to introduce our <strong><code>vectordb</code></strong> - a Python vector database tailored to your needs, no more, no less.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://github.com/jina-ai/vectordb?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">GitHub - jina-ai/vectordb: A Python vector database you just need - no more, no less.</div><div class="kg-bookmark-description">A Python vector database you just need - no more, no less. - GitHub - jina-ai/vectordb: A Python vector database you just need - no more, no less.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://github.com/fluidicon.png" alt=""><span class="kg-bookmark-author">GitHub</span><span class="kg-bookmark-publisher">jina-ai</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://repository-images.githubusercontent.com/635374751/522df31b-c3e2-4a73-a3c1-6fdba634b194" alt=""></div></a></figure><h2 id="what-is-a-vector-database">What is a vector database?</h2><p>Vector databases serve as sophisticated repositories for embeddings, capturing the essence of semantic similarity among disparate objects. These databases facilitate similarity searches across a myriad of multimodal data types, paving the way for a new era of information retrieval. By providing contextual understanding and enriching generation results, vector databases greatly enhance the performance and utility of Language Learning Models (LLM). This underscores their pivotal role in the evolution of data science and machine learning applications.</p><h2 id="what-is-vectordb">What is VectorDB?</h2><p><code>vectordb</code> is a Python library designed to manage, query, and retrieve high-dimensional vector data efficiently. It provides an easy-to-use API, allowing you to work with vector data just like how you work with regular Python objects. With <code>vectordb</code>, you can perform CRUD operations (Create, Read, Update, Delete) on your vector data, and conduct a nearest neighbor search based on vector similarity.</p><h2 id="why-do-we-need-vectordb">Why do we need VectorDB?</h2><p>Navigating the intersection of AI and databases, <code>vectordb</code> emerges as a Pythonic vector database, providing a balance of functionality and simplicity.</p><p>Boasting a comprehensive suite of CRUD operations, <code>vectordb</code> also provides robust scalability with sharding and replication features. It is deployable across various environments, including local, on-premise, or cloud setups, ensuring adaptability to your project requirements.</p><table>
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-</table><h2 id="features">Features</h2><p><strong>User-friendly Interface:</strong> With <code>vectordb</code>, simplicity is key. Its intuitive interface is designed to accommodate users across varying levels of expertise.</p><p><strong>Minimalistic Design:</strong> <code>vectordb</code> packs all the essentials, with no unnecessary complexity. It ensures a seamless transition from local to server and cloud deployment.</p><p><strong>Full CRUD Support:</strong> From indexing and searching to updating and deleting, <code>vectordb</code> covers the entire spectrum of CRUD operations.</p><p><strong>DB as a Service:</strong> Harness the power of gRPC, HTTP, and Websocket protocols with <code>vectordb</code>. It enables you to serve your databases and conduct insertion or searching operations efficiently.</p><p><strong>Scalability:</strong> Experience the raw power of <code>vectordb</code>'s deployment capabilities, including robust scalability features like sharding and replication. Improve your service latency with sharding, while replication enhances availability and throughput.</p><p><strong>Cloud Deployment:</strong> Deploying your service in the cloud is a breeze with <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a>. More deployment options are coming soon!</p><p><strong>Serverless Capability:</strong> <code>vectordb</code> can be deployed in a serverless mode in the cloud, ensuring optimal resource utilization and data availability as per your needs.</p><p><strong>Multiple ANN Algorithms:</strong> <code>vectordb</code> offers diverse implementations of Approximate Nearest Neighbors (ANN) algorithms. Here are the current offerings, with more integrations on the horizon:</p><ul><li>InMemoryExactNNVectorDB (Exact NN Search): Implements Simple Nearest Neighbor Algorithm.</li><li>HNSWVectorDB (based on HNSW): Utilizes <a href="https://github.com/nmslib/hnswlib?ref=jina-ai-gmbh.ghost.io">HNSWLib</a></li></ul><h2 id="roadmap">Roadmap</h2><p>The future of Vector Database looks bright, and we have ambitious plans! Here's a sneak peek into the features we're currently developing:</p><ul><li>More ANN Search Algorithms: Our goal is to support an even wider range of ANN search algorithms.</li><li>Enhanced Filtering Capabilities: We're working on enhancing our ANN Search solutions to support advanced filtering.</li><li>Customizability: We aim to make <code>vectordb</code> highly customizable, allowing Python developers to tailor its behavior to their specific needs with ease.</li><li>Expanding Serverless Capacity: We're striving to enhance the serverless capacity of <code>vectordb</code> in the cloud. While we currently support scaling between 0 and 1 replica, our goal is to extend this to 0 to N replicas.</li><li>Expanded Deployment Options: We're actively working on facilitating the deployment of <code>vectordb</code> across various cloud platforms, with a broad range of options.</li></ul><h2 id="contributing">Contributing</h2><p>The VectorDB project is backed by <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI</a> and licensed under Apache-2.0. Contributions from the community are greatly appreciated! If you have an idea for a new feature or an improvement, we would love to hear from you. 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+</table><h2 id="features">Features</h2><p><strong>User-friendly Interface:</strong> With <code>vectordb</code>, simplicity is key. Its intuitive interface is designed to accommodate users across varying levels of expertise.</p><p><strong>Minimalistic Design:</strong> <code>vectordb</code> packs all the essentials, with no unnecessary complexity. It ensures a seamless transition from local to server and cloud deployment.</p><p><strong>Full CRUD Support:</strong> From indexing and searching to updating and deleting, <code>vectordb</code> covers the entire spectrum of CRUD operations.</p><p><strong>DB as a Service:</strong> Harness the power of gRPC, HTTP, and Websocket protocols with <code>vectordb</code>. It enables you to serve your databases and conduct insertion or searching operations efficiently.</p><p><strong>Scalability:</strong> Experience the raw power of <code>vectordb</code>'s deployment capabilities, including robust scalability features like sharding and replication. Improve your service latency with sharding, while replication enhances availability and throughput.</p><p><strong>Cloud Deployment:</strong> Deploying your service in the cloud is a breeze with <a href="https://cloud.jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI Cloud</a>. More deployment options are coming soon!</p><p><strong>Serverless Capability:</strong> <code>vectordb</code> can be deployed in a serverless mode in the cloud, ensuring optimal resource utilization and data availability as per your needs.</p><p><strong>Multiple ANN Algorithms:</strong> <code>vectordb</code> offers diverse implementations of Approximate Nearest Neighbors (ANN) algorithms. Here are the current offerings, with more integrations on the horizon:</p><ul><li>InMemoryExactNNVectorDB (Exact NN Search): Implements Simple Nearest Neighbor Algorithm.</li><li>HNSWVectorDB (based on HNSW): Utilizes <a href="https://github.com/nmslib/hnswlib?ref=jina-ai-gmbh.ghost.io">HNSWLib</a></li></ul><h2 id="roadmap">Roadmap</h2><p>The future of Vector Database looks bright, and we have ambitious plans! Here's a sneak peek into the features we're currently developing:</p><ul><li>More ANN Search Algorithms: Our goal is to support an even wider range of ANN search algorithms.</li><li>Enhanced Filtering Capabilities: We're working on enhancing our ANN Search solutions to support advanced filtering.</li><li>Customizability: We aim to make <code>vectordb</code> highly customizable, allowing Python developers to tailor its behavior to their specific needs with ease.</li><li>Expanding Serverless Capacity: We're striving to enhance the serverless capacity of <code>vectordb</code> in the cloud. While we currently support scaling between 0 and 1 replica, our goal is to extend this to 0 to N replicas.</li><li>Expanded Deployment Options: We're actively working on facilitating the deployment of <code>vectordb</code> across various cloud platforms, with a broad range of options.</li></ul><h2 id="contributing">Contributing</h2><p>The VectorDB project is backed by <a href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io">Jina AI</a> and licensed under Apache-2.0. Contributions from the community are greatly appreciated! If you have an idea for a new feature or an improvement, we would love to hear from you. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/florian-small.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Alex C-G, Florian Hönicke</div><div class="q-item__label q-item__label--caption text-caption">December 19, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--27-.png" style="object-fit: cover; 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Want to Search Inside Videos Like a Pro? CLIP-as-service Can Help</title><meta charset="utf-8"><meta name="title" content="Want to Search Inside Videos Like a Pro? CLIP-as-service Can Help"><meta name="description" content="Imagine an AI-powered grep command, one that could process a film and find segments matching a text. With Jina AI's CLIP-as-service, you can do that today. We'll show you how."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/want-search-inside-videos-like-pro-clip-service-can-help"><meta property="og:title" content="Want to Search Inside Videos Like a Pro? CLIP-as-service Can Help"><meta property="og:description" content="Imagine an AI-powered grep command, one that could process a film and find segments matching a text. With Jina AI's CLIP-as-service, you can do that today. We'll show you how."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--54-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/want-search-inside-videos-like-pro-clip-service-can-help"><meta property="twitter:title" content="Want to Search Inside Videos Like a Pro? CLIP-as-service Can Help"><meta property="twitter:description" content="Imagine an AI-powered grep command, one that could process a film and find segments matching a text. With Jina AI's CLIP-as-service, you can do that today. We'll show you how."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--54-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Want to Search Inside Videos Like a Pro? CLIP-as-service Can Help</title><meta charset="utf-8"><meta name="title" content="Want to Search Inside Videos Like a Pro? CLIP-as-service Can Help"><meta name="description" content="Imagine an AI-powered grep command, one that could process a film and find segments matching a text. With Jina AI's CLIP-as-service, you can do that today. We'll show you how."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/want-search-inside-videos-like-pro-clip-service-can-help"><meta property="og:title" content="Want to Search Inside Videos Like a Pro? CLIP-as-service Can Help"><meta property="og:description" content="Imagine an AI-powered grep command, one that could process a film and find segments matching a text. With Jina AI's CLIP-as-service, you can do that today. We'll show you how."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--54-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/want-search-inside-videos-like-pro-clip-service-can-help"><meta property="twitter:title" content="Want to Search Inside Videos Like a Pro? CLIP-as-service Can Help"><meta property="twitter:description" content="Imagine an AI-powered grep command, one that could process a film and find segments matching a text. With Jina AI's CLIP-as-service, you can do that today. We'll show you how."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/12/Jina-AI-Website-Banners-Templates--54-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Want to Search Inside Videos Like a Pro? CLIP-as-service Can Help</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Imagine an AI-powered grep command, one that could process a film and find segments matching a text. With Jina AI's CLIP-as-service, you can do that today. We'll show you how.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/--.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jie Fu, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 13, 2022 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Wouldn’t it be great if you could search through a video the way you search through a text?</p><p>Imagine opening a digitized film, just hitting <em>ctrl-f</em> and typing “Santa”, then getting all the parts of the video with Santa Claus in it. Or just going to the command line and using the <code>grep</code> command:</p><pre><code class="language-bash hljs">grep <span class="hljs-string">"Santa Claus"</span> Santa_Claus_conquers_The_Martians.mp4
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Want to Search Inside Videos Like a Pro? CLIP-as-service Can Help</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Imagine an AI-powered grep command, one that could process a film and find segments matching a text. With Jina AI's CLIP-as-service, you can do that today. We'll show you how.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/--.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 118.041%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jie Fu, Scott Martens</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 13, 2022 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Wouldn’t it be great if you could search through a video the way you search through a text?</p><p>Imagine opening a digitized film, just hitting <em>ctrl-f</em> and typing “Santa”, then getting all the parts of the video with Santa Claus in it. Or just going to the command line and using the <code>grep</code> command:</p><pre><code class="language-bash hljs">grep <span class="hljs-string">"Santa Claus"</span> Santa_Claus_conquers_The_Martians.mp4
 </code></pre><p>Normally, this would be impossible, or only possible if you had gone through the film and carefully labeled all the parts with a Santa in them already. But with Jina AI and CLIP-as-service, you can create a <strong>video grep</strong> command for MP4 film with just a few Python functions and a standard computer setup. There is no need for a GPU and no complex AI tech stack to install, just off-the-shelf and open-source Python libraries, with Jina AI Cloud doing all the heavy lifting.</p><p>This has immediate applications for anyone who has video data: film archivists, stock image vendors, news photographers, or even regular people who just keep videos from their cellphones around and post them to social media.</p><h2 id="preliminaries">Preliminaries</h2><p>You need Python 3, and you might want to create a new virtual environment before starting. Then, install a few components at the command line with <code>pip</code>:</p><pre><code class="language-bash hljs">pip install clip_client <span class="hljs-string">"docarray[full]&gt;=0.20.0"</span></code></pre><p>This installs:</p><ul><li>Jina AI’s <a href="https://docarray.jina.ai/?ref=jina-ai-gmbh.ghost.io">DocArray library</a></li><li>Jina AI’s <a href="https://clip-as-service.jina.ai/?ref=jina-ai-gmbh.ghost.io">CLIP-as-service</a> client</li></ul><p>You'll also need an account for CLIP-as-service. If you don't already have one, there are <a href="https://docs.jina.ai/jina-ai-cloud/login/?ref=jina-ai-gmbh.ghost.io">instructions in the Jina AI documentation</a>. Once you have an account, you will need a token. You can get one from <a href="https://cloud.jina.ai/settings/tokens?ref=jina-ai-gmbh.ghost.io" rel="nofollow">your token settings page at Jina AI Cloud</a>, or at the command line:</p><pre><code class="language-bash hljs">&gt; jina auth login ⤶
 
 Your browser is going to open the login page.
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Web Summit, we are coming!</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">We are excited to go to Lisbon to attend the Web Summit on November 1-4th, 2022, and look forward to sharing our work with the wider community. If you're interested in connecting with us at the conference, please feel free to book a meeting! </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 27, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The Jina AI team is thrilled to attend the Web Summit on November 1-4th, 2022. As one of the world's premier tech conferences, Web Summit provides an invaluable opportunity to hear from leaders in the industry and learn about the latest advances in technology. We are excited to be a part of this event and look forward to sharing our work with the wider community.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://websummit.com/?utm_source=google&amp;utm_medium=cpc&amp;utm_campaign=18596301005&amp;utm_content=143300306118&amp;utm_term=web%20summit&amp;gclid=Cj0KCQjwkt6aBhDKARIsAAyeLJ2uxVifLOEPlJj1IcmmJGMe4QBM3xsTS6XD4Ut9wx61xCLwmY-Z5UgaAj5wEALw_wcB"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Web Summit | Lisbon, November 1-4, 2022 | Where the tech world meets</div><div class="kg-bookmark-description">Web Summit brings together the people and companies redefining the global tech industry. Web Summit will return to Lisbon this year. Join us in November.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://web-summit-library.imgix.net/websummit/2222/07/WS-logo_icon-colour-favicon.png?auto=compress%2Cformat&amp;ixlib=php-3.3.0&amp;s=ab327eaecf4fb1c8526cbb755f98c9ab" alt=""><span class="kg-bookmark-author">Web Summit | Lisbon</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://web-summit-library.imgix.net/websummit/2121/11/Centre-Stage-during-the-opening-night-of-Web-Summit-202.jpg?auto=compress%2Cformat&amp;ixlib=php-3.3.0&amp;s=f47ff0e21fad824de61b18a2b32adffb" alt=""></div></a><figcaption>Learn more about Web Summit</figcaption></figure><p>If you're interested in learning more about Jina AI and our technology, we'll be happy to connect with you at the conference. You can book a meeting with us through the Web Summit app. </p><p><strong>Meet the team</strong><br>Susana Guzman, Product Manager. Connect with Susana on<a href="https://twitter.com/capricareloaded?s=21&amp;t=po4UbiiyOkjuWVDtuSZjHw&amp;ref=jina-ai-gmbh.ghost.io"> Twitter </a><br>Leon Wolf, Product Manager. Connect with Leon on <a href="https://www.linkedin.com/in/leon-wolf-64945a14/?ref=jina-ai-gmbh.ghost.io">LinkedIn</a> <br>Florian Hoenicke, Jina NOW Team Lead. Connect with Florian on <a href="https://www.linkedin.com/in/florian-h%C3%B6nicke-b902b6aa/?ref=jina-ai-gmbh.ghost.io">LinkedIn </a><br>Joschka Braun, Software Engineer. Connect with Joschka on <a href="https://www.linkedin.com/in/joschkabraun/?ref=jina-ai-gmbh.ghost.io">LinkedIn </a></p><p><strong>Find us on Web Summit App</strong></p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://websummit.com/app?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Download the Web Summit app for iOS and Android | Web Summit</div><div class="kg-bookmark-description">Get the most out of Web Summit with the app. Personalise your profile so that attendees know who you are and plan your schedule so you don’t miss an essential talk. You’ll also be able to connect with fellow attendees and chat with them throughout the event.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://web-summit-library.imgix.net/websummit/2222/07/WS-logo_icon-colour-favicon.png?auto=compress%2Cformat&amp;ixlib=php-3.3.0&amp;s=ab327eaecf4fb1c8526cbb755f98c9ab" alt=""><span class="kg-bookmark-author">Web Summit | Lisbon</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://websummit.com/wp-content/uploads/2016/12/app-hero.jpg" alt=""></div></a></figure><h2 id="about-jina-ai"><strong>About Jina AI</strong></h2><p>Jina AI is a commercial open-source software company founded in February 2020. It provides businesses and developers with an MLOps platform for building multimodal applications on the cloud, including neural search, creative AI, etc. The company has raised 37.5 million USD backed by top investors such as Canaan Partners, GGV Capital, Yunqi Partners, SAP.io, and Mango Capital. The company is headquartered in Berlin, Germany with offices in San Jose, Beijing, and Shenzhen; its distributed team model includes members from all around the world.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI is a Neural Search Company</div><div class="kg-bookmark-description">Jina AI provides the most advanced MLOps framework for multimodal AI. Build neural search, creative AI and multimodal data services on the cloud at scale.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/assets/images/banner/jina.jpg" alt=""></div></a></figure><div class="kg-card kg-button-card kg-align-center"><a href="https://jina.ai/slack/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Join us on Slack</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fweb-summit-we-are-coming%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/a-tale-of-two-worlds-emnlp-2023-at-sentosa" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">A Tale of Two Worlds: EMNLP 2023 at Sentosa</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Just back from EMNLP2023 and my mind's still reeling! Witnessed NLP's seismic shift firsthand through daring papers and provocative posters that are challenging everything we thought we knew. Check out my take on the conference's boldest ideas.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/profile_low_quality.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao, Michael Günther</div><div class="q-item__label q-item__label--caption text-caption">December 16, 2023 • 17 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--26-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/discover-the-latest-in-embeddings-at-emnlp-2023-in-person-bof-session" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Discover the Latest in Embeddings at EMNLP 2023 In-Person BoF Session</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Mark your calendars for an immersive BoF session on Embeddings at EMNLP 2023. Join us on December 9th from 11:00 AM to 12:30 PM, Singapore time, in the 'Aquarius 1' room for a deep dive into the latest embeddings.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina AI</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Explore-image-storytelling-beyond-pixels--25--1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/give-and-take-in-fdps-ai-geopolitics-panel" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Give and Take in FDP's AI Geopolitics Panel</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">This blog post captures my personal reflections and contributions to the panel, highlighting key differences in AI strategies among global powers like the US, China, and the EU.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Han Xiao</div><div class="q-item__label q-item__label--caption text-caption">November 29, 2023 • 7 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 52.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--23-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">We are excited to go to Lisbon to attend the Web Summit on November 1-4th, 2022, and look forward to sharing our work with the wider community. If you're interested in connecting with us at the conference, please feel free to book a meeting! </p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">October 27, 2022 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>The Jina AI team is thrilled to attend the Web Summit on November 1-4th, 2022. As one of the world's premier tech conferences, Web Summit provides an invaluable opportunity to hear from leaders in the industry and learn about the latest advances in technology. We are excited to be a part of this event and look forward to sharing our work with the wider community.</p><figure class="kg-card kg-bookmark-card kg-card-hascaption"><a class="kg-bookmark-container" href="https://websummit.com/?utm_source=google&amp;utm_medium=cpc&amp;utm_campaign=18596301005&amp;utm_content=143300306118&amp;utm_term=web%20summit&amp;gclid=Cj0KCQjwkt6aBhDKARIsAAyeLJ2uxVifLOEPlJj1IcmmJGMe4QBM3xsTS6XD4Ut9wx61xCLwmY-Z5UgaAj5wEALw_wcB"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Web Summit | Lisbon, November 1-4, 2022 | Where the tech world meets</div><div class="kg-bookmark-description">Web Summit brings together the people and companies redefining the global tech industry. Web Summit will return to Lisbon this year. Join us in November.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://web-summit-library.imgix.net/websummit/2222/07/WS-logo_icon-colour-favicon.png?auto=compress%2Cformat&amp;ixlib=php-3.3.0&amp;s=ab327eaecf4fb1c8526cbb755f98c9ab" alt=""><span class="kg-bookmark-author">Web Summit | Lisbon</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://web-summit-library.imgix.net/websummit/2121/11/Centre-Stage-during-the-opening-night-of-Web-Summit-202.jpg?auto=compress%2Cformat&amp;ixlib=php-3.3.0&amp;s=f47ff0e21fad824de61b18a2b32adffb" alt=""></div></a><figcaption>Learn more about Web Summit</figcaption></figure><p>If you're interested in learning more about Jina AI and our technology, we'll be happy to connect with you at the conference. You can book a meeting with us through the Web Summit app. </p><p><strong>Meet the team</strong><br>Susana Guzman, Product Manager. Connect with Susana on<a href="https://twitter.com/capricareloaded?s=21&amp;t=po4UbiiyOkjuWVDtuSZjHw&amp;ref=jina-ai-gmbh.ghost.io"> Twitter </a><br>Leon Wolf, Product Manager. Connect with Leon on <a href="https://www.linkedin.com/in/leon-wolf-64945a14/?ref=jina-ai-gmbh.ghost.io">LinkedIn</a> <br>Florian Hoenicke, Jina NOW Team Lead. Connect with Florian on <a href="https://www.linkedin.com/in/florian-h%C3%B6nicke-b902b6aa/?ref=jina-ai-gmbh.ghost.io">LinkedIn </a><br>Joschka Braun, Software Engineer. Connect with Joschka on <a href="https://www.linkedin.com/in/joschkabraun/?ref=jina-ai-gmbh.ghost.io">LinkedIn </a></p><p><strong>Find us on Web Summit App</strong></p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://websummit.com/app?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Download the Web Summit app for iOS and Android | Web Summit</div><div class="kg-bookmark-description">Get the most out of Web Summit with the app. Personalise your profile so that attendees know who you are and plan your schedule so you don’t miss an essential talk. You’ll also be able to connect with fellow attendees and chat with them throughout the event.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://web-summit-library.imgix.net/websummit/2222/07/WS-logo_icon-colour-favicon.png?auto=compress%2Cformat&amp;ixlib=php-3.3.0&amp;s=ab327eaecf4fb1c8526cbb755f98c9ab" alt=""><span class="kg-bookmark-author">Web Summit | Lisbon</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://websummit.com/wp-content/uploads/2016/12/app-hero.jpg" alt=""></div></a></figure><h2 id="about-jina-ai"><strong>About Jina AI</strong></h2><p>Jina AI is a commercial open-source software company founded in February 2020. It provides businesses and developers with an MLOps platform for building multimodal applications on the cloud, including neural search, creative AI, etc. The company has raised 37.5 million USD backed by top investors such as Canaan Partners, GGV Capital, Yunqi Partners, SAP.io, and Mango Capital. The company is headquartered in Berlin, Germany with offices in San Jose, Beijing, and Shenzhen; its distributed team model includes members from all around the world.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina AI is a Neural Search Company</div><div class="kg-bookmark-description">Jina AI provides the most advanced MLOps framework for multimodal AI. Build neural search, creative AI and multimodal data services on the cloud at scale.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/assets/images/banner/jina.jpg" alt=""></div></a></figure><div class="kg-card kg-button-card kg-align-center"><a href="https://jina.ai/slack/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Join us on Slack</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Events</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fweb-summit-we-are-coming%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>What is Multimodal Deep Learning and What are the Applications?</title><meta charset="utf-8"><meta name="title" content="What is Multimodal Deep Learning and What are the Applications?"><meta name="description" content="Multimodal deep learning allows for a more holistic understanding of data, as well as increased accuracy and efficiency. But first, what are multimodal deep learning? And what are the applications? This article will answer these two questions."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/what-is-multimodal-deep-learning-and-what-are-the-applications"><meta property="og:title" content="What is Multimodal Deep Learning and What are the Applications?"><meta property="og:description" content="Multimodal deep learning allows for a more holistic understanding of data, as well as increased accuracy and efficiency. But first, what are multimodal deep learning? And what are the applications? This article will answer these two questions."><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--42-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/what-is-multimodal-deep-learning-and-what-are-the-applications"><meta property="twitter:title" content="What is Multimodal Deep Learning and What are the Applications?"><meta property="twitter:description" content="Multimodal deep learning allows for a more holistic understanding of data, as well as increased accuracy and efficiency. But first, what are multimodal deep learning? And what are the applications? This article will answer these two questions."><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--42-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">What is Multimodal Deep Learning and What are the Applications?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Multimodal deep learning allows for a more holistic understanding of data, as well as increased accuracy and efficiency. But first, what are multimodal deep learning? And what are the applications? This article will answer these two questions.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 24, 2022 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Thanks to recent advances in deep neural networks, multimodal technologies have made possible advanced, intelligent processing of all kinds of unstructured data, including images, audio, video, PDFs, and 3D meshes. Multimodal deep learning allows for a more holistic understanding of data, as well as increased accuracy and efficiency.</p><p>Jina AI is the most advanced MLOps platform for building multimodal AI applications in the cloud. Users can translate their data and a few lines of code into a production-ready service without dealing with infrastructure complexity or scaling hassles.</p><p>But first, what is multimodal deep learning? And what are its applications?</p><h2 id="what-does-modal-mean">What does "modal" mean?</h2><p>The term “modal” is a reference to the human senses: sight, hearing, touch, taste, smell. We use it here to mean <strong>data modality</strong>. You can think of it as indicating the <em>kind</em> of data you're working with, like <em>text, image, video</em>, etc.</p><p>Sometimes people use the terms “<strong>multimodal</strong>” and “<strong>unstructured</strong> <strong>data</strong>” interchangeably because both terms describe data that lacks a meaningful internal structure. <em>Multimodal data</em> is data that uses multiple modalities, while <em>unstructured data</em> is a catch-all term that describes any type of data that doesn't have a readily machine-readable structure.</p><h2 id="real-world-data-is-multimodal">Real-world data is multimodal</h2><p>In the early days of AI, research typically focused on one modality at a time. Some works dealt with written language, others with images, or speech. As a result, AI applications were almost always limited to a specific modality: A spam filter works with text. A photo classifier handles images. A speech recognizer deals with audio. </p><p>But real-world data is often multimodal. Video is usually accompanied by an audio track and may even have text subtitles. Social media posts, news articles, and any internet-published content routinely mix text with images, videos, and audio recordings. The need to manage and process this data is one factor motivating the development of multimodal AI.</p><h2 id="multimodal-vs-cross-modal">Multimodal vs cross-modal</h2><p>"Multimodal" and "cross<strong>-</strong>modal" are another two terms that are often confused for each other, but don't mean the same thing:</p><p><strong>Multimodal deep learning</strong> is a relatively new field that is concerned with algorithms that learn from data of multiple modalities. For example, a human can use both sight and hearing to identify a person or object, and multimodal deep learning is concerned with developing similar abilities for computers.</p><p><strong>Cross-modal deep learning</strong> is an approach to multimodal deep learning where information from one modality is used to improve performance in another. For example, if you see a picture of a bird, you might be able to identify it by its song when you hear it.</p><p>AI systems that are designed to work with multiple modalities are said to be “multimodal”. The term “cross-modality” is more accurate when referring narrowly to AI systems that integrate different modalities and use them together.</p><h2 id="multimodal-deep-learning-applications">Multimodal deep learning applications</h2><p>Multimodal deep learning has a broad array of potential uses. Among the applications already available:</p><ul><li>Automatically generating descriptions of images, like captioning for blind people.</li><li>Searching for images that match text queries (e.g. “find me a picture of a blue dog”).</li><li>Generative art system that create images from text descriptions (e.g. “make a picture of a blue dog”).</li></ul><p>All these applications rely on two pillar technologies: <strong>search </strong>and<strong> creation.</strong></p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/search-is-overfitted-create-create-is-underfitted-search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Search is Overfitted Create; Create is Underfitted Search</div><div class="kg-bookmark-description">The biggest competition of neural search may come from a technology that doesn’t even need embeddings as an intermediate representation – an end-to-end technology that directly returns the result you want.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--38-.png" alt=""></div></a></figure><h3 id="neural-search">Neural search</h3><p>The core idea behind neural search is to leverage state-of-the-art neural network models to build <em>every</em> component of a search system. In short, <strong>neural search is deep neural network-powered information retrieval</strong>.</p><p>Below is an example of an embedding space generated by <a href="https://github.com/jina-ai/docarray?ref=jina-ai-gmbh.ghost.io">DocArray</a> and used for content-based image retrieval.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://github.com/jina-ai/docarray/raw/main/.github/README-img/tsne.gif?raw=true" class="kg-image" alt="https://github.com/jina-ai/docarray/raw/main/.github/README-img/tsne.gif?raw=true"><figcaption>Projection of an array of image embeddings into a three dimensional display</figcaption></figure><p>Similar images are mapped together in the embedding space, and this property of the embedding space is what makes it useful for search applications. Searching for images that are most similar to some picture amounts to finding the closest images in this space, which you can easily do via the DocArray API:</p><pre><code class="language-python hljs">db = ...  <span class="hljs-comment"># a DocumentArray of indexed images</span>
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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">What is Multimodal Deep Learning and What are the Applications?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Multimodal deep learning allows for a more holistic understanding of data, as well as increased accuracy and efficiency. But first, what are multimodal deep learning? And what are the applications? This article will answer these two questions.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 24, 2022 • 6 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Thanks to recent advances in deep neural networks, multimodal technologies have made possible advanced, intelligent processing of all kinds of unstructured data, including images, audio, video, PDFs, and 3D meshes. Multimodal deep learning allows for a more holistic understanding of data, as well as increased accuracy and efficiency.</p><p>Jina AI is the most advanced MLOps platform for building multimodal AI applications in the cloud. Users can translate their data and a few lines of code into a production-ready service without dealing with infrastructure complexity or scaling hassles.</p><p>But first, what is multimodal deep learning? And what are its applications?</p><h2 id="what-does-modal-mean">What does "modal" mean?</h2><p>The term “modal” is a reference to the human senses: sight, hearing, touch, taste, smell. We use it here to mean <strong>data modality</strong>. You can think of it as indicating the <em>kind</em> of data you're working with, like <em>text, image, video</em>, etc.</p><p>Sometimes people use the terms “<strong>multimodal</strong>” and “<strong>unstructured</strong> <strong>data</strong>” interchangeably because both terms describe data that lacks a meaningful internal structure. <em>Multimodal data</em> is data that uses multiple modalities, while <em>unstructured data</em> is a catch-all term that describes any type of data that doesn't have a readily machine-readable structure.</p><h2 id="real-world-data-is-multimodal">Real-world data is multimodal</h2><p>In the early days of AI, research typically focused on one modality at a time. Some works dealt with written language, others with images, or speech. As a result, AI applications were almost always limited to a specific modality: A spam filter works with text. A photo classifier handles images. A speech recognizer deals with audio. </p><p>But real-world data is often multimodal. Video is usually accompanied by an audio track and may even have text subtitles. Social media posts, news articles, and any internet-published content routinely mix text with images, videos, and audio recordings. The need to manage and process this data is one factor motivating the development of multimodal AI.</p><h2 id="multimodal-vs-cross-modal">Multimodal vs cross-modal</h2><p>"Multimodal" and "cross<strong>-</strong>modal" are another two terms that are often confused for each other, but don't mean the same thing:</p><p><strong>Multimodal deep learning</strong> is a relatively new field that is concerned with algorithms that learn from data of multiple modalities. For example, a human can use both sight and hearing to identify a person or object, and multimodal deep learning is concerned with developing similar abilities for computers.</p><p><strong>Cross-modal deep learning</strong> is an approach to multimodal deep learning where information from one modality is used to improve performance in another. For example, if you see a picture of a bird, you might be able to identify it by its song when you hear it.</p><p>AI systems that are designed to work with multiple modalities are said to be “multimodal”. The term “cross-modality” is more accurate when referring narrowly to AI systems that integrate different modalities and use them together.</p><h2 id="multimodal-deep-learning-applications">Multimodal deep learning applications</h2><p>Multimodal deep learning has a broad array of potential uses. Among the applications already available:</p><ul><li>Automatically generating descriptions of images, like captioning for blind people.</li><li>Searching for images that match text queries (e.g. “find me a picture of a blue dog”).</li><li>Generative art system that create images from text descriptions (e.g. “make a picture of a blue dog”).</li></ul><p>All these applications rely on two pillar technologies: <strong>search </strong>and<strong> creation.</strong></p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/search-is-overfitted-create-create-is-underfitted-search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Search is Overfitted Create; Create is Underfitted Search</div><div class="kg-bookmark-description">The biggest competition of neural search may come from a technology that doesn’t even need embeddings as an intermediate representation – an end-to-end technology that directly returns the result you want.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--38-.png" alt=""></div></a></figure><h3 id="neural-search">Neural search</h3><p>The core idea behind neural search is to leverage state-of-the-art neural network models to build <em>every</em> component of a search system. In short, <strong>neural search is deep neural network-powered information retrieval</strong>.</p><p>Below is an example of an embedding space generated by <a href="https://github.com/jina-ai/docarray?ref=jina-ai-gmbh.ghost.io">DocArray</a> and used for content-based image retrieval.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://github.com/jina-ai/docarray/raw/main/.github/README-img/tsne.gif?raw=true" class="kg-image" alt="https://github.com/jina-ai/docarray/raw/main/.github/README-img/tsne.gif?raw=true"><figcaption>Projection of an array of image embeddings into a three dimensional display</figcaption></figure><p>Similar images are mapped together in the embedding space, and this property of the embedding space is what makes it useful for search applications. Searching for images that are most similar to some picture amounts to finding the closest images in this space, which you can easily do via the DocArray API:</p><pre><code class="language-python hljs">db = ...  <span class="hljs-comment"># a DocumentArray of indexed images</span>
 queries = ...  <span class="hljs-comment"># a DocumentArray of query images</span>
 
 db.find(queries, limit=<span class="hljs-number">9</span>)
@@ -26,4 +26,4 @@
 doc = Document(text=prompt).post(server_url, parameters={<span class="hljs-string">'num_images'</span>: <span class="hljs-number">8</span>})
 da = doc.matches
 
-da.plot_image_sprites(fig_size=(<span class="hljs-number">10</span>, <span class="hljs-number">10</span>), show_index=<span class="hljs-literal">True</span>)</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/dalle-flow/raw/main/.github/client-dalle.png?raw=true" class="kg-image" alt="https://github.com/jina-ai/dalle-flow/raw/main/.github/client-dalle.png?raw=true"></figure><p>Generative AI has a great deal of potential. It may revolutionize how we interact with machines by creating:</p><ul><li>More personalized experiences during computer-human interaction.</li><li>Realistic 3D images and videos of people and objects, which can be used in movies, video games, and other visual media.</li><li>Natural-sounding dialogue for video games or other interactive media.</li><li>New designs for products, which can be used in manufacturing and other industries.</li><li>New and innovative marketing materials.</li></ul><h2 id="multimodal-relationships">Multimodal relationships</h2><p>The way multimodal deep learning connects information in different modalities is equally central to generative AI and to neural search.</p><p>Let’s see the following illustration, where we represent the <code>cat</code> <code>dog</code> <code>human</code> <code>ape</code> texts and images into one embedding space:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-15.png" class="kg-image" alt="" width="1173" height="878" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-15.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-15.png 1173w" sizes="(min-width: 720px) 720px"></figure><p>The placement of these items in a single embedding space encodes relational information about their referents:</p><ul><li>The text embedding of <code>cat</code> is closer to <code>dog</code> (same modality);</li><li>The text embedding of <code>human</code> is closer to <code>ape</code> (same modality);</li><li>The text embedding of <code>cat</code> is farther from <code>human</code> (same modality);</li><li>The text embedding of <code>cat</code> is closer to the image embedding of <code>cat</code> (different modalities);</li><li>The image embedding of <code>cat</code> is closer to the image embedding of <code>dog</code> (same modalities);</li><li>etc.</li></ul><p>It's clear how this information is used in information retrieval, but generative AI also uses the same information. Instead of looking for nearest neighbors among a set of stored text or images, it constructs a text or image that has an embedding close to the prompt.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/alt_rel_img.png" class="kg-image" alt="../../_images/dna.png" width="1634" height="882" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/alt_rel_img.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/alt_rel_img.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/alt_rel_img.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/alt_rel_img.png 1634w" sizes="(min-width: 720px) 720px"></figure><p>In summary, the key to multimodal deep learning is understanding the way it relates different modalities. With this relationship in place, you can use it to search for existing data – i.e. <strong>neural search</strong> – or use it to make new data, which is <strong>generative AI</strong>. To learn more about multimodal deep learning, read the post below:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">The Paradigm Shift Towards Multimodal AI</div><div class="kg-bookmark-description">We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they’re right at the starting line of this paradigm shift, and build the applications of the future today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/9.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fwhat-is-multimodal-deep-learning-and-what-are-the-applications%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+da.plot_image_sprites(fig_size=(<span class="hljs-number">10</span>, <span class="hljs-number">10</span>), show_index=<span class="hljs-literal">True</span>)</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://github.com/jina-ai/dalle-flow/raw/main/.github/client-dalle.png?raw=true" class="kg-image" alt="https://github.com/jina-ai/dalle-flow/raw/main/.github/client-dalle.png?raw=true"></figure><p>Generative AI has a great deal of potential. It may revolutionize how we interact with machines by creating:</p><ul><li>More personalized experiences during computer-human interaction.</li><li>Realistic 3D images and videos of people and objects, which can be used in movies, video games, and other visual media.</li><li>Natural-sounding dialogue for video games or other interactive media.</li><li>New designs for products, which can be used in manufacturing and other industries.</li><li>New and innovative marketing materials.</li></ul><h2 id="multimodal-relationships">Multimodal relationships</h2><p>The way multimodal deep learning connects information in different modalities is equally central to generative AI and to neural search.</p><p>Let’s see the following illustration, where we represent the <code>cat</code> <code>dog</code> <code>human</code> <code>ape</code> texts and images into one embedding space:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-15.png" class="kg-image" alt="" width="1173" height="878" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-15.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-15.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-15.png 1173w" sizes="(min-width: 720px) 720px"></figure><p>The placement of these items in a single embedding space encodes relational information about their referents:</p><ul><li>The text embedding of <code>cat</code> is closer to <code>dog</code> (same modality);</li><li>The text embedding of <code>human</code> is closer to <code>ape</code> (same modality);</li><li>The text embedding of <code>cat</code> is farther from <code>human</code> (same modality);</li><li>The text embedding of <code>cat</code> is closer to the image embedding of <code>cat</code> (different modalities);</li><li>The image embedding of <code>cat</code> is closer to the image embedding of <code>dog</code> (same modalities);</li><li>etc.</li></ul><p>It's clear how this information is used in information retrieval, but generative AI also uses the same information. Instead of looking for nearest neighbors among a set of stored text or images, it constructs a text or image that has an embedding close to the prompt.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/alt_rel_img.png" class="kg-image" alt="../../_images/dna.png" width="1634" height="882" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/alt_rel_img.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/alt_rel_img.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/alt_rel_img.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/alt_rel_img.png 1634w" sizes="(min-width: 720px) 720px"></figure><p>In summary, the key to multimodal deep learning is understanding the way it relates different modalities. With this relationship in place, you can use it to search for existing data – i.e. <strong>neural search</strong> – or use it to make new data, which is <strong>generative AI</strong>. To learn more about multimodal deep learning, read the post below:</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/news/paradigm-shift-towards-multimodal-ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">The Paradigm Shift Towards Multimodal AI</div><div class="kg-bookmark-description">We are on the cusp of a new era in AI, one in which multimodal AI will be the norm. At Jina AI, our MLOps platform helps businesses and developers win while they’re right at the starting line of this paradigm shift, and build the applications of the future today.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/9.png" alt=""></div></a></figure></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Knowledge base</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fwhat-is-multimodal-deep-learning-and-what-are-the-applications%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Neural Search: The Definitive Guide to Building a Neural Search Engine with Jina</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">One of the most promising applications of cross-modal machine learning is neural search. The core idea of neural search is to leverage state-of-the-art deep neural networks to build every component of a search system.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 08, 2022 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="what-is-neural-search">What is Neural Search?</h2><p>One of the most promising applications of cross-modal machine learning is neural search. The core idea of neural search is to leverage state-of-the-art deep neural networks to build every component of a search system. In short, neural search is <strong>deep neural network-powered information retrieval</strong>. In academia, it’s often called neural information retrieval (neural IR for short).</p><p>Neural search is relevant to many industries. <strong>Search engines are critical for every business with an online presence</strong>. eCommerce platforms such as Amazon, Alibaba, and Walmart use search to match products with customers. Social media networks like Facebook and LinkedIn use search to connect people with content and groups. The popularity of mobile apps has led to a new type of search: app stores need efficient search algorithms to surface the right app for each user’s needs. Even non-digital businesses can benefit from neural IR technology. For example, hospitals could use it power next-generation clinical decision support systems by finding similar patients in past medical records.</p><h2 id="what-is-a-neural-search-engine">What is a Neural Search Engine?</h2><p>A neural search engine is simply a search engine that uses <strong>deep learning algorithms</strong> to perform its tasks. The three main components of any search engine are the indexer, the query processor, and the ranking algorithm. In a traditional search engine, each of these components would be designed separately using rule-based methods. However, in a neural search engine, all three components are designed using deep learning methods. </p><p>This approach has several advantages. First, it allows for end-to-end training of the system which can lead to better performance overall. Second, because all of the components are unified under one framework (like Jina), it’s easier to share information between them which can also lead to better performance. Finally, it makes it possible to use the same framework to build other types of neural search engines (e.g. an image search engine or a video search engine) which can be very helpful in domains where multiple modalities are important.</p><h2 id="differences-between-traditional-symbolic-search-and-neural-search">Differences Between Traditional (Symbolic) Search and Neural Search</h2><p>The biggest difference between neural search and symbolic search is that neural search uses vectors to represent data, whereas symbolic search relies on symbols. This allows neural search to be much <strong>more accurate</strong>, as it can utilize the relationships between data points in ways that symbolic search cannot. For instance, a vector representing an image can contain information about the shape, color, and content of the image, which can be used to better match it with other images or documents.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing--8-.svg" class="kg-image" alt="" width="300" height="126"><figcaption>Neural search utilizes the relationships between data points.</figcaption></figure><p>Additionally, neural search is not limited by the expressiveness of symbols like traditional approaches; rather, it can learn arbitrarily complex representations from data. This gives neural search an advantage when it comes to <strong>understanding the semantics</strong> of a query and retrieving matching documents.</p><p>Also, because neural search is based on learning algorithms rather than hand-crafted rules, it is able to <strong>adjust to changing real-world conditions</strong> over time (by fine-tuning). This is in contrast to symbolic search, which relies on hand-crafted rules that are brittle and require constant maintenance as the real world changes.</p><p>Finally, neural search is not limited to textual data; it can be used with <strong>any type of data</strong>, including images, videos, audio, and 3D data. Therefore, neural search enables the construction of search systems that are more flexible and powerful than traditional symbolic search engines.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-8.png" class="kg-image" alt="" width="1920" height="1080" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-8.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-8.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-8.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-8.png 1920w" sizes="(min-width: 720px) 720px"><figcaption>Neural search lets you search more than just textual data.</figcaption></figure><h2 id="what-are-neural-search%E2%80%99s-advantages">What Are Neural Search’s Advantages?</h2><ul><li>Natural language: With neural search, you can specify what you're looking for in <strong>natural language</strong> and the search engine will return results that match your query. This is a major improvement over traditional search engines, which can only understand keywords.</li><li>Improved usability: Neural IR systems can provide users with <strong>more natural ways to interact</strong> with them such as via conversational interfaces powered by chatbots.</li><li>Increased accuracy: Neural search is <strong>more accurate</strong> than traditional search methods. This is because it can learn complex patterns in data that are difficult for humans to code into rules. For example, a human might write rules to match documents containing the word “cat” with queries about pets, but a neural search engine could learn to match those documents without using the word “cat”, instead using words like "kitty" or "feline". This means that neural search engines can find relevant results even when the user’s query does not exactly match the terms used in the document.</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/wordcloud.png" class="kg-image" alt="" width="2000" height="2000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/wordcloud.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/wordcloud.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/wordcloud.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/wordcloud.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Neural search recognizes semantically similar words</figcaption></figure><p>One example is Google Search's use of RankBrain, a machine-learned ranking system that processes billions of searches per day and improves click-through rates by up to 15%.</p><p>Enhanced user experience: The improved accuracy of neural search engines leads to enhanced user experiences and satisfaction. When users get better results, they are <strong>more likely to use the system again and recommend it to others</strong>.</p><h2 id="difficulties-in-building-a-neural-search-engine">Difficulties in Building a Neural Search Engine</h2><p>Building a neural search engine is no small feat. While the benefits of using deep learning to power a search engine are numerous, there are also a number of challenges that must be addressed.</p><ul><li>Training a neural network requires <strong>large amounts of labeled data</strong> which can be difficult (and expensive) to obtain. This is especially true for complex tasks like search which require many different types of data (e.g., text, images, videos, etc.).</li><li>The need for <strong>expertise in deep learning algorithms and architectures</strong>: Deep learning is a very new field and there are still many open questions about which algorithms and architectures work best for various tasks. As a result, building a neural search engine requires access to experts who can design and implement the right models. This can make it difficult to find talent to build a team or consultants to help with specific challenges.</li><li>The need for <strong>computational resources</strong>: Deep learning algorithms are computationally intensive and training large models can take days or even weeks on standard hardware. This means that building a neural search engine requires access to powerful computing resources, such as GPUs.</li><li>Because all three components of the search engine (indexer, query processor, ranking algorithm) are unified under one framework (e.g. Jina), it’s important to carefully consider <strong>how information will flow between them</strong>. If not designed properly, this could lead to sub-optimal performance.</li></ul><p>Despite these challenges, building a neural search engine is an incredibly exciting endeavor with the potential to revolutionize how we access information on the web.</p><h2 id="guide-to-building-a-neural-search-engine">Guide to Building a Neural Search Engine</h2><p>Here is a step-by-step guide to building a neural search engine the <em>traditional</em> way:</p><ol><li>Collect and index your data: This step is where you take all of the data that you want to be searchable and put it into a format that can be read by a computer. For example, if you wanted to make all of the text in Wikipedia searchable, you would first need to download every article as an HTML file. Then, you would need to write code to extract the body text from each HTML file (ignoring the headers, sidebar content, etc.). This extracted text would then need to be saved in a format that can be read by your neural search engine (more on this later).</li><li>Choose or build a deep neural network: This step is where you choose or build the deep neural network that will power your neural search engine. As mentioned earlier, there are many different types of deep neural networks, so it’s important to choose one that is well-suited for the task of information retrieval. A few popular choices for this task are convolutional neural networks (CNNs) and recurrent neural networks (RNNs).</li><li>Train your deep neural network: Once you have chosen or built your deep neural network, it’s time to train it on your indexed data. The goal of this training process is to fine-tune the parameters of your neural network so that it produces good results when used for information retrieval tasks such as searching through indexed documents. There are many different ways to train a deep neural network; some common methods include supervised learning and reinforcement learning.</li><li>Use your trained model for inference: After your deep neural network has been trained, you can use it for inference tasks such as retrieving documents in response to user queries. When using your trained model for inference, there are typically three main components: 1) a document encoder which converts each document into a fixed-length vector representation; 2) a query encoder which converts user queries into vector representations; 3) a similarity function which compares the vectors produced by the document encoder and query encoder and outputs a score indicating how similar they are.</li></ol><p>That seems like a lot of work. But it gets a lot easier if you use a dedicated neural search framework like Jina.</p><h2 id="three-best-neural-search-frameworks-on-the-market">Three Best Neural Search Frameworks on the Market</h2><p><a href="https://jina.ai/product/jina/?ref=jina-ai-gmbh.ghost.io">Jina</a> is <em>the</em> <strong>open-source framework for neural search and semantic search</strong>. It scales easily with minimal resources thanks to its modular design, library ecosystem and growing community.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/product/jina/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina | Jina AI</div><div class="kg-bookmark-description">Build cross-modal and multi-modal applications in the cloud.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/assets/images/banner/core.jpg" alt=""></div></a></figure><p>Google Cloud Search: Built on the same technology that powers Googlebot, Cloud Search crawls, indexes, and serves content from G Suite—including Drive, Gmail, Sites, Groups, Calendar, Hangouts Chat messages and more—to surface the most relevant information for your users.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://workspace.google.com/products/cloud-search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Google Cloud Search: doorzoek Gmail, Drive en meer | Google&nbsp;Workspace</div><div class="kg-bookmark-description">Ontvang actuele, relevante hulp om overzicht te houden over e-mails, bestanden, meetings en meer. Gebruik de kracht van Google om te zoeken in Google&nbsp;Workspace.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://workspace.google.com/static/favicon.ico?cache=4926369" alt=""><span class="kg-bookmark-author">Google Workspace</span><span class="kg-bookmark-publisher">Andrew Lewis, Senior Manager, Winning Workplace,</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://lh3.googleusercontent.com/wZQCaQrSWMtfsI1l8JGBb8293-fl3CgugMKV6jo_NNdxYKOzMi28G-qaQktF7CXN4wOd8jWtruu75Kqd_65GweDZ2_x5PRXfL3o8PQ" alt=""></div></a></figure><p>Microsoft Azure Search: A cloud search service that provides a complete solution to deliver world-class search experiences for customers and developers. It offers built-in connectors that index data from many commonly used enterprise repositories such as SharePoint Online, Sitecore CMS, Drupal 8+ &amp; 9+, SQL Server databases (on premises &amp; in Azure), Cosmos DB, etc.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://azure.microsoft.com/en-us/products/search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Azure Cognitive Search - Cloud Search Service | Microsoft Azure</div><div class="kg-bookmark-description">Azure Cognitive Search is a fully managed cloud search service that provides a better user experience for customers. Add Cognitive Search to your websites.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://azurecomcdn.azureedge.net/cvt-de9ca363d31f6b1491ad067281bec80769be2c19b5b9c925ad39869042c183b5/images/icon/live-tile/azure-310x310.png" alt=""><span class="kg-bookmark-author">Microsoft Azure</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://azurecomcdn.azureedge.net/cvt-de9ca363d31f6b1491ad067281bec80769be2c19b5b9c925ad39869042c183b5/images/shared/social/azure-icon-250x250.png" alt=""></div></a></figure><h2 id="jina-one-of-the-best-neural-search-frameworks">Jina: One of the Best Neural Search Frameworks</h2><p>Neural search is still an emerging technology, and there are not many mature open-source options to choose from. This is where Jina comes in – it is the most complete open-source solution for neural search available today. Not only does it provide all the necessary components for building a neural search system, but it also makes deploying and scaling such a system easy thanks to its <strong>cloud-native design</strong>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/product/jina/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina | Jina AI</div><div class="kg-bookmark-description">Build cross-modal and multi-modal applications in the cloud.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/assets/images/banner/core.jpg" alt=""></div></a></figure><p>Another key advantage of using Jina is its <strong>performance</strong>. Thanks to its unique architecture based on microservices, Jina can <a href="https://docs.jina.ai/how-to/scale-out/?ref=jina-ai-gmbh.ghost.io">scale horizontally</a> very easily without sacrificing performance. And because each component of a Jina system can run in parallel, a neural search system built with Jina can achieve lightning-fast retrieval speeds.</p><p>In addition to being scalable and fast, Jina is also very <strong>flexible</strong>. It supports all popular deep learning frameworks (TensorFlow, PyTorch, MXNet etc.), so you can use whichever one you’re most comfortable with. And because it uses the gRPC protocol internally, you can easily integrate it with other systems using Jina Client or any of the gRPC language bindings (including Java, Python, C++ and Go).</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://docs.jina.ai/_images/arch-overview.svg" class="kg-image" alt="../../_images/arch-overview.svg"><figcaption>Jina uses gRPC internally and offers gRPC, RESTful and WebSocket gateways</figcaption></figure><p>One final advantage of Jina over other tools is its <strong>rich ecosystem</strong>. In addition to the core framework itself, Jina also provides a number of helpful services and libraries that make working with neural search easier (such as an <a href="https://hub.jina.ai/?ref=jina-ai-gmbh.ghost.io">Executor Hub</a> for sharing trained models and a <a href="https://docs.jina.ai/fundamentals/jcloud/?ref=jina-ai-gmbh.ghost.io">CLI tool for managing deployments</a>). Plus, thanks to its support for both <a href="https://docs.jina.ai/cloud-nativeness/k8s/?ref=jina-ai-gmbh.ghost.io">Kubernetes</a> and <a href="https://docs.jina.ai/cloud-nativeness/docker-compose/?ref=jina-ai-gmbh.ghost.io">Docker Compose</a>, Jina can be used in a wide variety of environments.</p><h2 id="conclusion">Conclusion</h2><p>In conclusion, neural search is a powerful tool that is rewriting the rules of search. The core idea is to leverage deep neural networks to build every component of a search system. This approach has led to significant advances in the field of information retrieval and has the potential to revolutionize the way we search for information.</p><p>Applications that use neural search are able to <strong>better understand the user’s intent</strong> and <strong>provide more relevant results</strong>. As the technology matures, it will become increasingly important for search engines and other information retrieval systems to adopt neural search in order to remain competitive. In addition to its potentially significant impact on commercial search applications, neural search also holds great promise for academic research in areas such as digital humanities and scientific literature discovery.</p><p>The ability to automatically extract features from unstructured data sources and the improved semantical understanding of queries are two key advantages that make neural search a very promising technology. In addition, because neural models are learned from data, they are <strong>more easily adapted</strong> to changes in the underlying distribution than rule-based methods. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Rationale</div><div class="q-item__label q-item__label--caption text-caption">Ultimate AI decision-making tools</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="30ea06d8-109a-494f-8e38-abfaa97c1643" aria-label="Expand &quot;For Developers&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">For Developers</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="30ea06d8-109a-494f-8e38-abfaa97c1643" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/docarray/docarray"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/doc-array.35372518.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Neural Search: The Definitive Guide to Building a Neural Search Engine with Jina</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">One of the most promising applications of cross-modal machine learning is neural search. The core idea of neural search is to leverage state-of-the-art deep neural networks to build every component of a search system.</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/08/Jjqb-JeY_400x400.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Jina AI</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">November 08, 2022 • 9 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><h2 id="what-is-neural-search">What is Neural Search?</h2><p>One of the most promising applications of cross-modal machine learning is neural search. The core idea of neural search is to leverage state-of-the-art deep neural networks to build every component of a search system. In short, neural search is <strong>deep neural network-powered information retrieval</strong>. In academia, it’s often called neural information retrieval (neural IR for short).</p><p>Neural search is relevant to many industries. <strong>Search engines are critical for every business with an online presence</strong>. eCommerce platforms such as Amazon, Alibaba, and Walmart use search to match products with customers. Social media networks like Facebook and LinkedIn use search to connect people with content and groups. The popularity of mobile apps has led to a new type of search: app stores need efficient search algorithms to surface the right app for each user’s needs. Even non-digital businesses can benefit from neural IR technology. For example, hospitals could use it power next-generation clinical decision support systems by finding similar patients in past medical records.</p><h2 id="what-is-a-neural-search-engine">What is a Neural Search Engine?</h2><p>A neural search engine is simply a search engine that uses <strong>deep learning algorithms</strong> to perform its tasks. The three main components of any search engine are the indexer, the query processor, and the ranking algorithm. In a traditional search engine, each of these components would be designed separately using rule-based methods. However, in a neural search engine, all three components are designed using deep learning methods. </p><p>This approach has several advantages. First, it allows for end-to-end training of the system which can lead to better performance overall. Second, because all of the components are unified under one framework (like Jina), it’s easier to share information between them which can also lead to better performance. Finally, it makes it possible to use the same framework to build other types of neural search engines (e.g. an image search engine or a video search engine) which can be very helpful in domains where multiple modalities are important.</p><h2 id="differences-between-traditional-symbolic-search-and-neural-search">Differences Between Traditional (Symbolic) Search and Neural Search</h2><p>The biggest difference between neural search and symbolic search is that neural search uses vectors to represent data, whereas symbolic search relies on symbols. This allows neural search to be much <strong>more accurate</strong>, as it can utilize the relationships between data points in ways that symbolic search cannot. For instance, a vector representing an image can contain information about the shape, color, and content of the image, which can be used to better match it with other images or documents.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-drawing--8-.svg" class="kg-image" alt="" width="300" height="126"><figcaption>Neural search utilizes the relationships between data points.</figcaption></figure><p>Additionally, neural search is not limited by the expressiveness of symbols like traditional approaches; rather, it can learn arbitrarily complex representations from data. This gives neural search an advantage when it comes to <strong>understanding the semantics</strong> of a query and retrieving matching documents.</p><p>Also, because neural search is based on learning algorithms rather than hand-crafted rules, it is able to <strong>adjust to changing real-world conditions</strong> over time (by fine-tuning). This is in contrast to symbolic search, which relies on hand-crafted rules that are brittle and require constant maintenance as the real world changes.</p><p>Finally, neural search is not limited to textual data; it can be used with <strong>any type of data</strong>, including images, videos, audio, and 3D data. Therefore, neural search enables the construction of search systems that are more flexible and powerful than traditional symbolic search engines.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-8.png" class="kg-image" alt="" width="1920" height="1080" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/image-8.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/image-8.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/image-8.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/image-8.png 1920w" sizes="(min-width: 720px) 720px"><figcaption>Neural search lets you search more than just textual data.</figcaption></figure><h2 id="what-are-neural-search%E2%80%99s-advantages">What Are Neural Search’s Advantages?</h2><ul><li>Natural language: With neural search, you can specify what you're looking for in <strong>natural language</strong> and the search engine will return results that match your query. This is a major improvement over traditional search engines, which can only understand keywords.</li><li>Improved usability: Neural IR systems can provide users with <strong>more natural ways to interact</strong> with them such as via conversational interfaces powered by chatbots.</li><li>Increased accuracy: Neural search is <strong>more accurate</strong> than traditional search methods. This is because it can learn complex patterns in data that are difficult for humans to code into rules. For example, a human might write rules to match documents containing the word “cat” with queries about pets, but a neural search engine could learn to match those documents without using the word “cat”, instead using words like "kitty" or "feline". This means that neural search engines can find relevant results even when the user’s query does not exactly match the terms used in the document.</li></ul><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/wordcloud.png" class="kg-image" alt="" width="2000" height="2000" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/wordcloud.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/wordcloud.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/11/wordcloud.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/11/wordcloud.png 2400w" sizes="(min-width: 720px) 720px"><figcaption>Neural search recognizes semantically similar words</figcaption></figure><p>One example is Google Search's use of RankBrain, a machine-learned ranking system that processes billions of searches per day and improves click-through rates by up to 15%.</p><p>Enhanced user experience: The improved accuracy of neural search engines leads to enhanced user experiences and satisfaction. When users get better results, they are <strong>more likely to use the system again and recommend it to others</strong>.</p><h2 id="difficulties-in-building-a-neural-search-engine">Difficulties in Building a Neural Search Engine</h2><p>Building a neural search engine is no small feat. While the benefits of using deep learning to power a search engine are numerous, there are also a number of challenges that must be addressed.</p><ul><li>Training a neural network requires <strong>large amounts of labeled data</strong> which can be difficult (and expensive) to obtain. This is especially true for complex tasks like search which require many different types of data (e.g., text, images, videos, etc.).</li><li>The need for <strong>expertise in deep learning algorithms and architectures</strong>: Deep learning is a very new field and there are still many open questions about which algorithms and architectures work best for various tasks. As a result, building a neural search engine requires access to experts who can design and implement the right models. This can make it difficult to find talent to build a team or consultants to help with specific challenges.</li><li>The need for <strong>computational resources</strong>: Deep learning algorithms are computationally intensive and training large models can take days or even weeks on standard hardware. This means that building a neural search engine requires access to powerful computing resources, such as GPUs.</li><li>Because all three components of the search engine (indexer, query processor, ranking algorithm) are unified under one framework (e.g. Jina), it’s important to carefully consider <strong>how information will flow between them</strong>. If not designed properly, this could lead to sub-optimal performance.</li></ul><p>Despite these challenges, building a neural search engine is an incredibly exciting endeavor with the potential to revolutionize how we access information on the web.</p><h2 id="guide-to-building-a-neural-search-engine">Guide to Building a Neural Search Engine</h2><p>Here is a step-by-step guide to building a neural search engine the <em>traditional</em> way:</p><ol><li>Collect and index your data: This step is where you take all of the data that you want to be searchable and put it into a format that can be read by a computer. For example, if you wanted to make all of the text in Wikipedia searchable, you would first need to download every article as an HTML file. Then, you would need to write code to extract the body text from each HTML file (ignoring the headers, sidebar content, etc.). This extracted text would then need to be saved in a format that can be read by your neural search engine (more on this later).</li><li>Choose or build a deep neural network: This step is where you choose or build the deep neural network that will power your neural search engine. As mentioned earlier, there are many different types of deep neural networks, so it’s important to choose one that is well-suited for the task of information retrieval. A few popular choices for this task are convolutional neural networks (CNNs) and recurrent neural networks (RNNs).</li><li>Train your deep neural network: Once you have chosen or built your deep neural network, it’s time to train it on your indexed data. The goal of this training process is to fine-tune the parameters of your neural network so that it produces good results when used for information retrieval tasks such as searching through indexed documents. There are many different ways to train a deep neural network; some common methods include supervised learning and reinforcement learning.</li><li>Use your trained model for inference: After your deep neural network has been trained, you can use it for inference tasks such as retrieving documents in response to user queries. When using your trained model for inference, there are typically three main components: 1) a document encoder which converts each document into a fixed-length vector representation; 2) a query encoder which converts user queries into vector representations; 3) a similarity function which compares the vectors produced by the document encoder and query encoder and outputs a score indicating how similar they are.</li></ol><p>That seems like a lot of work. But it gets a lot easier if you use a dedicated neural search framework like Jina.</p><h2 id="three-best-neural-search-frameworks-on-the-market">Three Best Neural Search Frameworks on the Market</h2><p><a href="https://jina.ai/product/jina/?ref=jina-ai-gmbh.ghost.io">Jina</a> is <em>the</em> <strong>open-source framework for neural search and semantic search</strong>. It scales easily with minimal resources thanks to its modular design, library ecosystem and growing community.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/product/jina/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina | Jina AI</div><div class="kg-bookmark-description">Build cross-modal and multi-modal applications in the cloud.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/assets/images/banner/core.jpg" alt=""></div></a></figure><p>Google Cloud Search: Built on the same technology that powers Googlebot, Cloud Search crawls, indexes, and serves content from G Suite—including Drive, Gmail, Sites, Groups, Calendar, Hangouts Chat messages and more—to surface the most relevant information for your users.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://workspace.google.com/products/cloud-search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Google Cloud Search: doorzoek Gmail, Drive en meer | Google&nbsp;Workspace</div><div class="kg-bookmark-description">Ontvang actuele, relevante hulp om overzicht te houden over e-mails, bestanden, meetings en meer. Gebruik de kracht van Google om te zoeken in Google&nbsp;Workspace.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://workspace.google.com/static/favicon.ico?cache=4926369" alt=""><span class="kg-bookmark-author">Google Workspace</span><span class="kg-bookmark-publisher">Andrew Lewis, Senior Manager, Winning Workplace,</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://lh3.googleusercontent.com/wZQCaQrSWMtfsI1l8JGBb8293-fl3CgugMKV6jo_NNdxYKOzMi28G-qaQktF7CXN4wOd8jWtruu75Kqd_65GweDZ2_x5PRXfL3o8PQ" alt=""></div></a></figure><p>Microsoft Azure Search: A cloud search service that provides a complete solution to deliver world-class search experiences for customers and developers. It offers built-in connectors that index data from many commonly used enterprise repositories such as SharePoint Online, Sitecore CMS, Drupal 8+ &amp; 9+, SQL Server databases (on premises &amp; in Azure), Cosmos DB, etc.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://azure.microsoft.com/en-us/products/search/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Azure Cognitive Search - Cloud Search Service | Microsoft Azure</div><div class="kg-bookmark-description">Azure Cognitive Search is a fully managed cloud search service that provides a better user experience for customers. Add Cognitive Search to your websites.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://azurecomcdn.azureedge.net/cvt-de9ca363d31f6b1491ad067281bec80769be2c19b5b9c925ad39869042c183b5/images/icon/live-tile/azure-310x310.png" alt=""><span class="kg-bookmark-author">Microsoft Azure</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://azurecomcdn.azureedge.net/cvt-de9ca363d31f6b1491ad067281bec80769be2c19b5b9c925ad39869042c183b5/images/shared/social/azure-icon-250x250.png" alt=""></div></a></figure><h2 id="jina-one-of-the-best-neural-search-frameworks">Jina: One of the Best Neural Search Frameworks</h2><p>Neural search is still an emerging technology, and there are not many mature open-source options to choose from. This is where Jina comes in – it is the most complete open-source solution for neural search available today. Not only does it provide all the necessary components for building a neural search system, but it also makes deploying and scaling such a system easy thanks to its <strong>cloud-native design</strong>.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://jina.ai/product/jina/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">Jina | Jina AI</div><div class="kg-bookmark-description">Build cross-modal and multi-modal applications in the cloud.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://jina.ai/android-icon-192x192.png" alt=""><span class="kg-bookmark-author">Jina AI</span><span class="kg-bookmark-publisher">Jina AI</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://jina.ai/assets/images/banner/core.jpg" alt=""></div></a></figure><p>Another key advantage of using Jina is its <strong>performance</strong>. Thanks to its unique architecture based on microservices, Jina can <a href="https://docs.jina.ai/how-to/scale-out/?ref=jina-ai-gmbh.ghost.io">scale horizontally</a> very easily without sacrificing performance. And because each component of a Jina system can run in parallel, a neural search system built with Jina can achieve lightning-fast retrieval speeds.</p><p>In addition to being scalable and fast, Jina is also very <strong>flexible</strong>. It supports all popular deep learning frameworks (TensorFlow, PyTorch, MXNet etc.), so you can use whichever one you’re most comfortable with. And because it uses the gRPC protocol internally, you can easily integrate it with other systems using Jina Client or any of the gRPC language bindings (including Java, Python, C++ and Go).</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://docs.jina.ai/_images/arch-overview.svg" class="kg-image" alt="../../_images/arch-overview.svg"><figcaption>Jina uses gRPC internally and offers gRPC, RESTful and WebSocket gateways</figcaption></figure><p>One final advantage of Jina over other tools is its <strong>rich ecosystem</strong>. In addition to the core framework itself, Jina also provides a number of helpful services and libraries that make working with neural search easier (such as an <a href="https://hub.jina.ai/?ref=jina-ai-gmbh.ghost.io">Executor Hub</a> for sharing trained models and a <a href="https://docs.jina.ai/fundamentals/jcloud/?ref=jina-ai-gmbh.ghost.io">CLI tool for managing deployments</a>). Plus, thanks to its support for both <a href="https://docs.jina.ai/cloud-nativeness/k8s/?ref=jina-ai-gmbh.ghost.io">Kubernetes</a> and <a href="https://docs.jina.ai/cloud-nativeness/docker-compose/?ref=jina-ai-gmbh.ghost.io">Docker Compose</a>, Jina can be used in a wide variety of environments.</p><h2 id="conclusion">Conclusion</h2><p>In conclusion, neural search is a powerful tool that is rewriting the rules of search. The core idea is to leverage deep neural networks to build every component of a search system. This approach has led to significant advances in the field of information retrieval and has the potential to revolutionize the way we search for information.</p><p>Applications that use neural search are able to <strong>better understand the user’s intent</strong> and <strong>provide more relevant results</strong>. As the technology matures, it will become increasingly important for search engines and other information retrieval systems to adopt neural search in order to remain competitive. In addition to its potentially significant impact on commercial search applications, neural search also holds great promise for academic research in areas such as digital humanities and scientific literature discovery.</p><p>The ability to automatically extract features from unstructured data sources and the improved semantical understanding of queries are two key advantages that make neural search a very promising technology. In addition, because neural models are learned from data, they are <strong>more easily adapted</strong> to changes in the underlying distribution than rule-based methods. 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(opens in new window)"><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square text-white q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fab fa-reddit" aria-hidden="true" role="img"> </i></span></button></a><button data-v-ecd25db0="" class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--square q-btn--actionable q-focusable q-hoverable q-btn--square q-py-lg" tabindex="0" type="button"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">rss_feed</i></span></button></div></div></div><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark" aria-orientation="horizontal"><div data-v-ecd25db0="" class="text-h6 text-grey-2 text-weight-bold q-mt-lg">Learn more</div><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/case-study-revolutionizing-e-commerce-user-experience-and-streamlining-search-with-scenexplain" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Case Study: Revolutionizing E-Commerce User Experience And Streamlining Search With SceneXplain</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">See how SceneXplain enhanced search quality, and enriched user experience for a top European e-commerce platform.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 30, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/unveiling-the-magic-become-a-part-of-promptperfects-affiliate-family" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Unveiling the Magic: Become a Part of PromptPerfect's Affiliate Family</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Introducing PromptPerfect's Affiliate Program, an initiative for enthusiasts to bring attention to Jina AI's innovative technologies and show our appreciation to the community that makes PromptPerfect great!</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/miru.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Miruna Nedelcu</div><div class="q-item__label q-item__label--caption text-caption">October 18, 2023 • 3 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/10/Explore-image-storytelling-beyond-pixels.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/scenexplain-vs-gpt-4-vision-the-best-image-captioning-tool-in-2023" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">SceneXplain vs. GPT-4 Vision: The Best Image Captioning Tool in 2023?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Discover the future of visual comprehension with SceneXplain, the leading image captioning tool of 2023. Dive deep into its transformative features, real-world applications, and see how it stands tall against GPT-4 Vision. </div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">September 28, 2023 • 5 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/09/Explore-image-storytelling-beyond-pixels--9-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">What's New in PromptPerfect? New Optimizer, Streaming and Bulk Optimization</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">PromptPerfect's brand new features are fresh out of the oven - try our new optimizer, streaming from Prompt-as-Service, and bulk prompt optimization</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 16, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Other people take holidays in summer. But we've been hard at work and sweating through the heat to make PromptPerfect even perfecter.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, MidJourney and StableDiffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficienc…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><p>Here's a rundown of what's new:</p><h2 id="brand-new-optimizer">Brand new optimizer</h2><p>The headline feature! We've made a bunch of enhancements and optimizations for your prompting pleasure.</p><h3 id="better-promptsespecially-for-images">Better prompts - especially for images</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-5.png" class="kg-image" alt="" width="1356" height="1720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-5.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-5.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-5.png 1356w" sizes="(min-width: 720px) 720px"></figure><h3 id="enhance-prompts-with-automatic-suggestions-and-completions">Enhance prompts with automatic suggestions and completions</h3><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/promptperfect-autocomplete.mp4" poster="https://img.spacergif.org/v1/1394x892/0a/spacer.png" width="1394" height="892" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember133.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h3 id="generate-up-to-four-optimized-results-at-once-and-choose-the-most-suitable">Generate up to four optimized results at once and choose the most suitable</h3><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/diversified_results.mp4" poster="https://img.spacergif.org/v1/2030x1080/0a/spacer.png" width="2030" height="1080" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember155.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>Note that the new optimizer is available not just on the Prompts page but also on the Streamline and Few-Shot Prompts pages.</p><h2 id="stream-your-prompt-as-service-output">Stream your Prompt-as-Service output.</h2><p>The latest update to Prompt-as-Service has implemented seamless streaming output. Now, you can say goodbye to waiting for results, as our new feature ensures a real-time flow of responses, making your experience even more dynamic and efficient.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/stream_output.mp4" poster="https://img.spacergif.org/v1/2030x1080/0a/spacer.png" width="2030" height="1080" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember93.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="manage-bulk-prompt-optimization-results">Manage bulk prompt optimization results.</h2><p>On the prompts page you can now switch between table and card view, toggle columns, and compare before-and-after views.</p><figure class="kg-card kg-embed-card"><div class="twitter-tweet twitter-tweet-rendered" style="display: flex; max-width: 550px; width: 100%; margin-top: 10px; margin-bottom: 10px;"><iframe id="twitter-widget-0" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" class="" style="position: static; visibility: visible; width: 550px; height: 645px; display: block; flex-grow: 1;" title="X Post" src="https://platform.twitter.com/embed/Tweet.html?dnt=false&amp;embedId=twitter-widget-0&amp;features=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%3D%3D&amp;frame=false&amp;hideCard=false&amp;hideThread=false&amp;id=1689717977757704193&amp;lang=en&amp;origin=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fwhats-new-in-promptperfect-new-optimizer-streaming-bulk-optimization%2F&amp;sessionId=84890feb94eb962e5c6c74d287087fa6cd49de39&amp;theme=light&amp;widgetsVersion=2615f7e52b7e0%3A1702314776716&amp;width=550px" data-tweet-id="1689717977757704193"></iframe></div>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">PromptPerfect's brand new features are fresh out of the oven - try our new optimizer, streaming from Prompt-as-Service, and bulk prompt optimization</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Engineering Group</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">August 16, 2023 • 2 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Other people take holidays in summer. But we've been hard at work and sweating through the heat to make PromptPerfect even perfecter.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection. Prompt Engineering, Optimizing, Debugging and Hosting.</div><div class="kg-bookmark-description">Unlock advanced prompt engineering and prompt optimization for large models such as GPT-4, ChatGPT, MidJourney and StableDiffusion. Seamlessly deploy your text and image prompts as dedicated services with our free prompt hosting plan. Enhance your large models with superior performance and efficienc…</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><p>Here's a rundown of what's new:</p><h2 id="brand-new-optimizer">Brand new optimizer</h2><p>The headline feature! We've made a bunch of enhancements and optimizations for your prompting pleasure.</p><h3 id="better-promptsespecially-for-images">Better prompts - especially for images</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-5.png" class="kg-image" alt="" width="1356" height="1720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/08/image-5.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2023/08/image-5.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2023/08/image-5.png 1356w" sizes="(min-width: 720px) 720px"></figure><h3 id="enhance-prompts-with-automatic-suggestions-and-completions">Enhance prompts with automatic suggestions and completions</h3><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/promptperfect-autocomplete.mp4" poster="https://img.spacergif.org/v1/1394x892/0a/spacer.png" width="1394" height="892" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember133.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h3 id="generate-up-to-four-optimized-results-at-once-and-choose-the-most-suitable">Generate up to four optimized results at once and choose the most suitable</h3><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/diversified_results.mp4" poster="https://img.spacergif.org/v1/2030x1080/0a/spacer.png" width="2030" height="1080" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember155.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>Note that the new optimizer is available not just on the Prompts page but also on the Streamline and Few-Shot Prompts pages.</p><h2 id="stream-your-prompt-as-service-output">Stream your Prompt-as-Service output.</h2><p>The latest update to Prompt-as-Service has implemented seamless streaming output. Now, you can say goodbye to waiting for results, as our new feature ensures a real-time flow of responses, making your experience even more dynamic and efficient.</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/08/stream_output.mp4" poster="https://img.spacergif.org/v1/2030x1080/0a/spacer.png" width="2030" height="1080" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/08/media-thumbnail-ember93.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><h2 id="manage-bulk-prompt-optimization-results">Manage bulk prompt optimization results.</h2><p>On the prompts page you can now switch between table and card view, toggle columns, and compare before-and-after views.</p><figure class="kg-card kg-embed-card"><blockquote class="twitter-tweet"><p lang="en" dir="ltr">Prefer cards or tables? With PromptPerfect 0.31, the choice is yours! Effortlessly manage your bulk prompt optimization results. Toggle columns and compare before-and-after views. Streamline your experience, your way. 🔄✨ <a href="https://twitter.com/hashtag/PromptPerfect?src=hash&amp;ref_src=twsrc%5Etfw&amp;ref=jina-ai-gmbh.ghost.io">#PromptPerfect</a><a href="https://t.co/i00h36SDrR?ref=jina-ai-gmbh.ghost.io">https://t.co/i00h36SDrR</a> <a href="https://t.co/X2jsVUQHRk?ref=jina-ai-gmbh.ghost.io">pic.twitter.com/X2jsVUQHRk</a></p>— Han Xiao (@hxiao) <a href="https://twitter.com/hxiao/status/1689717977757704193?ref_src=twsrc%5Etfw&amp;ref=jina-ai-gmbh.ghost.io">August 10, 2023</a></blockquote>
 <script async="" src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
-</figure><h2 id="what-would-you-like-to-see">What would you like to see?</h2><p>What new features would you like to see in PromptPerfect? Let us know on our <a href="https://discord.com/channels/1106542220112302130/1106543917979148369?ref=jina-ai-gmbh.ghost.io">Discord channel</a>!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://discord.com/channels/1106542220112302130/1106543917979148369?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Join PromptPerfect Discord</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fwhats-new-in-promptperfect-new-optimizer-streaming-bulk-optimization%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">DocArray 0.40.0 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">DocArray is a library for representing, sending and storing multi-modal data, perfect for Machine Learning applications.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 22, 2023 • 2 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-DocArray-dak-1.jpeg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-2-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.2 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 14, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark-1.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/jina-3-23-1-update" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Jina 3.23.1 Update</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Jina is a MLOps framework that empowers anyone to build cross-modal and multi-modal applications on the cloud.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/1.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Engineering Group</div><div class="q-item__label q-item__label--caption text-caption">December 01, 2023 • 1 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/12/Image-Jina-dark.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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+</figure><h2 id="what-would-you-like-to-see">What would you like to see?</h2><p>What new features would you like to see in PromptPerfect? Let us know on our <a href="https://discord.com/channels/1106542220112302130/1106543917979148369?ref=jina-ai-gmbh.ghost.io">Discord channel</a>!</p><div class="kg-card kg-button-card kg-align-center"><a href="https://discord.com/channels/1106542220112302130/1106543917979148369?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Join PromptPerfect Discord</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Software updates</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fwhats-new-in-promptperfect-new-optimizer-streaming-bulk-optimization%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>What's Next for Prompt Engineering? PromptPerfect's Prompt as a Service!</title><meta charset="utf-8"><meta name="title" content="What's Next for Prompt Engineering? PromptPerfect's Prompt as a Service!"><meta name="description" content="Deploy prompts and flexible template prompts as REST API services, and integrate them into your applications with just a few clicks"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/whats-next-for-prompt-engineering-prompts-as-a-service"><meta property="og:title" content="What's Next for Prompt Engineering? PromptPerfect's Prompt as a Service!"><meta property="og:description" content="Deploy prompts and flexible template prompts as REST API services, and integrate them into your applications with just a few clicks"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Pic.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/whats-next-for-prompt-engineering-prompts-as-a-service"><meta property="twitter:title" content="What's Next for Prompt Engineering? PromptPerfect's Prompt as a Service!"><meta property="twitter:description" content="Deploy prompts and flexible template prompts as REST API services, and integrate them into your applications with just a few clicks"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Pic.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>What's Next for Prompt Engineering? PromptPerfect's Prompt as a Service!</title><meta charset="utf-8"><meta name="title" content="What's Next for Prompt Engineering? PromptPerfect's Prompt as a Service!"><meta name="description" content="Deploy prompts and flexible template prompts as REST API services, and integrate them into your applications with just a few clicks"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/whats-next-for-prompt-engineering-prompts-as-a-service"><meta property="og:title" content="What's Next for Prompt Engineering? PromptPerfect's Prompt as a Service!"><meta property="og:description" content="Deploy prompts and flexible template prompts as REST API services, and integrate them into your applications with just a few clicks"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Pic.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/whats-next-for-prompt-engineering-prompts-as-a-service"><meta property="twitter:title" content="What's Next for Prompt Engineering? PromptPerfect's Prompt as a Service!"><meta property="twitter:description" content="Deploy prompts and flexible template prompts as REST API services, and integrate them into your applications with just a few clicks"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Pic.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DevGPT</div><div class="q-item__label q-item__label--caption text-caption">Your virtual development team</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/rungpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/run-gpt.5571707e.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">What's Next for Prompt Engineering? PromptPerfect's Prompt as a Service!</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Deploy prompts and flexible template prompts as REST API services, and integrate them into your applications with just a few clicks</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 22, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Announcing a brand new feature for PromptPerfect: Prompt as a Service! Now you can host your own flexible prompts on PromptPerfect, generate variants at will, and interact with language and image models via a REST API.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/services?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection with AI Prompt Engineering</div><div class="kg-bookmark-description">Optimize prompts for GPT-4, ChatGPT, StableLM, Claude, MidJourney, DALL-E, StableDiffusion, Kandinsky, and Lexica. Experience automatic prompt engineering done right. Create compelling Text and Image prompts today with our AI prompt generator.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><p>In this post we’ll cover several use cases for Prompt as a Service - though I’m sure you can come up with some ideas yourself!</p><p>We’ll cover:</p><ul><li>How to automate your tiring friendships</li><li>Building a SaaS (Sandwiches as a Service)</li><li>Generating knock-off Mona Lisas in the style of different artists</li></ul><p>For each of these, we’ll walk through the interface and show you to access your Prompt as a Service using cURL, Python, or JavaScript.</p><p>But first, a quick video overview:</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/promptperfect-paas-2.mp4" poster="https://img.spacergif.org/v1/2914x1660/0a/spacer.png" width="2914" height="1660" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/06/media-thumbnail-ember182.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>Now, let's dive in. Making your prompt servable is as easy as 1, 2, 3:</p><ol><li>Write your template</li><li>Specify variables with <code>[VAR]</code> or <code>$VAR</code></li><li>Deploy your prompt with one click</li></ol><p>You can also switch out your language model (or image model - keep reading for that):</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--14-.png" class="kg-image" alt="" width="582" height="150"></figure><p>By default, you’ll need a token to access your prompt, but with one click more you can make it publicly accessible:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--15-.png" class="kg-image" alt="" width="553" height="73"></figure><h2 id="prompt-as-a-service-in-action">Prompt as a Service in Action</h2><h3 id="automating-friendships-for-fun-and-profit">Automating friendships for fun and profit</h3><p>I've got this friend called Izzie. Well, that's not his <em>actual</em> name. But he always falls head over heels for some guy and asks:</p><blockquote>"Is he into me? Do you think he's into me? He says I'm like a _____ to him"</blockquote><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">👨🏻‍🤝‍👨🏽</div><div class="kg-callout-text">Izzie isn’t his real name. Any resemblance to people living, dead or undead is purely coincidental.</div></div><p>I think we've all had a friend like Izzie before. Like a sickly kitten that won’t budge from sitting on your keyboard. They’re annoying, but you just feel this instinct to look after them.</p><p>But after a while, instincts be damned. That's why I'm going to use Prompt as a Service to automate away this tiring relationship. Like an automatic cat feeder for humans, if you will.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-8.png" class="kg-image" alt="" width="370" height="640"><figcaption>Friendship is <s>priceless</s> about 8 Euros with free shipping</figcaption></figure><p>First, we create the prompt via PromptPerfect’s <strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong>Services</strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong> tool. We’ll specify a <code>[person]</code> variable which can be switched out for <code>mother</code>, <code>brother</code>, <code>cousin</code> or whatever:</p><pre><code class="language-jsx hljs language-javascript"><span class="hljs-title class_">Is</span> <span class="hljs-variable language_">this</span> guy into me? <span class="hljs-title class_">He</span> says I<span class="hljs-string">'m like a [person] to him
-</span></code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--16--1.png" class="kg-image" alt="" width="589" height="776"></figure><p>Testing it gives us more or less expected results:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--17-.png" class="kg-image" alt="" width="589" height="443"></figure><p>Right now, access is private, so you need a token to access it:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-13.png" class="kg-image" alt="" width="685" height="125" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image-13.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-13.png 685w"></figure><p>But we can make it publicly accessible for all the Izzies of the world, without the need for tokens:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--18-.png" class="kg-image" alt="" width="589" height="76"></figure><p>You can access the service via the REST API:</p><pre><code class="language-shell hljs">curl "https://api.promptperfect.jina.ai/4TFmeCo3aSBDlC44Wik8" \\
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jina</div><div class="q-item__label q-item__label--caption text-caption">Build multimodal AI applications on the cloud</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/finetuner"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/finetuner.c62eaafa.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">CLIP-as-service</div><div class="q-item__label q-item__label--caption text-caption">Embed images and sentences into fixed-length vectors with CLIP</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jcloud"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jcloud.669910ba.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">JCloud</div><div class="q-item__label q-item__label--caption text-caption">Deploy a local project as a cloud service. Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; FastAPI</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/vectordb"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/VectorDB.46be6cc1.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">VectorDB</div><div class="q-item__label q-item__label--caption text-caption">A Python vector database you just need - no more, no less</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://cloud.jina.ai/executors"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/hub.5e89f942.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">Deploy prompts and flexible template prompts as REST API services, and integrate them into your applications with just a few clicks</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">June 22, 2023 • 7 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><p>Announcing a brand new feature for PromptPerfect: Prompt as a Service! Now you can host your own flexible prompts on PromptPerfect, generate variants at will, and interact with language and image models via a REST API.</p><figure class="kg-card kg-bookmark-card"><a class="kg-bookmark-container" href="https://promptperfect.jina.ai/services?ref=jina-ai-gmbh.ghost.io"><div class="kg-bookmark-content"><div class="kg-bookmark-title">PromptPerfect - Elevate Your Prompts to Perfection with AI Prompt Engineering</div><div class="kg-bookmark-description">Optimize prompts for GPT-4, ChatGPT, StableLM, Claude, MidJourney, DALL-E, StableDiffusion, Kandinsky, and Lexica. Experience automatic prompt engineering done right. Create compelling Text and Image prompts today with our AI prompt generator.</div><div class="kg-bookmark-metadata"><img loading="lazy" class="kg-bookmark-icon" src="https://promptperfect.jina.ai/icons/apple-icon-180x180.png" alt=""><span class="kg-bookmark-author">PromptPerfect</span></div></div><div class="kg-bookmark-thumbnail"><img loading="lazy" src="https://promptperfect.jina.ai/banner.png" alt=""></div></a></figure><p>In this post we’ll cover several use cases for Prompt as a Service - though I’m sure you can come up with some ideas yourself!</p><p>We’ll cover:</p><ul><li>How to automate your tiring friendships</li><li>Building a SaaS (Sandwiches as a Service)</li><li>Generating knock-off Mona Lisas in the style of different artists</li></ul><p>For each of these, we’ll walk through the interface and show you to access your Prompt as a Service using cURL, Python, or JavaScript.</p><p>But first, a quick video overview:</p><figure class="kg-card kg-video-card"><div class="kg-video-container"><video src="https://jina-ai-gmbh.ghost.io/content/media/2023/06/promptperfect-paas-2.mp4" poster="https://img.spacergif.org/v1/2914x1660/0a/spacer.png" width="2914" height="1660" playsinline="" preload="metadata" style="background: transparent url('https://jina-ai-gmbh.ghost.io/content/images/2023/06/media-thumbnail-ember182.jpg') 50% 50% / cover no-repeat;"></video><div class="kg-video-overlay"><button class="kg-video-large-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button></div><div class="kg-video-player-container"><div class="kg-video-player"><button class="kg-video-play-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z"></path></svg></button><button class="kg-video-pause-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><rect x="3" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect><rect x="14" y="1" width="7" height="22" rx="1.5" ry="1.5"></rect></svg></button><span class="kg-video-current-time">0:00</span><div class="kg-video-time">/<span class="kg-video-duration"></span></div><input type="range" class="kg-video-seek-slider" max="100" value="0"><button class="kg-video-playback-rate">1×</button><button class="kg-video-unmute-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z"></path></svg></button><button class="kg-video-mute-icon kg-video-hide"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z"></path></svg></button><input type="range" class="kg-video-volume-slider" max="100" value="100"></div></div></div></figure><p>Now, let's dive in. Making your prompt servable is as easy as 1, 2, 3:</p><ol><li>Write your template</li><li>Specify variables with <code>[VAR]</code> or <code>$VAR</code></li><li>Deploy your prompt with one click</li></ol><p>You can also switch out your language model (or image model - keep reading for that):</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--14-.png" class="kg-image" alt="" width="582" height="150"></figure><p>By default, you’ll need a token to access your prompt, but with one click more you can make it publicly accessible:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--15-.png" class="kg-image" alt="" width="553" height="73"></figure><h2 id="prompt-as-a-service-in-action">Prompt as a Service in Action</h2><h3 id="automating-friendships-for-fun-and-profit">Automating friendships for fun and profit</h3><p>I've got this friend called Izzie. Well, that's not his <em>actual</em> name. But he always falls head over heels for some guy and asks:</p><blockquote>"Is he into me? Do you think he's into me? He says I'm like a _____ to him"</blockquote><div class="kg-card kg-callout-card kg-callout-card-red"><div class="kg-callout-emoji">👨🏻‍🤝‍👨🏽</div><div class="kg-callout-text">Izzie isn’t his real name. Any resemblance to people living, dead or undead is purely coincidental.</div></div><p>I think we've all had a friend like Izzie before. Like a sickly kitten that won’t budge from sitting on your keyboard. They’re annoying, but you just feel this instinct to look after them.</p><p>But after a while, instincts be damned. That's why I'm going to use Prompt as a Service to automate away this tiring relationship. Like an automatic cat feeder for humans, if you will.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-8.png" class="kg-image" alt="" width="370" height="640"><figcaption>Friendship is <s>priceless</s> about 8 Euros with free shipping</figcaption></figure><p>First, we create the prompt via PromptPerfect’s <strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong>Services</strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong> tool. We’ll specify a <code>[person]</code> variable which can be switched out for <code>mother</code>, <code>brother</code>, <code>cousin</code> or whatever:</p><pre><code class="language-jsx">Is this guy into me? He says I'm like a [person] to him
+</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--16--1.png" class="kg-image" alt="" width="589" height="776"></figure><p>Testing it gives us more or less expected results:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--17-.png" class="kg-image" alt="" width="589" height="443"></figure><p>Right now, access is private, so you need a token to access it:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-13.png" class="kg-image" alt="" width="685" height="125" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/image-13.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-13.png 685w"></figure><p>But we can make it publicly accessible for all the Izzies of the world, without the need for tokens:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--18-.png" class="kg-image" alt="" width="589" height="76"></figure><p>You can access the service via the REST API:</p><pre><code class="language-shell">curl "https://api.promptperfect.jina.ai/4TFmeCo3aSBDlC44Wik8" \\
   -H "x-api-key: token $YOUR_GENERATED_SECRET" \\
   -H "content-type: application/json" \\
   --data '{"parameters": {"person":"stalker"}}'
-</code></pre><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">I've disabled public access so we don’t overload our servers. There could be a lot of Izzies in the world.</div></div><p>That gives the output:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span><span class="hljs-attr">"code"</span><span class="hljs-punctuation">:</span><span class="hljs-number">200</span><span class="hljs-punctuation">,</span><span class="hljs-attr">"status"</span><span class="hljs-punctuation">:</span><span class="hljs-number">20000</span><span class="hljs-punctuation">,</span><span class="hljs-attr">"data"</span><span class="hljs-punctuation">:</span><span class="hljs-string">"As an AI language model, I cannot observe the behavior or interactions between you and this person. However, based on the description you provided, it seems like he might not be into you in a romantic way. The term \\"</span>stalker\\<span class="hljs-string">" typically has a negative connotation, suggesting that he might feel uncomfortable with your attention. It's important to respect his feelings and boundaries. If you're unsure about his feelings towards you, consider having an open and honest conversation with him about it."</span><span class="hljs-punctuation">}</span>%
-</code></pre><p>That cold hard terminal output won’t make Izzie feel very cared for. If only there were a way to soften the blow.</p><p>Hey, everything goes better with Pokémon, right?</p><p>To have Pikachu (considered by many to be the most empathic of pocket monsters) break the news, we’ll need to use:</p><ul><li><a href="https://curl.se/?ref=jina-ai-gmbh.ghost.io">cURL</a> - to access our prompt's REST API</li><li><a href="https://github.com/jqlang/jq?ref=jina-ai-gmbh.ghost.io">jq</a> - to pull out the <code>data</code> field</li><li><a href="https://github.com/possatti/pokemonsay?ref=jina-ai-gmbh.ghost.io">Pokemonsay</a> - to make a Pokémon say something (like <a href="https://en.wikipedia.org/wiki/Cowsay?ref=jina-ai-gmbh.ghost.io">cowsay</a>, but…Pokémon)</li></ul><p>We’ll pipe them together into the following command:</p><pre><code class="language-shell hljs">curl "https://api.promptperfect.jina.ai/4TFmeCo3aSBDlC44Wik8" \\
+</code></pre><div class="kg-card kg-callout-card kg-callout-card-yellow"><div class="kg-callout-emoji">💡</div><div class="kg-callout-text">I've disabled public access so we don’t overload our servers. There could be a lot of Izzies in the world.</div></div><p>That gives the output:</p><pre><code class="language-json">{"code":200,"status":20000,"data":"As an AI language model, I cannot observe the behavior or interactions between you and this person. However, based on the description you provided, it seems like he might not be into you in a romantic way. The term \\"stalker\\" typically has a negative connotation, suggesting that he might feel uncomfortable with your attention. It's important to respect his feelings and boundaries. If you're unsure about his feelings towards you, consider having an open and honest conversation with him about it."}%
+</code></pre><p>That cold hard terminal output won’t make Izzie feel very cared for. If only there were a way to soften the blow.</p><p>Hey, everything goes better with Pokémon, right?</p><p>To have Pikachu (considered by many to be the most empathic of pocket monsters) break the news, we’ll need to use:</p><ul><li><a href="https://curl.se/?ref=jina-ai-gmbh.ghost.io">cURL</a> - to access our prompt's REST API</li><li><a href="https://github.com/jqlang/jq?ref=jina-ai-gmbh.ghost.io">jq</a> - to pull out the <code>data</code> field</li><li><a href="https://github.com/possatti/pokemonsay?ref=jina-ai-gmbh.ghost.io">Pokemonsay</a> - to make a Pokémon say something (like <a href="https://en.wikipedia.org/wiki/Cowsay?ref=jina-ai-gmbh.ghost.io">cowsay</a>, but…Pokémon)</li></ul><p>We’ll pipe them together into the following command:</p><pre><code class="language-shell">curl "https://api.promptperfect.jina.ai/4TFmeCo3aSBDlC44Wik8" \\
   -H "x-api-key: token $YOUR_GENERATED_SECRET" \\
   -H "content-type: application/json" \\
   --data '{"parameters": {"person":"cousin-in-law"}}' | jq '.data' | pokemonsay -p pikachu
-</code></pre><p>Lo and behold, Pikachu speaks:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-9.png" class="kg-image" alt="" width="489" height="625"><figcaption>I would render this in a code block, but Pikachu refuses to be fenced</figcaption></figure><p>With a little bit of code, we’ve reduced our day-to-day effort, helped a friend in need, and brought more Pikachus into this world. All in all, a good day's work!</p><h3 id="saas-sandwiches-as-a-service">SaaS: Sandwiches as a Service</h3><p>Of course, you can easily build your own SaaS on such a service. And by SaaS I mean Sandwiches-as-a-Service.</p><div class="kg-card kg-callout-card kg-callout-card-purple"><div class="kg-callout-emoji">🏳️‍🌈</div><div class="kg-callout-text">In honor of Pride Month, I was going to go with <a href="https://en.wikipedia.org/wiki/Yakiniku?ref=jina-ai-gmbh.ghost.io">Yakiniku</a>-as-a-Service and title this post "YaaS, Queen". But yakiniku is tragically undervalued in this forsaken world.</div></div><p>Again, we start with a prompt, this time with a few more variables:</p><pre><code class="language-text hljs language-plaintext">You are the head chef at the Sandy Witch's Sandwich Shack, the
+</code></pre><p>Lo and behold, Pikachu speaks:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-9.png" class="kg-image" alt="" width="489" height="625"><figcaption>I would render this in a code block, but Pikachu refuses to be fenced</figcaption></figure><p>With a little bit of code, we’ve reduced our day-to-day effort, helped a friend in need, and brought more Pikachus into this world. All in all, a good day's work!</p><h3 id="saas-sandwiches-as-a-service">SaaS: Sandwiches as a Service</h3><p>Of course, you can easily build your own SaaS on such a service. And by SaaS I mean Sandwiches-as-a-Service.</p><div class="kg-card kg-callout-card kg-callout-card-purple"><div class="kg-callout-emoji">🏳️‍🌈</div><div class="kg-callout-text">In honor of Pride Month, I was going to go with <a href="https://en.wikipedia.org/wiki/Yakiniku?ref=jina-ai-gmbh.ghost.io">Yakiniku</a>-as-a-Service and title this post "YaaS, Queen". But yakiniku is tragically undervalued in this forsaken world.</div></div><p>Again, we start with a prompt, this time with a few more variables:</p><pre><code class="language-text">You are the head chef at the Sandy Witch's Sandwich Shack, the
 best sandwich restaurant in the world. Can you recommend a 
 [style] sandwich recipe for me? I have the following 
 ingredients: [ingredients]. Please use [units] units.
-</code></pre><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">🥪</div><div class="kg-callout-text">This is a really basic prompt. For something better, you can optimize your prompts with PromptPerfect's <a href="https://promptperfect.jina.ai/streamline?ref=jina-ai-gmbh.ghost.io">Streamline function</a>.</div></div><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-14.png" class="kg-image" alt="" width="595" height="529"><figcaption>I assure you, "4/20 requests" is purely coincidental</figcaption></figure><p>PromptPerfect gives us the code to access our Prompt as a Service:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--20-.png" class="kg-image" alt="" width="700" height="464" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Untitled--20-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--20-.png 700w"></figure><p>And we’ll adapt the Python snippet in <code>sandwich.py</code>:</p><pre><code class="language-python hljs"><span class="hljs-comment">#!pip install requests</span>
-<span class="hljs-keyword">import</span> requests
+</code></pre><div class="kg-card kg-callout-card kg-callout-card-green"><div class="kg-callout-emoji">🥪</div><div class="kg-callout-text">This is a really basic prompt. For something better, you can optimize your prompts with PromptPerfect's <a href="https://promptperfect.jina.ai/streamline?ref=jina-ai-gmbh.ghost.io">Streamline function</a>.</div></div><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-14.png" class="kg-image" alt="" width="595" height="529"><figcaption>I assure you, "4/20 requests" is purely coincidental</figcaption></figure><p>PromptPerfect gives us the code to access our Prompt as a Service:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--20-.png" class="kg-image" alt="" width="700" height="464" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2023/06/Untitled--20-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--20-.png 700w"></figure><p>And we’ll adapt the Python snippet in <code>sandwich.py</code>:</p><pre><code class="language-python">#!pip install requests
+import requests
 
-url = <span class="hljs-string">"https://api.promptperfect.jina.ai/rGzNHnrmfw2dKci7kB8X"</span>
+url = "https://api.promptperfect.jina.ai/rGzNHnrmfw2dKci7kB8X"
 
 headers = {
-    <span class="hljs-string">"Content-Type"</span>: <span class="hljs-string">"application/json"</span>
+    "Content-Type": "application/json"
 }
 
 response = requests.post(url, headers=headers, json={
-    <span class="hljs-string">"parameters"</span>: {<span class="hljs-string">"style"</span>:<span class="hljs-string">"fancy"</span>, <span class="hljs-string">"ingredients"</span>:<span class="hljs-string">"caramelized onions, gruyere cheese, truffle oil"</span>,<span class="hljs-string">"units"</span>:<span class="hljs-string">"metric"</span>}
+    "parameters": {"style":"fancy", "ingredients":"caramelized onions, gruyere cheese, truffle oil","units":"metric"}
 })
 
-<span class="hljs-built_in">print</span>(response.json()[<span class="hljs-string">'data'</span>])
-</code></pre><p>This gives us the recipe:</p><pre><code class="language-text hljs language-plaintext">Certainly! With those delicious ingredients, I recommend
+print(response.json()['data'])
+</code></pre><p>This gives us the recipe:</p><pre><code class="language-text">Certainly! With those delicious ingredients, I recommend
 creating a Truffled Gruyere and Caramelized Onion Grilled
 Cheese Sandwich. Here's the recipe:
 
@@ -88,19 +88,19 @@
 
 Enjoy your luxurious Truffled Gruyere and Caramelized Onion
 Grilled Cheese Sandwich at The Sandy Witch's Sandwich Shack!
-</code></pre><p>Stay tuned for more posts about sandwiches and PromptPerfect. We’ve got something baking…</p><h2 id="generating-images">Generating images</h2><p>Prompt as a Service goes way beyond just text. You can also choose from a range of image models, like <a href="https://stablediffusionweb.com/?ref=jina-ai-gmbh.ghost.io">Stable Diffusion</a>, <a href="https://github.com/ai-forever/Kandinsky-2?ref=jina-ai-gmbh.ghost.io">Kandinsky</a>, <a href="https://openai.com/dall-e-2?ref=jina-ai-gmbh.ghost.io">DALL-E-2</a>, and more:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--21-.png" class="kg-image" alt="" width="584" height="151"></figure><p>We'll use Kandinsky this time as our model, and go for a Mona Lisa vibe, using the prompt:</p><pre><code class="language-text hljs language-plaintext">Create a portrait of the Mona Lisa in the style of [artist]</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-11.png" class="kg-image" alt="" width="600" height="781" srcset="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-11.png 600w"></figure><p>Since we’ve accessed the API via cURL and Python so far, this time adapt the Javascript code snippet, in a file called <code>monalisa.js</code>:</p><pre><code class="language-javascript hljs">resp = <span class="hljs-title function_">fetch</span>(<span class="hljs-string">'https://api.promptperfect.jina.ai/aH4KYaiaf0e1Ermxvuml'</span>, {
-  <span class="hljs-attr">headers</span>: {
-    <span class="hljs-string">'content-type'</span>: <span class="hljs-string">'application/json'</span>
+</code></pre><p>Stay tuned for more posts about sandwiches and PromptPerfect. We’ve got something baking…</p><h2 id="generating-images">Generating images</h2><p>Prompt as a Service goes way beyond just text. You can also choose from a range of image models, like <a href="https://stablediffusionweb.com/?ref=jina-ai-gmbh.ghost.io">Stable Diffusion</a>, <a href="https://github.com/ai-forever/Kandinsky-2?ref=jina-ai-gmbh.ghost.io">Kandinsky</a>, <a href="https://openai.com/dall-e-2?ref=jina-ai-gmbh.ghost.io">DALL-E-2</a>, and more:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/Untitled--21-.png" class="kg-image" alt="" width="584" height="151"></figure><p>We'll use Kandinsky this time as our model, and go for a Mona Lisa vibe, using the prompt:</p><pre><code class="language-text">Create a portrait of the Mona Lisa in the style of [artist]</code></pre><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-11.png" class="kg-image" alt="" width="600" height="781" srcset="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-11.png 600w"></figure><p>Since we’ve accessed the API via cURL and Python so far, this time adapt the Javascript code snippet, in a file called <code>monalisa.js</code>:</p><pre><code class="language-javascript">resp = fetch('https://api.promptperfect.jina.ai/aH4KYaiaf0e1Ermxvuml', {
+  headers: {
+    'content-type': 'application/json'
   },
-  <span class="hljs-attr">body</span>: <span class="hljs-title class_">JSON</span>.<span class="hljs-title function_">stringify</span>({
-    <span class="hljs-string">"parameters"</span>: { <span class="hljs-string">"artist"</span>: <span class="hljs-string">"andy warhol"</span> },
+  body: JSON.stringify({
+    "parameters": { "artist": "andy warhol" },
   }),
-  <span class="hljs-attr">method</span>: <span class="hljs-string">'POST'</span>
+  method: 'POST'
 })
-  .<span class="hljs-title function_">then</span>(<span class="hljs-function"><span class="hljs-params">response</span> =&gt;</span> response.<span class="hljs-title function_">json</span>())
-  .<span class="hljs-title function_">then</span>(<span class="hljs-function"><span class="hljs-params">data</span> =&gt;</span> <span class="hljs-variable language_">console</span>.<span class="hljs-title function_">log</span>(data))
-  .<span class="hljs-title function_">catch</span>(<span class="hljs-function"><span class="hljs-params">error</span> =&gt;</span> <span class="hljs-variable language_">console</span>.<span class="hljs-title function_">error</span>(<span class="hljs-string">'Error:'</span>, error));</code></pre><p>Running this via <code>node monalisa.js</code> will output a URL where you can download your masterpiece:</p><pre><code class="language-json hljs"><span class="hljs-punctuation">{</span>
-  code<span class="hljs-punctuation">:</span> <span class="hljs-number">200</span><span class="hljs-punctuation">,</span>
-  status<span class="hljs-punctuation">:</span> <span class="hljs-number">20000</span><span class="hljs-punctuation">,</span>
-  data<span class="hljs-punctuation">:</span> 'https<span class="hljs-punctuation">:</span><span class="hljs-comment">//storage.googleapis.com/prompt-ops.appspot.com/kandinsky-2%2Fc1f90101-08c8-4083-9a8c-07022039d18c.png'</span>
-<span class="hljs-punctuation">}</span></code></pre><p>Et voilà:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-10.png" class="kg-image" alt="" width="512" height="512"><figcaption>Mona Lisa in the style of Andy Warhol</figcaption></figure><h2 id="get-started-with-prompt-as-a-service">Get started with Prompt as a Service</h2><p>These are just some toy examples - As I said before, I’m sure you can come up with something better!</p><p>To get started with Prompt as a Service, sign up for PromptPerfect and <a href="https://discord.com/channels/1106542220112302130/1106583990632198234?ref=jina-ai-gmbh.ghost.io">share your results on our Discord</a>.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Sign up for PromptPerfect</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fwhats-next-for-prompt-engineering-prompts-as-a-service%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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+  .then(response =&gt; response.json())
+  .then(data =&gt; console.log(data))
+  .catch(error =&gt; console.error('Error:', error));</code></pre><p>Running this via <code>node monalisa.js</code> will output a URL where you can download your masterpiece:</p><pre><code class="language-json">{
+  code: 200,
+  status: 20000,
+  data: 'https://storage.googleapis.com/prompt-ops.appspot.com/kandinsky-2%2Fc1f90101-08c8-4083-9a8c-07022039d18c.png'
+}</code></pre><p>Et voilà:</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2023/06/image-10.png" class="kg-image" alt="" width="512" height="512"><figcaption>Mona Lisa in the style of Andy Warhol</figcaption></figure><h2 id="get-started-with-prompt-as-a-service">Get started with Prompt as a Service</h2><p>These are just some toy examples - As I said before, I’m sure you can come up with something better!</p><p>To get started with Prompt as a Service, sign up for PromptPerfect and <a href="https://discord.com/channels/1106542220112302130/1106583990632198234?ref=jina-ai-gmbh.ghost.io">share your results on our Discord</a>.</p><div class="kg-card kg-button-card kg-align-center"><a href="https://promptperfect.jina.ai/?ref=jina-ai-gmbh.ghost.io" class="kg-btn kg-btn-accent">Sign up for PromptPerfect</a></div></section></article><hr data-v-ecd25db0="" class="q-separator q-separator--horizontal q-separator--dark q-mt-xl" aria-orientation="horizontal"><div data-v-ecd25db0="" class="row justify-between items-center q-py-md"><div data-v-ecd25db0=""><span data-v-ecd25db0="" class="text-weight-bold">Categories:</span><span data-v-ecd25db0="" class="q-ml-md"><div class="q-chip row inline no-wrap items-center q-chip--outline q-chip--square q-chip--dark q-dark non-selectable no-border-radius" style="font-size: 10px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">Tech blog</div></div></div></span></div><div data-v-ecd25db0=""><div data-v-ecd25db0="" class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--square inline"><a data-v-ecd25db0="" href="https://news.ycombinator.com/submitlink?u=http%3A%2F%2F127.0.0.1%3A3000%2Fnews%2Fwhats-next-for-prompt-engineering-prompts-as-a-service%2F" target="_blank" rel="nofollow noopener noreferrer" aria-label="Share this with HackerNews. 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-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Why Don't People Use Your Software Framework?</title><meta charset="utf-8"><meta name="title" content="Why Don't People Use Your Software Framework?"><meta name="description" content="The initial hype was great: You got hundreds of GitHub stars and fifty upvotes on Reddit. But then growth started to plateau and then drop. Why don't people use your software framework?"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/why-dont-people-use-your-software-framework"><meta property="og:title" content="Why Don't People Use Your Software Framework?"><meta property="og:description" content="The initial hype was great: You got hundreds of GitHub stars and fifty upvotes on Reddit. But then growth started to plateau and then drop. Why don't people use your software framework?"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--47-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/why-dont-people-use-your-software-framework"><meta property="twitter:title" content="Why Don't People Use Your Software Framework?"><meta property="twitter:description" content="The initial hype was great: You got hundreds of GitHub stars and fifty upvotes on Reddit. But then growth started to plateau and then drop. Why don't people use your software framework?"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--47-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Why Don't People Use Your Software Framework?</title><meta charset="utf-8"><meta name="title" content="Why Don't People Use Your Software Framework?"><meta name="description" content="The initial hype was great: You got hundreds of GitHub stars and fifty upvotes on Reddit. But then growth started to plateau and then drop. Why don't people use your software framework?"><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/news/why-dont-people-use-your-software-framework"><meta property="og:title" content="Why Don't People Use Your Software Framework?"><meta property="og:description" content="The initial hype was great: You got hundreds of GitHub stars and fifty upvotes on Reddit. But then growth started to plateau and then drop. Why don't people use your software framework?"><meta property="og:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--47-.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/news/why-dont-people-use-your-software-framework"><meta property="twitter:title" content="Why Don't People Use Your Software Framework?"><meta property="twitter:description" content="The initial hype was great: You got hundreds of GitHub stars and fifty upvotes on Reddit. But then growth started to plateau and then drop. Why don't people use your software framework?"><meta property="twitter:image" content="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--47-.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DALL-E Flow</div><div class="q-item__label q-item__label--caption text-caption">A human-in-the-Loop workflow for creating HD images from text</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/discoart"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/disco-art.f21a267f.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"><div data-v-ecd25db0="" class="text-white absolute-bottom q-pa-lg lock-blur text-h4" style="background: rgba(0, 0, 0, 0.5);">Why Don't People Use Your Software Framework?</div></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The initial hype was great: You got hundreds of GitHub stars and fifty upvotes on Reddit. But then growth started to plateau and then drop. Why don't people use your software framework?</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 01, 2022 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><blockquote>Fade in. Exterior. Unnamed city. Day.</blockquote><blockquote class="kg-blockquote-alt">- Three months earlier -</blockquote><p><em>"... and <strong>today's AI is all about engineering</strong>. With that, let's wrap up this episode. If you like our channel plea..."</em></p><p>You gasp, slamming the 'pause' button on your Airpods and skidding to a halt. A brilliant concept had just blossomed in your mind:</p><p>"<em>I need to build </em><strong><em>an AI framework</em></strong><em>!</em>", you exclaim to yourself, filled with excitement and a sudden burst of energy. You can't believe you never thought of it before!</p><p>Your mind is already racing, laying out the steps and moving parts needed to launch this product into reality. With shaking hands, you hastily pull off your running shoes, ignoring the small puddle of sweat pooling behind your ears.</p><p>The world around you stops suddenly: the birds stop chirping; the cars stop honking; the other joggers fade away. It's like you've been transported away from the hustle and bustle of the city, and into a world of possibility and success.</p><p>Your fingers move furiously, swiping and tapping your phone as you type out notes, ideas and random thoughts. You dream of potential investors, new applications, and the narrative of your first launch on Hacker News and Product Hunt. Your heart races as you write, almost like you could manifest success with every keystroke. Your mind fizzes with excitement, and nothing, NOTHING, can stop you now. Your Airpods drop to the ground as you take off, running toward the bright future and your newfound success.</p><blockquote class="kg-blockquote-alt">- This is not your day -</blockquote><p><strong>The initial hype was great.</strong> Within the first few days of its launch, thousands of users were trying out your framework and sharing their experiences. You got hundreds of GitHub stars and fifty upvotes on <code>r/machinelearning</code>. Not too shabby. Not too shabby at all.</p><p>But then...something happened. Something unexpected -<strong> user growth started to plateau and then drop. </strong>Suddenly, weeks had flown by and you hadn't seen any real growth. You started to worry that the software you'd poured your heart and soul into just wasn't sustainable.</p><p>Surely this couldn't <em>really</em> be true. There must be some problem with Google Analytics or the telemetry you set up. Maybe it's just a funny time of year - lots of people are on holiday right now and not using your software at work. You'd done everything by the book. There's no way this could be going off the rails so soon.</p><p>But deep down, your heart sank. You knew these are just flimsy excuses.</p><p>Now you meander down the street, your head bowed and your hands in your pockets, your mood as gray as the cloudy sky above. You think back to the launch of your software and the excitement and anticipation of that day, as you would the birth of a bouncing baby boy. You created something that you were passionate about, something that you <em>believed</em> in, and yet despite the initial buzz and hype, it was a flop. But you trudge on, determined to get to the bottom of what went wrong.</p><p><strong><em>"Why don't people use it?" </em></strong>You stare up at the sky and plead, trying to make sense of what had happened. God knows you'd put in the effort — maybe (probably. definitely) too much. You just wish you could have done something, anything, differently, to make your software take off.</p><p>Eventually, you find yourself on a bench in the park. The sun begins to peek out from behind the clouds, almost as if it knows your mood and is trying to brighten your day. You let out a long sigh that you didn't know you'd been keeping in, and let your eyes close, feeling the warm sun on your face and the cool breeze on your skin.</p><p>You sit in silence, pondering your next move.</p><blockquote>Fade out.</blockquote><blockquote class="kg-blockquote-alt">- The end? -</blockquote><h2 id="understanding-three-common-mistakes">Understanding three common mistakes</h2><p>Success stories are often similar; failures, on the other hand, are often unique.</p><p>When it comes to software like AI frameworks with low adoption, there are three common mistakes in the early stage: <strong>bad focusing, poor onboarding, and lack of features.</strong> In this article, I'll explain them step by step with illustrations and, most importantly, show you how to fix them.</p><h3 id="the-ai-solution-space">The AI solution space</h3><p>Every real problem needs a solution.</p><p>There are many AI problems, big or small, easy or complicated; as long as they're real, they all need solutions.</p><p>Let's use dots to represent a solution. You could picture the AI solution space as below:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/39.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/39.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/39.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/39.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>In reality, solutions are <strong>not </strong>uniformly distributed. They're clustered. This is because different problems may end up with similar solutions. For example, sentiment analysis and text classification can both be solved using one language model with different training labels. Image segmentation and object detection can be solved by training a ResNet. As a consequence, the real AI solution space looks more like this: </p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/40-1.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/40-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/40-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/40-1.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>The clustered nature of the AI solution space <strong>justifies the existence of software frameworks</strong>, abstractions that provide generic functionality shared by a cluster of solutions, and can be selectively changed by additional user-written code, providing a standard way to build and deploy solutions. If solutions <em>were</em> uniformly distributed in the AI solution space, then no common pattern could be abstracted, leaving no need for frameworks.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://landscape.lfai.foundation/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image.png" class="kg-image" alt="" width="2000" height="1170" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/image.png 2400w" sizes="(min-width: 720px) 720px"></a><figcaption>The LF AI &amp; Data Foundation landscape, covering 332 AI frameworks with a total of 2,765,397 stars, market cap of $13.3T and funding of $19.6B.</figcaption></figure><p>Let's recap the relationship between the problem, the solution, and the framework in the illustration below:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--48-.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Jina-AI-Website-Banners-Templates--48-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Jina-AI-Website-Banners-Templates--48-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--48-.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>Having those well-defined illustrative concepts helps us recognize the first mistake when building a software framework.</p><h3 id="mistake-1-bad-focus-on-a-tiny-niche-market">Mistake 1: Bad focus on a tiny niche market</h3><p>In the figure below, the bubbles A, B, C, and D represent four frameworks. In terms of focus, it is easy to see that A &gt; B &gt; C &gt; D, as A enables the most solutions and meets the demands of the most real-world problems. D is the worst as it has fictional demands that match no real problems. Therefore, A will have the highest adoption in the long run, while D will have low/no adoption regardless of how many posts you submit to Hacker News and how many stars you get on GitHub.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--49-.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Jina-AI-Website-Banners-Templates--49-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Jina-AI-Website-Banners-Templates--49-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--49-.png 1440w" sizes="(min-width: 720px) 720px"></figure><p><em>"Who would be stupid enough to choose C or D?"</em> you might ask.</p><p>The disturbing truth is if you get a sparkling idea during jogging, or if you're building a new framework when reading this article, you're very likely in C or D. Here's why:</p><ul><li>You can't see the full picture of the AI solution space. Your observable space is limited by your knowledge and expertise in AI and the industry.</li><li>The markets behind A and B are oceans filled with big (and hungry) fish. You don't have the resources to swim that fast or bite that hard.</li><li>Your experience and knowledge make you overestimate the number of solutions and requirements covered by C and D.</li><li>As an engineer, you are easily obsessed with the framework idea itself, ignoring that it lacks any practical use in the real world.</li></ul><p>In any case, <em>don't be D</em>. Don't be sad if you're in C. <strong>The solution space is huge and dynamic</strong>; it continuously changes over time. New problems and requirements emerge; old requirements will be unnecessary. One good example is the creative AI market in 2021 vs. 2022.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-2.png" class="kg-image" alt="" width="2000" height="1047" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-2.png 2322w" sizes="(min-width: 720px) 720px"><figcaption>We rarely see any search on creative/generative AI back in 2021 and now it is booming.</figcaption></figure><p>Say you have a good focus and your framework conceptually covers some real needs. Congratulations! Let's move on and see the other two common traps you may fall into.</p><h3 id="mistake-2-poor-onboarding-experience-and-education-resources">Mistake 2: Poor onboarding experience and education resources</h3><p>Let's zoom in on a framework "bubble":</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/42.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/42.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/42.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/42.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>The first thing to highlight is the knowledge gap between you and your users. Your framework may cover all the functionalities that users need. However, due to the lack of docs and poor onboarding experience, <strong>users don't know your framework can solve their problems</strong>. The consequence? Low adoption. </p><p>Unlike you (as the know-it-all of your framework), your users observe the framework from a completely different angle: they can learn it only from the docs, tutorials, references, videos, and code snippets that you expose to them. In reality, your impatient users will only learn from <em>well-written</em> resources. If they feel onboarding is rough, they'll immediately give up and seek alternatives. They are <em>not</em> as determined and passionate as you.</p><p>One common mistake developers make is ignoring the importance of educational resources and <a href="https://www.writethedocs.org/guide/doc-ops/?ref=jina-ai-gmbh.ghost.io">DocOps</a> when building a framework. They naively believe that as long as they commit a function to the <code>master</code> branch, users will use it; as long as you write a few vague keywords about a feature in the commit message, users will understand the feature; as long as you make breaking changes, users will adapt their code accordingly.</p><p>Users won't.</p><ul><li>Users won't spend time digging into your unit tests to understand how a function works.</li><li>Users won't read your commit message riddle and the pull request's title to guess your new feature.</li><li>Users won't check spam filters to read the newsletter where you announce the breaking changes.</li><li>Users won't read poorly written docs with non-executable code snippets and report bugs to you.</li></ul><p>Users won't waste their time on your software if you won't "waste" your time on educating them.</p><p>So, you've pulled out all the stops to minimize the knowledge gap: good docs, detailed tutorials, instructional videos, offline/online meetups, conference presentations, daily tweets and weekly newsletters.</p><p>That's that dealt with. And you already fixed your focus (from mistake one). But you still see low adoption. What is it <em>this</em> time?</p><h3 id="mistake-3-outdated-and-missing-features">Mistake 3: Outdated and missing features</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/43.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/43.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/43.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/43.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>AI is evolving fast, and the market is highly competitive. You, on the other hand, are outdated. Obsolete. A relic.</p><p>Every day, hundreds of new papers are published on ArXiv; benchmark leaderboards get refreshed; new repositories trend on GitHub. If you can't keep your knowledge up-to-date, your framework quickly becomes obsolete. It won't catch users' attention anymore.</p><p>Compared to the second mistake, where users <strong>don't know they can do it</strong> with your framework, in this case, users <strong>know they can't do it</strong> with your framework. That's game over for you.</p><p>Tired of this competition? Well, you chose it, right? It's the hot market flooded with opportunities and money. Are you going to deal with that heat or get cold feet and run away? What about your <code>insert_country_name</code> dream?</p><h2 id="how-to-fix-those-mistakes">How to fix those mistakes</h2><p>History is full of mistakes; that's how we learn. </p><p>Don't be afraid of those mistakes. Confronting them is just a part of your life.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--52-.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Jina-AI-Website-Banners-Templates--52-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Jina-AI-Website-Banners-Templates--52-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--52-.png 1440w" sizes="(min-width: 720px) 720px"><figcaption>You shouldn't be afraid of those mistakes, but if your manager talks like this, maybe you should reconsider your career.</figcaption></figure><p>The first step is to recognize which mistake you made. It sounds easy, but under the huge pressure of low adoption, you'll very likely jump to the conclusion that you made <em>all</em> the mistakes. Confessing you made all the mistakes is as easy as saying "it doesn't work". Without breaking it down, this confession leads to no action points. It's up to you to prioritize and solve problems one by one, given your limited resources.</p><h3 id="retarget-for-bigger-demands">Retarget for bigger demands </h3><p><strong>If you have a bad focus, you need to retarget.</strong> Learn more about what people need and abandon the obsession of making a framework. Build more ad-hoc solutions and recognize their connections before working on the framework. Do more user research and market analysis, find the slice of cake that's big and interesting enough.</p><p>It's also possible your intentional focus is good enough, but your narrative and branding suck, which makes users think the framework doesn't match their needs. In this case, reconsider the narrative, promote the features that really matter, and hide the complexities that nobody (besides you) cares about.</p><h3 id="revamp-docs-to-improve-onboarding">Revamp docs to improve onboarding</h3><p><strong>If your onboarding experience is poor, you must revamp the docs and organize educational resources. </strong>A software framework needs educational resources at multiple levels – an API reference, tutorials, code snippets, high-level applications, and industry benchmarks. Just having an API reference auto-generated from docstrings is nowhere <em>near</em> enough.</p><p>Think back to how you learn a second language: You use a dictionary to look up vocabulary (i.e. API reference). Your first-year book is filled with basic daily conversations (i.e. code snippets) to teach you how to greet and buy things. Your second-year book has longer stories (i.e. high-level applications) to help you master grammar and descriptive writing. To level up your skills, you watch movies or read books from famous writers (i.e. industry benchmarks).</p><p>Your users are the same. On day one, they're just novices. But they learn over time, making progress by consuming the knowledge <em>you</em> give them. Your task is to help users grow <em>as fast as possible</em>, by providing all levels of resources that they need. When they reach the master level, you can relax a bit, as they can now advocate to others; they can produce high-quality educational content without you.</p><p>Don't just stick to text; go multimodal! Try podcasts, videos, meetups, and conference presentations, if you have the resources.</p><h3 id="move-fast-with-lifelong-learning">Move fast with lifelong learning</h3><p><strong>If your features are outdated, you need to learn more about the state-of-the-art and update your framework. </strong>Learn APIs, design patterns and algorithms from popular open-source frameworks. Keep an eye on their new pull requests and new features in the release notes, and think if it makes sense to add them to your framework. Always keep your knowledge and your codebase up to date. From time to time, do some retrospective on the feature roadmap: are you moving in the right direction? Are you adding this feature because people really need it? </p><p>In the open source world, there is no absolute advance. You can always learn from other software, and it's all about velocity. If you fall behind but move faster than the pack, you can catch up eventually. If you're leading but stop updating, a predator will eat you for lunch. 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Recent talk about Artificial General Intelligence only highlights those curses.</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 30px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/photo-of-me-cropped.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Scott Martens</div><div class="q-item__label q-item__label--caption text-caption">November 20, 2023 • 13 minutes read</div></div></div></div><div class="q-img q-img--menu col-4" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2023/11/Explore-image-storytelling-beyond-pixels--22-.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div></a><a data-v-ecd25db0="" class="q-card q-card--dark q-dark q-card--flat no-shadow block cursor-pointer q-hoverable non-selectable q-my-md" href="/news/do-you-truly-need-a-dedicated-vector-store" style="overflow: hidden; text-decoration: none !important;"><span class="q-focus-helper"></span><div class="q-card__section q-card__section--horiz row no-wrap row justify-between full-height q-pa-none"><div class="q-card__section q-card__section--vert column justify-between"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label text-h5 text-weight-light q-mb-lg" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 2;">Do You Truly Need a Dedicated Vector Store?</div><div class="q-item__label q-item__label--caption text-caption" style="overflow: hidden; display: -webkit-box; -webkit-box-orient: vertical; -webkit-line-clamp: 3;">Unraveling vector search spaghetti: Lucene's charm vs. shiny vector stores. Navigating enterprise mazes &amp; startup vibes. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DiscoArt</div><div class="q-item__label q-item__label--caption text-caption">Create compelling Disco Diffusion artworks in one line of code</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/thinkgpt"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/think-gpt.0a671280.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div><div data-v-ecd25db0="" class="row justify-center q-mt-lg q-pt-lg"><div data-v-ecd25db0="" class="box col-10 col-md-6"><i data-v-ecd25db0="" class="fas fa-quote-left fa2"></i><div data-v-ecd25db0="" class="text"><i data-v-ecd25db0="" class="fas fa-quote-right fa1"></i><div data-v-ecd25db0=""><p data-v-ecd25db0="">The initial hype was great: You got hundreds of GitHub stars and fifty upvotes on Reddit. But then growth started to plateau and then drop. Why don't people use your software framework?</p></div></div></div></div><div data-v-ecd25db0="" class="row justify-center items-center q-mt-lg"><div data-v-ecd25db0="" class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div data-v-363418f9="" data-v-ecd25db0="" class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div data-v-363418f9="" class="relative-position" style="height: 30px; width: 55px;"><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 0px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/10/Untitled-2.png" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-from q-transition--fade-leave-active"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-from q-transition--fade-enter-active"></div></div></div></div><div data-v-363418f9="" class="q-avatar bg-grey-9 overlapping" style="font-size: 30px; left: 25px;"><div class="q-avatar__content row flex-center overflow-hidden"><div data-v-363418f9="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 100%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="https://jina-ai-gmbh.ghost.io/content/images/2022/09/alex.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center q-transition--fade-leave-active q-transition--fade-leave-to"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div><div class="q-img__content absolute-full q-anchor--skip q-transition--fade-enter-active q-transition--fade-enter-to"></div></div></div></div></div></div><div data-v-ecd25db0="" class="q-item__section column q-item__section--main justify-center text-grey-6"><div data-v-ecd25db0="" class="q-item__label">Han Xiao, Alex C-G</div><div data-v-ecd25db0="" class="q-item__label q-item__label--caption text-caption text-grey-6 q-mt-sm">December 01, 2022 • 10 minutes read</div></div></div></div><article data-v-ecd25db0="" class="article"><section data-v-ecd25db0="" class="gh-content"><blockquote>Fade in. Exterior. Unnamed city. Day.</blockquote><blockquote class="kg-blockquote-alt">- Three months earlier -</blockquote><p><em>"... and <strong>today's AI is all about engineering</strong>. With that, let's wrap up this episode. If you like our channel plea..."</em></p><p>You gasp, slamming the 'pause' button on your Airpods and skidding to a halt. A brilliant concept had just blossomed in your mind:</p><p>"<em>I need to build </em><strong><em>an AI framework</em></strong><em>!</em>", you exclaim to yourself, filled with excitement and a sudden burst of energy. You can't believe you never thought of it before!</p><p>Your mind is already racing, laying out the steps and moving parts needed to launch this product into reality. With shaking hands, you hastily pull off your running shoes, ignoring the small puddle of sweat pooling behind your ears.</p><p>The world around you stops suddenly: the birds stop chirping; the cars stop honking; the other joggers fade away. It's like you've been transported away from the hustle and bustle of the city, and into a world of possibility and success.</p><p>Your fingers move furiously, swiping and tapping your phone as you type out notes, ideas and random thoughts. You dream of potential investors, new applications, and the narrative of your first launch on Hacker News and Product Hunt. Your heart races as you write, almost like you could manifest success with every keystroke. Your mind fizzes with excitement, and nothing, NOTHING, can stop you now. Your Airpods drop to the ground as you take off, running toward the bright future and your newfound success.</p><blockquote class="kg-blockquote-alt">- This is not your day -</blockquote><p><strong>The initial hype was great.</strong> Within the first few days of its launch, thousands of users were trying out your framework and sharing their experiences. You got hundreds of GitHub stars and fifty upvotes on <code>r/machinelearning</code>. Not too shabby. Not too shabby at all.</p><p>But then...something happened. Something unexpected -<strong> user growth started to plateau and then drop. </strong>Suddenly, weeks had flown by and you hadn't seen any real growth. You started to worry that the software you'd poured your heart and soul into just wasn't sustainable.</p><p>Surely this couldn't <em>really</em> be true. There must be some problem with Google Analytics or the telemetry you set up. Maybe it's just a funny time of year - lots of people are on holiday right now and not using your software at work. You'd done everything by the book. There's no way this could be going off the rails so soon.</p><p>But deep down, your heart sank. You knew these are just flimsy excuses.</p><p>Now you meander down the street, your head bowed and your hands in your pockets, your mood as gray as the cloudy sky above. You think back to the launch of your software and the excitement and anticipation of that day, as you would the birth of a bouncing baby boy. You created something that you were passionate about, something that you <em>believed</em> in, and yet despite the initial buzz and hype, it was a flop. But you trudge on, determined to get to the bottom of what went wrong.</p><p><strong><em>"Why don't people use it?" </em></strong>You stare up at the sky and plead, trying to make sense of what had happened. God knows you'd put in the effort — maybe (probably. definitely) too much. You just wish you could have done something, anything, differently, to make your software take off.</p><p>Eventually, you find yourself on a bench in the park. The sun begins to peek out from behind the clouds, almost as if it knows your mood and is trying to brighten your day. You let out a long sigh that you didn't know you'd been keeping in, and let your eyes close, feeling the warm sun on your face and the cool breeze on your skin.</p><p>You sit in silence, pondering your next move.</p><blockquote>Fade out.</blockquote><blockquote class="kg-blockquote-alt">- The end? -</blockquote><h2 id="understanding-three-common-mistakes">Understanding three common mistakes</h2><p>Success stories are often similar; failures, on the other hand, are often unique.</p><p>When it comes to software like AI frameworks with low adoption, there are three common mistakes in the early stage: <strong>bad focusing, poor onboarding, and lack of features.</strong> In this article, I'll explain them step by step with illustrations and, most importantly, show you how to fix them.</p><h3 id="the-ai-solution-space">The AI solution space</h3><p>Every real problem needs a solution.</p><p>There are many AI problems, big or small, easy or complicated; as long as they're real, they all need solutions.</p><p>Let's use dots to represent a solution. You could picture the AI solution space as below:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/39.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/39.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/39.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/39.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>In reality, solutions are <strong>not </strong>uniformly distributed. They're clustered. This is because different problems may end up with similar solutions. For example, sentiment analysis and text classification can both be solved using one language model with different training labels. Image segmentation and object detection can be solved by training a ResNet. As a consequence, the real AI solution space looks more like this: </p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/40-1.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/40-1.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/40-1.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/40-1.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>The clustered nature of the AI solution space <strong>justifies the existence of software frameworks</strong>, abstractions that provide generic functionality shared by a cluster of solutions, and can be selectively changed by additional user-written code, providing a standard way to build and deploy solutions. If solutions <em>were</em> uniformly distributed in the AI solution space, then no common pattern could be abstracted, leaving no need for frameworks.</p><figure class="kg-card kg-image-card kg-card-hascaption"><a href="https://landscape.lfai.foundation/?ref=jina-ai-gmbh.ghost.io"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image.png" class="kg-image" alt="" width="2000" height="1170" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/size/w2400/2022/12/image.png 2400w" sizes="(min-width: 720px) 720px"></a><figcaption>The LF AI &amp; Data Foundation landscape, covering 332 AI frameworks with a total of 2,765,397 stars, market cap of $13.3T and funding of $19.6B.</figcaption></figure><p>Let's recap the relationship between the problem, the solution, and the framework in the illustration below:</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--48-.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Jina-AI-Website-Banners-Templates--48-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Jina-AI-Website-Banners-Templates--48-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--48-.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>Having those well-defined illustrative concepts helps us recognize the first mistake when building a software framework.</p><h3 id="mistake-1-bad-focus-on-a-tiny-niche-market">Mistake 1: Bad focus on a tiny niche market</h3><p>In the figure below, the bubbles A, B, C, and D represent four frameworks. In terms of focus, it is easy to see that A &gt; B &gt; C &gt; D, as A enables the most solutions and meets the demands of the most real-world problems. D is the worst as it has fictional demands that match no real problems. Therefore, A will have the highest adoption in the long run, while D will have low/no adoption regardless of how many posts you submit to Hacker News and how many stars you get on GitHub.</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--49-.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Jina-AI-Website-Banners-Templates--49-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Jina-AI-Website-Banners-Templates--49-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--49-.png 1440w" sizes="(min-width: 720px) 720px"></figure><p><em>"Who would be stupid enough to choose C or D?"</em> you might ask.</p><p>The disturbing truth is if you get a sparkling idea during jogging, or if you're building a new framework when reading this article, you're very likely in C or D. Here's why:</p><ul><li>You can't see the full picture of the AI solution space. Your observable space is limited by your knowledge and expertise in AI and the industry.</li><li>The markets behind A and B are oceans filled with big (and hungry) fish. You don't have the resources to swim that fast or bite that hard.</li><li>Your experience and knowledge make you overestimate the number of solutions and requirements covered by C and D.</li><li>As an engineer, you are easily obsessed with the framework idea itself, ignoring that it lacks any practical use in the real world.</li></ul><p>In any case, <em>don't be D</em>. Don't be sad if you're in C. <strong>The solution space is huge and dynamic</strong>; it continuously changes over time. New problems and requirements emerge; old requirements will be unnecessary. One good example is the creative AI market in 2021 vs. 2022.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-2.png" class="kg-image" alt="" width="2000" height="1047" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/12/image-2.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/12/image-2.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/size/w1600/2022/12/image-2.png 1600w, https://jina-ai-gmbh.ghost.io/content/images/2022/12/image-2.png 2322w" sizes="(min-width: 720px) 720px"><figcaption>We rarely see any search on creative/generative AI back in 2021 and now it is booming.</figcaption></figure><p>Say you have a good focus and your framework conceptually covers some real needs. Congratulations! Let's move on and see the other two common traps you may fall into.</p><h3 id="mistake-2-poor-onboarding-experience-and-education-resources">Mistake 2: Poor onboarding experience and education resources</h3><p>Let's zoom in on a framework "bubble":</p><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/42.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/42.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/42.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/42.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>The first thing to highlight is the knowledge gap between you and your users. Your framework may cover all the functionalities that users need. However, due to the lack of docs and poor onboarding experience, <strong>users don't know your framework can solve their problems</strong>. The consequence? Low adoption. </p><p>Unlike you (as the know-it-all of your framework), your users observe the framework from a completely different angle: they can learn it only from the docs, tutorials, references, videos, and code snippets that you expose to them. In reality, your impatient users will only learn from <em>well-written</em> resources. If they feel onboarding is rough, they'll immediately give up and seek alternatives. They are <em>not</em> as determined and passionate as you.</p><p>One common mistake developers make is ignoring the importance of educational resources and <a href="https://www.writethedocs.org/guide/doc-ops/?ref=jina-ai-gmbh.ghost.io">DocOps</a> when building a framework. They naively believe that as long as they commit a function to the <code>master</code> branch, users will use it; as long as you write a few vague keywords about a feature in the commit message, users will understand the feature; as long as you make breaking changes, users will adapt their code accordingly.</p><p>Users won't.</p><ul><li>Users won't spend time digging into your unit tests to understand how a function works.</li><li>Users won't read your commit message riddle and the pull request's title to guess your new feature.</li><li>Users won't check spam filters to read the newsletter where you announce the breaking changes.</li><li>Users won't read poorly written docs with non-executable code snippets and report bugs to you.</li></ul><p>Users won't waste their time on your software if you won't "waste" your time on educating them.</p><p>So, you've pulled out all the stops to minimize the knowledge gap: good docs, detailed tutorials, instructional videos, offline/online meetups, conference presentations, daily tweets and weekly newsletters.</p><p>That's that dealt with. And you already fixed your focus (from mistake one). But you still see low adoption. What is it <em>this</em> time?</p><h3 id="mistake-3-outdated-and-missing-features">Mistake 3: Outdated and missing features</h3><figure class="kg-card kg-image-card"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/43.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/43.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/43.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/43.png 1440w" sizes="(min-width: 720px) 720px"></figure><p>AI is evolving fast, and the market is highly competitive. You, on the other hand, are outdated. Obsolete. A relic.</p><p>Every day, hundreds of new papers are published on ArXiv; benchmark leaderboards get refreshed; new repositories trend on GitHub. If you can't keep your knowledge up-to-date, your framework quickly becomes obsolete. It won't catch users' attention anymore.</p><p>Compared to the second mistake, where users <strong>don't know they can do it</strong> with your framework, in this case, users <strong>know they can't do it</strong> with your framework. That's game over for you.</p><p>Tired of this competition? Well, you chose it, right? It's the hot market flooded with opportunities and money. Are you going to deal with that heat or get cold feet and run away? What about your <code>insert_country_name</code> dream?</p><h2 id="how-to-fix-those-mistakes">How to fix those mistakes</h2><p>History is full of mistakes; that's how we learn. </p><p>Don't be afraid of those mistakes. Confronting them is just a part of your life.</p><figure class="kg-card kg-image-card kg-card-hascaption"><img loading="lazy" src="https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--52-.png" class="kg-image" alt="" width="1440" height="720" srcset="https://jina-ai-gmbh.ghost.io/content/images/size/w600/2022/11/Jina-AI-Website-Banners-Templates--52-.png 600w, https://jina-ai-gmbh.ghost.io/content/images/size/w1000/2022/11/Jina-AI-Website-Banners-Templates--52-.png 1000w, https://jina-ai-gmbh.ghost.io/content/images/2022/11/Jina-AI-Website-Banners-Templates--52-.png 1440w" sizes="(min-width: 720px) 720px"><figcaption>You shouldn't be afraid of those mistakes, but if your manager talks like this, maybe you should reconsider your career.</figcaption></figure><p>The first step is to recognize which mistake you made. It sounds easy, but under the huge pressure of low adoption, you'll very likely jump to the conclusion that you made <em>all</em> the mistakes. Confessing you made all the mistakes is as easy as saying "it doesn't work". Without breaking it down, this confession leads to no action points. It's up to you to prioritize and solve problems one by one, given your limited resources.</p><h3 id="retarget-for-bigger-demands">Retarget for bigger demands </h3><p><strong>If you have a bad focus, you need to retarget.</strong> Learn more about what people need and abandon the obsession of making a framework. Build more ad-hoc solutions and recognize their connections before working on the framework. Do more user research and market analysis, find the slice of cake that's big and interesting enough.</p><p>It's also possible your intentional focus is good enough, but your narrative and branding suck, which makes users think the framework doesn't match their needs. In this case, reconsider the narrative, promote the features that really matter, and hide the complexities that nobody (besides you) cares about.</p><h3 id="revamp-docs-to-improve-onboarding">Revamp docs to improve onboarding</h3><p><strong>If your onboarding experience is poor, you must revamp the docs and organize educational resources. </strong>A software framework needs educational resources at multiple levels – an API reference, tutorials, code snippets, high-level applications, and industry benchmarks. Just having an API reference auto-generated from docstrings is nowhere <em>near</em> enough.</p><p>Think back to how you learn a second language: You use a dictionary to look up vocabulary (i.e. API reference). Your first-year book is filled with basic daily conversations (i.e. code snippets) to teach you how to greet and buy things. Your second-year book has longer stories (i.e. high-level applications) to help you master grammar and descriptive writing. To level up your skills, you watch movies or read books from famous writers (i.e. industry benchmarks).</p><p>Your users are the same. On day one, they're just novices. But they learn over time, making progress by consuming the knowledge <em>you</em> give them. Your task is to help users grow <em>as fast as possible</em>, by providing all levels of resources that they need. When they reach the master level, you can relax a bit, as they can now advocate to others; they can produce high-quality educational content without you.</p><p>Don't just stick to text; go multimodal! Try podcasts, videos, meetups, and conference presentations, if you have the resources.</p><h3 id="move-fast-with-lifelong-learning">Move fast with lifelong learning</h3><p><strong>If your features are outdated, you need to learn more about the state-of-the-art and update your framework. </strong>Learn APIs, design patterns and algorithms from popular open-source frameworks. Keep an eye on their new pull requests and new features in the release notes, and think if it makes sense to add them to your framework. Always keep your knowledge and your codebase up to date. From time to time, do some retrospective on the feature roadmap: are you moving in the right direction? Are you adding this feature because people really need it? </p><p>In the open source world, there is no absolute advance. You can always learn from other software, and it's all about velocity. If you fall behind but move faster than the pack, you can catch up eventually. If you're leading but stop updating, a predator will eat you for lunch. 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\ No newline at end of file
diff --git a/open-day/index.html b/open-day/index.html
index 759e763819b..0938d300814 100644
--- a/open-day/index.html
+++ b/open-day/index.html
@@ -1,6 +1,6 @@
-<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Open Day</title><meta charset="utf-8"><meta name="title" content="Open Day"><meta name="description" content="An exclusive opportunity to gain an insider's view of Jina AI."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/open-day"><meta property="og:title" content="Open Day"><meta property="og:description" content="An exclusive opportunity to gain an insider's view of Jina AI."><meta property="og:image" content="https://jina.ai/banner-open-day.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/open-day"><meta property="twitter:title" content="Open Day"><meta property="twitter:description" content="An exclusive opportunity to gain an insider's view of Jina AI."><meta property="twitter:image" content="https://jina.ai/banner-open-day.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.2b6e3ac7.js"></script>
+<!DOCTYPE html><html translate="no" dir="ltr" lang="en-US"><head><title>Open Day</title><meta charset="utf-8"><meta name="title" content="Open Day"><meta name="description" content="An exclusive opportunity to gain an insider's view of Jina AI."><meta property="og:type" content="website"><meta property="og:url" content="https://jina.ai/open-day"><meta property="og:title" content="Open Day"><meta property="og:description" content="An exclusive opportunity to gain an insider's view of Jina AI."><meta property="og:image" content="https://jina.ai/banner-open-day.png"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:url" content="https://jina.ai/open-day"><meta property="twitter:title" content="Open Day"><meta property="twitter:description" content="An exclusive opportunity to gain an insider's view of Jina AI."><meta property="twitter:image" content="https://jina.ai/banner-open-day.png"><meta name="format-detection" content="telephone=no"><meta name="msapplication-tap-highlight" content="no"><meta name="viewport" content="user-scalable=no,initial-scale=1,maximum-scale=1,minimum-scale=1,width=device-width"><link rel="icon" type="image/png" sizes="128x128" href="/icons/favicon-128x128.png"><link rel="icon" type="image/png" sizes="96x96" href="/icons/favicon-96x96.png"><link rel="icon" type="image/png" sizes="32x32" href="/icons/favicon-32x32.png"><link rel="icon" type="image/png" sizes="16x16" href="/icons/favicon-16x16.png"><link rel="icon" type="image/ico" href="/favicon.ico"><link rel="apple-touch-startup-image" media="(device-width: 428px) and (device-height: 926px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1284x2778.png"><link rel="apple-touch-startup-image" media="(device-width: 390px) and (device-height: 844px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1170x2532.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-828x1792.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 812px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1125x2436.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 896px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2688.png"><link rel="apple-touch-startup-image" media="(device-width: 375px) and (device-height: 667px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-750x1334.png"><link rel="apple-touch-startup-image" media="(device-width: 414px) and (device-height: 736px) and (-webkit-device-pixel-ratio: 3)" href="/icons/apple-launch-1242x2208.png"><link rel="apple-touch-startup-image" media="(device-width: 810px) and (device-height: 1080px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1620x2160.png"><link rel="apple-touch-startup-image" media="(device-width: 768px) and (device-height: 1024px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1536x2048.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1112px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2224.png"><link rel="apple-touch-startup-image" media="(device-width: 834px) and (device-height: 1194px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-1668x2388.png"><link rel="apple-touch-startup-image" media="(device-width: 1024px) and (device-height: 1366px) and (-webkit-device-pixel-ratio: 2)" href="/icons/apple-launch-2048x2732.png">  <script type="module" crossorigin="" src="/assets/index.ae19b4cb.js"></script>
   <link rel="stylesheet" href="/assets/index.9fe6336f.css">
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+<link rel="modulepreload" as="script" crossorigin="" href="/assets/register.7136f5fa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QTooltip.5338ff56.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/position-engine.2f7193db.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/selection.10af5b4d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/copy-to-clipboard.58aec584.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/index.ae19b4cb.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/MainLayout.702c6e21.js"><link rel="stylesheet" href="/assets/MainLayout.891b970f.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSpace.e72a2bc7.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QSelect.ec7f4034.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QChip.1a7b8095.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QItemLabel.737cbb7d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QMenu.d7b6411c.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/format.988231da.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/embedding.507e019a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QList.8bff8777.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnDropdown.8a71b3aa.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QBtnGroup.d8d0cf5d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResizeObserver.8b038ac4.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QImg.27db20fc.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QExpansionItem.b4d31658.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QScrollArea.ce7c28a8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/TouchPan.a03d231e.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/touch.3df10340.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QResponsive.d028432b.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/ClosePopup.84f03a4a.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/chunk.17bfede8.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isArrayLike.a2a00cef.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/isObject.cef35763.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/toNumber.476d0739.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/OpenDay.5172c3be.js"><link rel="stylesheet" href="/assets/OpenDay.8ba15cba.css"><link rel="modulepreload" as="script" crossorigin="" href="/assets/use-cache.b0833c75.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QParallax.bd31f995.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QPage.785c0d26.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/QForm.c9044a42.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/useMetaTags.f561479d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/regexp.d033247d.js"><link rel="modulepreload" as="script" crossorigin="" href="/assets/plugin-vue_export-helper.21dcd24c.js"><link prerender-ignore rel=preconnect href=//app.usercentrics.eu><link prerender-ignore rel=preconnect href=//api.usercentrics.eu><link prerender-ignore rel=preconnect href=//privacy-proxy.usercentrics.eu><link prerender-ignore rel=preload href=//app.usercentrics.eu/browser-ui/latest/loader.js as=script><link prerender-ignore rel=preload href=//privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js as=script><script prerender-ignore id=usercentrics-cmp data-settings-id=w5v6v2pJsC3wdR src=https://app.usercentrics.eu/browser-ui/latest/loader.js async></script><script prerender-ignore src=https://privacy-proxy.usercentrics.eu/latest/uc-block.bundle.js></script><script prerender-ignore>// (optional) additional configs for the Smart Data Protector
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id="f_0517f9a7-0172-43b9-a436-b7cf307c3393"></div><div class="q-field__label no-pointer-events absolute ellipsis">Which products are you interested in?</div></div><div class="q-field__append q-field__marginal row no-wrap items-center q-anchor--skip"><i class="q-icon fas fa-caret-down q-select__dropdown-icon" aria-hidden="true" role="presentation"> </i></div></div></div></label></div></div><div data-v-5651de69="" class="q-pl-sm"><label data-v-5651de69="" class="q-field row no-wrap items-start q-field--filled q-textarea q-field--square q-field--labeled q-field--dark q-field--with-bottom full-width q-mt-md" for="f_e6f30baa-624d-41e6-a6da-cf99acbc61b5"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><textarea class="q-field__native q-placeholder" tabindex="0" rows="6" aria-label="Why are you interested in our Open Day?" placeholder="Sharing your motivations will help us improve your experience." id="f_e6f30baa-624d-41e6-a6da-cf99acbc61b5"></textarea><div class="q-field__label no-pointer-events absolute ellipsis">Why are you interested in our Open Day?</div></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></div><div data-v-5651de69="" class="q-card__actions justify-start q-card__actions--horiz row"><div data-v-5651de69="" class="row justify-start items-start q-my-lg text-grey-6"><div data-v-5651de69="" class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy text-primary" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div data-v-5651de69="" class="q-pl-sm">By submitting, you confirm that you agree to the processing of your personal data by Jina AI as described in the <a data-v-5651de69="" href="/legal#privacy-policy" class="text-grey-6">Privacy Statement</a></div></div></div></div><button data-v-5651de69="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square disabled q-btn--square full-width" tabindex="-1" type="submit" disabled="" aria-disabled="true" style="font-size: 20px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">send</i><span class="block">Submit</span></span></button></div></form></div></div></div></div></div><div data-v-5651de69="" class="row"><div data-v-5651de69="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 66.6875%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/IMG_4726-2.30905e23.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div data-v-5651de69="" class="row q-py-xl justify-center bg-dark"><div data-v-5651de69="" class="q-my-xl col-11"><div data-v-5651de69="" class="text-h2 text-center">An Exclusive Deep Dive into <div data-v-5651de69="" class="dynamic-text">Multimodal AI</div></div><div data-v-5651de69="" class="text-center text-weight-light q-py-xl">A meticulously curated three-hour tour, bringing you closer to the heart of Jina AI's groundbreaking work in multimodal AI technology.</div></div><div data-v-5651de69="" class="q-list q-list--dark row justify-center"><div data-v-5651de69="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable col-10 col-sm-6 col-md-3" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow full-width bg-transparent q-ma-lg"><div data-v-5651de69="" class="q-parallax" style="height: 200px;"><div class="q-parallax__media absolute-full"><img src="/vision_card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-5651de69="" class="q-card__section q-card__section--vert text-h6 text-weight-light q-py-lg"><div data-v-5651de69="" class="q-item__section column q-item__section--main justify-center"><div data-v-5651de69="" class="q-item__label">Our Vision for the Future</div><div data-v-5651de69="" class="q-item__label q-item__label--caption text-caption"><div data-v-5651de69="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1 hour</div></div></div></div><div data-v-5651de69="" class="q-item__label q-item__label--caption text-caption q-py-md">Join us for a comprehensive overview of the AI landscape as we see it. Our discussion will focus on the potential of Large Language Models, multimodal AI, and the impact of open-source technology in shaping the future of global innovation.</div></div></div></div></div><div data-v-5651de69="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable col-10 col-sm-6 col-md-3" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow full-width bg-transparent q-ma-lg"><div data-v-5651de69="" class="q-parallax" style="height: 200px;"><div class="q-parallax__media absolute-full"><img src="/impact_card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-5651de69="" class="q-card__section q-card__section--vert text-h6 text-weight-light q-py-lg"><div data-v-5651de69="" class="q-item__section column q-item__section--main justify-center"><div data-v-5651de69="" class="q-item__label">Impact and Influence</div><div data-v-5651de69="" class="q-item__label q-item__label--caption text-caption"><div data-v-5651de69="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1 hour</div></div></div></div><div data-v-5651de69="" class="q-item__label q-item__label--caption text-caption q-py-md">Understand how our contributions to the open-source community and our work in multimodal AI technology are establishing Jina AI as an influential player in AI innovation. We aim to play a significant role in decision-making processes, ensuring that the advancement of AI technology benefits all.</div></div></div></div></div><div data-v-5651de69="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable col-10 col-sm-6 col-md-3" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow full-width bg-transparent q-ma-lg"><div data-v-5651de69="" class="q-parallax" style="height: 200px;"><div class="q-parallax__media absolute-full"><img src="/engage_card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-5651de69="" class="q-card__section q-card__section--vert text-h6 text-weight-light q-py-lg"><div data-v-5651de69="" class="q-item__section column q-item__section--main justify-center"><div data-v-5651de69="" class="q-item__label">Engage with Us</div><div data-v-5651de69="" class="q-item__label q-item__label--caption text-caption"><div data-v-5651de69="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1 hour</div></div></div></div><div data-v-5651de69="" class="q-item__label q-item__label--caption text-caption q-py-md">We highly encourage an interactive dialogue throughout the day. The exchange of thoughts and perspectives is invaluable to us. Potential collaborations stemming from these discussions could significantly contribute to a more integrated and innovative future.</div></div></div></div></div></div></div><div data-v-5651de69="" class="row q-py-xl non-selectable justify-center"><div data-v-5651de69="" class="text-h2">FAQ</div></div><div data-v-5651de69="" class="row q-py-xl items-start q-gutter-xl justify-center"><div data-v-5651de69="" class="q-list q-list--dark col-11 col-md-8"><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="4ee1b83f-9b50-4356-b330-e404636b542f" aria-label="Expand &quot;What languages do you offer for the tour?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What languages do you offer for the tour?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="4ee1b83f-9b50-4356-b330-e404636b542f" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">We offer tours in German, English, French, Spanish, Chinese, and Russian.</div></div></div></div></div><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="6f0b30ee-f09f-4226-93b7-db062102203e" aria-label="Expand &quot;What is the duration of the tour?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the duration of the tour?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="6f0b30ee-f09f-4226-93b7-db062102203e" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">The tour typically lasts for approximately three hours.</div></div></div></div></div><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="5aea93ee-39e0-4e39-92ba-479ccc910301" aria-label="Expand &quot;Is lunch provided?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is lunch provided?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="5aea93ee-39e0-4e39-92ba-479ccc910301" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">Lunch is optional and can be arranged upon request.</div></div></div></div></div><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="a40191a0-1783-47d0-a060-26cf7d7602f0" aria-label="Expand &quot;Can individuals register for the Open Day?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Can individuals register for the Open Day?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="a40191a0-1783-47d0-a060-26cf7d7602f0" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">Our Open Day is designed primarily for professional groups, such as politicians, NGOs, NPOs, and investors. However, we occasionally make exceptions based on the individual's profile.</div></div></div></div></div><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="3bd6f1a7-68b2-4c67-88f8-8f3dbf71a373" aria-label="Expand &quot;How many people can a group consist of for the Open Day?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How many people can a group consist of for the Open Day?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="3bd6f1a7-68b2-4c67-88f8-8f3dbf71a373" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">We can accommodate a variety of group sizes. Please indicate the size of your group in the registration form, and we will confirm the details with you.</div></div></div></div></div><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="341e0e94-cf9d-4428-9f0c-d413d6caceeb" aria-label="Expand &quot;How can I specify areas of interest for the tour?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How can I specify areas of interest for the tour?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="341e0e94-cf9d-4428-9f0c-d413d6caceeb" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">There's a section in the registration form where you can specify your areas of interest or any special requests. We will do our best to tailor the tour according to your needs.</div></div></div></div></div><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="c12b1ec6-3de4-45af-8c2c-97751f9e0544" aria-label="Expand &quot;Are tours available at your Beijing or Shenzhen offices?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Are tours available at your Beijing or Shenzhen offices?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="c12b1ec6-3de4-45af-8c2c-97751f9e0544" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">At this time, we only offer tours at our Berlin headquarter located in Kreuzberg. Our Beijing and Shenzhen offices are not currently open for tours.</div></div></div></div></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">DocArray</div><div class="q-item__label q-item__label--caption text-caption">The data structure for multimodal data</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jina"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/core.99751891.svg" style="object-fit: cover; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Finetuner</div><div class="q-item__label q-item__label--caption text-caption">Fine-tune embeddings on domain specific data for better search quality</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/clip-as-service"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/clip-as-service.f454ca2a.svg" style="object-fit: cover; 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Radically easy, no nasty surprises.</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/langchain-serve"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/langchain-serve.8cf53254.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">LangChain-Serve</div><div class="q-item__label q-item__label--caption text-caption">Langchain apps on production with Jina &amp; 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object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">RunGPT</div><div class="q-item__label q-item__label--caption text-caption">An open-source cloud-native of large multimodal models serving framework</div></div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://github.com/jina-ai/jerboa"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-img q-img--menu" role="img"><div style="padding-bottom: 56.25%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--waiting" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/jerboa.af6b308b.svg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__loading absolute-full flex flex-center"><svg class="q-spinner q-spinner-mat" width="1em" height="1em" viewBox="25 25 50 50"><circle class="path" cx="50" cy="50" r="20" fill="none" stroke="currentColor" stroke-width="5" stroke-miterlimit="10"></circle></svg></div></div></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Jerboa</div><div class="q-item__label q-item__label--caption text-caption">An experimental finetuner for open-source LLMs</div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div><div class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--standard"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="5f006f56-9d34-45b8-9485-ef4aac67e850" aria-label="Expand &quot;Company&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><span class="q-icon" aria-hidden="true" role="presentation"><img src="/J.svg"></span></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Company</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="5f006f56-9d34-45b8-9485-ef4aac67e850" style="display: none;"><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/about-us"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">About us</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/contact-sales"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Contact sales</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/open-day"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Open day</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="/internship"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Intern program</div></a><a class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="listitem" tabindex="0" href="https://jobs.lever.co/jina-ai"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center">Join us</div><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><div class="q-avatar"><div class="q-avatar__content row flex-center overflow-hidden"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation">open_in_new</i></div></div></div></a></div><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--top absolute-top" aria-orientation="horizontal"><hr class="q-separator q-separator--horizontal q-separator--dark q-expansion-item__border q-expansion-item__border--bottom absolute-bottom" aria-orientation="horizontal"></div></div></div></div></div><div class="q-scrollarea__bar q-scrollarea__bar--v absolute-right q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__bar q-scrollarea__bar--h absolute-bottom q-scrollarea__bar--invisible" aria-hidden="true"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--v absolute-right q-scrollarea__thumb--invisible" aria-hidden="true" style="top: 0px; height: 600px;"></div><div class="q-scrollarea__thumb q-scrollarea__thumb--h absolute-bottom q-scrollarea__thumb--invisible" aria-hidden="true" style="opacity: 0; left: 0px; width: 299px;"></div></div></div></aside></div><div class="q-page-container" style="padding-top: 82px; padding-bottom: 69px;"><main data-v-5651de69="" class="q-page" style="min-height: 449px;"><div data-v-5651de69="" class="column row"><div data-v-5651de69="" class="col-6"><div data-v-5651de69="" class="row q-py-xl justify-center items-center full-height q-px-lg open-day-background"><div data-v-5651de69="" class="col-12 col-md-10 relative-position q-py-xl q-ma-xl q-ml-sm q-pl-sm"><div data-v-5651de69="" class="q-my-xl text-weight-bold text-h2">Open Day</div><div data-v-5651de69="" class="q-pt-lg q-mb-xl text-subtitle1" style="width: 100%;"><div data-v-5651de69="">Jina AI is delighted to open our doors to esteemed entities and organizations interested in the progress and future of Artificial Intelligence. We extend this exclusive opportunity for those in politics, NGOs, NPOs, and investment sectors to gain an insider's view of our operations and visions here at our Berlin headquarters.</div></div><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--bordered q-card--flat no-shadow q-pa-lg bg-dark-page relative-position" style="width: 100%; margin-top: 50px; z-index: 1;"><form data-v-5651de69="" class="q-form"><div data-v-5651de69="" class="row justify-start items-center q-mb-lg"><div data-v-5651de69="" class="col-6 q-pa-sm"><label data-v-5651de69="" class="q-field row no-wrap items-start q-field--filled q-input q-field--square q-field--labeled q-field--dark q-field--with-bottom" for="f_fdf5da19-e592-4632-9352-7ee7b598a256"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native 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ellipsis">Work email</div></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></div><div data-v-5651de69="" class="col-12 q-pa-sm"><label data-v-5651de69="" class="q-field row no-wrap items-start q-field--filled q-input q-field--square q-field--labeled q-field--dark q-field--with-bottom" for="f_cbacec2e-9755-4208-b2f1-71ea2fc06cf5"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" aria-label="Country" id="f_cbacec2e-9755-4208-b2f1-71ea2fc06cf5" type="text"><div class="q-field__label no-pointer-events absolute ellipsis">Country</div></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages 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q-field--filled q-input q-field--square q-field--labeled q-field--dark q-field--with-bottom" for="f_a6fcf7c8-7879-41ee-9630-aa490ab42030"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" aria-label="Organization website" placeholder="URL for your organization's homepage or LinkedIn profile" id="f_a6fcf7c8-7879-41ee-9630-aa490ab42030" type="text"><div class="q-field__label no-pointer-events absolute ellipsis">Organization website</div></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></div><div data-v-5651de69="" class="col-4 q-pa-sm"><label data-v-5651de69="" class="q-field row no-wrap items-start q-field--filled q-input q-field--square q-field--labeled q-field--dark q-field--with-bottom" for="f_31e84305-6160-4cda-a78a-2fda06f5f032"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" aria-label="Number of visitors" id="f_31e84305-6160-4cda-a78a-2fda06f5f032" type="number"><div class="q-field__label no-pointer-events absolute ellipsis">Number of visitors</div></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></div><div data-v-5651de69="" class="col-4 q-pa-sm"><label data-v-5651de69="" class="q-field row no-wrap items-start q-field--filled q-select q-field--auto-height q-select--without-input q-select--without-chips q-select--single q-field--square q-field--labeled q-field--dark q-field--with-bottom" for="f_caa9458d-b7ad-4848-a2ef-d428951d4872"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><div class="q-field__native row items-center"><span></span><input class="q-select__focus-target" id="f_caa9458d-b7ad-4848-a2ef-d428951d4872" readonly="" tabindex="0" role="combobox" aria-label="Preferred language" aria-readonly="false" aria-autocomplete="none" aria-expanded="false" aria-controls="f_caa9458d-b7ad-4848-a2ef-d428951d4872_lb"></div><div class="q-field__label no-pointer-events absolute ellipsis">Preferred language</div></div><div class="q-field__append q-field__marginal row no-wrap items-center q-anchor--skip"><i class="q-icon fas fa-caret-down q-select__dropdown-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></div><div data-v-5651de69="" class="col-4 q-pa-sm"><label data-v-5651de69="" class="q-field row no-wrap items-start q-field--filled q-input q-field--square q-field--labeled q-field--dark q-field--with-bottom" for="f_3ec568df-9dc2-46bf-840f-3e8f7eb63329"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><input class="q-field__native q-placeholder" tabindex="0" aria-label="Preferred date" id="f_3ec568df-9dc2-46bf-840f-3e8f7eb63329" type="text"><div class="q-field__label no-pointer-events absolute ellipsis">Preferred date</div></div><div class="q-field__append q-field__marginal row no-wrap items-center"><i data-v-5651de69="" class="q-icon notranslate material-icons cursor-pointer" aria-hidden="true" role="presentation">event</i></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></div><div data-v-5651de69="" class="col-12 q-pa-sm"><label data-v-5651de69="" class="q-field row no-wrap items-start q-field--filled q-select q-field--auto-height q-select--with-input q-select--with-chips q-select--multiple q-field--square q-field--labeled q-field--dark" for="f_4a518c04-d17b-417e-bbac-8138bccdb575"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><div class="q-field__native row items-center"><input class="q-field__input q-placeholder col" type="search" tabindex="0" role="combobox" aria-label="Which products are you interested in?" aria-readonly="false" aria-autocomplete="list" aria-expanded="false" aria-controls="f_4a518c04-d17b-417e-bbac-8138bccdb575_lb" id="f_4a518c04-d17b-417e-bbac-8138bccdb575"></div><div class="q-field__label no-pointer-events absolute ellipsis">Which products are you interested in?</div></div><div class="q-field__append q-field__marginal row no-wrap items-center q-anchor--skip"><i class="q-icon fas fa-caret-down q-select__dropdown-icon" aria-hidden="true" role="presentation"> </i></div></div></div></label></div></div><div data-v-5651de69="" class="q-pl-sm"><label data-v-5651de69="" class="q-field row no-wrap items-start q-field--filled q-textarea q-field--square q-field--labeled q-field--dark q-field--with-bottom full-width q-mt-md" for="f_900ff5d9-4144-40cf-a2e4-107f6b92e3f8"><div class="q-field__inner relative-position col self-stretch"><div class="q-field__control relative-position row no-wrap" tabindex="-1"><div class="q-field__control-container col relative-position row no-wrap q-anchor--skip"><textarea class="q-field__native q-placeholder" tabindex="0" rows="6" aria-label="Why are you interested in our Open Day?" placeholder="Sharing your motivations will help us improve your experience." id="f_900ff5d9-4144-40cf-a2e4-107f6b92e3f8"></textarea><div class="q-field__label no-pointer-events absolute ellipsis">Why are you interested in our Open Day?</div></div></div><div class="q-field__bottom row items-start q-field__bottom--animated"><div class="q-field__messages col"></div></div></div></label></div><div data-v-5651de69="" class="q-card__actions justify-start q-card__actions--horiz row"><div data-v-5651de69="" class="row justify-start items-start q-my-lg text-grey-6"><div data-v-5651de69="" class="q-checkbox cursor-pointer no-outline row inline no-wrap items-center q-checkbox--dark" tabindex="0" role="checkbox" aria-checked="false"><div class="q-checkbox__inner relative-position non-selectable q-checkbox__inner--falsy text-primary" aria-hidden="true"><input class="hidden q-checkbox__native absolute q-ma-none q-pa-none" type="checkbox"><div class="q-checkbox__bg absolute"><svg class="q-checkbox__svg fit absolute-full" viewBox="0 0 24 24"><path class="q-checkbox__truthy" fill="none" d="M1.73,12.91 8.1,19.28 22.79,4.59"></path><path class="q-checkbox__indet" d="M4,14H20V10H4"></path></svg></div></div><span class="no-outline" tabindex="-1"></span><div class="q-checkbox__label q-anchor--skip"><div data-v-5651de69="" class="q-pl-sm">By submitting, you confirm that you agree to the processing of your personal data by Jina AI as described in the <a data-v-5651de69="" href="/legal#privacy-policy" class="text-grey-6">Privacy Statement</a></div></div></div></div><button data-v-5651de69="" class="q-btn q-btn-item non-selectable no-outline q-btn--outline q-btn--rectangle q-btn--square disabled q-btn--square full-width" tabindex="-1" type="submit" disabled="" aria-disabled="true" style="font-size: 20px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon on-left notranslate material-icons" aria-hidden="true" role="img">send</i><span class="block">Submit</span></span></button></div></form></div></div></div></div></div><div data-v-5651de69="" class="row"><div data-v-5651de69="" class="q-img q-img--menu" role="img"><div style="padding-bottom: 66.6875%;"></div><div class="q-img__container absolute-full"><img class="q-img__image q-img__image--with-transition q-img__image--loaded" loading="lazy" fetchpriority="auto" aria-hidden="true" draggable="false" src="/assets/IMG_4726-2.30905e23.jpg" style="object-fit: cover; object-position: 50% 50%;"></div><div class="q-img__content absolute-full q-anchor--skip"></div></div></div><div data-v-5651de69="" class="row q-py-xl justify-center bg-dark"><div data-v-5651de69="" class="q-my-xl col-11"><div data-v-5651de69="" class="text-h2 text-center">An Exclusive Deep Dive into <div data-v-5651de69="" class="dynamic-text">Multimodal AI</div></div><div data-v-5651de69="" class="text-center text-weight-light q-py-xl">A meticulously curated three-hour tour, bringing you closer to the heart of Jina AI's groundbreaking work in multimodal AI technology.</div></div><div data-v-5651de69="" class="q-list q-list--dark row justify-center"><div data-v-5651de69="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable col-10 col-sm-6 col-md-3" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow full-width bg-transparent q-ma-lg"><div data-v-5651de69="" class="q-parallax" style="height: 200px;"><div class="q-parallax__media absolute-full"><img src="/vision_card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-5651de69="" class="q-card__section q-card__section--vert text-h6 text-weight-light q-py-lg"><div data-v-5651de69="" class="q-item__section column q-item__section--main justify-center"><div data-v-5651de69="" class="q-item__label">Our Vision for the Future</div><div data-v-5651de69="" class="q-item__label q-item__label--caption text-caption"><div data-v-5651de69="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1 hour</div></div></div></div><div data-v-5651de69="" class="q-item__label q-item__label--caption text-caption q-py-md">Join us for a comprehensive overview of the AI landscape as we see it. Our discussion will focus on the potential of Large Language Models, multimodal AI, and the impact of open-source technology in shaping the future of global innovation.</div></div></div></div></div><div data-v-5651de69="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable col-10 col-sm-6 col-md-3" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow full-width bg-transparent q-ma-lg"><div data-v-5651de69="" class="q-parallax" style="height: 200px;"><div class="q-parallax__media absolute-full"><img src="/impact_card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-5651de69="" class="q-card__section q-card__section--vert text-h6 text-weight-light q-py-lg"><div data-v-5651de69="" class="q-item__section column q-item__section--main justify-center"><div data-v-5651de69="" class="q-item__label">Impact and Influence</div><div data-v-5651de69="" class="q-item__label q-item__label--caption text-caption"><div data-v-5651de69="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1 hour</div></div></div></div><div data-v-5651de69="" class="q-item__label q-item__label--caption text-caption q-py-md">Understand how our contributions to the open-source community and our work in multimodal AI technology are establishing Jina AI as an influential player in AI innovation. We aim to play a significant role in decision-making processes, ensuring that the advancement of AI technology benefits all.</div></div></div></div></div><div data-v-5651de69="" class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable col-10 col-sm-6 col-md-3" role="listitem" tabindex="0"><div class="q-focus-helper" tabindex="-1"></div><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow full-width bg-transparent q-ma-lg"><div data-v-5651de69="" class="q-parallax" style="height: 200px;"><div class="q-parallax__media absolute-full"><img src="/engage_card.svg" style="display: initial;"></div><div class="q-parallax__content absolute-full column flex-center"></div></div><div data-v-5651de69="" class="q-card__section q-card__section--vert text-h6 text-weight-light q-py-lg"><div data-v-5651de69="" class="q-item__section column q-item__section--main justify-center"><div data-v-5651de69="" class="q-item__label">Engage with Us</div><div data-v-5651de69="" class="q-item__label q-item__label--caption text-caption"><div data-v-5651de69="" class="q-chip row inline no-wrap items-center q-chip--outline q-chip--dark q-dark" style="font-size: 8px;"><div class="q-chip__content col row no-wrap items-center q-anchor--skip"><div class="ellipsis">1 hour</div></div></div></div><div data-v-5651de69="" class="q-item__label q-item__label--caption text-caption q-py-md">We highly encourage an interactive dialogue throughout the day. The exchange of thoughts and perspectives is invaluable to us. Potential collaborations stemming from these discussions could significantly contribute to a more integrated and innovative future.</div></div></div></div></div></div></div><div data-v-5651de69="" class="row q-py-xl non-selectable justify-center"><div data-v-5651de69="" class="text-h2">FAQ</div></div><div data-v-5651de69="" class="row q-py-xl items-start q-gutter-xl justify-center"><div data-v-5651de69="" class="q-list q-list--dark col-11 col-md-8"><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="7c7d427c-3ca5-4d26-8346-6039b329b11b" aria-label="Expand &quot;What languages do you offer for the tour?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What languages do you offer for the tour?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="7c7d427c-3ca5-4d26-8346-6039b329b11b" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">We offer tours in German, English, French, Spanish, Chinese, and Russian.</div></div></div></div></div><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="9e756335-6973-4bfa-96c4-d7a6b02256a7" aria-label="Expand &quot;What is the duration of the tour?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">What is the duration of the tour?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="9e756335-6973-4bfa-96c4-d7a6b02256a7" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">The tour typically lasts for approximately three hours.</div></div></div></div></div><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="da30a4c8-cbd4-4e02-9d7c-2437ad0c24d0" aria-label="Expand &quot;Is lunch provided?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Is lunch provided?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="da30a4c8-cbd4-4e02-9d7c-2437ad0c24d0" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">Lunch is optional and can be arranged upon request.</div></div></div></div></div><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="365876c1-46cc-4b1f-98da-e2dad9be09db" aria-label="Expand &quot;Can individuals register for the Open Day?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Can individuals register for the Open Day?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="365876c1-46cc-4b1f-98da-e2dad9be09db" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">Our Open Day is designed primarily for professional groups, such as politicians, NGOs, NPOs, and investors. However, we occasionally make exceptions based on the individual's profile.</div></div></div></div></div><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="427457ed-8b9b-4303-9be0-d288e10ad4e5" aria-label="Expand &quot;How many people can a group consist of for the Open Day?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How many people can a group consist of for the Open Day?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="427457ed-8b9b-4303-9be0-d288e10ad4e5" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">We can accommodate a variety of group sizes. Please indicate the size of your group in the registration form, and we will confirm the details with you.</div></div></div></div></div><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="2e0eba22-70b9-4592-9bc2-231c3fa741a8" aria-label="Expand &quot;How can I specify areas of interest for the tour?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">How can I specify areas of interest for the tour?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="2e0eba22-70b9-4592-9bc2-231c3fa741a8" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">There's a section in the registration form where you can specify your areas of interest or any special requests. We will do our best to tailor the tour according to your needs.</div></div></div></div></div><div data-v-5651de69="" class="q-expansion-item q-item-type q-expansion-item--collapsed q-expansion-item--popup"><div class="q-expansion-item__container relative-position"><div class="q-item q-item-type row no-wrap q-item--dark q-item--clickable q-link cursor-pointer q-focusable q-hoverable" role="button" tabindex="0" aria-expanded="false" aria-controls="f62e1441-e62f-42a3-876e-48f24601d5b8" aria-label="Expand &quot;Are tours available at your Beijing or Shenzhen offices?&quot;"><div class="q-focus-helper" tabindex="-1"></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Are tours available at your Beijing or Shenzhen offices?</div></div><div class="q-item__section column q-item__section--side justify-center q-focusable relative-position cursor-pointer"><i class="q-icon fas fa-chevron-down q-expansion-item__toggle-icon" aria-hidden="true" role="presentation"> </i></div></div><div class="q-expansion-item__content relative-position" id="f62e1441-e62f-42a3-876e-48f24601d5b8" style="display: none;"><div data-v-5651de69="" class="q-card q-card--dark q-dark q-card--flat no-shadow"><div data-v-5651de69="" class="q-card__section q-card__section--vert">At this time, we only offer tours at our Berlin headquarter located in Kreuzberg. Our Beijing and Shenzhen offices are not currently open for tours.</div></div></div></div></div></div></div></main></div><div class="q-card q-card--dark q-dark q-card--flat no-shadow overflow-hidden print-hide"><video autoplay="" loop="" playsinline="" class="non-selectable" poster="/assets/portal-2-poster.44997122.webp" style="width: 100%; height: 420px; object-fit: cover;"><source src="/assets/portal-2.0da13c26.mp4" type="video/mp4"></video><div class="q-card q-card--dark q-dark q-card--flat no-shadow row absolute-left items-center bg-transparent non-selectable fit"><div class="text-white bg-transparent lock-blur fit q-pa-sm"><div class="row justify-between q-gutter-lg"><div class="col-12 col-md-3"><div class="q-list q-list--dark"><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><strong>Offices</strong></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Berlin, Germany (HQ)</div><div class="q-item__label q-item__label--caption text-caption">Ohlauer Str. 43 (1st floor), zone A, 10999 Berlin, Germany</div><div class="q-item__label q-item__label--caption text-caption">Geschäftsanschrift: Leipziger str. 96, 10117 Berlin, Germany</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Beijing, China</div><div class="q-item__label q-item__label--caption text-caption">Level 5, Building 6, No.48 Haidian West St. Beijing Haidian, China</div></div></div><div class="q-item q-item-type row no-wrap q-item--dark" role="listitem"><div class="q-item__section column q-item__section--side justify-center q-item__section--avatar"><i class="q-icon notranslate material-icons" aria-hidden="true" role="presentation" style="font-size: 32px;">location_on</i></div><div class="q-item__section column q-item__section--main justify-center"><div class="q-item__label">Shenzhen, China</div><div class="q-item__label q-item__label--caption text-caption">402, Floor 4, Fu'an Technology Building, Shenzhen Nanshan, China</div></div></div></div></div></div><div class="row text-caption justify-center q-mt-xl"> © Jina AI GmbH 2020-2023. All rights reserved.</div></div></div></div><footer class="q-footer q-layout__section--marginal fixed-bottom lock-blur bg-transparent print-hide"><div class="row"><div class="q-btn-group row no-wrap q-btn-group--flat inline col-12 col-md-6 justify-center"><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://discord.jina.ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-discord" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://github.com/jina-ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-github" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://huggingface.co/jinaai" target="_blank" style="font-size: 10px; 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min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-x-twitter" aria-hidden="true" role="img"> </i></span></a><button class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" type="button" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-weixin" aria-hidden="true" role="img"> </i></span></button><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://www.youtube.com/c/JinaAI" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-youtube" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="https://www.meetup.com/jina-community-meetup/" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon fa-brands fa-meetup" aria-hidden="true" role="img"> </i></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable" tabindex="0" href="mailto:support@jina.ai" target="_blank" style="font-size: 10px; padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><i class="q-icon notranslate material-icons" aria-hidden="true" role="img">email</i></span></a></div><div class="row col-12 col-md-6 items-center text-caption justify-center"><div class="q-btn-group row no-wrap q-btn-group--flat q-btn-group--stretch inline" no-caps=""><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch text-caption" tabindex="0" href="/legal/#privacy-policy" style="padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">Privacy Policy</span></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch text-caption" tabindex="0" href="/legal/#terms-and-conditions" style="padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">Terms and Conditions</span></span></a><a class="q-btn q-btn-item non-selectable no-outline q-btn--flat q-btn--rectangle q-btn--actionable q-focusable q-hoverable q-btn--no-uppercase no-border-radius self-stretch text-caption" tabindex="0" href="javascript:UC_UI.showSecondLayer();" style="padding: 8px; min-width: 0px; min-height: 0px;"><span class="q-focus-helper"></span><span class="q-btn__content text-center col items-center q-anchor--skip justify-center row"><span class="block">Privacy Settings</span></span></a></div></div></div></footer></div></div><div id="q-notify" data-v-app=""><div class="q-notifications"><div class="q-notifications__list q-notifications__list--top fixed column no-wrap items-start"></div><div class="q-notifications__list q-notifications__list--top fixed column no-wrap items-end"></div><div class="q-notifications__list q-notifications__list--bottom fixed column no-wrap items-start"></div><div class="q-notifications__list q-notifications__list--bottom fixed column no-wrap items-end"></div><div class="q-notifications__list q-notifications__list--top fixed column no-wrap items-center"></div><div class="q-notifications__list q-notifications__list--bottom fixed column no-wrap items-center"></div><div class="q-notifications__list q-notifications__list--center fixed column no-wrap items-start justify-center"></div><div class="q-notifications__list q-notifications__list--center fixed column no-wrap items-end justify-center"></div><div class="q-notifications__list q-notifications__list--center fixed column no-wrap flex-center"></div></div></div></body></html>
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diff --git a/ru/index.html b/ru/index.html
index f6cf8960974..06b3d13cf79 100644
--- a/ru/index.html
+++ b/ru/index.html
@@ -9,6 +9,6 @@
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   <link rel="stylesheet" href="/assets/index.9fe6336f.css">
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\ No newline at end of file
diff --git a/sitemap.xml b/sitemap.xml
index 5982c943bca..012031b02d0 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -1,219 +1,219 @@
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-    <url><loc>https://jina.ai/</loc><changefreq>daily</changefreq><priority>1</priority><lastmod>2023-12-27T08:31:17.689Z</lastmod></url>
-    <url><loc>https://jina.ai/legal</loc><changefreq>daily</changefreq><priority>0.3</priority><lastmod>2023-12-27T08:31:17.689Z</lastmod></url>
+    <url><loc>https://jina.ai/</loc><changefreq>daily</changefreq><priority>1</priority><lastmod>2023-12-27T09:50:10.333Z</lastmod></url>
+    <url><loc>https://jina.ai/legal</loc><changefreq>daily</changefreq><priority>0.3</priority><lastmod>2023-12-27T09:50:10.333Z</lastmod></url>
   
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